Make heap TID a tiebreaker nbtree index column.

[postgresql] / src / backend / utils / sort / tuplesort.c

/*-------------------------------------------------------------------------
 *
 * tuplesort.c
 *        Generalized tuple sorting routines.
 *
 * This module handles sorting of heap tuples, index tuples, or single
 * Datums (and could easily support other kinds of sortable objects,
 * if necessary).  It works efficiently for both small and large amounts
 * of data.  Small amounts are sorted in-memory using qsort().  Large
 * amounts are sorted using temporary files and a standard external sort
 * algorithm.
 *
 * See Knuth, volume 3, for more than you want to know about the external
 * sorting algorithm.  Historically, we divided the input into sorted runs
 * using replacement selection, in the form of a priority tree implemented
 * as a heap (essentially his Algorithm 5.2.3H), but now we always use
 * quicksort for run generation.  We merge the runs using polyphase merge,
 * Knuth's Algorithm 5.4.2D.  The logical "tapes" used by Algorithm D are
 * implemented by logtape.c, which avoids space wastage by recycling disk
 * space as soon as each block is read from its "tape".
 *
 * The approximate amount of memory allowed for any one sort operation
 * is specified in kilobytes by the caller (most pass work_mem).  Initially,
 * we absorb tuples and simply store them in an unsorted array as long as
 * we haven't exceeded workMem.  If we reach the end of the input without
 * exceeding workMem, we sort the array using qsort() and subsequently return
 * tuples just by scanning the tuple array sequentially.  If we do exceed
 * workMem, we begin to emit tuples into sorted runs in temporary tapes.
 * When tuples are dumped in batch after quicksorting, we begin a new run
 * with a new output tape (selected per Algorithm D).  After the end of the
 * input is reached, we dump out remaining tuples in memory into a final run,
 * then merge the runs using Algorithm D.
 *
 * When merging runs, we use a heap containing just the frontmost tuple from
 * each source run; we repeatedly output the smallest tuple and replace it
 * with the next tuple from its source tape (if any).  When the heap empties,
 * the merge is complete.  The basic merge algorithm thus needs very little
 * memory --- only M tuples for an M-way merge, and M is constrained to a
 * small number.  However, we can still make good use of our full workMem
 * allocation by pre-reading additional blocks from each source tape.  Without
 * prereading, our access pattern to the temporary file would be very erratic;
 * on average we'd read one block from each of M source tapes during the same
 * time that we're writing M blocks to the output tape, so there is no
 * sequentiality of access at all, defeating the read-ahead methods used by
 * most Unix kernels.  Worse, the output tape gets written into a very random
 * sequence of blocks of the temp file, ensuring that things will be even
 * worse when it comes time to read that tape.  A straightforward merge pass
 * thus ends up doing a lot of waiting for disk seeks.  We can improve matters
 * by prereading from each source tape sequentially, loading about workMem/M
 * bytes from each tape in turn, and making the sequential blocks immediately
 * available for reuse.  This approach helps to localize both read and write
 * accesses.  The pre-reading is handled by logtape.c, we just tell it how
 * much memory to use for the buffers.
 *
 * When the caller requests random access to the sort result, we form
 * the final sorted run on a logical tape which is then "frozen", so
 * that we can access it randomly.  When the caller does not need random
 * access, we return from tuplesort_performsort() as soon as we are down
 * to one run per logical tape.  The final merge is then performed
 * on-the-fly as the caller repeatedly calls tuplesort_getXXX; this
 * saves one cycle of writing all the data out to disk and reading it in.
 *
 * Before Postgres 8.2, we always used a seven-tape polyphase merge, on the
 * grounds that 7 is the "sweet spot" on the tapes-to-passes curve according
 * to Knuth's figure 70 (section 5.4.2).  However, Knuth is assuming that
 * tape drives are expensive beasts, and in particular that there will always
 * be many more runs than tape drives.  In our implementation a "tape drive"
 * doesn't cost much more than a few Kb of memory buffers, so we can afford
 * to have lots of them.  In particular, if we can have as many tape drives
 * as sorted runs, we can eliminate any repeated I/O at all.  In the current
 * code we determine the number of tapes M on the basis of workMem: we want
 * workMem/M to be large enough that we read a fair amount of data each time
 * we preread from a tape, so as to maintain the locality of access described
 * above.  Nonetheless, with large workMem we can have many tapes (but not
 * too many -- see the comments in tuplesort_merge_order).
 *
 * This module supports parallel sorting.  Parallel sorts involve coordination
 * among one or more worker processes, and a leader process, each with its own
 * tuplesort state.  The leader process (or, more accurately, the
 * Tuplesortstate associated with a leader process) creates a full tapeset
 * consisting of worker tapes with one run to merge; a run for every
 * worker process.  This is then merged.  Worker processes are guaranteed to
 * produce exactly one output run from their partial input.
 *
 *
 * Portions Copyright (c) 1996-2019, PostgreSQL Global Development Group
 * Portions Copyright (c) 1994, Regents of the University of California
 *
 * IDENTIFICATION
 *        src/backend/utils/sort/tuplesort.c
 *
 *-------------------------------------------------------------------------
 */

#include "postgres.h"

#include <limits.h>

#include "access/hash.h"
#include "access/htup_details.h"
#include "access/nbtree.h"
#include "catalog/index.h"
#include "catalog/pg_am.h"
#include "commands/tablespace.h"
#include "executor/executor.h"
#include "miscadmin.h"
#include "pg_trace.h"
#include "utils/datum.h"
#include "utils/logtape.h"
#include "utils/lsyscache.h"
#include "utils/memutils.h"
#include "utils/pg_rusage.h"
#include "utils/rel.h"
#include "utils/sortsupport.h"
#include "utils/tuplesort.h"


/* sort-type codes for sort__start probes */
#define HEAP_SORT               0
#define INDEX_SORT              1
#define DATUM_SORT              2
#define CLUSTER_SORT    3

/* Sort parallel code from state for sort__start probes */
#define PARALLEL_SORT(state)    ((state)->shared == NULL ? 0 : \
                                                                 (state)->worker >= 0 ? 1 : 2)

/* GUC variables */
#ifdef TRACE_SORT
bool            trace_sort = false;
#endif

#ifdef DEBUG_BOUNDED_SORT
bool            optimize_bounded_sort = true;
#endif


/*
 * The objects we actually sort are SortTuple structs.  These contain
 * a pointer to the tuple proper (might be a MinimalTuple or IndexTuple),
 * which is a separate palloc chunk --- we assume it is just one chunk and
 * can be freed by a simple pfree() (except during merge, when we use a
 * simple slab allocator).  SortTuples also contain the tuple's first key
 * column in Datum/nullflag format, and an index integer.
 *
 * Storing the first key column lets us save heap_getattr or index_getattr
 * calls during tuple comparisons.  We could extract and save all the key
 * columns not just the first, but this would increase code complexity and
 * overhead, and wouldn't actually save any comparison cycles in the common
 * case where the first key determines the comparison result.  Note that
 * for a pass-by-reference datatype, datum1 points into the "tuple" storage.
 *
 * There is one special case: when the sort support infrastructure provides an
 * "abbreviated key" representation, where the key is (typically) a pass by
 * value proxy for a pass by reference type.  In this case, the abbreviated key
 * is stored in datum1 in place of the actual first key column.
 *
 * When sorting single Datums, the data value is represented directly by
 * datum1/isnull1 for pass by value types (or null values).  If the datatype is
 * pass-by-reference and isnull1 is false, then "tuple" points to a separately
 * palloc'd data value, otherwise "tuple" is NULL.  The value of datum1 is then
 * either the same pointer as "tuple", or is an abbreviated key value as
 * described above.  Accordingly, "tuple" is always used in preference to
 * datum1 as the authoritative value for pass-by-reference cases.
 *
 * tupindex holds the input tape number that each tuple in the heap was read
 * from during merge passes.
 */
typedef struct
{
        void       *tuple;                      /* the tuple itself */
        Datum           datum1;                 /* value of first key column */
        bool            isnull1;                /* is first key column NULL? */
        int                     tupindex;               /* see notes above */
} SortTuple;

/*
 * During merge, we use a pre-allocated set of fixed-size slots to hold
 * tuples.  To avoid palloc/pfree overhead.
 *
 * Merge doesn't require a lot of memory, so we can afford to waste some,
 * by using gratuitously-sized slots.  If a tuple is larger than 1 kB, the
 * palloc() overhead is not significant anymore.
 *
 * 'nextfree' is valid when this chunk is in the free list.  When in use, the
 * slot holds a tuple.
 */
#define SLAB_SLOT_SIZE 1024

typedef union SlabSlot
{
        union SlabSlot *nextfree;
        char            buffer[SLAB_SLOT_SIZE];
} SlabSlot;

/*
 * Possible states of a Tuplesort object.  These denote the states that
 * persist between calls of Tuplesort routines.
 */
typedef enum
{
        TSS_INITIAL,                            /* Loading tuples; still within memory limit */
        TSS_BOUNDED,                            /* Loading tuples into bounded-size heap */
        TSS_BUILDRUNS,                          /* Loading tuples; writing to tape */
        TSS_SORTEDINMEM,                        /* Sort completed entirely in memory */
        TSS_SORTEDONTAPE,                       /* Sort completed, final run is on tape */
        TSS_FINALMERGE                          /* Performing final merge on-the-fly */
} TupSortStatus;

/*
 * Parameters for calculation of number of tapes to use --- see inittapes()
 * and tuplesort_merge_order().
 *
 * In this calculation we assume that each tape will cost us about 1 blocks
 * worth of buffer space.  This ignores the overhead of all the other data
 * structures needed for each tape, but it's probably close enough.
 *
 * MERGE_BUFFER_SIZE is how much data we'd like to read from each input
 * tape during a preread cycle (see discussion at top of file).
 */
#define MINORDER                6               /* minimum merge order */
#define MAXORDER                500             /* maximum merge order */
#define TAPE_BUFFER_OVERHEAD            BLCKSZ
#define MERGE_BUFFER_SIZE                       (BLCKSZ * 32)

typedef int (*SortTupleComparator) (const SortTuple *a, const SortTuple *b,
                                                                        Tuplesortstate *state);

/*
 * Private state of a Tuplesort operation.
 */
struct Tuplesortstate
{
        TupSortStatus status;           /* enumerated value as shown above */
        int                     nKeys;                  /* number of columns in sort key */
        bool            randomAccess;   /* did caller request random access? */
        bool            bounded;                /* did caller specify a maximum number of
                                                                 * tuples to return? */
        bool            boundUsed;              /* true if we made use of a bounded heap */
        int                     bound;                  /* if bounded, the maximum number of tuples */
        bool            tuples;                 /* Can SortTuple.tuple ever be set? */
        int64           availMem;               /* remaining memory available, in bytes */
        int64           allowedMem;             /* total memory allowed, in bytes */
        int                     maxTapes;               /* number of tapes (Knuth's T) */
        int                     tapeRange;              /* maxTapes-1 (Knuth's P) */
        MemoryContext sortcontext;      /* memory context holding most sort data */
        MemoryContext tuplecontext; /* sub-context of sortcontext for tuple data */
        LogicalTapeSet *tapeset;        /* logtape.c object for tapes in a temp file */

        /*
         * These function pointers decouple the routines that must know what kind
         * of tuple we are sorting from the routines that don't need to know it.
         * They are set up by the tuplesort_begin_xxx routines.
         *
         * Function to compare two tuples; result is per qsort() convention, ie:
         * <0, 0, >0 according as a<b, a=b, a>b.  The API must match
         * qsort_arg_comparator.
         */
        SortTupleComparator comparetup;

        /*
         * Function to copy a supplied input tuple into palloc'd space and set up
         * its SortTuple representation (ie, set tuple/datum1/isnull1).  Also,
         * state->availMem must be decreased by the amount of space used for the
         * tuple copy (note the SortTuple struct itself is not counted).
         */
        void            (*copytup) (Tuplesortstate *state, SortTuple *stup, void *tup);

        /*
         * Function to write a stored tuple onto tape.  The representation of the
         * tuple on tape need not be the same as it is in memory; requirements on
         * the tape representation are given below.  Unless the slab allocator is
         * used, after writing the tuple, pfree() the out-of-line data (not the
         * SortTuple struct!), and increase state->availMem by the amount of
         * memory space thereby released.
         */
        void            (*writetup) (Tuplesortstate *state, int tapenum,
                                                         SortTuple *stup);

        /*
         * Function to read a stored tuple from tape back into memory. 'len' is
         * the already-read length of the stored tuple.  The tuple is allocated
         * from the slab memory arena, or is palloc'd, see readtup_alloc().
         */
        void            (*readtup) (Tuplesortstate *state, SortTuple *stup,
                                                        int tapenum, unsigned int len);

        /*
         * This array holds the tuples now in sort memory.  If we are in state
         * INITIAL, the tuples are in no particular order; if we are in state
         * SORTEDINMEM, the tuples are in final sorted order; in states BUILDRUNS
         * and FINALMERGE, the tuples are organized in "heap" order per Algorithm
         * H.  In state SORTEDONTAPE, the array is not used.
         */
        SortTuple  *memtuples;          /* array of SortTuple structs */
        int                     memtupcount;    /* number of tuples currently present */
        int                     memtupsize;             /* allocated length of memtuples array */
        bool            growmemtuples;  /* memtuples' growth still underway? */

        /*
         * Memory for tuples is sometimes allocated using a simple slab allocator,
         * rather than with palloc().  Currently, we switch to slab allocation
         * when we start merging.  Merging only needs to keep a small, fixed
         * number of tuples in memory at any time, so we can avoid the
         * palloc/pfree overhead by recycling a fixed number of fixed-size slots
         * to hold the tuples.
         *
         * For the slab, we use one large allocation, divided into SLAB_SLOT_SIZE
         * slots.  The allocation is sized to have one slot per tape, plus one
         * additional slot.  We need that many slots to hold all the tuples kept
         * in the heap during merge, plus the one we have last returned from the
         * sort, with tuplesort_gettuple.
         *
         * Initially, all the slots are kept in a linked list of free slots.  When
         * a tuple is read from a tape, it is put to the next available slot, if
         * it fits.  If the tuple is larger than SLAB_SLOT_SIZE, it is palloc'd
         * instead.
         *
         * When we're done processing a tuple, we return the slot back to the free
         * list, or pfree() if it was palloc'd.  We know that a tuple was
         * allocated from the slab, if its pointer value is between
         * slabMemoryBegin and -End.
         *
         * When the slab allocator is used, the USEMEM/LACKMEM mechanism of
         * tracking memory usage is not used.
         */
        bool            slabAllocatorUsed;

        char       *slabMemoryBegin;    /* beginning of slab memory arena */
        char       *slabMemoryEnd;      /* end of slab memory arena */
        SlabSlot   *slabFreeHead;       /* head of free list */

        /* Buffer size to use for reading input tapes, during merge. */
        size_t          read_buffer_size;

        /*
         * When we return a tuple to the caller in tuplesort_gettuple_XXX, that
         * came from a tape (that is, in TSS_SORTEDONTAPE or TSS_FINALMERGE
         * modes), we remember the tuple in 'lastReturnedTuple', so that we can
         * recycle the memory on next gettuple call.
         */
        void       *lastReturnedTuple;

        /*
         * While building initial runs, this is the current output run number.
         * Afterwards, it is the number of initial runs we made.
         */
        int                     currentRun;

        /*
         * Unless otherwise noted, all pointer variables below are pointers to
         * arrays of length maxTapes, holding per-tape data.
         */

        /*
         * This variable is only used during merge passes.  mergeactive[i] is true
         * if we are reading an input run from (actual) tape number i and have not
         * yet exhausted that run.
         */
        bool       *mergeactive;        /* active input run source? */

        /*
         * Variables for Algorithm D.  Note that destTape is a "logical" tape
         * number, ie, an index into the tp_xxx[] arrays.  Be careful to keep
         * "logical" and "actual" tape numbers straight!
         */
        int                     Level;                  /* Knuth's l */
        int                     destTape;               /* current output tape (Knuth's j, less 1) */
        int                *tp_fib;                     /* Target Fibonacci run counts (A[]) */
        int                *tp_runs;            /* # of real runs on each tape */
        int                *tp_dummy;           /* # of dummy runs for each tape (D[]) */
        int                *tp_tapenum;         /* Actual tape numbers (TAPE[]) */
        int                     activeTapes;    /* # of active input tapes in merge pass */

        /*
         * These variables are used after completion of sorting to keep track of
         * the next tuple to return.  (In the tape case, the tape's current read
         * position is also critical state.)
         */
        int                     result_tape;    /* actual tape number of finished output */
        int                     current;                /* array index (only used if SORTEDINMEM) */
        bool            eof_reached;    /* reached EOF (needed for cursors) */

        /* markpos_xxx holds marked position for mark and restore */
        long            markpos_block;  /* tape block# (only used if SORTEDONTAPE) */
        int                     markpos_offset; /* saved "current", or offset in tape block */
        bool            markpos_eof;    /* saved "eof_reached" */

        /*
         * These variables are used during parallel sorting.
         *
         * worker is our worker identifier.  Follows the general convention that
         * -1 value relates to a leader tuplesort, and values >= 0 worker
         * tuplesorts. (-1 can also be a serial tuplesort.)
         *
         * shared is mutable shared memory state, which is used to coordinate
         * parallel sorts.
         *
         * nParticipants is the number of worker Tuplesortstates known by the
         * leader to have actually been launched, which implies that they must
         * finish a run leader can merge.  Typically includes a worker state held
         * by the leader process itself.  Set in the leader Tuplesortstate only.
         */
        int                     worker;
        Sharedsort *shared;
        int                     nParticipants;

        /*
         * The sortKeys variable is used by every case other than the hash index
         * case; it is set by tuplesort_begin_xxx.  tupDesc is only used by the
         * MinimalTuple and CLUSTER routines, though.
         */
        TupleDesc       tupDesc;
        SortSupport sortKeys;           /* array of length nKeys */

        /*
         * This variable is shared by the single-key MinimalTuple case and the
         * Datum case (which both use qsort_ssup()).  Otherwise it's NULL.
         */
        SortSupport onlyKey;

        /*
         * Additional state for managing "abbreviated key" sortsupport routines
         * (which currently may be used by all cases except the hash index case).
         * Tracks the intervals at which the optimization's effectiveness is
         * tested.
         */
        int64           abbrevNext;             /* Tuple # at which to next check
                                                                 * applicability */

        /*
         * These variables are specific to the CLUSTER case; they are set by
         * tuplesort_begin_cluster.
         */
        IndexInfo  *indexInfo;          /* info about index being used for reference */
        EState     *estate;                     /* for evaluating index expressions */

        /*
         * These variables are specific to the IndexTuple case; they are set by
         * tuplesort_begin_index_xxx and used only by the IndexTuple routines.
         */
        Relation        heapRel;                /* table the index is being built on */
        Relation        indexRel;               /* index being built */

        /* These are specific to the index_btree subcase: */
        bool            enforceUnique;  /* complain if we find duplicate tuples */

        /* These are specific to the index_hash subcase: */
        uint32          high_mask;              /* masks for sortable part of hash code */
        uint32          low_mask;
        uint32          max_buckets;

        /*
         * These variables are specific to the Datum case; they are set by
         * tuplesort_begin_datum and used only by the DatumTuple routines.
         */
        Oid                     datumType;
        /* we need typelen in order to know how to copy the Datums. */
        int                     datumTypeLen;

