1 /*-------------------------------------------------------------------------
4 * Generalized tuple sorting routines.
6 * This module handles sorting of heap tuples, index tuples, or single
7 * Datums (and could easily support other kinds of sortable objects,
8 * if necessary). It works efficiently for both small and large amounts
9 * of data. Small amounts are sorted in-memory using qsort(). Large
10 * amounts are sorted using temporary files and a standard external sort
13 * See Knuth, volume 3, for more than you want to know about the external
14 * sorting algorithm. Historically, we divided the input into sorted runs
15 * using replacement selection, in the form of a priority tree implemented
16 * as a heap (essentially his Algorithm 5.2.3H), but now we only do that
17 * for the first run, and only if the run would otherwise end up being very
18 * short. We merge the runs using polyphase merge, Knuth's Algorithm
19 * 5.4.2D. The logical "tapes" used by Algorithm D are implemented by
20 * logtape.c, which avoids space wastage by recycling disk space as soon
21 * as each block is read from its "tape".
23 * We do not use Knuth's recommended data structure (Algorithm 5.4.1R) for
24 * the replacement selection, because it uses a fixed number of records
25 * in memory at all times. Since we are dealing with tuples that may vary
26 * considerably in size, we want to be able to vary the number of records
27 * kept in memory to ensure full utilization of the allowed sort memory
28 * space. So, we keep the tuples in a variable-size heap, with the next
29 * record to go out at the top of the heap. Like Algorithm 5.4.1R, each
30 * record is stored with the run number that it must go into, and we use
31 * (run number, key) as the ordering key for the heap. When the run number
32 * at the top of the heap changes, we know that no more records of the prior
33 * run are left in the heap. Note that there are in practice only ever two
34 * distinct run numbers, because since PostgreSQL 9.6, we only use
35 * replacement selection to form the first run.
37 * In PostgreSQL 9.6, a heap (based on Knuth's Algorithm H, with some small
38 * customizations) is only used with the aim of producing just one run,
39 * thereby avoiding all merging. Only the first run can use replacement
40 * selection, which is why there are now only two possible valid run
41 * numbers, and why heapification is customized to not distinguish between
42 * tuples in the second run (those will be quicksorted). We generally
43 * prefer a simple hybrid sort-merge strategy, where runs are sorted in much
44 * the same way as the entire input of an internal sort is sorted (using
45 * qsort()). The replacement_sort_tuples GUC controls the limited remaining
46 * use of replacement selection for the first run.
48 * There are several reasons to favor a hybrid sort-merge strategy.
49 * Maintaining a priority tree/heap has poor CPU cache characteristics.
50 * Furthermore, the growth in main memory sizes has greatly diminished the
51 * value of having runs that are larger than available memory, even in the
52 * case where there is partially sorted input and runs can be made far
53 * larger by using a heap. In most cases, a single-pass merge step is all
54 * that is required even when runs are no larger than available memory.
55 * Avoiding multiple merge passes was traditionally considered to be the
56 * major advantage of using replacement selection.
58 * The approximate amount of memory allowed for any one sort operation
59 * is specified in kilobytes by the caller (most pass work_mem). Initially,
60 * we absorb tuples and simply store them in an unsorted array as long as
61 * we haven't exceeded workMem. If we reach the end of the input without
62 * exceeding workMem, we sort the array using qsort() and subsequently return
63 * tuples just by scanning the tuple array sequentially. If we do exceed
64 * workMem, we begin to emit tuples into sorted runs in temporary tapes.
65 * When tuples are dumped in batch after quicksorting, we begin a new run
66 * with a new output tape (selected per Algorithm D). After the end of the
67 * input is reached, we dump out remaining tuples in memory into a final run
68 * (or two, when replacement selection is still used), then merge the runs
71 * When merging runs, we use a heap containing just the frontmost tuple from
72 * each source run; we repeatedly output the smallest tuple and replace it
73 * with the next tuple from its source tape (if any). When the heap empties,
74 * the merge is complete. The basic merge algorithm thus needs very little
75 * memory --- only M tuples for an M-way merge, and M is constrained to a
76 * small number. However, we can still make good use of our full workMem
77 * allocation by pre-reading additional blocks from each source tape. Without
78 * prereading, our access pattern to the temporary file would be very erratic;
79 * on average we'd read one block from each of M source tapes during the same
80 * time that we're writing M blocks to the output tape, so there is no
81 * sequentiality of access at all, defeating the read-ahead methods used by
82 * most Unix kernels. Worse, the output tape gets written into a very random
83 * sequence of blocks of the temp file, ensuring that things will be even
84 * worse when it comes time to read that tape. A straightforward merge pass
85 * thus ends up doing a lot of waiting for disk seeks. We can improve matters
86 * by prereading from each source tape sequentially, loading about workMem/M
87 * bytes from each tape in turn, and making the sequential blocks immediately
88 * available for reuse. This approach helps to localize both read and write
89 * accesses. The pre-reading is handled by logtape.c, we just tell it how
90 * much memory to use for the buffers.
92 * When the caller requests random access to the sort result, we form
93 * the final sorted run on a logical tape which is then "frozen", so
94 * that we can access it randomly. When the caller does not need random
95 * access, we return from tuplesort_performsort() as soon as we are down
96 * to one run per logical tape. The final merge is then performed
97 * on-the-fly as the caller repeatedly calls tuplesort_getXXX; this
98 * saves one cycle of writing all the data out to disk and reading it in.
100 * Before Postgres 8.2, we always used a seven-tape polyphase merge, on the
101 * grounds that 7 is the "sweet spot" on the tapes-to-passes curve according
102 * to Knuth's figure 70 (section 5.4.2). However, Knuth is assuming that
103 * tape drives are expensive beasts, and in particular that there will always
104 * be many more runs than tape drives. In our implementation a "tape drive"
105 * doesn't cost much more than a few Kb of memory buffers, so we can afford
106 * to have lots of them. In particular, if we can have as many tape drives
107 * as sorted runs, we can eliminate any repeated I/O at all. In the current
108 * code we determine the number of tapes M on the basis of workMem: we want
109 * workMem/M to be large enough that we read a fair amount of data each time
110 * we preread from a tape, so as to maintain the locality of access described
111 * above. Nonetheless, with large workMem we can have many tapes (but not
112 * too many -- see the comments in tuplesort_merge_order).
115 * Portions Copyright (c) 1996-2017, PostgreSQL Global Development Group
116 * Portions Copyright (c) 1994, Regents of the University of California
119 * src/backend/utils/sort/tuplesort.c
121 *-------------------------------------------------------------------------
124 #include "postgres.h"
128 #include "access/htup_details.h"
129 #include "access/nbtree.h"
130 #include "access/hash.h"
131 #include "catalog/index.h"
132 #include "catalog/pg_am.h"
133 #include "commands/tablespace.h"
134 #include "executor/executor.h"
135 #include "miscadmin.h"
136 #include "pg_trace.h"
137 #include "utils/datum.h"
138 #include "utils/logtape.h"
139 #include "utils/lsyscache.h"
140 #include "utils/memutils.h"
141 #include "utils/pg_rusage.h"
142 #include "utils/rel.h"
143 #include "utils/sortsupport.h"
144 #include "utils/tuplesort.h"
147 /* sort-type codes for sort__start probes */
151 #define CLUSTER_SORT 3
155 bool trace_sort = false;
158 #ifdef DEBUG_BOUNDED_SORT
159 bool optimize_bounded_sort = true;
164 * The objects we actually sort are SortTuple structs. These contain
165 * a pointer to the tuple proper (might be a MinimalTuple or IndexTuple),
166 * which is a separate palloc chunk --- we assume it is just one chunk and
167 * can be freed by a simple pfree() (except during merge, when we use a
168 * simple slab allocator). SortTuples also contain the tuple's first key
169 * column in Datum/nullflag format, and an index integer.
171 * Storing the first key column lets us save heap_getattr or index_getattr
172 * calls during tuple comparisons. We could extract and save all the key
173 * columns not just the first, but this would increase code complexity and
174 * overhead, and wouldn't actually save any comparison cycles in the common
175 * case where the first key determines the comparison result. Note that
176 * for a pass-by-reference datatype, datum1 points into the "tuple" storage.
178 * There is one special case: when the sort support infrastructure provides an
179 * "abbreviated key" representation, where the key is (typically) a pass by
180 * value proxy for a pass by reference type. In this case, the abbreviated key
181 * is stored in datum1 in place of the actual first key column.
183 * When sorting single Datums, the data value is represented directly by
184 * datum1/isnull1 for pass by value types (or null values). If the datatype is
185 * pass-by-reference and isnull1 is false, then "tuple" points to a separately
186 * palloc'd data value, otherwise "tuple" is NULL. The value of datum1 is then
187 * either the same pointer as "tuple", or is an abbreviated key value as
188 * described above. Accordingly, "tuple" is always used in preference to
189 * datum1 as the authoritative value for pass-by-reference cases.
191 * While building initial runs, tupindex holds the tuple's run number.
192 * Historically, the run number could meaningfully distinguish many runs, but
193 * it now only distinguishes RUN_FIRST and HEAP_RUN_NEXT, since replacement
194 * selection is always abandoned after the first run; no other run number
195 * should be represented here. During merge passes, we re-use it to hold the
196 * input tape number that each tuple in the heap was read from. tupindex goes
197 * unused if the sort occurs entirely in memory.
201 void *tuple; /* the tuple itself */
202 Datum datum1; /* value of first key column */
203 bool isnull1; /* is first key column NULL? */
204 int tupindex; /* see notes above */
208 * During merge, we use a pre-allocated set of fixed-size slots to hold
209 * tuples. To avoid palloc/pfree overhead.
211 * Merge doesn't require a lot of memory, so we can afford to waste some,
212 * by using gratuitously-sized slots. If a tuple is larger than 1 kB, the
213 * palloc() overhead is not significant anymore.
215 * 'nextfree' is valid when this chunk is in the free list. When in use, the
216 * slot holds a tuple.
218 #define SLAB_SLOT_SIZE 1024
220 typedef union SlabSlot
222 union SlabSlot *nextfree;
223 char buffer[SLAB_SLOT_SIZE];
227 * Possible states of a Tuplesort object. These denote the states that
228 * persist between calls of Tuplesort routines.
232 TSS_INITIAL, /* Loading tuples; still within memory limit */
233 TSS_BOUNDED, /* Loading tuples into bounded-size heap */
234 TSS_BUILDRUNS, /* Loading tuples; writing to tape */
235 TSS_SORTEDINMEM, /* Sort completed entirely in memory */
236 TSS_SORTEDONTAPE, /* Sort completed, final run is on tape */
237 TSS_FINALMERGE /* Performing final merge on-the-fly */
241 * Parameters for calculation of number of tapes to use --- see inittapes()
242 * and tuplesort_merge_order().
244 * In this calculation we assume that each tape will cost us about 1 blocks
245 * worth of buffer space. This ignores the overhead of all the other data
246 * structures needed for each tape, but it's probably close enough.
248 * MERGE_BUFFER_SIZE is how much data we'd like to read from each input
249 * tape during a preread cycle (see discussion at top of file).
251 #define MINORDER 6 /* minimum merge order */
252 #define MAXORDER 500 /* maximum merge order */
253 #define TAPE_BUFFER_OVERHEAD BLCKSZ
254 #define MERGE_BUFFER_SIZE (BLCKSZ * 32)
257 * Run numbers, used during external sort operations.
259 * HEAP_RUN_NEXT is only used for SortTuple.tupindex, never state.currentRun.
262 #define HEAP_RUN_NEXT INT_MAX
265 typedef int (*SortTupleComparator) (const SortTuple *a, const SortTuple *b,
266 Tuplesortstate *state);
269 * Private state of a Tuplesort operation.
271 struct Tuplesortstate
273 TupSortStatus status; /* enumerated value as shown above */
274 int nKeys; /* number of columns in sort key */
275 bool randomAccess; /* did caller request random access? */
276 bool bounded; /* did caller specify a maximum number of
277 * tuples to return? */
278 bool boundUsed; /* true if we made use of a bounded heap */
279 int bound; /* if bounded, the maximum number of tuples */
280 bool tuples; /* Can SortTuple.tuple ever be set? */
281 int64 availMem; /* remaining memory available, in bytes */
282 int64 allowedMem; /* total memory allowed, in bytes */
283 int maxTapes; /* number of tapes (Knuth's T) */
284 int tapeRange; /* maxTapes-1 (Knuth's P) */
285 MemoryContext sortcontext; /* memory context holding most sort data */
286 MemoryContext tuplecontext; /* sub-context of sortcontext for tuple data */
287 LogicalTapeSet *tapeset; /* logtape.c object for tapes in a temp file */
290 * These function pointers decouple the routines that must know what kind
291 * of tuple we are sorting from the routines that don't need to know it.
292 * They are set up by the tuplesort_begin_xxx routines.
294 * Function to compare two tuples; result is per qsort() convention, ie:
295 * <0, 0, >0 according as a<b, a=b, a>b. The API must match
296 * qsort_arg_comparator.
298 SortTupleComparator comparetup;
301 * Function to copy a supplied input tuple into palloc'd space and set up
302 * its SortTuple representation (ie, set tuple/datum1/isnull1). Also,
303 * state->availMem must be decreased by the amount of space used for the
304 * tuple copy (note the SortTuple struct itself is not counted).
306 void (*copytup) (Tuplesortstate *state, SortTuple *stup, void *tup);
309 * Function to write a stored tuple onto tape. The representation of the
310 * tuple on tape need not be the same as it is in memory; requirements on
311 * the tape representation are given below. Unless the slab allocator is
312 * used, after writing the tuple, pfree() the out-of-line data (not the
313 * SortTuple struct!), and increase state->availMem by the amount of
314 * memory space thereby released.
316 void (*writetup) (Tuplesortstate *state, int tapenum,
320 * Function to read a stored tuple from tape back into memory. 'len' is
321 * the already-read length of the stored tuple. The tuple is allocated
322 * from the slab memory arena, or is palloc'd, see readtup_alloc().
324 void (*readtup) (Tuplesortstate *state, SortTuple *stup,
325 int tapenum, unsigned int len);
328 * This array holds the tuples now in sort memory. If we are in state
329 * INITIAL, the tuples are in no particular order; if we are in state
330 * SORTEDINMEM, the tuples are in final sorted order; in states BUILDRUNS
331 * and FINALMERGE, the tuples are organized in "heap" order per Algorithm
332 * H. In state SORTEDONTAPE, the array is not used.
334 SortTuple *memtuples; /* array of SortTuple structs */
335 int memtupcount; /* number of tuples currently present */
336 int memtupsize; /* allocated length of memtuples array */
337 bool growmemtuples; /* memtuples' growth still underway? */
340 * Memory for tuples is sometimes allocated using a simple slab allocator,
341 * rather than with palloc(). Currently, we switch to slab allocation
342 * when we start merging. Merging only needs to keep a small, fixed
343 * number of tuples in memory at any time, so we can avoid the
344 * palloc/pfree overhead by recycling a fixed number of fixed-size slots
345 * to hold the tuples.
347 * For the slab, we use one large allocation, divided into SLAB_SLOT_SIZE
348 * slots. The allocation is sized to have one slot per tape, plus one
349 * additional slot. We need that many slots to hold all the tuples kept
350 * in the heap during merge, plus the one we have last returned from the
351 * sort, with tuplesort_gettuple.
353 * Initially, all the slots are kept in a linked list of free slots. When
354 * a tuple is read from a tape, it is put to the next available slot, if
355 * it fits. If the tuple is larger than SLAB_SLOT_SIZE, it is palloc'd
358 * When we're done processing a tuple, we return the slot back to the free
359 * list, or pfree() if it was palloc'd. We know that a tuple was
360 * allocated from the slab, if its pointer value is between
361 * slabMemoryBegin and -End.
363 * When the slab allocator is used, the USEMEM/LACKMEM mechanism of
364 * tracking memory usage is not used.
366 bool slabAllocatorUsed;
368 char *slabMemoryBegin; /* beginning of slab memory arena */
369 char *slabMemoryEnd; /* end of slab memory arena */
370 SlabSlot *slabFreeHead; /* head of free list */
372 /* Buffer size to use for reading input tapes, during merge. */
373 size_t read_buffer_size;
376 * When we return a tuple to the caller in tuplesort_gettuple_XXX, that
377 * came from a tape (that is, in TSS_SORTEDONTAPE or TSS_FINALMERGE
378 * modes), we remember the tuple in 'lastReturnedTuple', so that we can
379 * recycle the memory on next gettuple call.
381 void *lastReturnedTuple;
384 * While building initial runs, this indicates if the replacement
385 * selection strategy is in use. When it isn't, then a simple hybrid
386 * sort-merge strategy is in use instead (runs are quicksorted).
391 * While building initial runs, this is the current output run number
392 * (starting at RUN_FIRST). Afterwards, it is the number of initial runs
398 * Unless otherwise noted, all pointer variables below are pointers to
399 * arrays of length maxTapes, holding per-tape data.
403 * This variable is only used during merge passes. mergeactive[i] is true
404 * if we are reading an input run from (actual) tape number i and have not
405 * yet exhausted that run.
407 bool *mergeactive; /* active input run source? */
410 * Variables for Algorithm D. Note that destTape is a "logical" tape
411 * number, ie, an index into the tp_xxx[] arrays. Be careful to keep
412 * "logical" and "actual" tape numbers straight!
414 int Level; /* Knuth's l */
415 int destTape; /* current output tape (Knuth's j, less 1) */
416 int *tp_fib; /* Target Fibonacci run counts (A[]) */
417 int *tp_runs; /* # of real runs on each tape */
418 int *tp_dummy; /* # of dummy runs for each tape (D[]) */
419 int *tp_tapenum; /* Actual tape numbers (TAPE[]) */
420 int activeTapes; /* # of active input tapes in merge pass */
423 * These variables are used after completion of sorting to keep track of
424 * the next tuple to return. (In the tape case, the tape's current read
425 * position is also critical state.)
427 int result_tape; /* actual tape number of finished output */
428 int current; /* array index (only used if SORTEDINMEM) */
429 bool eof_reached; /* reached EOF (needed for cursors) */
431 /* markpos_xxx holds marked position for mark and restore */
432 long markpos_block; /* tape block# (only used if SORTEDONTAPE) */
433 int markpos_offset; /* saved "current", or offset in tape block */
434 bool markpos_eof; /* saved "eof_reached" */
437 * The sortKeys variable is used by every case other than the hash index
438 * case; it is set by tuplesort_begin_xxx. tupDesc is only used by the
439 * MinimalTuple and CLUSTER routines, though.
442 SortSupport sortKeys; /* array of length nKeys */
445 * This variable is shared by the single-key MinimalTuple case and the
446 * Datum case (which both use qsort_ssup()). Otherwise it's NULL.
451 * Additional state for managing "abbreviated key" sortsupport routines
452 * (which currently may be used by all cases except the hash index case).
453 * Tracks the intervals at which the optimization's effectiveness is
456 int64 abbrevNext; /* Tuple # at which to next check
460 * These variables are specific to the CLUSTER case; they are set by
461 * tuplesort_begin_cluster.
463 IndexInfo *indexInfo; /* info about index being used for reference */
464 EState *estate; /* for evaluating index expressions */
467 * These variables are specific to the IndexTuple case; they are set by
468 * tuplesort_begin_index_xxx and used only by the IndexTuple routines.
470 Relation heapRel; /* table the index is being built on */
471 Relation indexRel; /* index being built */
473 /* These are specific to the index_btree subcase: */
474 bool enforceUnique; /* complain if we find duplicate tuples */
476 /* These are specific to the index_hash subcase: */
477 uint32 high_mask; /* masks for sortable part of hash code */
482 * These variables are specific to the Datum case; they are set by
483 * tuplesort_begin_datum and used only by the DatumTuple routines.
486 /* we need typelen in order to know how to copy the Datums. */
490 * Resource snapshot for time of sort start.
498 * Is the given tuple allocated from the slab memory arena?
500 #define IS_SLAB_SLOT(state, tuple) \
501 ((char *) (tuple) >= (state)->slabMemoryBegin && \
502 (char *) (tuple) < (state)->slabMemoryEnd)
505 * Return the given tuple to the slab memory free list, or free it
506 * if it was palloc'd.
508 #define RELEASE_SLAB_SLOT(state, tuple) \
510 SlabSlot *buf = (SlabSlot *) tuple; \
512 if (IS_SLAB_SLOT((state), buf)) \
514 buf->nextfree = (state)->slabFreeHead; \
515 (state)->slabFreeHead = buf; \
520 #define COMPARETUP(state,a,b) ((*(state)->comparetup) (a, b, state))
521 #define COPYTUP(state,stup,tup) ((*(state)->copytup) (state, stup, tup))
522 #define WRITETUP(state,tape,stup) ((*(state)->writetup) (state, tape, stup))
523 #define READTUP(state,stup,tape,len) ((*(state)->readtup) (state, stup, tape, len))
524 #define LACKMEM(state) ((state)->availMem < 0 && !(state)->slabAllocatorUsed)
525 #define USEMEM(state,amt) ((state)->availMem -= (amt))
526 #define FREEMEM(state,amt) ((state)->availMem += (amt))
529 * NOTES about on-tape representation of tuples:
531 * We require the first "unsigned int" of a stored tuple to be the total size
532 * on-tape of the tuple, including itself (so it is never zero; an all-zero
533 * unsigned int is used to delimit runs). The remainder of the stored tuple
534 * may or may not match the in-memory representation of the tuple ---
535 * any conversion needed is the job of the writetup and readtup routines.
537 * If state->randomAccess is true, then the stored representation of the
538 * tuple must be followed by another "unsigned int" that is a copy of the
539 * length --- so the total tape space used is actually sizeof(unsigned int)
540 * more than the stored length value. This allows read-backwards. When
541 * randomAccess is not true, the write/read routines may omit the extra
544 * writetup is expected to write both length words as well as the tuple
545 * data. When readtup is called, the tape is positioned just after the
546 * front length word; readtup must read the tuple data and advance past
547 * the back length word (if present).
549 * The write/read routines can make use of the tuple description data
550 * stored in the Tuplesortstate record, if needed. They are also expected
551 * to adjust state->availMem by the amount of memory space (not tape space!)
552 * released or consumed. There is no error return from either writetup
553 * or readtup; they should ereport() on failure.
556 * NOTES about memory consumption calculations:
558 * We count space allocated for tuples against the workMem limit, plus
559 * the space used by the variable-size memtuples array. Fixed-size space
560 * is not counted; it's small enough to not be interesting.
562 * Note that we count actual space used (as shown by GetMemoryChunkSpace)
563 * rather than the originally-requested size. This is important since
564 * palloc can add substantial overhead. It's not a complete answer since
565 * we won't count any wasted space in palloc allocation blocks, but it's
566 * a lot better than what we were doing before 7.3. As of 9.6, a
567 * separate memory context is used for caller passed tuples. Resetting
568 * it at certain key increments significantly ameliorates fragmentation.