        /*
         * Resource snapshot for time of sort start.
         */
#ifdef TRACE_SORT
        PGRUsage        ru_start;
#endif
};

/*
 * Private mutable state of tuplesort-parallel-operation.  This is allocated
 * in shared memory.
 */
struct Sharedsort
{
        /* mutex protects all fields prior to tapes */
        slock_t         mutex;

        /*
         * currentWorker generates ordinal identifier numbers for parallel sort
         * workers.  These start from 0, and are always gapless.
         *
         * Workers increment workersFinished to indicate having finished.  If this
         * is equal to state.nParticipants within the leader, leader is ready to
         * merge worker runs.
         */
        int                     currentWorker;
        int                     workersFinished;

        /* Temporary file space */
        SharedFileSet fileset;

        /* Size of tapes flexible array */
        int                     nTapes;

        /*
         * Tapes array used by workers to report back information needed by the
         * leader to concatenate all worker tapes into one for merging
         */
        TapeShare       tapes[FLEXIBLE_ARRAY_MEMBER];
};

/*
 * Is the given tuple allocated from the slab memory arena?
 */
#define IS_SLAB_SLOT(state, tuple) \
        ((char *) (tuple) >= (state)->slabMemoryBegin && \
         (char *) (tuple) < (state)->slabMemoryEnd)

/*
 * Return the given tuple to the slab memory free list, or free it
 * if it was palloc'd.
 */
#define RELEASE_SLAB_SLOT(state, tuple) \
        do { \
                SlabSlot *buf = (SlabSlot *) tuple; \
                \
                if (IS_SLAB_SLOT((state), buf)) \
                { \
                        buf->nextfree = (state)->slabFreeHead; \
                        (state)->slabFreeHead = buf; \
                } else \
                        pfree(buf); \
        } while(0)

#define COMPARETUP(state,a,b)   ((*(state)->comparetup) (a, b, state))
#define COPYTUP(state,stup,tup) ((*(state)->copytup) (state, stup, tup))
#define WRITETUP(state,tape,stup)       ((*(state)->writetup) (state, tape, stup))
#define READTUP(state,stup,tape,len) ((*(state)->readtup) (state, stup, tape, len))
#define LACKMEM(state)          ((state)->availMem < 0 && !(state)->slabAllocatorUsed)
#define USEMEM(state,amt)       ((state)->availMem -= (amt))
#define FREEMEM(state,amt)      ((state)->availMem += (amt))
#define SERIAL(state)           ((state)->shared == NULL)
#define WORKER(state)           ((state)->shared && (state)->worker != -1)
#define LEADER(state)           ((state)->shared && (state)->worker == -1)

/*
 * NOTES about on-tape representation of tuples:
 *
 * We require the first "unsigned int" of a stored tuple to be the total size
 * on-tape of the tuple, including itself (so it is never zero; an all-zero
 * unsigned int is used to delimit runs).  The remainder of the stored tuple
 * may or may not match the in-memory representation of the tuple ---
 * any conversion needed is the job of the writetup and readtup routines.
 *
 * If state->randomAccess is true, then the stored representation of the
 * tuple must be followed by another "unsigned int" that is a copy of the
 * length --- so the total tape space used is actually sizeof(unsigned int)
 * more than the stored length value.  This allows read-backwards.  When
 * randomAccess is not true, the write/read routines may omit the extra
 * length word.
 *
 * writetup is expected to write both length words as well as the tuple
 * data.  When readtup is called, the tape is positioned just after the
 * front length word; readtup must read the tuple data and advance past
 * the back length word (if present).
 *
 * The write/read routines can make use of the tuple description data
 * stored in the Tuplesortstate record, if needed.  They are also expected
 * to adjust state->availMem by the amount of memory space (not tape space!)
 * released or consumed.  There is no error return from either writetup
 * or readtup; they should ereport() on failure.
 *
 *
 * NOTES about memory consumption calculations:
 *
 * We count space allocated for tuples against the workMem limit, plus
 * the space used by the variable-size memtuples array.  Fixed-size space
 * is not counted; it's small enough to not be interesting.
 *
 * Note that we count actual space used (as shown by GetMemoryChunkSpace)
 * rather than the originally-requested size.  This is important since
 * palloc can add substantial overhead.  It's not a complete answer since
 * we won't count any wasted space in palloc allocation blocks, but it's
 * a lot better than what we were doing before 7.3.  As of 9.6, a
 * separate memory context is used for caller passed tuples.  Resetting
 * it at certain key increments significantly ameliorates fragmentation.
 * Note that this places a responsibility on readtup and copytup routines
 * to use the right memory context for these tuples (and to not use the
 * reset context for anything whose lifetime needs to span multiple
 * external sort runs).
 */

/* When using this macro, beware of double evaluation of len */
#define LogicalTapeReadExact(tapeset, tapenum, ptr, len) \
        do { \
                if (LogicalTapeRead(tapeset, tapenum, ptr, len) != (size_t) (len)) \
                        elog(ERROR, "unexpected end of data"); \
        } while(0)


static Tuplesortstate *tuplesort_begin_common(int workMem,
                                           SortCoordinate coordinate,
                                           bool randomAccess);
static void puttuple_common(Tuplesortstate *state, SortTuple *tuple);
static bool consider_abort_common(Tuplesortstate *state);
static void inittapes(Tuplesortstate *state, bool mergeruns);
static void inittapestate(Tuplesortstate *state, int maxTapes);
static void selectnewtape(Tuplesortstate *state);
static void init_slab_allocator(Tuplesortstate *state, int numSlots);
static void mergeruns(Tuplesortstate *state);
static void mergeonerun(Tuplesortstate *state);
static void beginmerge(Tuplesortstate *state);
static bool mergereadnext(Tuplesortstate *state, int srcTape, SortTuple *stup);
static void dumptuples(Tuplesortstate *state, bool alltuples);
static void make_bounded_heap(Tuplesortstate *state);
static void sort_bounded_heap(Tuplesortstate *state);
static void tuplesort_sort_memtuples(Tuplesortstate *state);
static void tuplesort_heap_insert(Tuplesortstate *state, SortTuple *tuple);
static void tuplesort_heap_replace_top(Tuplesortstate *state, SortTuple *tuple);
static void tuplesort_heap_delete_top(Tuplesortstate *state);
static void reversedirection(Tuplesortstate *state);
static unsigned int getlen(Tuplesortstate *state, int tapenum, bool eofOK);
static void markrunend(Tuplesortstate *state, int tapenum);
static void *readtup_alloc(Tuplesortstate *state, Size tuplen);
static int comparetup_heap(const SortTuple *a, const SortTuple *b,
                                Tuplesortstate *state);
static void copytup_heap(Tuplesortstate *state, SortTuple *stup, void *tup);
static void writetup_heap(Tuplesortstate *state, int tapenum,
                          SortTuple *stup);
static void readtup_heap(Tuplesortstate *state, SortTuple *stup,
                         int tapenum, unsigned int len);
static int comparetup_cluster(const SortTuple *a, const SortTuple *b,
                                   Tuplesortstate *state);
static void copytup_cluster(Tuplesortstate *state, SortTuple *stup, void *tup);
static void writetup_cluster(Tuplesortstate *state, int tapenum,
                                 SortTuple *stup);
static void readtup_cluster(Tuplesortstate *state, SortTuple *stup,
                                int tapenum, unsigned int len);
static int comparetup_index_btree(const SortTuple *a, const SortTuple *b,
                                           Tuplesortstate *state);
static int comparetup_index_hash(const SortTuple *a, const SortTuple *b,
                                          Tuplesortstate *state);
static void copytup_index(Tuplesortstate *state, SortTuple *stup, void *tup);
static void writetup_index(Tuplesortstate *state, int tapenum,
                           SortTuple *stup);
static void readtup_index(Tuplesortstate *state, SortTuple *stup,
                          int tapenum, unsigned int len);
static int comparetup_datum(const SortTuple *a, const SortTuple *b,
                                 Tuplesortstate *state);
static void copytup_datum(Tuplesortstate *state, SortTuple *stup, void *tup);
static void writetup_datum(Tuplesortstate *state, int tapenum,
                           SortTuple *stup);
static void readtup_datum(Tuplesortstate *state, SortTuple *stup,
                          int tapenum, unsigned int len);
static int      worker_get_identifier(Tuplesortstate *state);
static void worker_freeze_result_tape(Tuplesortstate *state);
static void worker_nomergeruns(Tuplesortstate *state);
static void leader_takeover_tapes(Tuplesortstate *state);
static void free_sort_tuple(Tuplesortstate *state, SortTuple *stup);

/*
 * Special versions of qsort just for SortTuple objects.  qsort_tuple() sorts
 * any variant of SortTuples, using the appropriate comparetup function.
 * qsort_ssup() is specialized for the case where the comparetup function
 * reduces to ApplySortComparator(), that is single-key MinimalTuple sorts
 * and Datum sorts.
 */
#include "qsort_tuple.c"


/*
 *              tuplesort_begin_xxx
 *
 * Initialize for a tuple sort operation.
 *
 * After calling tuplesort_begin, the caller should call tuplesort_putXXX
 * zero or more times, then call tuplesort_performsort when all the tuples
 * have been supplied.  After performsort, retrieve the tuples in sorted
 * order by calling tuplesort_getXXX until it returns false/NULL.  (If random
 * access was requested, rescan, markpos, and restorepos can also be called.)
 * Call tuplesort_end to terminate the operation and release memory/disk space.
 *
 * Each variant of tuplesort_begin has a workMem parameter specifying the
 * maximum number of kilobytes of RAM to use before spilling data to disk.
 * (The normal value of this parameter is work_mem, but some callers use
 * other values.)  Each variant also has a randomAccess parameter specifying
 * whether the caller needs non-sequential access to the sort result.
 */

static Tuplesortstate *
tuplesort_begin_common(int workMem, SortCoordinate coordinate,
                                           bool randomAccess)
{
        Tuplesortstate *state;
        MemoryContext sortcontext;
        MemoryContext tuplecontext;
        MemoryContext oldcontext;

        /* See leader_takeover_tapes() remarks on randomAccess support */
        if (coordinate && randomAccess)
                elog(ERROR, "random access disallowed under parallel sort");

        /*
         * Create a working memory context for this sort operation. All data
         * needed by the sort will live inside this context.
         */
        sortcontext = AllocSetContextCreate(CurrentMemoryContext,
                                                                                "TupleSort main",
                                                                                ALLOCSET_DEFAULT_SIZES);

        /*
         * Caller tuple (e.g. IndexTuple) memory context.
         *
         * A dedicated child context used exclusively for caller passed tuples
         * eases memory management.  Resetting at key points reduces
         * fragmentation. Note that the memtuples array of SortTuples is allocated
         * in the parent context, not this context, because there is no need to
         * free memtuples early.
         */
        tuplecontext = AllocSetContextCreate(sortcontext,
                                                                                 "Caller tuples",
                                                                                 ALLOCSET_DEFAULT_SIZES);

        /*
         * Make the Tuplesortstate within the per-sort context.  This way, we
         * don't need a separate pfree() operation for it at shutdown.
         */
        oldcontext = MemoryContextSwitchTo(sortcontext);

        state = (Tuplesortstate *) palloc0(sizeof(Tuplesortstate));

#ifdef TRACE_SORT
        if (trace_sort)
                pg_rusage_init(&state->ru_start);
#endif

        state->status = TSS_INITIAL;
        state->randomAccess = randomAccess;
        state->bounded = false;
        state->tuples = true;
        state->boundUsed = false;

        /*
         * workMem is forced to be at least 64KB, the current minimum valid value
         * for the work_mem GUC.  This is a defense against parallel sort callers
         * that divide out memory among many workers in a way that leaves each
         * with very little memory.
         */
        state->allowedMem = Max(workMem, 64) * (int64) 1024;
        state->availMem = state->allowedMem;
        state->sortcontext = sortcontext;
        state->tuplecontext = tuplecontext;
        state->tapeset = NULL;

        state->memtupcount = 0;

        /*
         * Initial size of array must be more than ALLOCSET_SEPARATE_THRESHOLD;
         * see comments in grow_memtuples().
         */
        state->memtupsize = Max(1024,
                                                        ALLOCSET_SEPARATE_THRESHOLD / sizeof(SortTuple) + 1);

        state->growmemtuples = true;
        state->slabAllocatorUsed = false;
        state->memtuples = (SortTuple *) palloc(state->memtupsize * sizeof(SortTuple));

        USEMEM(state, GetMemoryChunkSpace(state->memtuples));

        /* workMem must be large enough for the minimal memtuples array */
        if (LACKMEM(state))
                elog(ERROR, "insufficient memory allowed for sort");

        state->currentRun = 0;

        /*
         * maxTapes, tapeRange, and Algorithm D variables will be initialized by
         * inittapes(), if needed
         */

        state->result_tape = -1;        /* flag that result tape has not been formed */

        /*
         * Initialize parallel-related state based on coordination information
         * from caller
         */
        if (!coordinate)
        {
                /* Serial sort */
                state->shared = NULL;
                state->worker = -1;
                state->nParticipants = -1;
        }
        else if (coordinate->isWorker)
        {
                /* Parallel worker produces exactly one final run from all input */
                state->shared = coordinate->sharedsort;
                state->worker = worker_get_identifier(state);
                state->nParticipants = -1;
        }
        else
        {
                /* Parallel leader state only used for final merge */
                state->shared = coordinate->sharedsort;
                state->worker = -1;
                state->nParticipants = coordinate->nParticipants;
                Assert(state->nParticipants >= 1);
        }

        MemoryContextSwitchTo(oldcontext);

        return state;
}

Tuplesortstate *
tuplesort_begin_heap(TupleDesc tupDesc,
                                         int nkeys, AttrNumber *attNums,
                                         Oid *sortOperators, Oid *sortCollations,
                                         bool *nullsFirstFlags,
                                         int workMem, SortCoordinate coordinate, bool randomAccess)
{
        Tuplesortstate *state = tuplesort_begin_common(workMem, coordinate,
                                                                                                   randomAccess);
        MemoryContext oldcontext;
        int                     i;

        oldcontext = MemoryContextSwitchTo(state->sortcontext);

        AssertArg(nkeys > 0);

#ifdef TRACE_SORT
        if (trace_sort)
                elog(LOG,
                         "begin tuple sort: nkeys = %d, workMem = %d, randomAccess = %c",
                         nkeys, workMem, randomAccess ? 't' : 'f');
#endif

        state->nKeys = nkeys;

        TRACE_POSTGRESQL_SORT_START(HEAP_SORT,
                                                                false,  /* no unique check */
                                                                nkeys,
                                                                workMem,
                                                                randomAccess,
                                                                PARALLEL_SORT(state));

        state->comparetup = comparetup_heap;
        state->copytup = copytup_heap;
        state->writetup = writetup_heap;
        state->readtup = readtup_heap;

        state->tupDesc = tupDesc;       /* assume we need not copy tupDesc */
        state->abbrevNext = 10;

        /* Prepare SortSupport data for each column */
        state->sortKeys = (SortSupport) palloc0(nkeys * sizeof(SortSupportData));

        for (i = 0; i < nkeys; i++)
        {
                SortSupport sortKey = state->sortKeys + i;

                AssertArg(attNums[i] != 0);
                AssertArg(sortOperators[i] != 0);

                sortKey->ssup_cxt = CurrentMemoryContext;
                sortKey->ssup_collation = sortCollations[i];
                sortKey->ssup_nulls_first = nullsFirstFlags[i];
                sortKey->ssup_attno = attNums[i];
                /* Convey if abbreviation optimization is applicable in principle */
                sortKey->abbreviate = (i == 0);

                PrepareSortSupportFromOrderingOp(sortOperators[i], sortKey);
        }

        /*
         * The "onlyKey" optimization cannot be used with abbreviated keys, since
         * tie-breaker comparisons may be required.  Typically, the optimization
         * is only of value to pass-by-value types anyway, whereas abbreviated
         * keys are typically only of value to pass-by-reference types.
         */
        if (nkeys == 1 && !state->sortKeys->abbrev_converter)
                state->onlyKey = state->sortKeys;

        MemoryContextSwitchTo(oldcontext);

        return state;
}

Tuplesortstate *
tuplesort_begin_cluster(TupleDesc tupDesc,
                                                Relation indexRel,
                                                int workMem,
                                                SortCoordinate coordinate, bool randomAccess)
{
        Tuplesortstate *state = tuplesort_begin_common(workMem, coordinate,
                                                                                                   randomAccess);
        BTScanInsert indexScanKey;
        MemoryContext oldcontext;
        int                     i;

        Assert(indexRel->rd_rel->relam == BTREE_AM_OID);

        oldcontext = MemoryContextSwitchTo(state->sortcontext);

#ifdef TRACE_SORT
        if (trace_sort)
                elog(LOG,
                         "begin tuple sort: nkeys = %d, workMem = %d, randomAccess = %c",
                         RelationGetNumberOfAttributes(indexRel),
                         workMem, randomAccess ? 't' : 'f');
#endif

        state->nKeys = IndexRelationGetNumberOfKeyAttributes(indexRel);

        TRACE_POSTGRESQL_SORT_START(CLUSTER_SORT,
                                                                false,  /* no unique check */
                                                                state->nKeys,
                                                                workMem,
                                                                randomAccess,
                                                                PARALLEL_SORT(state));

        state->comparetup = comparetup_cluster;
        state->copytup = copytup_cluster;
        state->writetup = writetup_cluster;
        state->readtup = readtup_cluster;
        state->abbrevNext = 10;

        state->indexInfo = BuildIndexInfo(indexRel);

        state->tupDesc = tupDesc;       /* assume we need not copy tupDesc */

        indexScanKey = _bt_mkscankey(indexRel, NULL);

        if (state->indexInfo->ii_Expressions != NULL)
        {
                TupleTableSlot *slot;
                ExprContext *econtext;

                /*
                 * We will need to use FormIndexDatum to evaluate the index
                 * expressions.  To do that, we need an EState, as well as a
                 * TupleTableSlot to put the table tuples into.  The econtext's
                 * scantuple has to point to that slot, too.
                 */
                state->estate = CreateExecutorState();
                slot = MakeSingleTupleTableSlot(tupDesc, &TTSOpsVirtual);
                econtext = GetPerTupleExprContext(state->estate);
                econtext->ecxt_scantuple = slot;
        }

        /* Prepare SortSupport data for each column */
        state->sortKeys = (SortSupport) palloc0(state->nKeys *
                                                                                        sizeof(SortSupportData));

        for (i = 0; i < state->nKeys; i++)
        {
                SortSupport sortKey = state->sortKeys + i;
                ScanKey         scanKey = indexScanKey->scankeys + i;
                int16           strategy;

                sortKey->ssup_cxt = CurrentMemoryContext;
                sortKey->ssup_collation = scanKey->sk_collation;
                sortKey->ssup_nulls_first =
                        (scanKey->sk_flags & SK_BT_NULLS_FIRST) != 0;
                sortKey->ssup_attno = scanKey->sk_attno;
                /* Convey if abbreviation optimization is applicable in principle */
                sortKey->abbreviate = (i == 0);

                AssertState(sortKey->ssup_attno != 0);

                strategy = (scanKey->sk_flags & SK_BT_DESC) != 0 ?
                        BTGreaterStrategyNumber : BTLessStrategyNumber;

                PrepareSortSupportFromIndexRel(indexRel, strategy, sortKey);
        }

        pfree(indexScanKey);