569 * Note that this places a responsibility on readtup and copytup routines
570 * to use the right memory context for these tuples (and to not use the
571 * reset context for anything whose lifetime needs to span multiple
572 * external sort runs).
575 /* When using this macro, beware of double evaluation of len */
576 #define LogicalTapeReadExact(tapeset, tapenum, ptr, len) \
578 if (LogicalTapeRead(tapeset, tapenum, ptr, len) != (size_t) (len)) \
579 elog(ERROR, "unexpected end of data"); \
583 static Tuplesortstate *tuplesort_begin_common(int workMem, bool randomAccess);
584 static void puttuple_common(Tuplesortstate *state, SortTuple *tuple);
585 static bool consider_abort_common(Tuplesortstate *state);
586 static bool useselection(Tuplesortstate *state);
587 static void inittapes(Tuplesortstate *state);
588 static void selectnewtape(Tuplesortstate *state);
589 static void init_slab_allocator(Tuplesortstate *state, int numSlots);
590 static void mergeruns(Tuplesortstate *state);
591 static void mergeonerun(Tuplesortstate *state);
592 static void beginmerge(Tuplesortstate *state);
593 static bool mergereadnext(Tuplesortstate *state, int srcTape, SortTuple *stup);
594 static void dumptuples(Tuplesortstate *state, bool alltuples);
595 static void dumpbatch(Tuplesortstate *state, bool alltuples);
596 static void make_bounded_heap(Tuplesortstate *state);
597 static void sort_bounded_heap(Tuplesortstate *state);
598 static void tuplesort_sort_memtuples(Tuplesortstate *state);
599 static void tuplesort_heap_insert(Tuplesortstate *state, SortTuple *tuple,
601 static void tuplesort_heap_replace_top(Tuplesortstate *state, SortTuple *tuple,
603 static void tuplesort_heap_delete_top(Tuplesortstate *state, bool checkIndex);
604 static void reversedirection(Tuplesortstate *state);
605 static unsigned int getlen(Tuplesortstate *state, int tapenum, bool eofOK);
606 static void markrunend(Tuplesortstate *state, int tapenum);
607 static void *readtup_alloc(Tuplesortstate *state, Size tuplen);
608 static int comparetup_heap(const SortTuple *a, const SortTuple *b,
609 Tuplesortstate *state);
610 static void copytup_heap(Tuplesortstate *state, SortTuple *stup, void *tup);
611 static void writetup_heap(Tuplesortstate *state, int tapenum,
613 static void readtup_heap(Tuplesortstate *state, SortTuple *stup,
614 int tapenum, unsigned int len);
615 static int comparetup_cluster(const SortTuple *a, const SortTuple *b,
616 Tuplesortstate *state);
617 static void copytup_cluster(Tuplesortstate *state, SortTuple *stup, void *tup);
618 static void writetup_cluster(Tuplesortstate *state, int tapenum,
620 static void readtup_cluster(Tuplesortstate *state, SortTuple *stup,
621 int tapenum, unsigned int len);
622 static int comparetup_index_btree(const SortTuple *a, const SortTuple *b,
623 Tuplesortstate *state);
624 static int comparetup_index_hash(const SortTuple *a, const SortTuple *b,
625 Tuplesortstate *state);
626 static void copytup_index(Tuplesortstate *state, SortTuple *stup, void *tup);
627 static void writetup_index(Tuplesortstate *state, int tapenum,
629 static void readtup_index(Tuplesortstate *state, SortTuple *stup,
630 int tapenum, unsigned int len);
631 static int comparetup_datum(const SortTuple *a, const SortTuple *b,
632 Tuplesortstate *state);
633 static void copytup_datum(Tuplesortstate *state, SortTuple *stup, void *tup);
634 static void writetup_datum(Tuplesortstate *state, int tapenum,
636 static void readtup_datum(Tuplesortstate *state, SortTuple *stup,
637 int tapenum, unsigned int len);
638 static void free_sort_tuple(Tuplesortstate *state, SortTuple *stup);
641 * Special versions of qsort just for SortTuple objects. qsort_tuple() sorts
642 * any variant of SortTuples, using the appropriate comparetup function.
643 * qsort_ssup() is specialized for the case where the comparetup function
644 * reduces to ApplySortComparator(), that is single-key MinimalTuple sorts
647 #include "qsort_tuple.c"
651 * tuplesort_begin_xxx
653 * Initialize for a tuple sort operation.
655 * After calling tuplesort_begin, the caller should call tuplesort_putXXX
656 * zero or more times, then call tuplesort_performsort when all the tuples
657 * have been supplied. After performsort, retrieve the tuples in sorted
658 * order by calling tuplesort_getXXX until it returns false/NULL. (If random
659 * access was requested, rescan, markpos, and restorepos can also be called.)
660 * Call tuplesort_end to terminate the operation and release memory/disk space.
662 * Each variant of tuplesort_begin has a workMem parameter specifying the
663 * maximum number of kilobytes of RAM to use before spilling data to disk.
664 * (The normal value of this parameter is work_mem, but some callers use
665 * other values.) Each variant also has a randomAccess parameter specifying
666 * whether the caller needs non-sequential access to the sort result.
669 static Tuplesortstate *
670 tuplesort_begin_common(int workMem, bool randomAccess)
672 Tuplesortstate *state;
673 MemoryContext sortcontext;
674 MemoryContext tuplecontext;
675 MemoryContext oldcontext;
678 * Create a working memory context for this sort operation. All data
679 * needed by the sort will live inside this context.
681 sortcontext = AllocSetContextCreate(CurrentMemoryContext,
683 ALLOCSET_DEFAULT_SIZES);
686 * Caller tuple (e.g. IndexTuple) memory context.
688 * A dedicated child context used exclusively for caller passed tuples
689 * eases memory management. Resetting at key points reduces
690 * fragmentation. Note that the memtuples array of SortTuples is allocated
691 * in the parent context, not this context, because there is no need to
692 * free memtuples early.
694 tuplecontext = AllocSetContextCreate(sortcontext,
696 ALLOCSET_DEFAULT_SIZES);
699 * Make the Tuplesortstate within the per-sort context. This way, we
700 * don't need a separate pfree() operation for it at shutdown.
702 oldcontext = MemoryContextSwitchTo(sortcontext);
704 state = (Tuplesortstate *) palloc0(sizeof(Tuplesortstate));
708 pg_rusage_init(&state->ru_start);
711 state->status = TSS_INITIAL;
712 state->randomAccess = randomAccess;
713 state->bounded = false;
714 state->tuples = true;
715 state->boundUsed = false;
716 state->allowedMem = workMem * (int64) 1024;
717 state->availMem = state->allowedMem;
718 state->sortcontext = sortcontext;
719 state->tuplecontext = tuplecontext;
720 state->tapeset = NULL;
722 state->memtupcount = 0;
725 * Initial size of array must be more than ALLOCSET_SEPARATE_THRESHOLD;
726 * see comments in grow_memtuples().
728 state->memtupsize = Max(1024,
729 ALLOCSET_SEPARATE_THRESHOLD / sizeof(SortTuple) + 1);
731 state->growmemtuples = true;
732 state->slabAllocatorUsed = false;
733 state->memtuples = (SortTuple *) palloc(state->memtupsize * sizeof(SortTuple));
735 USEMEM(state, GetMemoryChunkSpace(state->memtuples));
737 /* workMem must be large enough for the minimal memtuples array */
739 elog(ERROR, "insufficient memory allowed for sort");
741 state->currentRun = RUN_FIRST;
744 * maxTapes, tapeRange, and Algorithm D variables will be initialized by
745 * inittapes(), if needed
748 state->result_tape = -1; /* flag that result tape has not been formed */
750 MemoryContextSwitchTo(oldcontext);
756 tuplesort_begin_heap(TupleDesc tupDesc,
757 int nkeys, AttrNumber *attNums,
758 Oid *sortOperators, Oid *sortCollations,
759 bool *nullsFirstFlags,
760 int workMem, bool randomAccess)
762 Tuplesortstate *state = tuplesort_begin_common(workMem, randomAccess);
763 MemoryContext oldcontext;
766 oldcontext = MemoryContextSwitchTo(state->sortcontext);
768 AssertArg(nkeys > 0);
773 "begin tuple sort: nkeys = %d, workMem = %d, randomAccess = %c",
774 nkeys, workMem, randomAccess ? 't' : 'f');
777 state->nKeys = nkeys;
779 TRACE_POSTGRESQL_SORT_START(HEAP_SORT,
780 false, /* no unique check */
785 state->comparetup = comparetup_heap;
786 state->copytup = copytup_heap;
787 state->writetup = writetup_heap;
788 state->readtup = readtup_heap;
790 state->tupDesc = tupDesc; /* assume we need not copy tupDesc */
791 state->abbrevNext = 10;
793 /* Prepare SortSupport data for each column */
794 state->sortKeys = (SortSupport) palloc0(nkeys * sizeof(SortSupportData));
796 for (i = 0; i < nkeys; i++)
798 SortSupport sortKey = state->sortKeys + i;
800 AssertArg(attNums[i] != 0);
801 AssertArg(sortOperators[i] != 0);
803 sortKey->ssup_cxt = CurrentMemoryContext;
804 sortKey->ssup_collation = sortCollations[i];
805 sortKey->ssup_nulls_first = nullsFirstFlags[i];
806 sortKey->ssup_attno = attNums[i];
807 /* Convey if abbreviation optimization is applicable in principle */
808 sortKey->abbreviate = (i == 0);
810 PrepareSortSupportFromOrderingOp(sortOperators[i], sortKey);
814 * The "onlyKey" optimization cannot be used with abbreviated keys, since
815 * tie-breaker comparisons may be required. Typically, the optimization
816 * is only of value to pass-by-value types anyway, whereas abbreviated
817 * keys are typically only of value to pass-by-reference types.
819 if (nkeys == 1 && !state->sortKeys->abbrev_converter)
820 state->onlyKey = state->sortKeys;
822 MemoryContextSwitchTo(oldcontext);
828 tuplesort_begin_cluster(TupleDesc tupDesc,
830 int workMem, bool randomAccess)
832 Tuplesortstate *state = tuplesort_begin_common(workMem, randomAccess);
833 ScanKey indexScanKey;
834 MemoryContext oldcontext;
837 Assert(indexRel->rd_rel->relam == BTREE_AM_OID);
839 oldcontext = MemoryContextSwitchTo(state->sortcontext);
844 "begin tuple sort: nkeys = %d, workMem = %d, randomAccess = %c",
845 RelationGetNumberOfAttributes(indexRel),
846 workMem, randomAccess ? 't' : 'f');
849 state->nKeys = RelationGetNumberOfAttributes(indexRel);
851 TRACE_POSTGRESQL_SORT_START(CLUSTER_SORT,
852 false, /* no unique check */
857 state->comparetup = comparetup_cluster;
858 state->copytup = copytup_cluster;
859 state->writetup = writetup_cluster;
860 state->readtup = readtup_cluster;
861 state->abbrevNext = 10;
863 state->indexInfo = BuildIndexInfo(indexRel);
865 state->tupDesc = tupDesc; /* assume we need not copy tupDesc */
867 indexScanKey = _bt_mkscankey_nodata(indexRel);
869 if (state->indexInfo->ii_Expressions != NULL)
871 TupleTableSlot *slot;
872 ExprContext *econtext;
875 * We will need to use FormIndexDatum to evaluate the index
876 * expressions. To do that, we need an EState, as well as a
877 * TupleTableSlot to put the table tuples into. The econtext's
878 * scantuple has to point to that slot, too.
880 state->estate = CreateExecutorState();
881 slot = MakeSingleTupleTableSlot(tupDesc);
882 econtext = GetPerTupleExprContext(state->estate);
883 econtext->ecxt_scantuple = slot;
886 /* Prepare SortSupport data for each column */
887 state->sortKeys = (SortSupport) palloc0(state->nKeys *
888 sizeof(SortSupportData));
890 for (i = 0; i < state->nKeys; i++)
892 SortSupport sortKey = state->sortKeys + i;
893 ScanKey scanKey = indexScanKey + i;
896 sortKey->ssup_cxt = CurrentMemoryContext;
897 sortKey->ssup_collation = scanKey->sk_collation;
898 sortKey->ssup_nulls_first =
899 (scanKey->sk_flags & SK_BT_NULLS_FIRST) != 0;
900 sortKey->ssup_attno = scanKey->sk_attno;
901 /* Convey if abbreviation optimization is applicable in principle */
902 sortKey->abbreviate = (i == 0);
904 AssertState(sortKey->ssup_attno != 0);
906 strategy = (scanKey->sk_flags & SK_BT_DESC) != 0 ?
907 BTGreaterStrategyNumber : BTLessStrategyNumber;
909 PrepareSortSupportFromIndexRel(indexRel, strategy, sortKey);
912 _bt_freeskey(indexScanKey);
914 MemoryContextSwitchTo(oldcontext);
920 tuplesort_begin_index_btree(Relation heapRel,
923 int workMem, bool randomAccess)
925 Tuplesortstate *state = tuplesort_begin_common(workMem, randomAccess);
926 ScanKey indexScanKey;
927 MemoryContext oldcontext;
930 oldcontext = MemoryContextSwitchTo(state->sortcontext);
935 "begin index sort: unique = %c, workMem = %d, randomAccess = %c",
936 enforceUnique ? 't' : 'f',
937 workMem, randomAccess ? 't' : 'f');
940 state->nKeys = RelationGetNumberOfAttributes(indexRel);
942 TRACE_POSTGRESQL_SORT_START(INDEX_SORT,
948 state->comparetup = comparetup_index_btree;
949 state->copytup = copytup_index;
950 state->writetup = writetup_index;
951 state->readtup = readtup_index;
952 state->abbrevNext = 10;
954 state->heapRel = heapRel;
955 state->indexRel = indexRel;
956 state->enforceUnique = enforceUnique;
958 indexScanKey = _bt_mkscankey_nodata(indexRel);
959 state->nKeys = RelationGetNumberOfAttributes(indexRel);
961 /* Prepare SortSupport data for each column */
962 state->sortKeys = (SortSupport) palloc0(state->nKeys *
963 sizeof(SortSupportData));
965 for (i = 0; i < state->nKeys; i++)
967 SortSupport sortKey = state->sortKeys + i;
968 ScanKey scanKey = indexScanKey + i;
971 sortKey->ssup_cxt = CurrentMemoryContext;
972 sortKey->ssup_collation = scanKey->sk_collation;
973 sortKey->ssup_nulls_first =
974 (scanKey->sk_flags & SK_BT_NULLS_FIRST) != 0;
975 sortKey->ssup_attno = scanKey->sk_attno;
976 /* Convey if abbreviation optimization is applicable in principle */
977 sortKey->abbreviate = (i == 0);
979 AssertState(sortKey->ssup_attno != 0);
981 strategy = (scanKey->sk_flags & SK_BT_DESC) != 0 ?
982 BTGreaterStrategyNumber : BTLessStrategyNumber;
984 PrepareSortSupportFromIndexRel(indexRel, strategy, sortKey);
987 _bt_freeskey(indexScanKey);
989 MemoryContextSwitchTo(oldcontext);
995 tuplesort_begin_index_hash(Relation heapRel,
1000 int workMem, bool randomAccess)
1002 Tuplesortstate *state = tuplesort_begin_common(workMem, randomAccess);
1003 MemoryContext oldcontext;
1005 oldcontext = MemoryContextSwitchTo(state->sortcontext);
1010 "begin index sort: high_mask = 0x%x, low_mask = 0x%x, "
1011 "max_buckets = 0x%x, workMem = %d, randomAccess = %c",
1015 workMem, randomAccess ? 't' : 'f');
1018 state->nKeys = 1; /* Only one sort column, the hash code */
1020 state->comparetup = comparetup_index_hash;
1021 state->copytup = copytup_index;
1022 state->writetup = writetup_index;
1023 state->readtup = readtup_index;
1025 state->heapRel = heapRel;
1026 state->indexRel = indexRel;
1028 state->high_mask = high_mask;
1029 state->low_mask = low_mask;
1030 state->max_buckets = max_buckets;
1032 MemoryContextSwitchTo(oldcontext);
1038 tuplesort_begin_datum(Oid datumType, Oid sortOperator, Oid sortCollation,
1039 bool nullsFirstFlag,
1040 int workMem, bool randomAccess)
1042 Tuplesortstate *state = tuplesort_begin_common(workMem, randomAccess);
1043 MemoryContext oldcontext;
1047 oldcontext = MemoryContextSwitchTo(state->sortcontext);
1052 "begin datum sort: workMem = %d, randomAccess = %c",
1053 workMem, randomAccess ? 't' : 'f');
1056 state->nKeys = 1; /* always a one-column sort */
1058 TRACE_POSTGRESQL_SORT_START(DATUM_SORT,
1059 false, /* no unique check */
1064 state->comparetup = comparetup_datum;
1065 state->copytup = copytup_datum;
1066 state->writetup = writetup_datum;
1067 state->readtup = readtup_datum;
1068 state->abbrevNext = 10;
1070 state->datumType = datumType;
1072 /* lookup necessary attributes of the datum type */
1073 get_typlenbyval(datumType, &typlen, &typbyval);
1074 state->datumTypeLen = typlen;
1075 state->tuples = !typbyval;
1077 /* Prepare SortSupport data */
1078 state->sortKeys = (SortSupport) palloc0(sizeof(SortSupportData));
1080 state->sortKeys->ssup_cxt = CurrentMemoryContext;
1081 state->sortKeys->ssup_collation = sortCollation;
1082 state->sortKeys->ssup_nulls_first = nullsFirstFlag;
1085 * Abbreviation is possible here only for by-reference types. In theory,
1086 * a pass-by-value datatype could have an abbreviated form that is cheaper
1087 * to compare. In a tuple sort, we could support that, because we can
1088 * always extract the original datum from the tuple is needed. Here, we
1089 * can't, because a datum sort only stores a single copy of the datum; the
1090 * "tuple" field of each sortTuple is NULL.
1092 state->sortKeys->abbreviate = !typbyval;
1094 PrepareSortSupportFromOrderingOp(sortOperator, state->sortKeys);
1097 * The "onlyKey" optimization cannot be used with abbreviated keys, since
1098 * tie-breaker comparisons may be required. Typically, the optimization
1099 * is only of value to pass-by-value types anyway, whereas abbreviated
1100 * keys are typically only of value to pass-by-reference types.
1102 if (!state->sortKeys->abbrev_converter)
1103 state->onlyKey = state->sortKeys;
1105 MemoryContextSwitchTo(oldcontext);
1111 * tuplesort_set_bound
1113 * Advise tuplesort that at most the first N result tuples are required.
1115 * Must be called before inserting any tuples. (Actually, we could allow it
1116 * as long as the sort hasn't spilled to disk, but there seems no need for
1117 * delayed calls at the moment.)
1119 * This is a hint only. The tuplesort may still return more tuples than
1123 tuplesort_set_bound(Tuplesortstate *state, int64 bound)
1125 /* Assert we're called before loading any tuples */
1126 Assert(state->status == TSS_INITIAL);
1127 Assert(state->memtupcount == 0);
1128 Assert(!state->bounded);
1130 #ifdef DEBUG_BOUNDED_SORT
1131 /* Honor GUC setting that disables the feature (for easy testing) */
1132 if (!optimize_bounded_sort)
1136 /* We want to be able to compute bound * 2, so limit the setting */
1137 if (bound > (int64) (INT_MAX / 2))
1140 state->bounded = true;
1141 state->bound = (int) bound;
1144 * Bounded sorts are not an effective target for abbreviated key
1145 * optimization. Disable by setting state to be consistent with no
1146 * abbreviation support.
1148 state->sortKeys->abbrev_converter = NULL;
1149 if (state->sortKeys->abbrev_full_comparator)
1150 state->sortKeys->comparator = state->sortKeys->abbrev_full_comparator;
1152 /* Not strictly necessary, but be tidy */
1153 state->sortKeys->abbrev_abort = NULL;
1154 state->sortKeys->abbrev_full_comparator = NULL;
1160 * Release resources and clean up.
1162 * NOTE: after calling this, any pointers returned by tuplesort_getXXX are
1163 * pointing to garbage. Be careful not to attempt to use or free such
1164 * pointers afterwards!
1167 tuplesort_end(Tuplesortstate *state)
1169 /* context swap probably not needed, but let's be safe */
1170 MemoryContext oldcontext = MemoryContextSwitchTo(state->sortcontext);
1176 spaceUsed = LogicalTapeSetBlocks(state->tapeset);
1178 spaceUsed = (state->allowedMem - state->availMem + 1023) / 1024;
1182 * Delete temporary "tape" files, if any.
1184 * Note: want to include this in reported total cost of sort, hence need
1185 * for two #ifdef TRACE_SORT sections.
1188 LogicalTapeSetClose(state->tapeset);
1194 elog(LOG, "external sort ended, %ld disk blocks used: %s",
1195 spaceUsed, pg_rusage_show(&state->ru_start));
1197 elog(LOG, "internal sort ended, %ld KB used: %s",
1198 spaceUsed, pg_rusage_show(&state->ru_start));
1201 TRACE_POSTGRESQL_SORT_DONE(state->tapeset != NULL, spaceUsed);
1205 * If you disabled TRACE_SORT, you can still probe sort__done, but you
1206 * ain't getting space-used stats.
1208 TRACE_POSTGRESQL_SORT_DONE(state->tapeset != NULL, 0L);
1211 /* Free any execution state created for CLUSTER case */
1212 if (state->estate != NULL)
1214 ExprContext *econtext = GetPerTupleExprContext(state->estate);
1216 ExecDropSingleTupleTableSlot(econtext->ecxt_scantuple);
1217 FreeExecutorState(state->estate);
1220 MemoryContextSwitchTo(oldcontext);
1223 * Free the per-sort memory context, thereby releasing all working memory,
1224 * including the Tuplesortstate struct itself.
1226 MemoryContextDelete(state->sortcontext);
1230 * Grow the memtuples[] array, if possible within our memory constraint. We
1231 * must not exceed INT_MAX tuples in memory or the caller-provided memory
1232 * limit. Return TRUE if we were able to enlarge the array, FALSE if not.
1234 * Normally, at each increment we double the size of the array. When doing
1235 * that would exceed a limit, we attempt one last, smaller increase (and then
1236 * clear the growmemtuples flag so we don't try any more). That allows us to
1237 * use memory as fully as permitted; sticking to the pure doubling rule could
1238 * result in almost half going unused. Because availMem moves around with
1239 * tuple addition/removal, we need some rule to prevent making repeated small
1240 * increases in memtupsize, which would just be useless thrashing. The
1241 * growmemtuples flag accomplishes that and also prevents useless
1242 * recalculations in this function.