        MemoryContextSwitchTo(oldcontext);

        return state;
}

Tuplesortstate *
tuplesort_begin_index_btree(Relation heapRel,
                                                        Relation indexRel,
                                                        bool enforceUnique,
                                                        int workMem,
                                                        SortCoordinate coordinate,
                                                        bool randomAccess)
{
        Tuplesortstate *state = tuplesort_begin_common(workMem, coordinate,
                                                                                                   randomAccess);
        BTScanInsert indexScanKey;
        MemoryContext oldcontext;
        int                     i;

        oldcontext = MemoryContextSwitchTo(state->sortcontext);

#ifdef TRACE_SORT
        if (trace_sort)
                elog(LOG,
                         "begin index sort: unique = %c, workMem = %d, randomAccess = %c",
                         enforceUnique ? 't' : 'f',
                         workMem, randomAccess ? 't' : 'f');
#endif

        state->nKeys = IndexRelationGetNumberOfKeyAttributes(indexRel);

        TRACE_POSTGRESQL_SORT_START(INDEX_SORT,
                                                                enforceUnique,
                                                                state->nKeys,
                                                                workMem,
                                                                randomAccess,
                                                                PARALLEL_SORT(state));

        state->comparetup = comparetup_index_btree;
        state->copytup = copytup_index;
        state->writetup = writetup_index;
        state->readtup = readtup_index;
        state->abbrevNext = 10;

        state->heapRel = heapRel;
        state->indexRel = indexRel;
        state->enforceUnique = enforceUnique;

        indexScanKey = _bt_mkscankey(indexRel, NULL);

        /* Prepare SortSupport data for each column */
        state->sortKeys = (SortSupport) palloc0(state->nKeys *
                                                                                        sizeof(SortSupportData));

        for (i = 0; i < state->nKeys; i++)
        {
                SortSupport sortKey = state->sortKeys + i;
                ScanKey         scanKey = indexScanKey->scankeys + i;
                int16           strategy;

                sortKey->ssup_cxt = CurrentMemoryContext;
                sortKey->ssup_collation = scanKey->sk_collation;
                sortKey->ssup_nulls_first =
                        (scanKey->sk_flags & SK_BT_NULLS_FIRST) != 0;
                sortKey->ssup_attno = scanKey->sk_attno;
                /* Convey if abbreviation optimization is applicable in principle */
                sortKey->abbreviate = (i == 0);

                AssertState(sortKey->ssup_attno != 0);

                strategy = (scanKey->sk_flags & SK_BT_DESC) != 0 ?
                        BTGreaterStrategyNumber : BTLessStrategyNumber;

                PrepareSortSupportFromIndexRel(indexRel, strategy, sortKey);
        }

        pfree(indexScanKey);

        MemoryContextSwitchTo(oldcontext);

        return state;
}

Tuplesortstate *
tuplesort_begin_index_hash(Relation heapRel,
                                                   Relation indexRel,
                                                   uint32 high_mask,
                                                   uint32 low_mask,
                                                   uint32 max_buckets,
                                                   int workMem,
                                                   SortCoordinate coordinate,
                                                   bool randomAccess)
{
        Tuplesortstate *state = tuplesort_begin_common(workMem, coordinate,
                                                                                                   randomAccess);
        MemoryContext oldcontext;

        oldcontext = MemoryContextSwitchTo(state->sortcontext);

#ifdef TRACE_SORT
        if (trace_sort)
                elog(LOG,
                         "begin index sort: high_mask = 0x%x, low_mask = 0x%x, "
                         "max_buckets = 0x%x, workMem = %d, randomAccess = %c",
                         high_mask,
                         low_mask,
                         max_buckets,
                         workMem, randomAccess ? 't' : 'f');
#endif

        state->nKeys = 1;                       /* Only one sort column, the hash code */

        state->comparetup = comparetup_index_hash;
        state->copytup = copytup_index;
        state->writetup = writetup_index;
        state->readtup = readtup_index;

        state->heapRel = heapRel;
        state->indexRel = indexRel;

        state->high_mask = high_mask;
        state->low_mask = low_mask;
        state->max_buckets = max_buckets;

        MemoryContextSwitchTo(oldcontext);

        return state;
}

Tuplesortstate *
tuplesort_begin_datum(Oid datumType, Oid sortOperator, Oid sortCollation,
                                          bool nullsFirstFlag, int workMem,
                                          SortCoordinate coordinate, bool randomAccess)
{
        Tuplesortstate *state = tuplesort_begin_common(workMem, coordinate,
                                                                                                   randomAccess);
        MemoryContext oldcontext;
        int16           typlen;
        bool            typbyval;

        oldcontext = MemoryContextSwitchTo(state->sortcontext);

#ifdef TRACE_SORT
        if (trace_sort)
                elog(LOG,
                         "begin datum sort: workMem = %d, randomAccess = %c",
                         workMem, randomAccess ? 't' : 'f');
#endif

        state->nKeys = 1;                       /* always a one-column sort */

        TRACE_POSTGRESQL_SORT_START(DATUM_SORT,
                                                                false,  /* no unique check */
                                                                1,
                                                                workMem,
                                                                randomAccess,
                                                                PARALLEL_SORT(state));

        state->comparetup = comparetup_datum;
        state->copytup = copytup_datum;
        state->writetup = writetup_datum;
        state->readtup = readtup_datum;
        state->abbrevNext = 10;

        state->datumType = datumType;

        /* lookup necessary attributes of the datum type */
        get_typlenbyval(datumType, &typlen, &typbyval);
        state->datumTypeLen = typlen;
        state->tuples = !typbyval;

        /* Prepare SortSupport data */
        state->sortKeys = (SortSupport) palloc0(sizeof(SortSupportData));

        state->sortKeys->ssup_cxt = CurrentMemoryContext;
        state->sortKeys->ssup_collation = sortCollation;
        state->sortKeys->ssup_nulls_first = nullsFirstFlag;

        /*
         * Abbreviation is possible here only for by-reference types.  In theory,
         * a pass-by-value datatype could have an abbreviated form that is cheaper
         * to compare.  In a tuple sort, we could support that, because we can
         * always extract the original datum from the tuple is needed.  Here, we
         * can't, because a datum sort only stores a single copy of the datum; the
         * "tuple" field of each sortTuple is NULL.
         */
        state->sortKeys->abbreviate = !typbyval;

        PrepareSortSupportFromOrderingOp(sortOperator, state->sortKeys);

        /*
         * The "onlyKey" optimization cannot be used with abbreviated keys, since
         * tie-breaker comparisons may be required.  Typically, the optimization
         * is only of value to pass-by-value types anyway, whereas abbreviated
         * keys are typically only of value to pass-by-reference types.
         */
        if (!state->sortKeys->abbrev_converter)
                state->onlyKey = state->sortKeys;

        MemoryContextSwitchTo(oldcontext);

        return state;
}

/*
 * tuplesort_set_bound
 *
 *      Advise tuplesort that at most the first N result tuples are required.
 *
 * Must be called before inserting any tuples.  (Actually, we could allow it
 * as long as the sort hasn't spilled to disk, but there seems no need for
 * delayed calls at the moment.)
 *
 * This is a hint only. The tuplesort may still return more tuples than
 * requested.  Parallel leader tuplesorts will always ignore the hint.
 */
void
tuplesort_set_bound(Tuplesortstate *state, int64 bound)
{
        /* Assert we're called before loading any tuples */
        Assert(state->status == TSS_INITIAL);
        Assert(state->memtupcount == 0);
        Assert(!state->bounded);
        Assert(!WORKER(state));

#ifdef DEBUG_BOUNDED_SORT
        /* Honor GUC setting that disables the feature (for easy testing) */
        if (!optimize_bounded_sort)
                return;
#endif

        /* Parallel leader ignores hint */
        if (LEADER(state))
                return;

        /* We want to be able to compute bound * 2, so limit the setting */
        if (bound > (int64) (INT_MAX / 2))
                return;

        state->bounded = true;
        state->bound = (int) bound;

        /*
         * Bounded sorts are not an effective target for abbreviated key
         * optimization.  Disable by setting state to be consistent with no
         * abbreviation support.
         */
        state->sortKeys->abbrev_converter = NULL;
        if (state->sortKeys->abbrev_full_comparator)
                state->sortKeys->comparator = state->sortKeys->abbrev_full_comparator;

        /* Not strictly necessary, but be tidy */
        state->sortKeys->abbrev_abort = NULL;
        state->sortKeys->abbrev_full_comparator = NULL;
}

/*
 * tuplesort_end
 *
 *      Release resources and clean up.
 *
 * NOTE: after calling this, any pointers returned by tuplesort_getXXX are
 * pointing to garbage.  Be careful not to attempt to use or free such
 * pointers afterwards!
 */
void
tuplesort_end(Tuplesortstate *state)
{
        /* context swap probably not needed, but let's be safe */
        MemoryContext oldcontext = MemoryContextSwitchTo(state->sortcontext);

#ifdef TRACE_SORT
        long            spaceUsed;

        if (state->tapeset)
                spaceUsed = LogicalTapeSetBlocks(state->tapeset);
        else
                spaceUsed = (state->allowedMem - state->availMem + 1023) / 1024;
#endif

        /*
         * Delete temporary "tape" files, if any.
         *
         * Note: want to include this in reported total cost of sort, hence need
         * for two #ifdef TRACE_SORT sections.
         */
        if (state->tapeset)
                LogicalTapeSetClose(state->tapeset);

#ifdef TRACE_SORT
        if (trace_sort)
        {
                if (state->tapeset)
                        elog(LOG, "%s of worker %d ended, %ld disk blocks used: %s",
                                 SERIAL(state) ? "external sort" : "parallel external sort",
                                 state->worker, spaceUsed, pg_rusage_show(&state->ru_start));
                else
                        elog(LOG, "%s of worker %d ended, %ld KB used: %s",
                                 SERIAL(state) ? "internal sort" : "unperformed parallel sort",
                                 state->worker, spaceUsed, pg_rusage_show(&state->ru_start));
        }

        TRACE_POSTGRESQL_SORT_DONE(state->tapeset != NULL, spaceUsed);
#else

        /*
         * If you disabled TRACE_SORT, you can still probe sort__done, but you
         * ain't getting space-used stats.
         */
        TRACE_POSTGRESQL_SORT_DONE(state->tapeset != NULL, 0L);
#endif

        /* Free any execution state created for CLUSTER case */
        if (state->estate != NULL)
        {
                ExprContext *econtext = GetPerTupleExprContext(state->estate);

                ExecDropSingleTupleTableSlot(econtext->ecxt_scantuple);
                FreeExecutorState(state->estate);
        }

        MemoryContextSwitchTo(oldcontext);

        /*
         * Free the per-sort memory context, thereby releasing all working memory,
         * including the Tuplesortstate struct itself.
         */
        MemoryContextDelete(state->sortcontext);
}

/*
 * Grow the memtuples[] array, if possible within our memory constraint.  We
 * must not exceed INT_MAX tuples in memory or the caller-provided memory
 * limit.  Return true if we were able to enlarge the array, false if not.
 *
 * Normally, at each increment we double the size of the array.  When doing
 * that would exceed a limit, we attempt one last, smaller increase (and then
 * clear the growmemtuples flag so we don't try any more).  That allows us to
 * use memory as fully as permitted; sticking to the pure doubling rule could
 * result in almost half going unused.  Because availMem moves around with
 * tuple addition/removal, we need some rule to prevent making repeated small
 * increases in memtupsize, which would just be useless thrashing.  The
 * growmemtuples flag accomplishes that and also prevents useless
 * recalculations in this function.
 */
static bool
grow_memtuples(Tuplesortstate *state)
{
        int                     newmemtupsize;
        int                     memtupsize = state->memtupsize;
        int64           memNowUsed = state->allowedMem - state->availMem;

        /* Forget it if we've already maxed out memtuples, per comment above */
        if (!state->growmemtuples)
                return false;

        /* Select new value of memtupsize */
        if (memNowUsed <= state->availMem)
        {
                /*
                 * We've used no more than half of allowedMem; double our usage,
                 * clamping at INT_MAX tuples.
                 */
                if (memtupsize < INT_MAX / 2)
                        newmemtupsize = memtupsize * 2;
                else
                {
                        newmemtupsize = INT_MAX;
                        state->growmemtuples = false;
                }
        }
        else
        {
                /*
                 * This will be the last increment of memtupsize.  Abandon doubling
                 * strategy and instead increase as much as we safely can.
                 *
                 * To stay within allowedMem, we can't increase memtupsize by more
                 * than availMem / sizeof(SortTuple) elements.  In practice, we want
                 * to increase it by considerably less, because we need to leave some
                 * space for the tuples to which the new array slots will refer.  We
                 * assume the new tuples will be about the same size as the tuples
                 * we've already seen, and thus we can extrapolate from the space
                 * consumption so far to estimate an appropriate new size for the
                 * memtuples array.  The optimal value might be higher or lower than
                 * this estimate, but it's hard to know that in advance.  We again
                 * clamp at INT_MAX tuples.
                 *
                 * This calculation is safe against enlarging the array so much that
                 * LACKMEM becomes true, because the memory currently used includes
                 * the present array; thus, there would be enough allowedMem for the
                 * new array elements even if no other memory were currently used.
                 *
                 * We do the arithmetic in float8, because otherwise the product of
                 * memtupsize and allowedMem could overflow.  Any inaccuracy in the
                 * result should be insignificant; but even if we computed a
                 * completely insane result, the checks below will prevent anything
                 * really bad from happening.
                 */
                double          grow_ratio;

                grow_ratio = (double) state->allowedMem / (double) memNowUsed;
                if (memtupsize * grow_ratio < INT_MAX)
                        newmemtupsize = (int) (memtupsize * grow_ratio);
                else
                        newmemtupsize = INT_MAX;

                /* We won't make any further enlargement attempts */
                state->growmemtuples = false;
        }

        /* Must enlarge array by at least one element, else report failure */
        if (newmemtupsize <= memtupsize)
                goto noalloc;

        /*
         * On a 32-bit machine, allowedMem could exceed MaxAllocHugeSize.  Clamp
         * to ensure our request won't be rejected.  Note that we can easily
         * exhaust address space before facing this outcome.  (This is presently
         * impossible due to guc.c's MAX_KILOBYTES limitation on work_mem, but
         * don't rely on that at this distance.)
         */
        if ((Size) newmemtupsize >= MaxAllocHugeSize / sizeof(SortTuple))
        {
                newmemtupsize = (int) (MaxAllocHugeSize / sizeof(SortTuple));
                state->growmemtuples = false;   /* can't grow any more */
        }

        /*
         * We need to be sure that we do not cause LACKMEM to become true, else
         * the space management algorithm will go nuts.  The code above should
         * never generate a dangerous request, but to be safe, check explicitly
         * that the array growth fits within availMem.  (We could still cause
         * LACKMEM if the memory chunk overhead associated with the memtuples
         * array were to increase.  That shouldn't happen because we chose the
         * initial array size large enough to ensure that palloc will be treating
         * both old and new arrays as separate chunks.  But we'll check LACKMEM
         * explicitly below just in case.)
         */
        if (state->availMem < (int64) ((newmemtupsize - memtupsize) * sizeof(SortTuple)))
                goto noalloc;

        /* OK, do it */
        FREEMEM(state, GetMemoryChunkSpace(state->memtuples));
        state->memtupsize = newmemtupsize;
        state->memtuples = (SortTuple *)
                repalloc_huge(state->memtuples,
                                          state->memtupsize * sizeof(SortTuple));
        USEMEM(state, GetMemoryChunkSpace(state->memtuples));
        if (LACKMEM(state))
                elog(ERROR, "unexpected out-of-memory situation in tuplesort");
        return true;

noalloc:
        /* If for any reason we didn't realloc, shut off future attempts */
        state->growmemtuples = false;
        return false;
}

/*
 * Accept one tuple while collecting input data for sort.
 *
 * Note that the input data is always copied; the caller need not save it.
 */
void
tuplesort_puttupleslot(Tuplesortstate *state, TupleTableSlot *slot)
{
        MemoryContext oldcontext = MemoryContextSwitchTo(state->sortcontext);
        SortTuple       stup;

        /*
         * Copy the given tuple into memory we control, and decrease availMem.
         * Then call the common code.
         */
        COPYTUP(state, &stup, (void *) slot);

        puttuple_common(state, &stup);

        MemoryContextSwitchTo(oldcontext);
}

/*
 * Accept one tuple while collecting input data for sort.
 *
 * Note that the input data is always copied; the caller need not save it.
 */
void
tuplesort_putheaptuple(Tuplesortstate *state, HeapTuple tup)
{
        MemoryContext oldcontext = MemoryContextSwitchTo(state->sortcontext);
        SortTuple       stup;

        /*
         * Copy the given tuple into memory we control, and decrease availMem.
         * Then call the common code.
         */
        COPYTUP(state, &stup, (void *) tup);

        puttuple_common(state, &stup);

        MemoryContextSwitchTo(oldcontext);
}

/*
 * Collect one index tuple while collecting input data for sort, building
 * it from caller-supplied values.
 */
void
tuplesort_putindextuplevalues(Tuplesortstate *state, Relation rel,
                                                          ItemPointer self, Datum *values,
                                                          bool *isnull)
{
        MemoryContext oldcontext = MemoryContextSwitchTo(state->tuplecontext);
        SortTuple       stup;
        Datum           original;
        IndexTuple      tuple;

        stup.tuple = index_form_tuple(RelationGetDescr(rel), values, isnull);
        tuple = ((IndexTuple) stup.tuple);
        tuple->t_tid = *self;
        USEMEM(state, GetMemoryChunkSpace(stup.tuple));
        /* set up first-column key value */
        original = index_getattr(tuple,
                                                         1,
                                                         RelationGetDescr(state->indexRel),
                                                         &stup.isnull1);

        MemoryContextSwitchTo(state->sortcontext);

        if (!state->sortKeys || !state->sortKeys->abbrev_converter || stup.isnull1)
        {
                /*
                 * Store ordinary Datum representation, or NULL value.  If there is a
                 * converter it won't expect NULL values, and cost model is not
                 * required to account for NULL, so in that case we avoid calling
                 * converter and just set datum1 to zeroed representation (to be
                 * consistent, and to support cheap inequality tests for NULL
                 * abbreviated keys).
                 */
                stup.datum1 = original;
        }
        else if (!consider_abort_common(state))
        {
                /* Store abbreviated key representation */
                stup.datum1 = state->sortKeys->abbrev_converter(original,
                                                                                                                state->sortKeys);
        }
        else
        {
                /* Abort abbreviation */
                int                     i;

                stup.datum1 = original;

                /*
                 * Set state to be consistent with never trying abbreviation.
                 *
                 * Alter datum1 representation in already-copied tuples, so as to
                 * ensure a consistent representation (current tuple was just
                 * handled).  It does not matter if some dumped tuples are already
                 * sorted on tape, since serialized tuples lack abbreviated keys
                 * (TSS_BUILDRUNS state prevents control reaching here in any case).
                 */
                for (i = 0; i < state->memtupcount; i++)
                {
                        SortTuple  *mtup = &state->memtuples[i];

                        tuple = mtup->tuple;
                        mtup->datum1 = index_getattr(tuple,
                                                                                 1,
                                                                                 RelationGetDescr(state->indexRel),
                                                                                 &mtup->isnull1);
                }
        }

        puttuple_common(state, &stup);