1245 grow_memtuples(Tuplesortstate *state)
1248 int memtupsize = state->memtupsize;
1249 int64 memNowUsed = state->allowedMem - state->availMem;
1251 /* Forget it if we've already maxed out memtuples, per comment above */
1252 if (!state->growmemtuples)
1255 /* Select new value of memtupsize */
1256 if (memNowUsed <= state->availMem)
1259 * We've used no more than half of allowedMem; double our usage,
1260 * clamping at INT_MAX tuples.
1262 if (memtupsize < INT_MAX / 2)
1263 newmemtupsize = memtupsize * 2;
1266 newmemtupsize = INT_MAX;
1267 state->growmemtuples = false;
1273 * This will be the last increment of memtupsize. Abandon doubling
1274 * strategy and instead increase as much as we safely can.
1276 * To stay within allowedMem, we can't increase memtupsize by more
1277 * than availMem / sizeof(SortTuple) elements. In practice, we want
1278 * to increase it by considerably less, because we need to leave some
1279 * space for the tuples to which the new array slots will refer. We
1280 * assume the new tuples will be about the same size as the tuples
1281 * we've already seen, and thus we can extrapolate from the space
1282 * consumption so far to estimate an appropriate new size for the
1283 * memtuples array. The optimal value might be higher or lower than
1284 * this estimate, but it's hard to know that in advance. We again
1285 * clamp at INT_MAX tuples.
1287 * This calculation is safe against enlarging the array so much that
1288 * LACKMEM becomes true, because the memory currently used includes
1289 * the present array; thus, there would be enough allowedMem for the
1290 * new array elements even if no other memory were currently used.
1292 * We do the arithmetic in float8, because otherwise the product of
1293 * memtupsize and allowedMem could overflow. Any inaccuracy in the
1294 * result should be insignificant; but even if we computed a
1295 * completely insane result, the checks below will prevent anything
1296 * really bad from happening.
1300 grow_ratio = (double) state->allowedMem / (double) memNowUsed;
1301 if (memtupsize * grow_ratio < INT_MAX)
1302 newmemtupsize = (int) (memtupsize * grow_ratio);
1304 newmemtupsize = INT_MAX;
1306 /* We won't make any further enlargement attempts */
1307 state->growmemtuples = false;
1310 /* Must enlarge array by at least one element, else report failure */
1311 if (newmemtupsize <= memtupsize)
1315 * On a 32-bit machine, allowedMem could exceed MaxAllocHugeSize. Clamp
1316 * to ensure our request won't be rejected. Note that we can easily
1317 * exhaust address space before facing this outcome. (This is presently
1318 * impossible due to guc.c's MAX_KILOBYTES limitation on work_mem, but
1319 * don't rely on that at this distance.)
1321 if ((Size) newmemtupsize >= MaxAllocHugeSize / sizeof(SortTuple))
1323 newmemtupsize = (int) (MaxAllocHugeSize / sizeof(SortTuple));
1324 state->growmemtuples = false; /* can't grow any more */
1328 * We need to be sure that we do not cause LACKMEM to become true, else
1329 * the space management algorithm will go nuts. The code above should
1330 * never generate a dangerous request, but to be safe, check explicitly
1331 * that the array growth fits within availMem. (We could still cause
1332 * LACKMEM if the memory chunk overhead associated with the memtuples
1333 * array were to increase. That shouldn't happen because we chose the
1334 * initial array size large enough to ensure that palloc will be treating
1335 * both old and new arrays as separate chunks. But we'll check LACKMEM
1336 * explicitly below just in case.)
1338 if (state->availMem < (int64) ((newmemtupsize - memtupsize) * sizeof(SortTuple)))
1342 FREEMEM(state, GetMemoryChunkSpace(state->memtuples));
1343 state->memtupsize = newmemtupsize;
1344 state->memtuples = (SortTuple *)
1345 repalloc_huge(state->memtuples,
1346 state->memtupsize * sizeof(SortTuple));
1347 USEMEM(state, GetMemoryChunkSpace(state->memtuples));
1349 elog(ERROR, "unexpected out-of-memory situation in tuplesort");
1353 /* If for any reason we didn't realloc, shut off future attempts */
1354 state->growmemtuples = false;
1359 * Accept one tuple while collecting input data for sort.
1361 * Note that the input data is always copied; the caller need not save it.
1364 tuplesort_puttupleslot(Tuplesortstate *state, TupleTableSlot *slot)
1366 MemoryContext oldcontext = MemoryContextSwitchTo(state->sortcontext);
1370 * Copy the given tuple into memory we control, and decrease availMem.
1371 * Then call the common code.
1373 COPYTUP(state, &stup, (void *) slot);
1375 puttuple_common(state, &stup);
1377 MemoryContextSwitchTo(oldcontext);
1381 * Accept one tuple while collecting input data for sort.
1383 * Note that the input data is always copied; the caller need not save it.
1386 tuplesort_putheaptuple(Tuplesortstate *state, HeapTuple tup)
1388 MemoryContext oldcontext = MemoryContextSwitchTo(state->sortcontext);
1392 * Copy the given tuple into memory we control, and decrease availMem.
1393 * Then call the common code.
1395 COPYTUP(state, &stup, (void *) tup);
1397 puttuple_common(state, &stup);
1399 MemoryContextSwitchTo(oldcontext);
1403 * Collect one index tuple while collecting input data for sort, building
1404 * it from caller-supplied values.
1407 tuplesort_putindextuplevalues(Tuplesortstate *state, Relation rel,
1408 ItemPointer self, Datum *values,
1411 MemoryContext oldcontext = MemoryContextSwitchTo(state->tuplecontext);
1416 stup.tuple = index_form_tuple(RelationGetDescr(rel), values, isnull);
1417 tuple = ((IndexTuple) stup.tuple);
1418 tuple->t_tid = *self;
1419 USEMEM(state, GetMemoryChunkSpace(stup.tuple));
1420 /* set up first-column key value */
1421 original = index_getattr(tuple,
1423 RelationGetDescr(state->indexRel),
1426 MemoryContextSwitchTo(state->sortcontext);
1428 if (!state->sortKeys || !state->sortKeys->abbrev_converter || stup.isnull1)
1431 * Store ordinary Datum representation, or NULL value. If there is a
1432 * converter it won't expect NULL values, and cost model is not
1433 * required to account for NULL, so in that case we avoid calling
1434 * converter and just set datum1 to zeroed representation (to be
1435 * consistent, and to support cheap inequality tests for NULL
1436 * abbreviated keys).
1438 stup.datum1 = original;
1440 else if (!consider_abort_common(state))
1442 /* Store abbreviated key representation */
1443 stup.datum1 = state->sortKeys->abbrev_converter(original,
1448 /* Abort abbreviation */
1451 stup.datum1 = original;
1454 * Set state to be consistent with never trying abbreviation.
1456 * Alter datum1 representation in already-copied tuples, so as to
1457 * ensure a consistent representation (current tuple was just
1458 * handled). It does not matter if some dumped tuples are already
1459 * sorted on tape, since serialized tuples lack abbreviated keys
1460 * (TSS_BUILDRUNS state prevents control reaching here in any case).
1462 for (i = 0; i < state->memtupcount; i++)
1464 SortTuple *mtup = &state->memtuples[i];
1466 tuple = mtup->tuple;
1467 mtup->datum1 = index_getattr(tuple,
1469 RelationGetDescr(state->indexRel),
1474 puttuple_common(state, &stup);
1476 MemoryContextSwitchTo(oldcontext);
1480 * Accept one Datum while collecting input data for sort.
1482 * If the Datum is pass-by-ref type, the value will be copied.
1485 tuplesort_putdatum(Tuplesortstate *state, Datum val, bool isNull)
1487 MemoryContext oldcontext = MemoryContextSwitchTo(state->tuplecontext);
1491 * Pass-by-value types or null values are just stored directly in
1492 * stup.datum1 (and stup.tuple is not used and set to NULL).
1494 * Non-null pass-by-reference values need to be copied into memory we
1495 * control, and possibly abbreviated. The copied value is pointed to by
1496 * stup.tuple and is treated as the canonical copy (e.g. to return via
1497 * tuplesort_getdatum or when writing to tape); stup.datum1 gets the
1498 * abbreviated value if abbreviation is happening, otherwise it's
1499 * identical to stup.tuple.
1502 if (isNull || !state->tuples)
1505 * Set datum1 to zeroed representation for NULLs (to be consistent,
1506 * and to support cheap inequality tests for NULL abbreviated keys).
1508 stup.datum1 = !isNull ? val : (Datum) 0;
1509 stup.isnull1 = isNull;
1510 stup.tuple = NULL; /* no separate storage */
1511 MemoryContextSwitchTo(state->sortcontext);
1515 Datum original = datumCopy(val, false, state->datumTypeLen);
1517 stup.isnull1 = false;
1518 stup.tuple = DatumGetPointer(original);
1519 USEMEM(state, GetMemoryChunkSpace(stup.tuple));
1520 MemoryContextSwitchTo(state->sortcontext);
1522 if (!state->sortKeys->abbrev_converter)
1524 stup.datum1 = original;
1526 else if (!consider_abort_common(state))
1528 /* Store abbreviated key representation */
1529 stup.datum1 = state->sortKeys->abbrev_converter(original,
1534 /* Abort abbreviation */
1537 stup.datum1 = original;
1540 * Set state to be consistent with never trying abbreviation.
1542 * Alter datum1 representation in already-copied tuples, so as to
1543 * ensure a consistent representation (current tuple was just
1544 * handled). It does not matter if some dumped tuples are already
1545 * sorted on tape, since serialized tuples lack abbreviated keys
1546 * (TSS_BUILDRUNS state prevents control reaching here in any
1549 for (i = 0; i < state->memtupcount; i++)
1551 SortTuple *mtup = &state->memtuples[i];
1553 mtup->datum1 = PointerGetDatum(mtup->tuple);
1558 puttuple_common(state, &stup);
1560 MemoryContextSwitchTo(oldcontext);
1564 * Shared code for tuple and datum cases.
1567 puttuple_common(Tuplesortstate *state, SortTuple *tuple)
1569 switch (state->status)
1574 * Save the tuple into the unsorted array. First, grow the array
1575 * as needed. Note that we try to grow the array when there is
1576 * still one free slot remaining --- if we fail, there'll still be
1577 * room to store the incoming tuple, and then we'll switch to
1578 * tape-based operation.
1580 if (state->memtupcount >= state->memtupsize - 1)
1582 (void) grow_memtuples(state);
1583 Assert(state->memtupcount < state->memtupsize);
1585 state->memtuples[state->memtupcount++] = *tuple;
1588 * Check if it's time to switch over to a bounded heapsort. We do
1589 * so if the input tuple count exceeds twice the desired tuple
1590 * count (this is a heuristic for where heapsort becomes cheaper
1591 * than a quicksort), or if we've just filled workMem and have
1592 * enough tuples to meet the bound.
1594 * Note that once we enter TSS_BOUNDED state we will always try to
1595 * complete the sort that way. In the worst case, if later input
1596 * tuples are larger than earlier ones, this might cause us to
1597 * exceed workMem significantly.
1599 if (state->bounded &&
1600 (state->memtupcount > state->bound * 2 ||
1601 (state->memtupcount > state->bound && LACKMEM(state))))
1605 elog(LOG, "switching to bounded heapsort at %d tuples: %s",
1607 pg_rusage_show(&state->ru_start));
1609 make_bounded_heap(state);
1614 * Done if we still fit in available memory and have array slots.
1616 if (state->memtupcount < state->memtupsize && !LACKMEM(state))
1620 * Nope; time to switch to tape-based operation.