        MemoryContextSwitchTo(oldcontext);
}

/*
 * Accept one Datum while collecting input data for sort.
 *
 * If the Datum is pass-by-ref type, the value will be copied.
 */
void
tuplesort_putdatum(Tuplesortstate *state, Datum val, bool isNull)
{
        MemoryContext oldcontext = MemoryContextSwitchTo(state->tuplecontext);
        SortTuple       stup;

        /*
         * Pass-by-value types or null values are just stored directly in
         * stup.datum1 (and stup.tuple is not used and set to NULL).
         *
         * Non-null pass-by-reference values need to be copied into memory we
         * control, and possibly abbreviated. The copied value is pointed to by
         * stup.tuple and is treated as the canonical copy (e.g. to return via
         * tuplesort_getdatum or when writing to tape); stup.datum1 gets the
         * abbreviated value if abbreviation is happening, otherwise it's
         * identical to stup.tuple.
         */

        if (isNull || !state->tuples)
        {
                /*
                 * Set datum1 to zeroed representation for NULLs (to be consistent,
                 * and to support cheap inequality tests for NULL abbreviated keys).
                 */
                stup.datum1 = !isNull ? val : (Datum) 0;
                stup.isnull1 = isNull;
                stup.tuple = NULL;              /* no separate storage */
                MemoryContextSwitchTo(state->sortcontext);
        }
        else
        {
                Datum           original = datumCopy(val, false, state->datumTypeLen);

                stup.isnull1 = false;
                stup.tuple = DatumGetPointer(original);
                USEMEM(state, GetMemoryChunkSpace(stup.tuple));
                MemoryContextSwitchTo(state->sortcontext);

                if (!state->sortKeys->abbrev_converter)
                {
                        stup.datum1 = original;
                }
                else if (!consider_abort_common(state))
                {
                        /* Store abbreviated key representation */
                        stup.datum1 = state->sortKeys->abbrev_converter(original,
                                                                                                                        state->sortKeys);
                }
                else
                {
                        /* Abort abbreviation */
                        int                     i;

                        stup.datum1 = original;

                        /*
                         * Set state to be consistent with never trying abbreviation.
                         *
                         * Alter datum1 representation in already-copied tuples, so as to
                         * ensure a consistent representation (current tuple was just
                         * handled).  It does not matter if some dumped tuples are already
                         * sorted on tape, since serialized tuples lack abbreviated keys
                         * (TSS_BUILDRUNS state prevents control reaching here in any
                         * case).
                         */
                        for (i = 0; i < state->memtupcount; i++)
                        {
                                SortTuple  *mtup = &state->memtuples[i];

                                mtup->datum1 = PointerGetDatum(mtup->tuple);
                        }
                }
        }

        puttuple_common(state, &stup);

        MemoryContextSwitchTo(oldcontext);
}

/*
 * Shared code for tuple and datum cases.
 */
static void
puttuple_common(Tuplesortstate *state, SortTuple *tuple)
{
        Assert(!LEADER(state));

        switch (state->status)
        {
                case TSS_INITIAL:

                        /*
                         * Save the tuple into the unsorted array.  First, grow the array
                         * as needed.  Note that we try to grow the array when there is
                         * still one free slot remaining --- if we fail, there'll still be
                         * room to store the incoming tuple, and then we'll switch to
                         * tape-based operation.
                         */
                        if (state->memtupcount >= state->memtupsize - 1)
                        {
                                (void) grow_memtuples(state);
                                Assert(state->memtupcount < state->memtupsize);
                        }
                        state->memtuples[state->memtupcount++] = *tuple;

                        /*
                         * Check if it's time to switch over to a bounded heapsort. We do
                         * so if the input tuple count exceeds twice the desired tuple
                         * count (this is a heuristic for where heapsort becomes cheaper
                         * than a quicksort), or if we've just filled workMem and have
                         * enough tuples to meet the bound.
                         *
                         * Note that once we enter TSS_BOUNDED state we will always try to
                         * complete the sort that way.  In the worst case, if later input
                         * tuples are larger than earlier ones, this might cause us to
                         * exceed workMem significantly.
                         */
                        if (state->bounded &&
                                (state->memtupcount > state->bound * 2 ||
                                 (state->memtupcount > state->bound && LACKMEM(state))))
                        {
#ifdef TRACE_SORT
                                if (trace_sort)
                                        elog(LOG, "switching to bounded heapsort at %d tuples: %s",
                                                 state->memtupcount,
                                                 pg_rusage_show(&state->ru_start));
#endif
                                make_bounded_heap(state);
                                return;
                        }

                        /*
                         * Done if we still fit in available memory and have array slots.
                         */
                        if (state->memtupcount < state->memtupsize && !LACKMEM(state))
                                return;

                        /*
                         * Nope; time to switch to tape-based operation.
                         */
                        inittapes(state, true);

                        /*
                         * Dump all tuples.
                         */
                        dumptuples(state, false);
                        break;

                case TSS_BOUNDED:

                        /*
                         * We don't want to grow the array here, so check whether the new
                         * tuple can be discarded before putting it in.  This should be a
                         * good speed optimization, too, since when there are many more
                         * input tuples than the bound, most input tuples can be discarded
                         * with just this one comparison.  Note that because we currently
                         * have the sort direction reversed, we must check for <= not >=.
                         */
                        if (COMPARETUP(state, tuple, &state->memtuples[0]) <= 0)
                        {
                                /* new tuple <= top of the heap, so we can discard it */
                                free_sort_tuple(state, tuple);
                                CHECK_FOR_INTERRUPTS();
                        }
                        else
                        {
                                /* discard top of heap, replacing it with the new tuple */
                                free_sort_tuple(state, &state->memtuples[0]);
                                tuplesort_heap_replace_top(state, tuple);
                        }
                        break;

                case TSS_BUILDRUNS:

                        /*
                         * Save the tuple into the unsorted array (there must be space)
                         */
                        state->memtuples[state->memtupcount++] = *tuple;

                        /*
                         * If we are over the memory limit, dump all tuples.
                         */
                        dumptuples(state, false);
                        break;

                default:
                        elog(ERROR, "invalid tuplesort state");
                        break;
        }
}

static bool
consider_abort_common(Tuplesortstate *state)
{
        Assert(state->sortKeys[0].abbrev_converter != NULL);
        Assert(state->sortKeys[0].abbrev_abort != NULL);
        Assert(state->sortKeys[0].abbrev_full_comparator != NULL);

        /*
         * Check effectiveness of abbreviation optimization.  Consider aborting
         * when still within memory limit.
         */
        if (state->status == TSS_INITIAL &&
                state->memtupcount >= state->abbrevNext)
        {
                state->abbrevNext *= 2;

                /*
                 * Check opclass-supplied abbreviation abort routine.  It may indicate
                 * that abbreviation should not proceed.
                 */
                if (!state->sortKeys->abbrev_abort(state->memtupcount,
                                                                                   state->sortKeys))
                        return false;

                /*
                 * Finally, restore authoritative comparator, and indicate that
                 * abbreviation is not in play by setting abbrev_converter to NULL
                 */
                state->sortKeys[0].comparator = state->sortKeys[0].abbrev_full_comparator;
                state->sortKeys[0].abbrev_converter = NULL;
                /* Not strictly necessary, but be tidy */
                state->sortKeys[0].abbrev_abort = NULL;
                state->sortKeys[0].abbrev_full_comparator = NULL;

                /* Give up - expect original pass-by-value representation */
                return true;
        }

        return false;
}

/*
 * All tuples have been provided; finish the sort.
 */
void
tuplesort_performsort(Tuplesortstate *state)
{
        MemoryContext oldcontext = MemoryContextSwitchTo(state->sortcontext);

#ifdef TRACE_SORT
        if (trace_sort)
                elog(LOG, "performsort of worker %d starting: %s",
                         state->worker, pg_rusage_show(&state->ru_start));
#endif

        switch (state->status)
        {
                case TSS_INITIAL:

                        /*
                         * We were able to accumulate all the tuples within the allowed
                         * amount of memory, or leader to take over worker tapes
                         */
                        if (SERIAL(state))
                        {
                                /* Just qsort 'em and we're done */
                                tuplesort_sort_memtuples(state);
                                state->status = TSS_SORTEDINMEM;
                        }
                        else if (WORKER(state))
                        {
                                /*
                                 * Parallel workers must still dump out tuples to tape.  No
                                 * merge is required to produce single output run, though.
                                 */
                                inittapes(state, false);
                                dumptuples(state, true);
                                worker_nomergeruns(state);
                                state->status = TSS_SORTEDONTAPE;
                        }
                        else
                        {
                                /*
                                 * Leader will take over worker tapes and merge worker runs.
                                 * Note that mergeruns sets the correct state->status.
                                 */
                                leader_takeover_tapes(state);
                                mergeruns(state);
                        }
                        state->current = 0;
                        state->eof_reached = false;
                        state->markpos_block = 0L;
                        state->markpos_offset = 0;
                        state->markpos_eof = false;
                        break;

                case TSS_BOUNDED:

                        /*
                         * We were able to accumulate all the tuples required for output
                         * in memory, using a heap to eliminate excess tuples.  Now we
                         * have to transform the heap to a properly-sorted array.
                         */
                        sort_bounded_heap(state);
                        state->current = 0;
                        state->eof_reached = false;
                        state->markpos_offset = 0;
                        state->markpos_eof = false;
                        state->status = TSS_SORTEDINMEM;
                        break;

                case TSS_BUILDRUNS:

                        /*
                         * Finish tape-based sort.  First, flush all tuples remaining in
                         * memory out to tape; then merge until we have a single remaining
                         * run (or, if !randomAccess and !WORKER(), one run per tape).
                         * Note that mergeruns sets the correct state->status.
                         */
                        dumptuples(state, true);
                        mergeruns(state);
                        state->eof_reached = false;
                        state->markpos_block = 0L;
                        state->markpos_offset = 0;
                        state->markpos_eof = false;
                        break;

                default:
                        elog(ERROR, "invalid tuplesort state");
                        break;
        }

#ifdef TRACE_SORT
        if (trace_sort)
        {
                if (state->status == TSS_FINALMERGE)
                        elog(LOG, "performsort of worker %d done (except %d-way final merge): %s",
                                 state->worker, state->activeTapes,
                                 pg_rusage_show(&state->ru_start));
                else
                        elog(LOG, "performsort of worker %d done: %s",
                                 state->worker, pg_rusage_show(&state->ru_start));
        }
#endif

        MemoryContextSwitchTo(oldcontext);
}

/*
 * Internal routine to fetch the next tuple in either forward or back
 * direction into *stup.  Returns false if no more tuples.
 * Returned tuple belongs to tuplesort memory context, and must not be freed
 * by caller.  Note that fetched tuple is stored in memory that may be
 * recycled by any future fetch.
 */
static bool
tuplesort_gettuple_common(Tuplesortstate *state, bool forward,
                                                  SortTuple *stup)
{
        unsigned int tuplen;
        size_t          nmoved;

        Assert(!WORKER(state));

        switch (state->status)
        {
                case TSS_SORTEDINMEM:
                        Assert(forward || state->randomAccess);
                        Assert(!state->slabAllocatorUsed);
                        if (forward)
                        {
                                if (state->current < state->memtupcount)
                                {
                                        *stup = state->memtuples[state->current++];
                                        return true;
                                }
                                state->eof_reached = true;

                                /*
                                 * Complain if caller tries to retrieve more tuples than
                                 * originally asked for in a bounded sort.  This is because
                                 * returning EOF here might be the wrong thing.
                                 */
                                if (state->bounded && state->current >= state->bound)
                                        elog(ERROR, "retrieved too many tuples in a bounded sort");

                                return false;
                        }
                        else
                        {
                                if (state->current <= 0)
                                        return false;

                                /*
                                 * if all tuples are fetched already then we return last
                                 * tuple, else - tuple before last returned.
                                 */
                                if (state->eof_reached)
                                        state->eof_reached = false;
                                else
                                {
                                        state->current--;       /* last returned tuple */
                                        if (state->current <= 0)
                                                return false;
                                }
                                *stup = state->memtuples[state->current - 1];
                                return true;
                        }
                        break;

                case TSS_SORTEDONTAPE:
                        Assert(forward || state->randomAccess);
                        Assert(state->slabAllocatorUsed);

                        /*
                         * The slot that held the tuple that we returned in previous
                         * gettuple call can now be reused.
                         */
                        if (state->lastReturnedTuple)
                        {
                                RELEASE_SLAB_SLOT(state, state->lastReturnedTuple);
                                state->lastReturnedTuple = NULL;
                        }

                        if (forward)
                        {
                                if (state->eof_reached)
                                        return false;

                                if ((tuplen = getlen(state, state->result_tape, true)) != 0)
                                {
                                        READTUP(state, stup, state->result_tape, tuplen);

                                        /*
                                         * Remember the tuple we return, so that we can recycle
                                         * its memory on next call.  (This can be NULL, in the
                                         * !state->tuples case).
                                         */
                                        state->lastReturnedTuple = stup->tuple;

                                        return true;
                                }
                                else
                                {
                                        state->eof_reached = true;
                                        return false;
                                }
                        }

                        /*
                         * Backward.
                         *
                         * if all tuples are fetched already then we return last tuple,
                         * else - tuple before last returned.
                         */
                        if (state->eof_reached)
                        {
                                /*
                                 * Seek position is pointing just past the zero tuplen at the
                                 * end of file; back up to fetch last tuple's ending length
                                 * word.  If seek fails we must have a completely empty file.
                                 */
                                nmoved = LogicalTapeBackspace(state->tapeset,
                                                                                          state->result_tape,
                                                                                          2 * sizeof(unsigned int));
                                if (nmoved == 0)
                                        return false;
                                else if (nmoved != 2 * sizeof(unsigned int))
                                        elog(ERROR, "unexpected tape position");
                                state->eof_reached = false;
                        }
                        else
                        {
                                /*
                                 * Back up and fetch previously-returned tuple's ending length
                                 * word.  If seek fails, assume we are at start of file.
                                 */
                                nmoved = LogicalTapeBackspace(state->tapeset,
                                                                                          state->result_tape,
                                                                                          sizeof(unsigned int));
                                if (nmoved == 0)
                                        return false;
                                else if (nmoved != sizeof(unsigned int))
                                        elog(ERROR, "unexpected tape position");
                                tuplen = getlen(state, state->result_tape, false);

                                /*
                                 * Back up to get ending length word of tuple before it.
                                 */
                                nmoved = LogicalTapeBackspace(state->tapeset,
                                                                                          state->result_tape,
                                                                                          tuplen + 2 * sizeof(unsigned int));
                                if (nmoved == tuplen + sizeof(unsigned int))
                                {
                                        /*
                                         * We backed up over the previous tuple, but there was no
                                         * ending length word before it.  That means that the prev
                                         * tuple is the first tuple in the file.  It is now the
                                         * next to read in forward direction (not obviously right,
                                         * but that is what in-memory case does).
                                         */
                                        return false;
                                }
                                else if (nmoved != tuplen + 2 * sizeof(unsigned int))
                                        elog(ERROR, "bogus tuple length in backward scan");
                        }

                        tuplen = getlen(state, state->result_tape, false);

                        /*
                         * Now we have the length of the prior tuple, back up and read it.
                         * Note: READTUP expects we are positioned after the initial
                         * length word of the tuple, so back up to that point.
                         */
                        nmoved = LogicalTapeBackspace(state->tapeset,
                                                                                  state->result_tape,
                                                                                  tuplen);
                        if (nmoved != tuplen)
                                elog(ERROR, "bogus tuple length in backward scan");
                        READTUP(state, stup, state->result_tape, tuplen);

                        /*
                         * Remember the tuple we return, so that we can recycle its memory
                         * on next call. (This can be NULL, in the Datum case).
                         */
                        state->lastReturnedTuple = stup->tuple;

                        return true;

                case TSS_FINALMERGE:
                        Assert(forward);
                        /* We are managing memory ourselves, with the slab allocator. */
                        Assert(state->slabAllocatorUsed);

                        /*
                         * The slab slot holding the tuple that we returned in previous
                         * gettuple call can now be reused.
                         */
                        if (state->lastReturnedTuple)
                        {
                                RELEASE_SLAB_SLOT(state, state->lastReturnedTuple);
                                state->lastReturnedTuple = NULL;
                        }

                        /*
                         * This code should match the inner loop of mergeonerun().
                         */
                        if (state->memtupcount > 0)
                        {
                                int                     srcTape = state->memtuples[0].tupindex;
                                SortTuple       newtup;

                                *stup = state->memtuples[0];

                                /*
                                 * Remember the tuple we return, so that we can recycle its
                                 * memory on next call. (This can be NULL, in the Datum case).
                                 */
                                state->lastReturnedTuple = stup->tuple;

                                /*
                                 * Pull next tuple from tape, and replace the returned tuple
                                 * at top of the heap with it.
                                 */
                                if (!mergereadnext(state, srcTape, &newtup))
                                {
                                        /*
                                         * If no more data, we've reached end of run on this tape.
                                         * Remove the top node from the heap.
                                         */
                                        tuplesort_heap_delete_top(state);

                                        /*
                                         * Rewind to free the read buffer.  It'd go away at the
                                         * end of the sort anyway, but better to release the
                                         * memory early.
                                         */
                                        LogicalTapeRewindForWrite(state->tapeset, srcTape);
                                        return true;
                                }
                                newtup.tupindex = srcTape;
                                tuplesort_heap_replace_top(state, &newtup);
                                return true;
                        }
                        return false;

                default:
                        elog(ERROR, "invalid tuplesort state");
                        return false;           /* keep compiler quiet */
        }
}

/*
 * Fetch the next tuple in either forward or back direction.
 * If successful, put tuple in slot and return true; else, clear the slot
 * and return false.
 *
 * Caller may optionally be passed back abbreviated value (on true return
 * value) when abbreviation was used, which can be used to cheaply avoid
 * equality checks that might otherwise be required.  Caller can safely make a
 * determination of "non-equal tuple" based on simple binary inequality.  A
 * NULL value in leading attribute will set abbreviated value to zeroed
 * representation, which caller may rely on in abbreviated inequality check.
 *
 * If copy is true, the slot receives a tuple that's been copied into the
 * caller's memory context, so that it will stay valid regardless of future
 * manipulations of the tuplesort's state (up to and including deleting the
 * tuplesort).  If copy is false, the slot will just receive a pointer to a
 * tuple held within the tuplesort, which is more efficient, but only safe for
 * callers that are prepared to have any subsequent manipulation of the
 * tuplesort's state invalidate slot contents.
 */
bool
tuplesort_gettupleslot(Tuplesortstate *state, bool forward, bool copy,
                                           TupleTableSlot *slot, Datum *abbrev)
{
        MemoryContext oldcontext = MemoryContextSwitchTo(state->sortcontext);
        SortTuple       stup;

        if (!tuplesort_gettuple_common(state, forward, &stup))
                stup.tuple = NULL;

        MemoryContextSwitchTo(oldcontext);

        if (stup.tuple)
        {
                /* Record abbreviated key for caller */
                if (state->sortKeys->abbrev_converter && abbrev)
                        *abbrev = stup.datum1;

                if (copy)
                        stup.tuple = heap_copy_minimal_tuple((MinimalTuple) stup.tuple);

                ExecStoreMinimalTuple((MinimalTuple) stup.tuple, slot, copy);
                return true;
        }
        else
        {
                ExecClearTuple(slot);
                return false;
        }
}

/*
 * Fetch the next tuple in either forward or back direction.
 * Returns NULL if no more tuples.  Returned tuple belongs to tuplesort memory
 * context, and must not be freed by caller.  Caller may not rely on tuple
 * remaining valid after any further manipulation of tuplesort.
 */
HeapTuple
tuplesort_getheaptuple(Tuplesortstate *state, bool forward)
{
        MemoryContext oldcontext = MemoryContextSwitchTo(state->sortcontext);
        SortTuple       stup;

        if (!tuplesort_gettuple_common(state, forward, &stup))
                stup.tuple = NULL;

        MemoryContextSwitchTo(oldcontext);

        return stup.tuple;
}

/*
 * Fetch the next index tuple in either forward or back direction.
 * Returns NULL if no more tuples.  Returned tuple belongs to tuplesort memory
 * context, and must not be freed by caller.  Caller may not rely on tuple
 * remaining valid after any further manipulation of tuplesort.
 */
IndexTuple
tuplesort_getindextuple(Tuplesortstate *state, bool forward)
{
        MemoryContext oldcontext = MemoryContextSwitchTo(state->sortcontext);
        SortTuple       stup;

        if (!tuplesort_gettuple_common(state, forward, &stup))
                stup.tuple = NULL;

        MemoryContextSwitchTo(oldcontext);

        return (IndexTuple) stup.tuple;
}

/*
 * Fetch the next Datum in either forward or back direction.
 * Returns false if no more datums.
 *
 * If the Datum is pass-by-ref type, the returned value is freshly palloc'd
 * in caller's context, and is now owned by the caller (this differs from
 * similar routines for other types of tuplesorts).
 *
 * Caller may optionally be passed back abbreviated value (on true return
 * value) when abbreviation was used, which can be used to cheaply avoid
 * equality checks that might otherwise be required.  Caller can safely make a
 * determination of "non-equal tuple" based on simple binary inequality.  A
 * NULL value will have a zeroed abbreviated value representation, which caller
 * may rely on in abbreviated inequality check.
 */
bool
tuplesort_getdatum(Tuplesortstate *state, bool forward,
                                   Datum *val, bool *isNull, Datum *abbrev)
{
        MemoryContext oldcontext = MemoryContextSwitchTo(state->sortcontext);
        SortTuple       stup;

        if (!tuplesort_gettuple_common(state, forward, &stup))
        {
                MemoryContextSwitchTo(oldcontext);
                return false;
        }

        /* Ensure we copy into caller's memory context */
        MemoryContextSwitchTo(oldcontext);

        /* Record abbreviated key for caller */
        if (state->sortKeys->abbrev_converter && abbrev)
                *abbrev = stup.datum1;

        if (stup.isnull1 || !state->tuples)
        {
                *val = stup.datum1;
                *isNull = stup.isnull1;
        }
        else
        {
                /* use stup.tuple because stup.datum1 may be an abbreviation */
                *val = datumCopy(PointerGetDatum(stup.tuple), false, state->datumTypeLen);
                *isNull = false;
        }

        return true;
}

/*
 * Advance over N tuples in either forward or back direction,
 * without returning any data.  N==0 is a no-op.
 * Returns true if successful, false if ran out of tuples.
 */
bool
tuplesort_skiptuples(Tuplesortstate *state, int64 ntuples, bool forward)
{
        MemoryContext oldcontext;

        /*
         * We don't actually support backwards skip yet, because no callers need
         * it.  The API is designed to allow for that later, though.
         */
        Assert(forward);
        Assert(ntuples >= 0);
        Assert(!WORKER(state));

        switch (state->status)
        {
                case TSS_SORTEDINMEM:
                        if (state->memtupcount - state->current >= ntuples)
                        {
                                state->current += ntuples;
                                return true;
                        }
                        state->current = state->memtupcount;
                        state->eof_reached = true;

                        /*
                         * Complain if caller tries to retrieve more tuples than
                         * originally asked for in a bounded sort.  This is because
                         * returning EOF here might be the wrong thing.
                         */
                        if (state->bounded && state->current >= state->bound)
                                elog(ERROR, "retrieved too many tuples in a bounded sort");

                        return false;

                case TSS_SORTEDONTAPE:
                case TSS_FINALMERGE:

                        /*
                         * We could probably optimize these cases better, but for now it's
                         * not worth the trouble.
                         */
                        oldcontext = MemoryContextSwitchTo(state->sortcontext);
                        while (ntuples-- > 0)
                        {
                                SortTuple       stup;

                                if (!tuplesort_gettuple_common(state, forward, &stup))
                                {
                                        MemoryContextSwitchTo(oldcontext);
                                        return false;
                                }
                                CHECK_FOR_INTERRUPTS();
                        }
                        MemoryContextSwitchTo(oldcontext);
                        return true;

                default:
                        elog(ERROR, "invalid tuplesort state");
                        return false;           /* keep compiler quiet */
        }
}

/*
 * tuplesort_merge_order - report merge order we'll use for given memory
 * (note: "merge order" just means the number of input tapes in the merge).
 *
 * This is exported for use by the planner.  allowedMem is in bytes.
 */
int
tuplesort_merge_order(int64 allowedMem)
{
        int                     mOrder;

        /*
         * We need one tape for each merge input, plus another one for the output,
         * and each of these tapes needs buffer space.  In addition we want
         * MERGE_BUFFER_SIZE workspace per input tape (but the output tape doesn't
         * count).
         *
         * Note: you might be thinking we need to account for the memtuples[]
         * array in this calculation, but we effectively treat that as part of the
         * MERGE_BUFFER_SIZE workspace.
         */
        mOrder = (allowedMem - TAPE_BUFFER_OVERHEAD) /
                (MERGE_BUFFER_SIZE + TAPE_BUFFER_OVERHEAD);

        /*
         * Even in minimum memory, use at least a MINORDER merge.  On the other
         * hand, even when we have lots of memory, do not use more than a MAXORDER
         * merge.  Tapes are pretty cheap, but they're not entirely free.  Each
         * additional tape reduces the amount of memory available to build runs,
         * which in turn can cause the same sort to need more runs, which makes
         * merging slower even if it can still be done in a single pass.  Also,
         * high order merges are quite slow due to CPU cache effects; it can be
         * faster to pay the I/O cost of a polyphase merge than to perform a
         * single merge pass across many hundreds of tapes.
         */
        mOrder = Max(mOrder, MINORDER);
        mOrder = Min(mOrder, MAXORDER);

        return mOrder;
}

/*
 * inittapes - initialize for tape sorting.
 *
 * This is called only if we have found we won't sort in memory.
 */
static void
inittapes(Tuplesortstate *state, bool mergeruns)
{
        int                     maxTapes,
                                j;

        Assert(!LEADER(state));

        if (mergeruns)
        {
                /* Compute number of tapes to use: merge order plus 1 */
                maxTapes = tuplesort_merge_order(state->allowedMem) + 1;
        }
        else
        {
                /* Workers can sometimes produce single run, output without merge */
                Assert(WORKER(state));
                maxTapes = MINORDER + 1;
        }

#ifdef TRACE_SORT
        if (trace_sort)
                elog(LOG, "worker %d switching to external sort with %d tapes: %s",
                         state->worker, maxTapes, pg_rusage_show(&state->ru_start));
#endif

        /* Create the tape set and allocate the per-tape data arrays */
        inittapestate(state, maxTapes);
        state->tapeset =
                LogicalTapeSetCreate(maxTapes, NULL,
                                                         state->shared ? &state->shared->fileset : NULL,
                                                         state->worker);

        state->currentRun = 0;

        /*
         * Initialize variables of Algorithm D (step D1).
         */
        for (j = 0; j < maxTapes; j++)
        {
                state->tp_fib[j] = 1;
                state->tp_runs[j] = 0;
                state->tp_dummy[j] = 1;
                state->tp_tapenum[j] = j;
        }
        state->tp_fib[state->tapeRange] = 0;
        state->tp_dummy[state->tapeRange] = 0;

        state->Level = 1;
        state->destTape = 0;

        state->status = TSS_BUILDRUNS;
}

/*
 * inittapestate - initialize generic tape management state
 */
static void
inittapestate(Tuplesortstate *state, int maxTapes)
{
        int64           tapeSpace;

        /*
         * Decrease availMem to reflect the space needed for tape buffers; but
         * don't decrease it to the point that we have no room for tuples. (That
         * case is only likely to occur if sorting pass-by-value Datums; in all
         * other scenarios the memtuples[] array is unlikely to occupy more than
         * half of allowedMem.  In the pass-by-value case it's not important to
         * account for tuple space, so we don't care if LACKMEM becomes
         * inaccurate.)
         */
        tapeSpace = (int64) maxTapes * TAPE_BUFFER_OVERHEAD;

        if (tapeSpace + GetMemoryChunkSpace(state->memtuples) < state->allowedMem)
                USEMEM(state, tapeSpace);

        /*
         * Make sure that the temp file(s) underlying the tape set are created in
         * suitable temp tablespaces.  For parallel sorts, this should have been
         * called already, but it doesn't matter if it is called a second time.
         */
        PrepareTempTablespaces();

        state->mergeactive = (bool *) palloc0(maxTapes * sizeof(bool));
        state->tp_fib = (int *) palloc0(maxTapes * sizeof(int));
        state->tp_runs = (int *) palloc0(maxTapes * sizeof(int));
        state->tp_dummy = (int *) palloc0(maxTapes * sizeof(int));
        state->tp_tapenum = (int *) palloc0(maxTapes * sizeof(int));

        /* Record # of tapes allocated (for duration of sort) */
        state->maxTapes = maxTapes;
        /* Record maximum # of tapes usable as inputs when merging */
        state->tapeRange = maxTapes - 1;
}

/*
 * selectnewtape -- select new tape for new initial run.
 *
 * This is called after finishing a run when we know another run
 * must be started.  This implements steps D3, D4 of Algorithm D.
 */
static void
selectnewtape(Tuplesortstate *state)
{
        int                     j;
        int                     a;

        /* Step D3: advance j (destTape) */
        if (state->tp_dummy[state->destTape] < state->tp_dummy[state->destTape + 1])
        {
                state->destTape++;
                return;
        }
        if (state->tp_dummy[state->destTape] != 0)
        {
                state->destTape = 0;
                return;
        }

        /* Step D4: increase level */
        state->Level++;
        a = state->tp_fib[0];
        for (j = 0; j < state->tapeRange; j++)
        {
                state->tp_dummy[j] = a + state->tp_fib[j + 1] - state->tp_fib[j];
                state->tp_fib[j] = a + state->tp_fib[j + 1];
        }
        state->destTape = 0;
}

/*
 * Initialize the slab allocation arena, for the given number of slots.
 */
static void
init_slab_allocator(Tuplesortstate *state, int numSlots)
{
        if (numSlots > 0)
        {
                char       *p;
                int                     i;

                state->slabMemoryBegin = palloc(numSlots * SLAB_SLOT_SIZE);
                state->slabMemoryEnd = state->slabMemoryBegin +
                        numSlots * SLAB_SLOT_SIZE;
                state->slabFreeHead = (SlabSlot *) state->slabMemoryBegin;
                USEMEM(state, numSlots * SLAB_SLOT_SIZE);

                p = state->slabMemoryBegin;
                for (i = 0; i < numSlots - 1; i++)
                {
                        ((SlabSlot *) p)->nextfree = (SlabSlot *) (p + SLAB_SLOT_SIZE);
                        p += SLAB_SLOT_SIZE;
                }
                ((SlabSlot *) p)->nextfree = NULL;
        }
        else
        {
                state->slabMemoryBegin = state->slabMemoryEnd = NULL;
                state->slabFreeHead = NULL;
        }
        state->slabAllocatorUsed = true;
}

/*
 * mergeruns -- merge all the completed initial runs.
 *
 * This implements steps D5, D6 of Algorithm D.  All input data has
 * already been written to initial runs on tape (see dumptuples).
 */
static void
mergeruns(Tuplesortstate *state)
{
        int                     tapenum,
                                svTape,
                                svRuns,
                                svDummy;
        int                     numTapes;
        int                     numInputTapes;

        Assert(state->status == TSS_BUILDRUNS);
        Assert(state->memtupcount == 0);

        if (state->sortKeys != NULL && state->sortKeys->abbrev_converter != NULL)
        {
                /*
                 * If there are multiple runs to be merged, when we go to read back
                 * tuples from disk, abbreviated keys will not have been stored, and
                 * we don't care to regenerate them.  Disable abbreviation from this
                 * point on.
                 */
                state->sortKeys->abbrev_converter = NULL;
                state->sortKeys->comparator = state->sortKeys->abbrev_full_comparator;

                /* Not strictly necessary, but be tidy */
                state->sortKeys->abbrev_abort = NULL;
                state->sortKeys->abbrev_full_comparator = NULL;
        }

        /*
         * Reset tuple memory.  We've freed all the tuples that we previously
         * allocated.  We will use the slab allocator from now on.
         */
        MemoryContextDelete(state->tuplecontext);
        state->tuplecontext = NULL;

        /*
         * We no longer need a large memtuples array.  (We will allocate a smaller
         * one for the heap later.)
         */
        FREEMEM(state, GetMemoryChunkSpace(state->memtuples));
        pfree(state->memtuples);
        state->memtuples = NULL;

        /*
         * If we had fewer runs than tapes, refund the memory that we imagined we
         * would need for the tape buffers of the unused tapes.
         *
         * numTapes and numInputTapes reflect the actual number of tapes we will
         * use.  Note that the output tape's tape number is maxTapes - 1, so the
         * tape numbers of the used tapes are not consecutive, and you cannot just
         * loop from 0 to numTapes to visit all used tapes!
         */
        if (state->Level == 1)
        {
                numInputTapes = state->currentRun;
                numTapes = numInputTapes + 1;
                FREEMEM(state, (state->maxTapes - numTapes) * TAPE_BUFFER_OVERHEAD);
        }
        else
        {
                numInputTapes = state->tapeRange;
                numTapes = state->maxTapes;
        }

        /*
         * Initialize the slab allocator.  We need one slab slot per input tape,
         * for the tuples in the heap, plus one to hold the tuple last returned
         * from tuplesort_gettuple.  (If we're sorting pass-by-val Datums,
         * however, we don't need to do allocate anything.)
         *
         * From this point on, we no longer use the USEMEM()/LACKMEM() mechanism
         * to track memory usage of individual tuples.
         */
        if (state->tuples)
                init_slab_allocator(state, numInputTapes + 1);
        else
                init_slab_allocator(state, 0);

        /*
         * Allocate a new 'memtuples' array, for the heap.  It will hold one tuple
         * from each input tape.
         */
        state->memtupsize = numInputTapes;
        state->memtuples = (SortTuple *) palloc(numInputTapes * sizeof(SortTuple));
        USEMEM(state, GetMemoryChunkSpace(state->memtuples));

        /*
         * Use all the remaining memory we have available for read buffers among
         * the input tapes.
         *
         * We don't try to "rebalance" the memory among tapes, when we start a new
         * merge phase, even if some tapes are inactive in the new phase.  That
         * would be hard, because logtape.c doesn't know where one run ends and
         * another begins.  When a new merge phase begins, and a tape doesn't
         * participate in it, its buffer nevertheless already contains tuples from
         * the next run on same tape, so we cannot release the buffer.  That's OK
         * in practice, merge performance isn't that sensitive to the amount of
         * buffers used, and most merge phases use all or almost all tapes,
         * anyway.
         */
#ifdef TRACE_SORT
        if (trace_sort)
                elog(LOG, "worker %d using " INT64_FORMAT " KB of memory for read buffers among %d input tapes",
                         state->worker, state->availMem / 1024, numInputTapes);
#endif

        state->read_buffer_size = Max(state->availMem / numInputTapes, 0);
        USEMEM(state, state->read_buffer_size * numInputTapes);

        /* End of step D2: rewind all output tapes to prepare for merging */
        for (tapenum = 0; tapenum < state->tapeRange; tapenum++)
                LogicalTapeRewindForRead(state->tapeset, tapenum, state->read_buffer_size);

        for (;;)
        {
                /*
                 * At this point we know that tape[T] is empty.  If there's just one
                 * (real or dummy) run left on each input tape, then only one merge
                 * pass remains.  If we don't have to produce a materialized sorted
                 * tape, we can stop at this point and do the final merge on-the-fly.
                 */
                if (!state->randomAccess && !WORKER(state))
                {
                        bool            allOneRun = true;

                        Assert(state->tp_runs[state->tapeRange] == 0);
                        for (tapenum = 0; tapenum < state->tapeRange; tapenum++)
                        {
                                if (state->tp_runs[tapenum] + state->tp_dummy[tapenum] != 1)
                                {
                                        allOneRun = false;
                                        break;
                                }
                        }
                        if (allOneRun)
                        {
                                /* Tell logtape.c we won't be writing anymore */
                                LogicalTapeSetForgetFreeSpace(state->tapeset);
                                /* Initialize for the final merge pass */
                                beginmerge(state);
                                state->status = TSS_FINALMERGE;
                                return;
                        }
                }

                /* Step D5: merge runs onto tape[T] until tape[P] is empty */
                while (state->tp_runs[state->tapeRange - 1] ||
                           state->tp_dummy[state->tapeRange - 1])
                {
                        bool            allDummy = true;

                        for (tapenum = 0; tapenum < state->tapeRange; tapenum++)
                        {
                                if (state->tp_dummy[tapenum] == 0)
                                {
                                        allDummy = false;
                                        break;
                                }
                        }

                        if (allDummy)
                        {
                                state->tp_dummy[state->tapeRange]++;
                                for (tapenum = 0; tapenum < state->tapeRange; tapenum++)
                                        state->tp_dummy[tapenum]--;
                        }
                        else
                                mergeonerun(state);
                }

                /* Step D6: decrease level */
                if (--state->Level == 0)
                        break;
                /* rewind output tape T to use as new input */
                LogicalTapeRewindForRead(state->tapeset, state->tp_tapenum[state->tapeRange],
                                                                 state->read_buffer_size);
                /* rewind used-up input tape P, and prepare it for write pass */
                LogicalTapeRewindForWrite(state->tapeset, state->tp_tapenum[state->tapeRange - 1]);
                state->tp_runs[state->tapeRange - 1] = 0;

                /*
                 * reassign tape units per step D6; note we no longer care about A[]
                 */
                svTape = state->tp_tapenum[state->tapeRange];
                svDummy = state->tp_dummy[state->tapeRange];
                svRuns = state->tp_runs[state->tapeRange];
                for (tapenum = state->tapeRange; tapenum > 0; tapenum--)
                {
                        state->tp_tapenum[tapenum] = state->tp_tapenum[tapenum - 1];
                        state->tp_dummy[tapenum] = state->tp_dummy[tapenum - 1];
                        state->tp_runs[tapenum] = state->tp_runs[tapenum - 1];
                }
                state->tp_tapenum[0] = svTape;
                state->tp_dummy[0] = svDummy;
                state->tp_runs[0] = svRuns;
        }

        /*
         * Done.  Knuth says that the result is on TAPE[1], but since we exited
         * the loop without performing the last iteration of step D6, we have not
         * rearranged the tape unit assignment, and therefore the result is on
         * TAPE[T].  We need to do it this way so that we can freeze the final
         * output tape while rewinding it.  The last iteration of step D6 would be
         * a waste of cycles anyway...
         */
        state->result_tape = state->tp_tapenum[state->tapeRange];
        if (!WORKER(state))
                LogicalTapeFreeze(state->tapeset, state->result_tape, NULL);
        else
                worker_freeze_result_tape(state);
        state->status = TSS_SORTEDONTAPE;