1625 * Dump tuples until we are back under the limit.
1627 dumptuples(state, false);
1633 * We don't want to grow the array here, so check whether the new
1634 * tuple can be discarded before putting it in. This should be a
1635 * good speed optimization, too, since when there are many more
1636 * input tuples than the bound, most input tuples can be discarded
1637 * with just this one comparison. Note that because we currently
1638 * have the sort direction reversed, we must check for <= not >=.
1640 if (COMPARETUP(state, tuple, &state->memtuples[0]) <= 0)
1642 /* new tuple <= top of the heap, so we can discard it */
1643 free_sort_tuple(state, tuple);
1644 CHECK_FOR_INTERRUPTS();
1648 /* discard top of heap, replacing it with the new tuple */
1649 free_sort_tuple(state, &state->memtuples[0]);
1650 tuple->tupindex = 0; /* not used */
1651 tuplesort_heap_replace_top(state, tuple, false);
1658 * Insert the tuple into the heap, with run number currentRun if
1659 * it can go into the current run, else HEAP_RUN_NEXT. The tuple
1660 * can go into the current run if it is >= the first
1661 * not-yet-output tuple. (Actually, it could go into the current
1662 * run if it is >= the most recently output tuple ... but that
1663 * would require keeping around the tuple we last output, and it's
1664 * simplest to let writetup free each tuple as soon as it's
1667 * Note that this only applies when:
1669 * - currentRun is RUN_FIRST
1671 * - Replacement selection is in use (typically it is never used).
1673 * When these two conditions are not both true, all tuples are
1674 * appended indifferently, much like the TSS_INITIAL case.
1676 * There should always be room to store the incoming tuple.
1678 Assert(!state->replaceActive || state->memtupcount > 0);
1679 if (state->replaceActive &&
1680 COMPARETUP(state, tuple, &state->memtuples[0]) >= 0)
1682 Assert(state->currentRun == RUN_FIRST);
1685 * Insert tuple into first, fully heapified run.
1687 * Unlike classic replacement selection, which this module was
1688 * previously based on, only RUN_FIRST tuples are fully
1689 * heapified. Any second/next run tuples are appended
1690 * indifferently. While HEAP_RUN_NEXT tuples may be sifted
1691 * out of the way of first run tuples, COMPARETUP() will never
1692 * be called for the run's tuples during sifting (only our
1693 * initial COMPARETUP() call is required for the tuple, to
1694 * determine that the tuple does not belong in RUN_FIRST).
1696 tuple->tupindex = state->currentRun;
1697 tuplesort_heap_insert(state, tuple, true);
1702 * Tuple was determined to not belong to heapified RUN_FIRST,
1703 * or replacement selection not in play. Append the tuple to
1704 * memtuples indifferently.
1706 * dumptuples() does not trust that the next run's tuples are
1707 * heapified. Anything past the first run will always be
1708 * quicksorted even when replacement selection is initially
1709 * used. (When it's never used, every tuple still takes this
1712 tuple->tupindex = HEAP_RUN_NEXT;
1713 state->memtuples[state->memtupcount++] = *tuple;
1717 * If we are over the memory limit, dump tuples till we're under.
1719 dumptuples(state, false);
1723 elog(ERROR, "invalid tuplesort state");
1729 consider_abort_common(Tuplesortstate *state)
1731 Assert(state->sortKeys[0].abbrev_converter != NULL);
1732 Assert(state->sortKeys[0].abbrev_abort != NULL);
1733 Assert(state->sortKeys[0].abbrev_full_comparator != NULL);
1736 * Check effectiveness of abbreviation optimization. Consider aborting
1737 * when still within memory limit.
1739 if (state->status == TSS_INITIAL &&
1740 state->memtupcount >= state->abbrevNext)
1742 state->abbrevNext *= 2;
1745 * Check opclass-supplied abbreviation abort routine. It may indicate
1746 * that abbreviation should not proceed.
1748 if (!state->sortKeys->abbrev_abort(state->memtupcount,
1753 * Finally, restore authoritative comparator, and indicate that
1754 * abbreviation is not in play by setting abbrev_converter to NULL
1756 state->sortKeys[0].comparator = state->sortKeys[0].abbrev_full_comparator;
1757 state->sortKeys[0].abbrev_converter = NULL;
1758 /* Not strictly necessary, but be tidy */
1759 state->sortKeys[0].abbrev_abort = NULL;
1760 state->sortKeys[0].abbrev_full_comparator = NULL;
1762 /* Give up - expect original pass-by-value representation */
1770 * All tuples have been provided; finish the sort.
1773 tuplesort_performsort(Tuplesortstate *state)
1775 MemoryContext oldcontext = MemoryContextSwitchTo(state->sortcontext);
1779 elog(LOG, "performsort starting: %s",
1780 pg_rusage_show(&state->ru_start));
1783 switch (state->status)
1788 * We were able to accumulate all the tuples within the allowed
1789 * amount of memory. Just qsort 'em and we're done.
1791 tuplesort_sort_memtuples(state);
1793 state->eof_reached = false;
1794 state->markpos_offset = 0;
1795 state->markpos_eof = false;
1796 state->status = TSS_SORTEDINMEM;
1802 * We were able to accumulate all the tuples required for output
1803 * in memory, using a heap to eliminate excess tuples. Now we
1804 * have to transform the heap to a properly-sorted array.
1806 sort_bounded_heap(state);
1808 state->eof_reached = false;
1809 state->markpos_offset = 0;
1810 state->markpos_eof = false;
1811 state->status = TSS_SORTEDINMEM;
1817 * Finish tape-based sort. First, flush all tuples remaining in
1818 * memory out to tape; then merge until we have a single remaining
1819 * run (or, if !randomAccess, one run per tape). Note that
1820 * mergeruns sets the correct state->status.
1822 dumptuples(state, true);
1824 state->eof_reached = false;
1825 state->markpos_block = 0L;
1826 state->markpos_offset = 0;
1827 state->markpos_eof = false;
1831 elog(ERROR, "invalid tuplesort state");
1838 if (state->status == TSS_FINALMERGE)
1839 elog(LOG, "performsort done (except %d-way final merge): %s",
1841 pg_rusage_show(&state->ru_start));
1843 elog(LOG, "performsort done: %s",
1844 pg_rusage_show(&state->ru_start));
1848 MemoryContextSwitchTo(oldcontext);
1852 * Internal routine to fetch the next tuple in either forward or back
1853 * direction into *stup. Returns FALSE if no more tuples.
1854 * Returned tuple belongs to tuplesort memory context, and must not be freed
1855 * by caller. Caller should not use tuple following next call here.
1858 tuplesort_gettuple_common(Tuplesortstate *state, bool forward,
1861 unsigned int tuplen;
1864 switch (state->status)
1866 case TSS_SORTEDINMEM:
1867 Assert(forward || state->randomAccess);
1868 Assert(!state->slabAllocatorUsed);
1871 if (state->current < state->memtupcount)
1873 *stup = state->memtuples[state->current++];
1876 state->eof_reached = true;
1879 * Complain if caller tries to retrieve more tuples than
1880 * originally asked for in a bounded sort. This is because
1881 * returning EOF here might be the wrong thing.
1883 if (state->bounded && state->current >= state->bound)
1884 elog(ERROR, "retrieved too many tuples in a bounded sort");
1890 if (state->current <= 0)
1894 * if all tuples are fetched already then we return last
1895 * tuple, else - tuple before last returned.
1897 if (state->eof_reached)
1898 state->eof_reached = false;
1901 state->current--; /* last returned tuple */
1902 if (state->current <= 0)
1905 *stup = state->memtuples[state->current - 1];
1910 case TSS_SORTEDONTAPE:
1911 Assert(forward || state->randomAccess);
1912 Assert(state->slabAllocatorUsed);
1915 * The slot that held the tuple that we returned in previous
1916 * gettuple call can now be reused.
1918 if (state->lastReturnedTuple)
1920 RELEASE_SLAB_SLOT(state, state->lastReturnedTuple);
1921 state->lastReturnedTuple = NULL;
1926 if (state->eof_reached)
1929 if ((tuplen = getlen(state, state->result_tape, true)) != 0)
1931 READTUP(state, stup, state->result_tape, tuplen);
1934 * Remember the tuple we return, so that we can recycle
1935 * its memory on next call. (This can be NULL, in the
1936 * !state->tuples case).
1938 state->lastReturnedTuple = stup->tuple;
1944 state->eof_reached = true;
1952 * if all tuples are fetched already then we return last tuple,
1953 * else - tuple before last returned.
1955 if (state->eof_reached)
1958 * Seek position is pointing just past the zero tuplen at the
1959 * end of file; back up to fetch last tuple's ending length
1960 * word. If seek fails we must have a completely empty file.
1962 nmoved = LogicalTapeBackspace(state->tapeset,
1964 2 * sizeof(unsigned int));
1967 else if (nmoved != 2 * sizeof(unsigned int))
1968 elog(ERROR, "unexpected tape position");
1969 state->eof_reached = false;
1974 * Back up and fetch previously-returned tuple's ending length
1975 * word. If seek fails, assume we are at start of file.
1977 nmoved = LogicalTapeBackspace(state->tapeset,
1979 sizeof(unsigned int));
1982 else if (nmoved != sizeof(unsigned int))
1983 elog(ERROR, "unexpected tape position");
1984 tuplen = getlen(state, state->result_tape, false);
1987 * Back up to get ending length word of tuple before it.
1989 nmoved = LogicalTapeBackspace(state->tapeset,
1991 tuplen + 2 * sizeof(unsigned int));
1992 if (nmoved == tuplen + sizeof(unsigned int))
1995 * We backed up over the previous tuple, but there was no
1996 * ending length word before it. That means that the prev
1997 * tuple is the first tuple in the file. It is now the
1998 * next to read in forward direction (not obviously right,
1999 * but that is what in-memory case does).
2003 else if (nmoved != tuplen + 2 * sizeof(unsigned int))
2004 elog(ERROR, "bogus tuple length in backward scan");
2007 tuplen = getlen(state, state->result_tape, false);
2010 * Now we have the length of the prior tuple, back up and read it.
2011 * Note: READTUP expects we are positioned after the initial
2012 * length word of the tuple, so back up to that point.
2014 nmoved = LogicalTapeBackspace(state->tapeset,
2017 if (nmoved != tuplen)
2018 elog(ERROR, "bogus tuple length in backward scan");
2019 READTUP(state, stup, state->result_tape, tuplen);
2022 * Remember the tuple we return, so that we can recycle its memory
2023 * on next call. (This can be NULL, in the Datum case).
2025 state->lastReturnedTuple = stup->tuple;
2029 case TSS_FINALMERGE:
2031 /* We are managing memory ourselves, with the slab allocator. */
2032 Assert(state->slabAllocatorUsed);
2035 * The slab slot holding the tuple that we returned in previous
2036 * gettuple call can now be reused.
2038 if (state->lastReturnedTuple)
2040 RELEASE_SLAB_SLOT(state, state->lastReturnedTuple);
2041 state->lastReturnedTuple = NULL;
2045 * This code should match the inner loop of mergeonerun().
2047 if (state->memtupcount > 0)
2049 int srcTape = state->memtuples[0].tupindex;
2052 *stup = state->memtuples[0];
2055 * Remember the tuple we return, so that we can recycle its
2056 * memory on next call. (This can be NULL, in the Datum case).
2058 state->lastReturnedTuple = stup->tuple;
2061 * Pull next tuple from tape, and replace the returned tuple
2062 * at top of the heap with it.