        /* Release the read buffers of all the other tapes, by rewinding them. */
        for (tapenum = 0; tapenum < state->maxTapes; tapenum++)
        {
                if (tapenum != state->result_tape)
                        LogicalTapeRewindForWrite(state->tapeset, tapenum);
        }
}

/*
 * Merge one run from each input tape, except ones with dummy runs.
 *
 * This is the inner loop of Algorithm D step D5.  We know that the
 * output tape is TAPE[T].
 */
static void
mergeonerun(Tuplesortstate *state)
{
        int                     destTape = state->tp_tapenum[state->tapeRange];
        int                     srcTape;

        /*
         * Start the merge by loading one tuple from each active source tape into
         * the heap.  We can also decrease the input run/dummy run counts.
         */
        beginmerge(state);

        /*
         * Execute merge by repeatedly extracting lowest tuple in heap, writing it
         * out, and replacing it with next tuple from same tape (if there is
         * another one).
         */
        while (state->memtupcount > 0)
        {
                SortTuple       stup;

                /* write the tuple to destTape */
                srcTape = state->memtuples[0].tupindex;
                WRITETUP(state, destTape, &state->memtuples[0]);

                /* recycle the slot of the tuple we just wrote out, for the next read */
                if (state->memtuples[0].tuple)
                        RELEASE_SLAB_SLOT(state, state->memtuples[0].tuple);

                /*
                 * pull next tuple from the tape, and replace the written-out tuple in
                 * the heap with it.
                 */
                if (mergereadnext(state, srcTape, &stup))
                {
                        stup.tupindex = srcTape;
                        tuplesort_heap_replace_top(state, &stup);

                }
                else
                        tuplesort_heap_delete_top(state);
        }

        /*
         * When the heap empties, we're done.  Write an end-of-run marker on the
         * output tape, and increment its count of real runs.
         */
        markrunend(state, destTape);
        state->tp_runs[state->tapeRange]++;

#ifdef TRACE_SORT
        if (trace_sort)
                elog(LOG, "worker %d finished %d-way merge step: %s", state->worker,
                         state->activeTapes, pg_rusage_show(&state->ru_start));
#endif
}

/*
 * beginmerge - initialize for a merge pass
 *
 * We decrease the counts of real and dummy runs for each tape, and mark
 * which tapes contain active input runs in mergeactive[].  Then, fill the
 * merge heap with the first tuple from each active tape.
 */
static void
beginmerge(Tuplesortstate *state)
{
        int                     activeTapes;
        int                     tapenum;
        int                     srcTape;

        /* Heap should be empty here */
        Assert(state->memtupcount == 0);

        /* Adjust run counts and mark the active tapes */
        memset(state->mergeactive, 0,
                   state->maxTapes * sizeof(*state->mergeactive));
        activeTapes = 0;
        for (tapenum = 0; tapenum < state->tapeRange; tapenum++)
        {
                if (state->tp_dummy[tapenum] > 0)
                        state->tp_dummy[tapenum]--;
                else
                {
                        Assert(state->tp_runs[tapenum] > 0);
                        state->tp_runs[tapenum]--;
                        srcTape = state->tp_tapenum[tapenum];
                        state->mergeactive[srcTape] = true;
                        activeTapes++;
                }
        }
        Assert(activeTapes > 0);
        state->activeTapes = activeTapes;

        /* Load the merge heap with the first tuple from each input tape */
        for (srcTape = 0; srcTape < state->maxTapes; srcTape++)
        {
                SortTuple       tup;

                if (mergereadnext(state, srcTape, &tup))
                {
                        tup.tupindex = srcTape;
                        tuplesort_heap_insert(state, &tup);
                }
        }
}

/*
 * mergereadnext - read next tuple from one merge input tape
 *
 * Returns false on EOF.
 */
static bool
mergereadnext(Tuplesortstate *state, int srcTape, SortTuple *stup)
{
        unsigned int tuplen;

        if (!state->mergeactive[srcTape])
                return false;                   /* tape's run is already exhausted */

        /* read next tuple, if any */
        if ((tuplen = getlen(state, srcTape, true)) == 0)
        {
                state->mergeactive[srcTape] = false;
                return false;
        }
        READTUP(state, stup, srcTape, tuplen);

        return true;
}

/*
 * dumptuples - remove tuples from memtuples and write initial run to tape
 *
 * When alltuples = true, dump everything currently in memory.  (This case is
 * only used at end of input data.)
 */
static void
dumptuples(Tuplesortstate *state, bool alltuples)
{
        int                     memtupwrite;
        int                     i;

        /*
         * Nothing to do if we still fit in available memory and have array slots,
         * unless this is the final call during initial run generation.
         */
        if (state->memtupcount < state->memtupsize && !LACKMEM(state) &&
                !alltuples)
                return;

        /*
         * Final call might require no sorting, in rare cases where we just so
         * happen to have previously LACKMEM()'d at the point where exactly all
         * remaining tuples are loaded into memory, just before input was
         * exhausted.
         *
         * In general, short final runs are quite possible.  Rather than allowing
         * a special case where there was a superfluous selectnewtape() call (i.e.
         * a call with no subsequent run actually written to destTape), we prefer
         * to write out a 0 tuple run.
         *
         * mergereadnext() is prepared for 0 tuple runs, and will reliably mark
         * the tape inactive for the merge when called from beginmerge().  This
         * case is therefore similar to the case where mergeonerun() finds a dummy
         * run for the tape, and so doesn't need to merge a run from the tape (or
         * conceptually "merges" the dummy run, if you prefer).  According to
         * Knuth, Algorithm D "isn't strictly optimal" in its method of
         * distribution and dummy run assignment; this edge case seems very
         * unlikely to make that appreciably worse.
         */
        Assert(state->status == TSS_BUILDRUNS);

        /*
         * It seems unlikely that this limit will ever be exceeded, but take no
         * chances
         */
        if (state->currentRun == INT_MAX)
                ereport(ERROR,
                                (errcode(ERRCODE_PROGRAM_LIMIT_EXCEEDED),
                                 errmsg("cannot have more than %d runs for an external sort",
                                                INT_MAX)));

        state->currentRun++;

#ifdef TRACE_SORT
        if (trace_sort)
                elog(LOG, "worker %d starting quicksort of run %d: %s",
                         state->worker, state->currentRun,
                         pg_rusage_show(&state->ru_start));
#endif

        /*
         * Sort all tuples accumulated within the allowed amount of memory for
         * this run using quicksort
         */
        tuplesort_sort_memtuples(state);

#ifdef TRACE_SORT
        if (trace_sort)
                elog(LOG, "worker %d finished quicksort of run %d: %s",
                         state->worker, state->currentRun,
                         pg_rusage_show(&state->ru_start));
#endif

        memtupwrite = state->memtupcount;
        for (i = 0; i < memtupwrite; i++)
        {
                WRITETUP(state, state->tp_tapenum[state->destTape],
                                 &state->memtuples[i]);
                state->memtupcount--;
        }

        /*
         * Reset tuple memory.  We've freed all of the tuples that we previously
         * allocated.  It's important to avoid fragmentation when there is a stark
         * change in the sizes of incoming tuples.  Fragmentation due to
         * AllocSetFree's bucketing by size class might be particularly bad if
         * this step wasn't taken.
         */
        MemoryContextReset(state->tuplecontext);

        markrunend(state, state->tp_tapenum[state->destTape]);
        state->tp_runs[state->destTape]++;
        state->tp_dummy[state->destTape]--; /* per Alg D step D2 */

#ifdef TRACE_SORT
        if (trace_sort)
                elog(LOG, "worker %d finished writing run %d to tape %d: %s",
                         state->worker, state->currentRun, state->destTape,
                         pg_rusage_show(&state->ru_start));
#endif

        if (!alltuples)
                selectnewtape(state);
}

/*
 * tuplesort_rescan             - rewind and replay the scan
 */
void
tuplesort_rescan(Tuplesortstate *state)
{
        MemoryContext oldcontext = MemoryContextSwitchTo(state->sortcontext);

        Assert(state->randomAccess);

        switch (state->status)
        {
                case TSS_SORTEDINMEM:
                        state->current = 0;
                        state->eof_reached = false;
                        state->markpos_offset = 0;
                        state->markpos_eof = false;
                        break;
                case TSS_SORTEDONTAPE:
                        LogicalTapeRewindForRead(state->tapeset,
                                                                         state->result_tape,
                                                                         0);
                        state->eof_reached = false;
                        state->markpos_block = 0L;
                        state->markpos_offset = 0;
                        state->markpos_eof = false;
                        break;
                default:
                        elog(ERROR, "invalid tuplesort state");
                        break;
        }

        MemoryContextSwitchTo(oldcontext);
}

/*
 * tuplesort_markpos    - saves current position in the merged sort file
 */
void
tuplesort_markpos(Tuplesortstate *state)
{
        MemoryContext oldcontext = MemoryContextSwitchTo(state->sortcontext);

        Assert(state->randomAccess);

        switch (state->status)
        {
                case TSS_SORTEDINMEM:
                        state->markpos_offset = state->current;
                        state->markpos_eof = state->eof_reached;
                        break;
                case TSS_SORTEDONTAPE:
                        LogicalTapeTell(state->tapeset,
                                                        state->result_tape,
                                                        &state->markpos_block,
                                                        &state->markpos_offset);
                        state->markpos_eof = state->eof_reached;
                        break;
                default:
                        elog(ERROR, "invalid tuplesort state");
                        break;
        }

        MemoryContextSwitchTo(oldcontext);
}

/*
 * tuplesort_restorepos - restores current position in merged sort file to
 *                                                last saved position
 */
void
tuplesort_restorepos(Tuplesortstate *state)
{
        MemoryContext oldcontext = MemoryContextSwitchTo(state->sortcontext);

        Assert(state->randomAccess);

        switch (state->status)
        {
                case TSS_SORTEDINMEM:
                        state->current = state->markpos_offset;
                        state->eof_reached = state->markpos_eof;
                        break;
                case TSS_SORTEDONTAPE:
                        LogicalTapeSeek(state->tapeset,
                                                        state->result_tape,
                                                        state->markpos_block,
                                                        state->markpos_offset);
                        state->eof_reached = state->markpos_eof;
                        break;
                default:
                        elog(ERROR, "invalid tuplesort state");
                        break;
        }

        MemoryContextSwitchTo(oldcontext);
}

/*
 * tuplesort_get_stats - extract summary statistics
 *
 * This can be called after tuplesort_performsort() finishes to obtain
 * printable summary information about how the sort was performed.
 */
void
tuplesort_get_stats(Tuplesortstate *state,
                                        TuplesortInstrumentation *stats)
{
        /*
         * Note: it might seem we should provide both memory and disk usage for a
         * disk-based sort.  However, the current code doesn't track memory space
         * accurately once we have begun to return tuples to the caller (since we
         * don't account for pfree's the caller is expected to do), so we cannot
         * rely on availMem in a disk sort.  This does not seem worth the overhead
         * to fix.  Is it worth creating an API for the memory context code to
         * tell us how much is actually used in sortcontext?
         */
        if (state->tapeset)
        {
                stats->spaceType = SORT_SPACE_TYPE_DISK;
                stats->spaceUsed = LogicalTapeSetBlocks(state->tapeset) * (BLCKSZ / 1024);
        }
        else
        {
                stats->spaceType = SORT_SPACE_TYPE_MEMORY;
                stats->spaceUsed = (state->allowedMem - state->availMem + 1023) / 1024;
        }

        switch (state->status)
        {
                case TSS_SORTEDINMEM:
                        if (state->boundUsed)
                                stats->sortMethod = SORT_TYPE_TOP_N_HEAPSORT;
                        else
                                stats->sortMethod = SORT_TYPE_QUICKSORT;
                        break;
                case TSS_SORTEDONTAPE:
                        stats->sortMethod = SORT_TYPE_EXTERNAL_SORT;
                        break;
                case TSS_FINALMERGE:
                        stats->sortMethod = SORT_TYPE_EXTERNAL_MERGE;
                        break;
                default:
                        stats->sortMethod = SORT_TYPE_STILL_IN_PROGRESS;
                        break;
        }
}

/*
 * Convert TuplesortMethod to a string.
 */
const char *
tuplesort_method_name(TuplesortMethod m)
{
        switch (m)
        {
                case SORT_TYPE_STILL_IN_PROGRESS:
                        return "still in progress";
                case SORT_TYPE_TOP_N_HEAPSORT:
                        return "top-N heapsort";
                case SORT_TYPE_QUICKSORT:
                        return "quicksort";
                case SORT_TYPE_EXTERNAL_SORT:
                        return "external sort";
                case SORT_TYPE_EXTERNAL_MERGE:
                        return "external merge";
        }

        return "unknown";
}

/*
 * Convert TuplesortSpaceType to a string.
 */
const char *
tuplesort_space_type_name(TuplesortSpaceType t)
{
        Assert(t == SORT_SPACE_TYPE_DISK || t == SORT_SPACE_TYPE_MEMORY);
        return t == SORT_SPACE_TYPE_DISK ? "Disk" : "Memory";
}


/*
 * Heap manipulation routines, per Knuth's Algorithm 5.2.3H.
 */

/*
 * Convert the existing unordered array of SortTuples to a bounded heap,
 * discarding all but the smallest "state->bound" tuples.
 *
 * When working with a bounded heap, we want to keep the largest entry
 * at the root (array entry zero), instead of the smallest as in the normal
 * sort case.  This allows us to discard the largest entry cheaply.
 * Therefore, we temporarily reverse the sort direction.
 */
static void
make_bounded_heap(Tuplesortstate *state)
{
        int                     tupcount = state->memtupcount;
        int                     i;

        Assert(state->status == TSS_INITIAL);
        Assert(state->bounded);
        Assert(tupcount >= state->bound);
        Assert(SERIAL(state));

        /* Reverse sort direction so largest entry will be at root */
        reversedirection(state);

        state->memtupcount = 0;         /* make the heap empty */
        for (i = 0; i < tupcount; i++)
        {
                if (state->memtupcount < state->bound)
                {
                        /* Insert next tuple into heap */
                        /* Must copy source tuple to avoid possible overwrite */
                        SortTuple       stup = state->memtuples[i];

                        tuplesort_heap_insert(state, &stup);
                }
                else
                {
                        /*
                         * The heap is full.  Replace the largest entry with the new
                         * tuple, or just discard it, if it's larger than anything already
                         * in the heap.
                         */
                        if (COMPARETUP(state, &state->memtuples[i], &state->memtuples[0]) <= 0)
                        {
                                free_sort_tuple(state, &state->memtuples[i]);
                                CHECK_FOR_INTERRUPTS();
                        }
                        else
                                tuplesort_heap_replace_top(state, &state->memtuples[i]);
                }
        }

        Assert(state->memtupcount == state->bound);
        state->status = TSS_BOUNDED;
}

/*
 * Convert the bounded heap to a properly-sorted array
 */
static void
sort_bounded_heap(Tuplesortstate *state)
{
        int                     tupcount = state->memtupcount;

        Assert(state->status == TSS_BOUNDED);
        Assert(state->bounded);
        Assert(tupcount == state->bound);
        Assert(SERIAL(state));

        /*
         * We can unheapify in place because each delete-top call will remove the
         * largest entry, which we can promptly store in the newly freed slot at
         * the end.  Once we're down to a single-entry heap, we're done.
         */
        while (state->memtupcount > 1)
        {
                SortTuple       stup = state->memtuples[0];

                /* this sifts-up the next-largest entry and decreases memtupcount */
                tuplesort_heap_delete_top(state);
                state->memtuples[state->memtupcount] = stup;
        }
        state->memtupcount = tupcount;

        /*
         * Reverse sort direction back to the original state.  This is not
         * actually necessary but seems like a good idea for tidiness.
         */
        reversedirection(state);

        state->status = TSS_SORTEDINMEM;
        state->boundUsed = true;
}

/*
 * Sort all memtuples using specialized qsort() routines.
 *
 * Quicksort is used for small in-memory sorts, and external sort runs.
 */
static void
tuplesort_sort_memtuples(Tuplesortstate *state)
{
        Assert(!LEADER(state));

        if (state->memtupcount > 1)
        {
                /* Can we use the single-key sort function? */
                if (state->onlyKey != NULL)
                        qsort_ssup(state->memtuples, state->memtupcount,
                                           state->onlyKey);
                else
                        qsort_tuple(state->memtuples,
                                                state->memtupcount,
                                                state->comparetup,
                                                state);
        }
}

/*
 * Insert a new tuple into an empty or existing heap, maintaining the
 * heap invariant.  Caller is responsible for ensuring there's room.
 *
 * Note: For some callers, tuple points to a memtuples[] entry above the
 * end of the heap.  This is safe as long as it's not immediately adjacent
 * to the end of the heap (ie, in the [memtupcount] array entry) --- if it
 * is, it might get overwritten before being moved into the heap!
 */
static void
tuplesort_heap_insert(Tuplesortstate *state, SortTuple *tuple)
{
        SortTuple  *memtuples;
        int                     j;

        memtuples = state->memtuples;
        Assert(state->memtupcount < state->memtupsize);

        CHECK_FOR_INTERRUPTS();

        /*
         * Sift-up the new entry, per Knuth 5.2.3 exercise 16. Note that Knuth is
         * using 1-based array indexes, not 0-based.
         */
        j = state->memtupcount++;
        while (j > 0)
        {
                int                     i = (j - 1) >> 1;

                if (COMPARETUP(state, tuple, &memtuples[i]) >= 0)
                        break;
                memtuples[j] = memtuples[i];
                j = i;
        }
        memtuples[j] = *tuple;
}

/*
 * Remove the tuple at state->memtuples[0] from the heap.  Decrement
 * memtupcount, and sift up to maintain the heap invariant.
 *
 * The caller has already free'd the tuple the top node points to,
 * if necessary.
 */
static void
tuplesort_heap_delete_top(Tuplesortstate *state)
{
        SortTuple  *memtuples = state->memtuples;
        SortTuple  *tuple;

        if (--state->memtupcount <= 0)
                return;

        /*
         * Remove the last tuple in the heap, and re-insert it, by replacing the
         * current top node with it.
         */
        tuple = &memtuples[state->memtupcount];
        tuplesort_heap_replace_top(state, tuple);
}

/*
 * Replace the tuple at state->memtuples[0] with a new tuple.  Sift up to
 * maintain the heap invariant.
 *
 * This corresponds to Knuth's "sift-up" algorithm (Algorithm 5.2.3H,
 * Heapsort, steps H3-H8).
 */
static void
tuplesort_heap_replace_top(Tuplesortstate *state, SortTuple *tuple)
{
        SortTuple  *memtuples = state->memtuples;
        unsigned int i,
                                n;

        Assert(state->memtupcount >= 1);

        CHECK_FOR_INTERRUPTS();

        /*
         * state->memtupcount is "int", but we use "unsigned int" for i, j, n.
         * This prevents overflow in the "2 * i + 1" calculation, since at the top
         * of the loop we must have i < n <= INT_MAX <= UINT_MAX/2.
         */
        n = state->memtupcount;
        i = 0;                                          /* i is where the "hole" is */
        for (;;)
        {
                unsigned int j = 2 * i + 1;

                if (j >= n)
                        break;
                if (j + 1 < n &&
                        COMPARETUP(state, &memtuples[j], &memtuples[j + 1]) > 0)
                        j++;
                if (COMPARETUP(state, tuple, &memtuples[j]) <= 0)
                        break;
                memtuples[i] = memtuples[j];
                i = j;
        }
        memtuples[i] = *tuple;
}

/*
 * Function to reverse the sort direction from its current state
 *
 * It is not safe to call this when performing hash tuplesorts
 */
static void
reversedirection(Tuplesortstate *state)
{
        SortSupport sortKey = state->sortKeys;
        int                     nkey;

        for (nkey = 0; nkey < state->nKeys; nkey++, sortKey++)
        {
                sortKey->ssup_reverse = !sortKey->ssup_reverse;
                sortKey->ssup_nulls_first = !sortKey->ssup_nulls_first;
        }
}


/*
 * Tape interface routines
 */

static unsigned int
getlen(Tuplesortstate *state, int tapenum, bool eofOK)
{
        unsigned int len;

        if (LogicalTapeRead(state->tapeset, tapenum,
                                                &len, sizeof(len)) != sizeof(len))
                elog(ERROR, "unexpected end of tape");
        if (len == 0 && !eofOK)
                elog(ERROR, "unexpected end of data");
        return len;
}

static void
markrunend(Tuplesortstate *state, int tapenum)
{
        unsigned int len = 0;

        LogicalTapeWrite(state->tapeset, tapenum, (void *) &len, sizeof(len));
}

/*
 * Get memory for tuple from within READTUP() routine.
 *
 * We use next free slot from the slab allocator, or palloc() if the tuple
 * is too large for that.
 */
static void *
readtup_alloc(Tuplesortstate *state, Size tuplen)
{
        SlabSlot   *buf;

        /*
         * We pre-allocate enough slots in the slab arena that we should never run
         * out.
         */
        Assert(state->slabFreeHead);

        if (tuplen > SLAB_SLOT_SIZE || !state->slabFreeHead)
                return MemoryContextAlloc(state->sortcontext, tuplen);
        else
        {
                buf = state->slabFreeHead;
                /* Reuse this slot */
                state->slabFreeHead = buf->nextfree;

                return buf;
        }
}


/*
 * Routines specialized for HeapTuple (actually MinimalTuple) case
 */

static int
comparetup_heap(const SortTuple *a, const SortTuple *b, Tuplesortstate *state)
{
        SortSupport sortKey = state->sortKeys;
        HeapTupleData ltup;
        HeapTupleData rtup;
        TupleDesc       tupDesc;
        int                     nkey;
        int32           compare;
        AttrNumber      attno;
        Datum           datum1,
                                datum2;
        bool            isnull1,
                                isnull2;


        /* Compare the leading sort key */
        compare = ApplySortComparator(a->datum1, a->isnull1,
                                                                  b->datum1, b->isnull1,
                                                                  sortKey);
        if (compare != 0)
                return compare;

        /* Compare additional sort keys */
        ltup.t_len = ((MinimalTuple) a->tuple)->t_len + MINIMAL_TUPLE_OFFSET;
        ltup.t_data = (HeapTupleHeader) ((char *) a->tuple - MINIMAL_TUPLE_OFFSET);
        rtup.t_len = ((MinimalTuple) b->tuple)->t_len + MINIMAL_TUPLE_OFFSET;
        rtup.t_data = (HeapTupleHeader) ((char *) b->tuple - MINIMAL_TUPLE_OFFSET);
        tupDesc = state->tupDesc;

        if (sortKey->abbrev_converter)
        {
                attno = sortKey->ssup_attno;

                datum1 = heap_getattr(&ltup, attno, tupDesc, &isnull1);
                datum2 = heap_getattr(&rtup, attno, tupDesc, &isnull2);

                compare = ApplySortAbbrevFullComparator(datum1, isnull1,
                                                                                                datum2, isnull2,
                                                                                                sortKey);
                if (compare != 0)
                        return compare;
        }

        sortKey++;
        for (nkey = 1; nkey < state->nKeys; nkey++, sortKey++)
        {
                attno = sortKey->ssup_attno;

                datum1 = heap_getattr(&ltup, attno, tupDesc, &isnull1);
                datum2 = heap_getattr(&rtup, attno, tupDesc, &isnull2);

                compare = ApplySortComparator(datum1, isnull1,
                                                                          datum2, isnull2,
                                                                          sortKey);
                if (compare != 0)
                        return compare;
        }

        return 0;
}

static void
copytup_heap(Tuplesortstate *state, SortTuple *stup, void *tup)
{
        /*
         * We expect the passed "tup" to be a TupleTableSlot, and form a
         * MinimalTuple using the exported interface for that.
         */
        TupleTableSlot *slot = (TupleTableSlot *) tup;
        Datum           original;
        MinimalTuple tuple;
        HeapTupleData htup;
        MemoryContext oldcontext = MemoryContextSwitchTo(state->tuplecontext);

        /* copy the tuple into sort storage */
        tuple = ExecCopySlotMinimalTuple(slot);
        stup->tuple = (void *) tuple;
        USEMEM(state, GetMemoryChunkSpace(tuple));
        /* set up first-column key value */
        htup.t_len = tuple->t_len + MINIMAL_TUPLE_OFFSET;
        htup.t_data = (HeapTupleHeader) ((char *) tuple - MINIMAL_TUPLE_OFFSET);
        original = heap_getattr(&htup,
                                                        state->sortKeys[0].ssup_attno,
                                                        state->tupDesc,
                                                        &stup->isnull1);

        MemoryContextSwitchTo(oldcontext);

        if (!state->sortKeys->abbrev_converter || stup->isnull1)
        {
                /*
                 * Store ordinary Datum representation, or NULL value.  If there is a
                 * converter it won't expect NULL values, and cost model is not
                 * required to account for NULL, so in that case we avoid calling
                 * converter and just set datum1 to zeroed representation (to be
                 * consistent, and to support cheap inequality tests for NULL
                 * abbreviated keys).
                 */
                stup->datum1 = original;
        }
        else if (!consider_abort_common(state))
        {
                /* Store abbreviated key representation */
                stup->datum1 = state->sortKeys->abbrev_converter(original,
                                                                                                                 state->sortKeys);
        }
        else
        {
                /* Abort abbreviation */
                int                     i;

                stup->datum1 = original;

                /*
                 * Set state to be consistent with never trying abbreviation.
                 *
                 * Alter datum1 representation in already-copied tuples, so as to
                 * ensure a consistent representation (current tuple was just
                 * handled).  It does not matter if some dumped tuples are already
                 * sorted on tape, since serialized tuples lack abbreviated keys
                 * (TSS_BUILDRUNS state prevents control reaching here in any case).
                 */
                for (i = 0; i < state->memtupcount; i++)
                {
                        SortTuple  *mtup = &state->memtuples[i];

                        htup.t_len = ((MinimalTuple) mtup->tuple)->t_len +
                                MINIMAL_TUPLE_OFFSET;
                        htup.t_data = (HeapTupleHeader) ((char *) mtup->tuple -
                                                                                         MINIMAL_TUPLE_OFFSET);

                        mtup->datum1 = heap_getattr(&htup,
                                                                                state->sortKeys[0].ssup_attno,
                                                                                state->tupDesc,
                                                                                &mtup->isnull1);
                }
        }
}

static void
writetup_heap(Tuplesortstate *state, int tapenum, SortTuple *stup)
{
        MinimalTuple tuple = (MinimalTuple) stup->tuple;

        /* the part of the MinimalTuple we'll write: */
        char       *tupbody = (char *) tuple + MINIMAL_TUPLE_DATA_OFFSET;
        unsigned int tupbodylen = tuple->t_len - MINIMAL_TUPLE_DATA_OFFSET;

        /* total on-disk footprint: */
        unsigned int tuplen = tupbodylen + sizeof(int);

        LogicalTapeWrite(state->tapeset, tapenum,
                                         (void *) &tuplen, sizeof(tuplen));
        LogicalTapeWrite(state->tapeset, tapenum,
                                         (void *) tupbody, tupbodylen);
        if (state->randomAccess)        /* need trailing length word? */
                LogicalTapeWrite(state->tapeset, tapenum,
                                                 (void *) &tuplen, sizeof(tuplen));

        if (!state->slabAllocatorUsed)
        {
                FREEMEM(state, GetMemoryChunkSpace(tuple));
                heap_free_minimal_tuple(tuple);
        }
}

static void
readtup_heap(Tuplesortstate *state, SortTuple *stup,
                         int tapenum, unsigned int len)
{
        unsigned int tupbodylen = len - sizeof(int);
        unsigned int tuplen = tupbodylen + MINIMAL_TUPLE_DATA_OFFSET;
        MinimalTuple tuple = (MinimalTuple) readtup_alloc(state, tuplen);
        char       *tupbody = (char *) tuple + MINIMAL_TUPLE_DATA_OFFSET;
        HeapTupleData htup;

        /* read in the tuple proper */
        tuple->t_len = tuplen;
        LogicalTapeReadExact(state->tapeset, tapenum,
                                                 tupbody, tupbodylen);
        if (state->randomAccess)        /* need trailing length word? */
                LogicalTapeReadExact(state->tapeset, tapenum,
                                                         &tuplen, sizeof(tuplen));
        stup->tuple = (void *) tuple;
        /* set up first-column key value */
        htup.t_len = tuple->t_len + MINIMAL_TUPLE_OFFSET;
        htup.t_data = (HeapTupleHeader) ((char *) tuple - MINIMAL_TUPLE_OFFSET);
        stup->datum1 = heap_getattr(&htup,
                                                                state->sortKeys[0].ssup_attno,
                                                                state->tupDesc,
                                                                &stup->isnull1);
}

/*
 * Routines specialized for the CLUSTER case (HeapTuple data, with
 * comparisons per a btree index definition)
 */

static int
comparetup_cluster(const SortTuple *a, const SortTuple *b,
                                   Tuplesortstate *state)
{
        SortSupport sortKey = state->sortKeys;
        HeapTuple       ltup;
        HeapTuple       rtup;
        TupleDesc       tupDesc;
        int                     nkey;
        int32           compare;
        Datum           datum1,
                                datum2;
        bool            isnull1,
                                isnull2;
        AttrNumber      leading = state->indexInfo->ii_IndexAttrNumbers[0];

        /* Be prepared to compare additional sort keys */
        ltup = (HeapTuple) a->tuple;
        rtup = (HeapTuple) b->tuple;
        tupDesc = state->tupDesc;

        /* Compare the leading sort key, if it's simple */
        if (leading != 0)
        {
                compare = ApplySortComparator(a->datum1, a->isnull1,
                                                                          b->datum1, b->isnull1,
                                                                          sortKey);
                if (compare != 0)
                        return compare;

                if (sortKey->abbrev_converter)
                {
                        datum1 = heap_getattr(ltup, leading, tupDesc, &isnull1);
                        datum2 = heap_getattr(rtup, leading, tupDesc, &isnull2);

                        compare = ApplySortAbbrevFullComparator(datum1, isnull1,
                                                                                                        datum2, isnull2,
                                                                                                        sortKey);
                }
                if (compare != 0 || state->nKeys == 1)
                        return compare;
                /* Compare additional columns the hard way */
                sortKey++;
                nkey = 1;
        }
        else
        {
                /* Must compare all keys the hard way */
                nkey = 0;
        }

        if (state->indexInfo->ii_Expressions == NULL)
        {
                /* If not expression index, just compare the proper heap attrs */

                for (; nkey < state->nKeys; nkey++, sortKey++)
                {
                        AttrNumber      attno = state->indexInfo->ii_IndexAttrNumbers[nkey];

                        datum1 = heap_getattr(ltup, attno, tupDesc, &isnull1);
                        datum2 = heap_getattr(rtup, attno, tupDesc, &isnull2);

                        compare = ApplySortComparator(datum1, isnull1,
                                                                                  datum2, isnull2,
                                                                                  sortKey);
                        if (compare != 0)
                                return compare;
                }
        }
        else
        {
                /*
                 * In the expression index case, compute the whole index tuple and
                 * then compare values.  It would perhaps be faster to compute only as
                 * many columns as we need to compare, but that would require
                 * duplicating all the logic in FormIndexDatum.
                 */
                Datum           l_index_values[INDEX_MAX_KEYS];
                bool            l_index_isnull[INDEX_MAX_KEYS];
                Datum           r_index_values[INDEX_MAX_KEYS];
                bool            r_index_isnull[INDEX_MAX_KEYS];
                TupleTableSlot *ecxt_scantuple;

                /* Reset context each time to prevent memory leakage */
                ResetPerTupleExprContext(state->estate);

                ecxt_scantuple = GetPerTupleExprContext(state->estate)->ecxt_scantuple;

                ExecStoreHeapTuple(ltup, ecxt_scantuple, false);
                FormIndexDatum(state->indexInfo, ecxt_scantuple, state->estate,
                                           l_index_values, l_index_isnull);

                ExecStoreHeapTuple(rtup, ecxt_scantuple, false);
                FormIndexDatum(state->indexInfo, ecxt_scantuple, state->estate,
                                           r_index_values, r_index_isnull);

                for (; nkey < state->nKeys; nkey++, sortKey++)
                {
                        compare = ApplySortComparator(l_index_values[nkey],
                                                                                  l_index_isnull[nkey],
                                                                                  r_index_values[nkey],
                                                                                  r_index_isnull[nkey],
                                                                                  sortKey);
                        if (compare != 0)
                                return compare;
                }
        }

        return 0;
}

static void
copytup_cluster(Tuplesortstate *state, SortTuple *stup, void *tup)
{
        HeapTuple       tuple = (HeapTuple) tup;
        Datum           original;
        MemoryContext oldcontext = MemoryContextSwitchTo(state->tuplecontext);

        /* copy the tuple into sort storage */
        tuple = heap_copytuple(tuple);
        stup->tuple = (void *) tuple;
        USEMEM(state, GetMemoryChunkSpace(tuple));

        MemoryContextSwitchTo(oldcontext);

        /*
         * set up first-column key value, and potentially abbreviate, if it's a
         * simple column
         */
        if (state->indexInfo->ii_IndexAttrNumbers[0] == 0)
                return;

        original = heap_getattr(tuple,
                                                        state->indexInfo->ii_IndexAttrNumbers[0],
                                                        state->tupDesc,
                                                        &stup->isnull1);

        if (!state->sortKeys->abbrev_converter || stup->isnull1)
        {
                /*
                 * Store ordinary Datum representation, or NULL value.  If there is a
                 * converter it won't expect NULL values, and cost model is not
                 * required to account for NULL, so in that case we avoid calling
                 * converter and just set datum1 to zeroed representation (to be
                 * consistent, and to support cheap inequality tests for NULL
                 * abbreviated keys).
                 */
                stup->datum1 = original;
        }
        else if (!consider_abort_common(state))
        {
                /* Store abbreviated key representation */
                stup->datum1 = state->sortKeys->abbrev_converter(original,
                                                                                                                 state->sortKeys);
        }
        else
        {
                /* Abort abbreviation */
                int                     i;

                stup->datum1 = original;

                /*
                 * Set state to be consistent with never trying abbreviation.
                 *
                 * Alter datum1 representation in already-copied tuples, so as to
                 * ensure a consistent representation (current tuple was just
                 * handled).  It does not matter if some dumped tuples are already
                 * sorted on tape, since serialized tuples lack abbreviated keys
                 * (TSS_BUILDRUNS state prevents control reaching here in any case).
                 */
                for (i = 0; i < state->memtupcount; i++)
                {
                        SortTuple  *mtup = &state->memtuples[i];

                        tuple = (HeapTuple) mtup->tuple;
                        mtup->datum1 = heap_getattr(tuple,
                                                                                state->indexInfo->ii_IndexAttrNumbers[0],
                                                                                state->tupDesc,
                                                                                &mtup->isnull1);
                }
        }
}

static void
writetup_cluster(Tuplesortstate *state, int tapenum, SortTuple *stup)
{
        HeapTuple       tuple = (HeapTuple) stup->tuple;
        unsigned int tuplen = tuple->t_len + sizeof(ItemPointerData) + sizeof(int);

        /* We need to store t_self, but not other fields of HeapTupleData */
        LogicalTapeWrite(state->tapeset, tapenum,
                                         &tuplen, sizeof(tuplen));
        LogicalTapeWrite(state->tapeset, tapenum,
                                         &tuple->t_self, sizeof(ItemPointerData));
        LogicalTapeWrite(state->tapeset, tapenum,
                                         tuple->t_data, tuple->t_len);
        if (state->randomAccess)        /* need trailing length word? */
                LogicalTapeWrite(state->tapeset, tapenum,
                                                 &tuplen, sizeof(tuplen));

        if (!state->slabAllocatorUsed)
        {
                FREEMEM(state, GetMemoryChunkSpace(tuple));
                heap_freetuple(tuple);
        }
}

static void
readtup_cluster(Tuplesortstate *state, SortTuple *stup,
                                int tapenum, unsigned int tuplen)
{
        unsigned int t_len = tuplen - sizeof(ItemPointerData) - sizeof(int);
        HeapTuple       tuple = (HeapTuple) readtup_alloc(state,
                                                                                                  t_len + HEAPTUPLESIZE);

        /* Reconstruct the HeapTupleData header */
        tuple->t_data = (HeapTupleHeader) ((char *) tuple + HEAPTUPLESIZE);
        tuple->t_len = t_len;
        LogicalTapeReadExact(state->tapeset, tapenum,
                                                 &tuple->t_self, sizeof(ItemPointerData));
        /* We don't currently bother to reconstruct t_tableOid */
        tuple->t_tableOid = InvalidOid;
        /* Read in the tuple body */
        LogicalTapeReadExact(state->tapeset, tapenum,
                                                 tuple->t_data, tuple->t_len);
        if (state->randomAccess)        /* need trailing length word? */
                LogicalTapeReadExact(state->tapeset, tapenum,
                                                         &tuplen, sizeof(tuplen));
        stup->tuple = (void *) tuple;
        /* set up first-column key value, if it's a simple column */
        if (state->indexInfo->ii_IndexAttrNumbers[0] != 0)
                stup->datum1 = heap_getattr(tuple,
                                                                        state->indexInfo->ii_IndexAttrNumbers[0],
                                                                        state->tupDesc,
                                                                        &stup->isnull1);
}

/*
 * Routines specialized for IndexTuple case
 *
 * The btree and hash cases require separate comparison functions, but the
 * IndexTuple representation is the same so the copy/write/read support
 * functions can be shared.
 */

static int
comparetup_index_btree(const SortTuple *a, const SortTuple *b,
                                           Tuplesortstate *state)
{
        /*
         * This is similar to comparetup_heap(), but expects index tuples.  There
         * is also special handling for enforcing uniqueness, and special
         * treatment for equal keys at the end.
         */
        SortSupport sortKey = state->sortKeys;
        IndexTuple      tuple1;
        IndexTuple      tuple2;
        int                     keysz;
        TupleDesc       tupDes;
        bool            equal_hasnull = false;
        int                     nkey;
        int32           compare;
        Datum           datum1,
                                datum2;
        bool            isnull1,
                                isnull2;


        /* Compare the leading sort key */
        compare = ApplySortComparator(a->datum1, a->isnull1,
                                                                  b->datum1, b->isnull1,
                                                                  sortKey);
        if (compare != 0)
                return compare;