2064 if (!mergereadnext(state, srcTape, &newtup))
2067 * If no more data, we've reached end of run on this tape.
2068 * Remove the top node from the heap.
2070 tuplesort_heap_delete_top(state, false);
2073 * Rewind to free the read buffer. It'd go away at the
2074 * end of the sort anyway, but better to release the
2077 LogicalTapeRewindForWrite(state->tapeset, srcTape);
2080 newtup.tupindex = srcTape;
2081 tuplesort_heap_replace_top(state, &newtup, false);
2087 elog(ERROR, "invalid tuplesort state");
2088 return false; /* keep compiler quiet */
2093 * Fetch the next tuple in either forward or back direction.
2094 * If successful, put tuple in slot and return TRUE; else, clear the slot
2097 * Caller may optionally be passed back abbreviated value (on TRUE return
2098 * value) when abbreviation was used, which can be used to cheaply avoid
2099 * equality checks that might otherwise be required. Caller can safely make a
2100 * determination of "non-equal tuple" based on simple binary inequality. A
2101 * NULL value in leading attribute will set abbreviated value to zeroed
2102 * representation, which caller may rely on in abbreviated inequality check.
2104 * The slot receives a copied tuple (sometimes allocated in caller memory
2105 * context) that will stay valid regardless of future manipulations of the
2106 * tuplesort's state.
2109 tuplesort_gettupleslot(Tuplesortstate *state, bool forward,
2110 TupleTableSlot *slot, Datum *abbrev)
2112 MemoryContext oldcontext = MemoryContextSwitchTo(state->sortcontext);
2115 if (!tuplesort_gettuple_common(state, forward, &stup))
2118 MemoryContextSwitchTo(oldcontext);
2122 /* Record abbreviated key for caller */
2123 if (state->sortKeys->abbrev_converter && abbrev)
2124 *abbrev = stup.datum1;
2126 stup.tuple = heap_copy_minimal_tuple((MinimalTuple) stup.tuple);
2127 ExecStoreMinimalTuple((MinimalTuple) stup.tuple, slot, true);
2132 ExecClearTuple(slot);
2138 * Fetch the next tuple in either forward or back direction.
2139 * Returns NULL if no more tuples. Returned tuple belongs to tuplesort memory
2140 * context, and must not be freed by caller. Caller should not use tuple
2141 * following next call here.
2144 tuplesort_getheaptuple(Tuplesortstate *state, bool forward)
2146 MemoryContext oldcontext = MemoryContextSwitchTo(state->sortcontext);
2149 if (!tuplesort_gettuple_common(state, forward, &stup))
2152 MemoryContextSwitchTo(oldcontext);
2158 * Fetch the next index tuple in either forward or back direction.
2159 * Returns NULL if no more tuples. Returned tuple belongs to tuplesort memory
2160 * context, and must not be freed by caller. Caller should not use tuple
2161 * following next call here.
2164 tuplesort_getindextuple(Tuplesortstate *state, bool forward)
2166 MemoryContext oldcontext = MemoryContextSwitchTo(state->sortcontext);
2169 if (!tuplesort_gettuple_common(state, forward, &stup))
2172 MemoryContextSwitchTo(oldcontext);
2174 return (IndexTuple) stup.tuple;
2178 * Fetch the next Datum in either forward or back direction.
2179 * Returns FALSE if no more datums.
2181 * If the Datum is pass-by-ref type, the returned value is freshly palloc'd
2182 * and is now owned by the caller (this differs from similar routines for
2183 * other types of tuplesorts).
2185 * Caller may optionally be passed back abbreviated value (on TRUE return
2186 * value) when abbreviation was used, which can be used to cheaply avoid
2187 * equality checks that might otherwise be required. Caller can safely make a
2188 * determination of "non-equal tuple" based on simple binary inequality. A
2189 * NULL value will have a zeroed abbreviated value representation, which caller
2190 * may rely on in abbreviated inequality check.
2193 tuplesort_getdatum(Tuplesortstate *state, bool forward,
2194 Datum *val, bool *isNull, Datum *abbrev)
2196 MemoryContext oldcontext = MemoryContextSwitchTo(state->sortcontext);
2199 if (!tuplesort_gettuple_common(state, forward, &stup))
2201 MemoryContextSwitchTo(oldcontext);
2205 /* Record abbreviated key for caller */
2206 if (state->sortKeys->abbrev_converter && abbrev)
2207 *abbrev = stup.datum1;
2209 if (stup.isnull1 || !state->tuples)
2212 *isNull = stup.isnull1;
2216 /* use stup.tuple because stup.datum1 may be an abbreviation */
2217 *val = datumCopy(PointerGetDatum(stup.tuple), false, state->datumTypeLen);
2221 MemoryContextSwitchTo(oldcontext);
2227 * Advance over N tuples in either forward or back direction,
2228 * without returning any data. N==0 is a no-op.
2229 * Returns TRUE if successful, FALSE if ran out of tuples.
2232 tuplesort_skiptuples(Tuplesortstate *state, int64 ntuples, bool forward)
2234 MemoryContext oldcontext;
2237 * We don't actually support backwards skip yet, because no callers need
2238 * it. The API is designed to allow for that later, though.
2241 Assert(ntuples >= 0);
2243 switch (state->status)
2245 case TSS_SORTEDINMEM:
2246 if (state->memtupcount - state->current >= ntuples)
2248 state->current += ntuples;
2251 state->current = state->memtupcount;
2252 state->eof_reached = true;
2255 * Complain if caller tries to retrieve more tuples than
2256 * originally asked for in a bounded sort. This is because
2257 * returning EOF here might be the wrong thing.
2259 if (state->bounded && state->current >= state->bound)
2260 elog(ERROR, "retrieved too many tuples in a bounded sort");
2264 case TSS_SORTEDONTAPE:
2265 case TSS_FINALMERGE:
2268 * We could probably optimize these cases better, but for now it's
2269 * not worth the trouble.
2271 oldcontext = MemoryContextSwitchTo(state->sortcontext);
2272 while (ntuples-- > 0)
2276 if (!tuplesort_gettuple_common(state, forward, &stup))
2278 MemoryContextSwitchTo(oldcontext);
2281 CHECK_FOR_INTERRUPTS();
2283 MemoryContextSwitchTo(oldcontext);
2287 elog(ERROR, "invalid tuplesort state");
2288 return false; /* keep compiler quiet */
2293 * tuplesort_merge_order - report merge order we'll use for given memory
2294 * (note: "merge order" just means the number of input tapes in the merge).
2296 * This is exported for use by the planner. allowedMem is in bytes.
2299 tuplesort_merge_order(int64 allowedMem)
2304 * We need one tape for each merge input, plus another one for the output,
2305 * and each of these tapes needs buffer space. In addition we want
2306 * MERGE_BUFFER_SIZE workspace per input tape (but the output tape doesn't
2309 * Note: you might be thinking we need to account for the memtuples[]
2310 * array in this calculation, but we effectively treat that as part of the
2311 * MERGE_BUFFER_SIZE workspace.
2313 mOrder = (allowedMem - TAPE_BUFFER_OVERHEAD) /
2314 (MERGE_BUFFER_SIZE + TAPE_BUFFER_OVERHEAD);
2317 * Even in minimum memory, use at least a MINORDER merge. On the other
2318 * hand, even when we have lots of memory, do not use more than a MAXORDER
2319 * merge. Tapes are pretty cheap, but they're not entirely free. Each
2320 * additional tape reduces the amount of memory available to build runs,
2321 * which in turn can cause the same sort to need more runs, which makes
2322 * merging slower even if it can still be done in a single pass. Also,
2323 * high order merges are quite slow due to CPU cache effects; it can be
2324 * faster to pay the I/O cost of a polyphase merge than to perform a single
2325 * merge pass across many hundreds of tapes.
2327 mOrder = Max(mOrder, MINORDER);
2328 mOrder = Min(mOrder, MAXORDER);
2334 * useselection - determine algorithm to use to sort first run.
2336 * It can sometimes be useful to use the replacement selection algorithm if it
2337 * results in one large run, and there is little available workMem. See
2338 * remarks on RUN_SECOND optimization within dumptuples().
2341 useselection(Tuplesortstate *state)
2344 * memtupsize might be noticeably higher than memtupcount here in atypical
2345 * cases. It seems slightly preferable to not allow recent outliers to
2346 * impact this determination. Note that caller's trace_sort output
2347 * reports memtupcount instead.
2349 if (state->memtupsize <= replacement_sort_tuples)
2356 * inittapes - initialize for tape sorting.
2358 * This is called only if we have found we don't have room to sort in memory.
2361 inittapes(Tuplesortstate *state)
2367 /* Compute number of tapes to use: merge order plus 1 */
2368 maxTapes = tuplesort_merge_order(state->allowedMem) + 1;
2370 state->maxTapes = maxTapes;
2371 state->tapeRange = maxTapes - 1;
2375 elog(LOG, "switching to external sort with %d tapes: %s",
2376 maxTapes, pg_rusage_show(&state->ru_start));
2380 * Decrease availMem to reflect the space needed for tape buffers, when
2381 * writing the initial runs; but don't decrease it to the point that we
2382 * have no room for tuples. (That case is only likely to occur if sorting
2383 * pass-by-value Datums; in all other scenarios the memtuples[] array is
2384 * unlikely to occupy more than half of allowedMem. In the pass-by-value
2385 * case it's not important to account for tuple space, so we don't care if
2386 * LACKMEM becomes inaccurate.)
2388 tapeSpace = (int64) maxTapes *TAPE_BUFFER_OVERHEAD;
2390 if (tapeSpace + GetMemoryChunkSpace(state->memtuples) < state->allowedMem)
2391 USEMEM(state, tapeSpace);
2394 * Make sure that the temp file(s) underlying the tape set are created in
2395 * suitable temp tablespaces.
2397 PrepareTempTablespaces();
2400 * Create the tape set and allocate the per-tape data arrays.
2402 state->tapeset = LogicalTapeSetCreate(maxTapes);
2404 state->mergeactive = (bool *) palloc0(maxTapes * sizeof(bool));
2405 state->tp_fib = (int *) palloc0(maxTapes * sizeof(int));
2406 state->tp_runs = (int *) palloc0(maxTapes * sizeof(int));
2407 state->tp_dummy = (int *) palloc0(maxTapes * sizeof(int));
2408 state->tp_tapenum = (int *) palloc0(maxTapes * sizeof(int));
2411 * Give replacement selection a try based on user setting. There will be
2412 * a switch to a simple hybrid sort-merge strategy after the first run
2413 * (iff we could not output one long run).
2415 state->replaceActive = useselection(state);
2417 if (state->replaceActive)
2420 * Convert the unsorted contents of memtuples[] into a heap. Each
2421 * tuple is marked as belonging to run number zero.
2423 * NOTE: we pass false for checkIndex since there's no point in
2424 * comparing indexes in this step, even though we do intend the
2425 * indexes to be part of the sort key...
2427 int ntuples = state->memtupcount;
2431 elog(LOG, "replacement selection will sort %d first run tuples",
2432 state->memtupcount);
2434 state->memtupcount = 0; /* make the heap empty */
2436 for (j = 0; j < ntuples; j++)
2438 /* Must copy source tuple to avoid possible overwrite */
2439 SortTuple stup = state->memtuples[j];
2441 stup.tupindex = RUN_FIRST;
2442 tuplesort_heap_insert(state, &stup, false);
2444 Assert(state->memtupcount == ntuples);
2447 state->currentRun = RUN_FIRST;
2450 * Initialize variables of Algorithm D (step D1).