        /* Compare additional sort keys */
        tuple1 = (IndexTuple) a->tuple;
        tuple2 = (IndexTuple) b->tuple;
        keysz = state->nKeys;
        tupDes = RelationGetDescr(state->indexRel);

        if (sortKey->abbrev_converter)
        {
                datum1 = index_getattr(tuple1, 1, tupDes, &isnull1);
                datum2 = index_getattr(tuple2, 1, tupDes, &isnull2);

                compare = ApplySortAbbrevFullComparator(datum1, isnull1,
                                                                                                datum2, isnull2,
                                                                                                sortKey);
                if (compare != 0)
                        return compare;
        }

        /* they are equal, so we only need to examine one null flag */
        if (a->isnull1)
                equal_hasnull = true;

        sortKey++;
        for (nkey = 2; nkey <= keysz; nkey++, sortKey++)
        {
                datum1 = index_getattr(tuple1, nkey, tupDes, &isnull1);
                datum2 = index_getattr(tuple2, nkey, tupDes, &isnull2);

                compare = ApplySortComparator(datum1, isnull1,
                                                                          datum2, isnull2,
                                                                          sortKey);
                if (compare != 0)
                        return compare;         /* done when we find unequal attributes */

                /* they are equal, so we only need to examine one null flag */
                if (isnull1)
                        equal_hasnull = true;
        }

        /*
         * If btree has asked us to enforce uniqueness, complain if two equal
         * tuples are detected (unless there was at least one NULL field).
         *
         * It is sufficient to make the test here, because if two tuples are equal
         * they *must* get compared at some stage of the sort --- otherwise the
         * sort algorithm wouldn't have checked whether one must appear before the
         * other.
         */
        if (state->enforceUnique && !equal_hasnull)
        {
                Datum           values[INDEX_MAX_KEYS];
                bool            isnull[INDEX_MAX_KEYS];
                char       *key_desc;

                /*
                 * Some rather brain-dead implementations of qsort (such as the one in
                 * QNX 4) will sometimes call the comparison routine to compare a
                 * value to itself, but we always use our own implementation, which
                 * does not.
                 */
                Assert(tuple1 != tuple2);

                index_deform_tuple(tuple1, tupDes, values, isnull);

                key_desc = BuildIndexValueDescription(state->indexRel, values, isnull);

                ereport(ERROR,
                                (errcode(ERRCODE_UNIQUE_VIOLATION),
                                 errmsg("could not create unique index \"%s\"",
                                                RelationGetRelationName(state->indexRel)),
                                 key_desc ? errdetail("Key %s is duplicated.", key_desc) :
                                 errdetail("Duplicate keys exist."),
                                 errtableconstraint(state->heapRel,
                                                                        RelationGetRelationName(state->indexRel))));
        }

        /*
         * If key values are equal, we sort on ItemPointer.  This is required for
         * btree indexes, since heap TID is treated as an implicit last key
         * attribute in order to ensure that all keys in the index are physically
         * unique.
         */
        {
                BlockNumber blk1 = ItemPointerGetBlockNumber(&tuple1->t_tid);
                BlockNumber blk2 = ItemPointerGetBlockNumber(&tuple2->t_tid);

                if (blk1 != blk2)
                        return (blk1 < blk2) ? -1 : 1;
        }
        {
                OffsetNumber pos1 = ItemPointerGetOffsetNumber(&tuple1->t_tid);
                OffsetNumber pos2 = ItemPointerGetOffsetNumber(&tuple2->t_tid);

                if (pos1 != pos2)
                        return (pos1 < pos2) ? -1 : 1;
        }

        /* ItemPointer values should never be equal */
        Assert(false);

        return 0;
}

static int
comparetup_index_hash(const SortTuple *a, const SortTuple *b,
                                          Tuplesortstate *state)
{
        Bucket          bucket1;
        Bucket          bucket2;
        IndexTuple      tuple1;
        IndexTuple      tuple2;

        /*
         * Fetch hash keys and mask off bits we don't want to sort by. We know
         * that the first column of the index tuple is the hash key.
         */
        Assert(!a->isnull1);
        bucket1 = _hash_hashkey2bucket(DatumGetUInt32(a->datum1),
                                                                   state->max_buckets, state->high_mask,
                                                                   state->low_mask);
        Assert(!b->isnull1);
        bucket2 = _hash_hashkey2bucket(DatumGetUInt32(b->datum1),
                                                                   state->max_buckets, state->high_mask,
                                                                   state->low_mask);
        if (bucket1 > bucket2)
                return 1;
        else if (bucket1 < bucket2)
                return -1;

        /*
         * If hash values are equal, we sort on ItemPointer.  This does not affect
         * validity of the finished index, but it may be useful to have index
         * scans in physical order.
         */
        tuple1 = (IndexTuple) a->tuple;
        tuple2 = (IndexTuple) b->tuple;

        {
                BlockNumber blk1 = ItemPointerGetBlockNumber(&tuple1->t_tid);
                BlockNumber blk2 = ItemPointerGetBlockNumber(&tuple2->t_tid);

                if (blk1 != blk2)
                        return (blk1 < blk2) ? -1 : 1;
        }
        {
                OffsetNumber pos1 = ItemPointerGetOffsetNumber(&tuple1->t_tid);
                OffsetNumber pos2 = ItemPointerGetOffsetNumber(&tuple2->t_tid);

                if (pos1 != pos2)
                        return (pos1 < pos2) ? -1 : 1;
        }

        /* ItemPointer values should never be equal */
        Assert(false);

        return 0;
}

static void
copytup_index(Tuplesortstate *state, SortTuple *stup, void *tup)
{
        IndexTuple      tuple = (IndexTuple) tup;
        unsigned int tuplen = IndexTupleSize(tuple);
        IndexTuple      newtuple;
        Datum           original;

        /* copy the tuple into sort storage */
        newtuple = (IndexTuple) MemoryContextAlloc(state->tuplecontext, tuplen);
        memcpy(newtuple, tuple, tuplen);
        USEMEM(state, GetMemoryChunkSpace(newtuple));
        stup->tuple = (void *) newtuple;
        /* set up first-column key value */
        original = index_getattr(newtuple,
                                                         1,
                                                         RelationGetDescr(state->indexRel),
                                                         &stup->isnull1);

        if (!state->sortKeys->abbrev_converter || stup->isnull1)
        {
                /*
                 * Store ordinary Datum representation, or NULL value.  If there is a
                 * converter it won't expect NULL values, and cost model is not
                 * required to account for NULL, so in that case we avoid calling
                 * converter and just set datum1 to zeroed representation (to be
                 * consistent, and to support cheap inequality tests for NULL
                 * abbreviated keys).
                 */
                stup->datum1 = original;
        }
        else if (!consider_abort_common(state))
        {
                /* Store abbreviated key representation */
                stup->datum1 = state->sortKeys->abbrev_converter(original,
                                                                                                                 state->sortKeys);
        }
        else
        {
                /* Abort abbreviation */
                int                     i;

                stup->datum1 = original;

                /*
                 * Set state to be consistent with never trying abbreviation.
                 *
                 * Alter datum1 representation in already-copied tuples, so as to
                 * ensure a consistent representation (current tuple was just
                 * handled).  It does not matter if some dumped tuples are already
                 * sorted on tape, since serialized tuples lack abbreviated keys
                 * (TSS_BUILDRUNS state prevents control reaching here in any case).
                 */
                for (i = 0; i < state->memtupcount; i++)
                {
                        SortTuple  *mtup = &state->memtuples[i];

                        tuple = (IndexTuple) mtup->tuple;
                        mtup->datum1 = index_getattr(tuple,
                                                                                 1,
                                                                                 RelationGetDescr(state->indexRel),
                                                                                 &mtup->isnull1);
                }
        }
}

static void
writetup_index(Tuplesortstate *state, int tapenum, SortTuple *stup)
{
        IndexTuple      tuple = (IndexTuple) stup->tuple;
        unsigned int tuplen;

        tuplen = IndexTupleSize(tuple) + sizeof(tuplen);
        LogicalTapeWrite(state->tapeset, tapenum,
                                         (void *) &tuplen, sizeof(tuplen));
        LogicalTapeWrite(state->tapeset, tapenum,
                                         (void *) tuple, IndexTupleSize(tuple));
        if (state->randomAccess)        /* need trailing length word? */
                LogicalTapeWrite(state->tapeset, tapenum,
                                                 (void *) &tuplen, sizeof(tuplen));

        if (!state->slabAllocatorUsed)
        {
                FREEMEM(state, GetMemoryChunkSpace(tuple));
                pfree(tuple);
        }
}

static void
readtup_index(Tuplesortstate *state, SortTuple *stup,
                          int tapenum, unsigned int len)
{
        unsigned int tuplen = len - sizeof(unsigned int);
        IndexTuple      tuple = (IndexTuple) readtup_alloc(state, tuplen);

        LogicalTapeReadExact(state->tapeset, tapenum,
                                                 tuple, tuplen);
        if (state->randomAccess)        /* need trailing length word? */
                LogicalTapeReadExact(state->tapeset, tapenum,
                                                         &tuplen, sizeof(tuplen));
        stup->tuple = (void *) tuple;
        /* set up first-column key value */
        stup->datum1 = index_getattr(tuple,
                                                                 1,
                                                                 RelationGetDescr(state->indexRel),
                                                                 &stup->isnull1);
}

/*
 * Routines specialized for DatumTuple case
 */

static int
comparetup_datum(const SortTuple *a, const SortTuple *b, Tuplesortstate *state)
{
        int                     compare;

        compare = ApplySortComparator(a->datum1, a->isnull1,
                                                                  b->datum1, b->isnull1,
                                                                  state->sortKeys);
        if (compare != 0)
                return compare;

        /* if we have abbreviations, then "tuple" has the original value */

        if (state->sortKeys->abbrev_converter)
                compare = ApplySortAbbrevFullComparator(PointerGetDatum(a->tuple), a->isnull1,
                                                                                                PointerGetDatum(b->tuple), b->isnull1,
                                                                                                state->sortKeys);

        return compare;
}

static void
copytup_datum(Tuplesortstate *state, SortTuple *stup, void *tup)
{
        /* Not currently needed */
        elog(ERROR, "copytup_datum() should not be called");
}

static void
writetup_datum(Tuplesortstate *state, int tapenum, SortTuple *stup)
{
        void       *waddr;
        unsigned int tuplen;
        unsigned int writtenlen;

        if (stup->isnull1)
        {
                waddr = NULL;
                tuplen = 0;
        }
        else if (!state->tuples)
        {
                waddr = &stup->datum1;
                tuplen = sizeof(Datum);
        }
        else
        {
                waddr = stup->tuple;
                tuplen = datumGetSize(PointerGetDatum(stup->tuple), false, state->datumTypeLen);
                Assert(tuplen != 0);
        }

        writtenlen = tuplen + sizeof(unsigned int);

        LogicalTapeWrite(state->tapeset, tapenum,
                                         (void *) &writtenlen, sizeof(writtenlen));
        LogicalTapeWrite(state->tapeset, tapenum,
                                         waddr, tuplen);
        if (state->randomAccess)        /* need trailing length word? */
                LogicalTapeWrite(state->tapeset, tapenum,
                                                 (void *) &writtenlen, sizeof(writtenlen));

        if (!state->slabAllocatorUsed && stup->tuple)
        {
                FREEMEM(state, GetMemoryChunkSpace(stup->tuple));
                pfree(stup->tuple);
        }
}

static void
readtup_datum(Tuplesortstate *state, SortTuple *stup,
                          int tapenum, unsigned int len)
{
        unsigned int tuplen = len - sizeof(unsigned int);

        if (tuplen == 0)
        {
                /* it's NULL */
                stup->datum1 = (Datum) 0;
                stup->isnull1 = true;
                stup->tuple = NULL;
        }
        else if (!state->tuples)
        {
                Assert(tuplen == sizeof(Datum));
                LogicalTapeReadExact(state->tapeset, tapenum,
                                                         &stup->datum1, tuplen);
                stup->isnull1 = false;
                stup->tuple = NULL;
        }
        else
        {
                void       *raddr = readtup_alloc(state, tuplen);

                LogicalTapeReadExact(state->tapeset, tapenum,
                                                         raddr, tuplen);
                stup->datum1 = PointerGetDatum(raddr);
                stup->isnull1 = false;
                stup->tuple = raddr;
        }

        if (state->randomAccess)        /* need trailing length word? */
                LogicalTapeReadExact(state->tapeset, tapenum,
                                                         &tuplen, sizeof(tuplen));
}

/*
 * Parallel sort routines
 */

/*
 * tuplesort_estimate_shared - estimate required shared memory allocation
 *
 * nWorkers is an estimate of the number of workers (it's the number that
 * will be requested).
 */
Size
tuplesort_estimate_shared(int nWorkers)
{
        Size            tapesSize;

        Assert(nWorkers > 0);

        /* Make sure that BufFile shared state is MAXALIGN'd */
        tapesSize = mul_size(sizeof(TapeShare), nWorkers);
        tapesSize = MAXALIGN(add_size(tapesSize, offsetof(Sharedsort, tapes)));

        return tapesSize;
}

/*
 * tuplesort_initialize_shared - initialize shared tuplesort state
 *
 * Must be called from leader process before workers are launched, to
 * establish state needed up-front for worker tuplesortstates.  nWorkers
 * should match the argument passed to tuplesort_estimate_shared().
 */
void
tuplesort_initialize_shared(Sharedsort *shared, int nWorkers, dsm_segment *seg)
{
        int                     i;

        Assert(nWorkers > 0);

        SpinLockInit(&shared->mutex);
        shared->currentWorker = 0;
        shared->workersFinished = 0;
        SharedFileSetInit(&shared->fileset, seg);
        shared->nTapes = nWorkers;
        for (i = 0; i < nWorkers; i++)
        {
                shared->tapes[i].firstblocknumber = 0L;
        }
}

/*
 * tuplesort_attach_shared - attach to shared tuplesort state
 *
 * Must be called by all worker processes.
 */
void
tuplesort_attach_shared(Sharedsort *shared, dsm_segment *seg)
{
        /* Attach to SharedFileSet */
        SharedFileSetAttach(&shared->fileset, seg);
}

/*
 * worker_get_identifier - Assign and return ordinal identifier for worker
 *
 * The order in which these are assigned is not well defined, and should not
 * matter; worker numbers across parallel sort participants need only be
 * distinct and gapless.  logtape.c requires this.
 *
 * Note that the identifiers assigned from here have no relation to
 * ParallelWorkerNumber number, to avoid making any assumption about
 * caller's requirements.  However, we do follow the ParallelWorkerNumber
 * convention of representing a non-worker with worker number -1.  This
 * includes the leader, as well as serial Tuplesort processes.
 */
static int
worker_get_identifier(Tuplesortstate *state)
{
        Sharedsort *shared = state->shared;
        int                     worker;

        Assert(WORKER(state));

        SpinLockAcquire(&shared->mutex);
        worker = shared->currentWorker++;
        SpinLockRelease(&shared->mutex);

        return worker;
}

/*
 * worker_freeze_result_tape - freeze worker's result tape for leader
 *
 * This is called by workers just after the result tape has been determined,
 * instead of calling LogicalTapeFreeze() directly.  They do so because
 * workers require a few additional steps over similar serial
 * TSS_SORTEDONTAPE external sort cases, which also happen here.  The extra
 * steps are around freeing now unneeded resources, and representing to
 * leader that worker's input run is available for its merge.
 *
 * There should only be one final output run for each worker, which consists
 * of all tuples that were originally input into worker.
 */
static void
worker_freeze_result_tape(Tuplesortstate *state)
{
        Sharedsort *shared = state->shared;
        TapeShare       output;

        Assert(WORKER(state));
        Assert(state->result_tape != -1);
        Assert(state->memtupcount == 0);

        /*
         * Free most remaining memory, in case caller is sensitive to our holding
         * on to it.  memtuples may not be a tiny merge heap at this point.
         */
        pfree(state->memtuples);
        /* Be tidy */
        state->memtuples = NULL;
        state->memtupsize = 0;

        /*
         * Parallel worker requires result tape metadata, which is to be stored in
         * shared memory for leader
         */
        LogicalTapeFreeze(state->tapeset, state->result_tape, &output);

        /* Store properties of output tape, and update finished worker count */
        SpinLockAcquire(&shared->mutex);
        shared->tapes[state->worker] = output;
        shared->workersFinished++;
        SpinLockRelease(&shared->mutex);
}

/*
 * worker_nomergeruns - dump memtuples in worker, without merging
 *
 * This called as an alternative to mergeruns() with a worker when no
 * merging is required.
 */
static void
worker_nomergeruns(Tuplesortstate *state)
{
        Assert(WORKER(state));
        Assert(state->result_tape == -1);

        state->result_tape = state->tp_tapenum[state->destTape];
        worker_freeze_result_tape(state);
}

/*
 * leader_takeover_tapes - create tapeset for leader from worker tapes
 *
 * So far, leader Tuplesortstate has performed no actual sorting.  By now, all
 * sorting has occurred in workers, all of which must have already returned
 * from tuplesort_performsort().
 *
 * When this returns, leader process is left in a state that is virtually
 * indistinguishable from it having generated runs as a serial external sort
 * might have.
 */
static void
leader_takeover_tapes(Tuplesortstate *state)
{
        Sharedsort *shared = state->shared;
        int                     nParticipants = state->nParticipants;
        int                     workersFinished;
        int                     j;

        Assert(LEADER(state));
        Assert(nParticipants >= 1);

        SpinLockAcquire(&shared->mutex);
        workersFinished = shared->workersFinished;
        SpinLockRelease(&shared->mutex);

        if (nParticipants != workersFinished)
                elog(ERROR, "cannot take over tapes before all workers finish");

        /*
         * Create the tapeset from worker tapes, including a leader-owned tape at
         * the end.  Parallel workers are far more expensive than logical tapes,
         * so the number of tapes allocated here should never be excessive.
         *
         * We still have a leader tape, though it's not possible to write to it
         * due to restrictions in the shared fileset infrastructure used by
         * logtape.c.  It will never be written to in practice because
         * randomAccess is disallowed for parallel sorts.
         */
        inittapestate(state, nParticipants + 1);
        state->tapeset = LogicalTapeSetCreate(nParticipants + 1, shared->tapes,
                                                                                  &shared->fileset, state->worker);

        /* mergeruns() relies on currentRun for # of runs (in one-pass cases) */
        state->currentRun = nParticipants;

        /*
         * Initialize variables of Algorithm D to be consistent with runs from
         * workers having been generated in the leader.
         *
         * There will always be exactly 1 run per worker, and exactly one input
         * tape per run, because workers always output exactly 1 run, even when
         * there were no input tuples for workers to sort.
         */
        for (j = 0; j < state->maxTapes; j++)
        {
                /* One real run; no dummy runs for worker tapes */
                state->tp_fib[j] = 1;
                state->tp_runs[j] = 1;
                state->tp_dummy[j] = 0;
                state->tp_tapenum[j] = j;
        }
        /* Leader tape gets one dummy run, and no real runs */
        state->tp_fib[state->tapeRange] = 0;
        state->tp_runs[state->tapeRange] = 0;
        state->tp_dummy[state->tapeRange] = 1;

        state->Level = 1;
        state->destTape = 0;

        state->status = TSS_BUILDRUNS;
}

/*
 * Convenience routine to free a tuple previously loaded into sort memory
 */
static void
free_sort_tuple(Tuplesortstate *state, SortTuple *stup)
{
        FREEMEM(state, GetMemoryChunkSpace(stup->tuple));
        pfree(stup->tuple);
}