2452 for (j = 0; j < maxTapes; j++)
2454 state->tp_fib[j] = 1;
2455 state->tp_runs[j] = 0;
2456 state->tp_dummy[j] = 1;
2457 state->tp_tapenum[j] = j;
2459 state->tp_fib[state->tapeRange] = 0;
2460 state->tp_dummy[state->tapeRange] = 0;
2463 state->destTape = 0;
2465 state->status = TSS_BUILDRUNS;
2469 * selectnewtape -- select new tape for new initial run.
2471 * This is called after finishing a run when we know another run
2472 * must be started. This implements steps D3, D4 of Algorithm D.
2475 selectnewtape(Tuplesortstate *state)
2480 /* Step D3: advance j (destTape) */
2481 if (state->tp_dummy[state->destTape] < state->tp_dummy[state->destTape + 1])
2486 if (state->tp_dummy[state->destTape] != 0)
2488 state->destTape = 0;
2492 /* Step D4: increase level */
2494 a = state->tp_fib[0];
2495 for (j = 0; j < state->tapeRange; j++)
2497 state->tp_dummy[j] = a + state->tp_fib[j + 1] - state->tp_fib[j];
2498 state->tp_fib[j] = a + state->tp_fib[j + 1];
2500 state->destTape = 0;
2504 * Initialize the slab allocation arena, for the given number of slots.
2507 init_slab_allocator(Tuplesortstate *state, int numSlots)
2514 state->slabMemoryBegin = palloc(numSlots * SLAB_SLOT_SIZE);
2515 state->slabMemoryEnd = state->slabMemoryBegin +
2516 numSlots * SLAB_SLOT_SIZE;
2517 state->slabFreeHead = (SlabSlot *) state->slabMemoryBegin;
2518 USEMEM(state, numSlots * SLAB_SLOT_SIZE);
2520 p = state->slabMemoryBegin;
2521 for (i = 0; i < numSlots - 1; i++)
2523 ((SlabSlot *) p)->nextfree = (SlabSlot *) (p + SLAB_SLOT_SIZE);
2524 p += SLAB_SLOT_SIZE;
2526 ((SlabSlot *) p)->nextfree = NULL;
2530 state->slabMemoryBegin = state->slabMemoryEnd = NULL;
2531 state->slabFreeHead = NULL;
2533 state->slabAllocatorUsed = true;
2537 * mergeruns -- merge all the completed initial runs.
2539 * This implements steps D5, D6 of Algorithm D. All input data has
2540 * already been written to initial runs on tape (see dumptuples).
2543 mergeruns(Tuplesortstate *state)
2552 Assert(state->status == TSS_BUILDRUNS);
2553 Assert(state->memtupcount == 0);
2555 if (state->sortKeys != NULL && state->sortKeys->abbrev_converter != NULL)
2558 * If there are multiple runs to be merged, when we go to read back
2559 * tuples from disk, abbreviated keys will not have been stored, and
2560 * we don't care to regenerate them. Disable abbreviation from this
2563 state->sortKeys->abbrev_converter = NULL;
2564 state->sortKeys->comparator = state->sortKeys->abbrev_full_comparator;
2566 /* Not strictly necessary, but be tidy */
2567 state->sortKeys->abbrev_abort = NULL;
2568 state->sortKeys->abbrev_full_comparator = NULL;
2572 * Reset tuple memory. We've freed all the tuples that we previously
2573 * allocated. We will use the slab allocator from now on.
2575 MemoryContextDelete(state->tuplecontext);
2576 state->tuplecontext = NULL;
2579 * We no longer need a large memtuples array. (We will allocate a smaller
2580 * one for the heap later.)
2582 FREEMEM(state, GetMemoryChunkSpace(state->memtuples));
2583 pfree(state->memtuples);
2584 state->memtuples = NULL;
2587 * If we had fewer runs than tapes, refund the memory that we imagined we
2588 * would need for the tape buffers of the unused tapes.
2590 * numTapes and numInputTapes reflect the actual number of tapes we will
2591 * use. Note that the output tape's tape number is maxTapes - 1, so the
2592 * tape numbers of the used tapes are not consecutive, and you cannot just
2593 * loop from 0 to numTapes to visit all used tapes!
2595 if (state->Level == 1)
2597 numInputTapes = state->currentRun;
2598 numTapes = numInputTapes + 1;
2599 FREEMEM(state, (state->maxTapes - numTapes) * TAPE_BUFFER_OVERHEAD);
2603 numInputTapes = state->tapeRange;
2604 numTapes = state->maxTapes;
2608 * Initialize the slab allocator. We need one slab slot per input tape,
2609 * for the tuples in the heap, plus one to hold the tuple last returned
2610 * from tuplesort_gettuple. (If we're sorting pass-by-val Datums,
2611 * however, we don't need to do allocate anything.)
2613 * From this point on, we no longer use the USEMEM()/LACKMEM() mechanism
2614 * to track memory usage of individual tuples.
2617 init_slab_allocator(state, numInputTapes + 1);
2619 init_slab_allocator(state, 0);
2622 * If we produced only one initial run (quite likely if the total data
2623 * volume is between 1X and 2X workMem when replacement selection is used,
2624 * but something we particular count on when input is presorted), we can
2625 * just use that tape as the finished output, rather than doing a useless
2626 * merge. (This obvious optimization is not in Knuth's algorithm.)
2628 if (state->currentRun == RUN_SECOND)
2630 state->result_tape = state->tp_tapenum[state->destTape];
2631 /* must freeze and rewind the finished output tape */
2632 LogicalTapeFreeze(state->tapeset, state->result_tape);
2633 state->status = TSS_SORTEDONTAPE;
2638 * Allocate a new 'memtuples' array, for the heap. It will hold one tuple
2639 * from each input tape.
2641 state->memtupsize = numInputTapes;
2642 state->memtuples = (SortTuple *) palloc(numInputTapes * sizeof(SortTuple));
2643 USEMEM(state, GetMemoryChunkSpace(state->memtuples));
2646 * Use all the remaining memory we have available for read buffers among
2649 * We do this only after checking for the case that we produced only one
2650 * initial run, because there is no need to use a large read buffer when
2651 * we're reading from a single tape. With one tape, the I/O pattern will
2652 * be the same regardless of the buffer size.
2654 * We don't try to "rebalance" the memory among tapes, when we start a new
2655 * merge phase, even if some tapes are inactive in the new phase. That
2656 * would be hard, because logtape.c doesn't know where one run ends and
2657 * another begins. When a new merge phase begins, and a tape doesn't
2658 * participate in it, its buffer nevertheless already contains tuples from
2659 * the next run on same tape, so we cannot release the buffer. That's OK
2660 * in practice, merge performance isn't that sensitive to the amount of
2661 * buffers used, and most merge phases use all or almost all tapes,
2666 elog(LOG, "using " INT64_FORMAT " KB of memory for read buffers among %d input tapes",
2667 (state->availMem) / 1024, numInputTapes);
2670 state->read_buffer_size = Max(state->availMem / numInputTapes, 0);
2671 USEMEM(state, state->read_buffer_size * numInputTapes);
2673 /* End of step D2: rewind all output tapes to prepare for merging */
2674 for (tapenum = 0; tapenum < state->tapeRange; tapenum++)
2675 LogicalTapeRewindForRead(state->tapeset, tapenum, state->read_buffer_size);
2680 * At this point we know that tape[T] is empty. If there's just one
2681 * (real or dummy) run left on each input tape, then only one merge
2682 * pass remains. If we don't have to produce a materialized sorted
2683 * tape, we can stop at this point and do the final merge on-the-fly.
2685 if (!state->randomAccess)
2687 bool allOneRun = true;
2689 Assert(state->tp_runs[state->tapeRange] == 0);
2690 for (tapenum = 0; tapenum < state->tapeRange; tapenum++)
2692 if (state->tp_runs[tapenum] + state->tp_dummy[tapenum] != 1)
2700 /* Tell logtape.c we won't be writing anymore */
2701 LogicalTapeSetForgetFreeSpace(state->tapeset);
2702 /* Initialize for the final merge pass */
2704 state->status = TSS_FINALMERGE;
2709 /* Step D5: merge runs onto tape[T] until tape[P] is empty */
2710 while (state->tp_runs[state->tapeRange - 1] ||
2711 state->tp_dummy[state->tapeRange - 1])
2713 bool allDummy = true;
2715 for (tapenum = 0; tapenum < state->tapeRange; tapenum++)
2717 if (state->tp_dummy[tapenum] == 0)
2726 state->tp_dummy[state->tapeRange]++;
2727 for (tapenum = 0; tapenum < state->tapeRange; tapenum++)
2728 state->tp_dummy[tapenum]--;
2734 /* Step D6: decrease level */
2735 if (--state->Level == 0)
2737 /* rewind output tape T to use as new input */
2738 LogicalTapeRewindForRead(state->tapeset, state->tp_tapenum[state->tapeRange],
2739 state->read_buffer_size);
2740 /* rewind used-up input tape P, and prepare it for write pass */
2741 LogicalTapeRewindForWrite(state->tapeset, state->tp_tapenum[state->tapeRange - 1]);
2742 state->tp_runs[state->tapeRange - 1] = 0;
2745 * reassign tape units per step D6; note we no longer care about A[]
2747 svTape = state->tp_tapenum[state->tapeRange];
2748 svDummy = state->tp_dummy[state->tapeRange];
2749 svRuns = state->tp_runs[state->tapeRange];
2750 for (tapenum = state->tapeRange; tapenum > 0; tapenum--)
2752 state->tp_tapenum[tapenum] = state->tp_tapenum[tapenum - 1];
2753 state->tp_dummy[tapenum] = state->tp_dummy[tapenum - 1];
2754 state->tp_runs[tapenum] = state->tp_runs[tapenum - 1];
2756 state->tp_tapenum[0] = svTape;
2757 state->tp_dummy[0] = svDummy;
2758 state->tp_runs[0] = svRuns;
2762 * Done. Knuth says that the result is on TAPE[1], but since we exited
2763 * the loop without performing the last iteration of step D6, we have not
2764 * rearranged the tape unit assignment, and therefore the result is on
2765 * TAPE[T]. We need to do it this way so that we can freeze the final
2766 * output tape while rewinding it. The last iteration of step D6 would be
2767 * a waste of cycles anyway...
2769 state->result_tape = state->tp_tapenum[state->tapeRange];
2770 LogicalTapeFreeze(state->tapeset, state->result_tape);
2771 state->status = TSS_SORTEDONTAPE;
2773 /* Release the read buffers of all the other tapes, by rewinding them. */
2774 for (tapenum = 0; tapenum < state->maxTapes; tapenum++)
2776 if (tapenum != state->result_tape)
2777 LogicalTapeRewindForWrite(state->tapeset, tapenum);
2782 * Merge one run from each input tape, except ones with dummy runs.
2784 * This is the inner loop of Algorithm D step D5. We know that the
2785 * output tape is TAPE[T].
2788 mergeonerun(Tuplesortstate *state)
2790 int destTape = state->tp_tapenum[state->tapeRange];
2794 * Start the merge by loading one tuple from each active source tape into
2795 * the heap. We can also decrease the input run/dummy run counts.
2800 * Execute merge by repeatedly extracting lowest tuple in heap, writing it
2801 * out, and replacing it with next tuple from same tape (if there is
2804 while (state->memtupcount > 0)
2808 /* write the tuple to destTape */
2809 srcTape = state->memtuples[0].tupindex;
2810 WRITETUP(state, destTape, &state->memtuples[0]);
2812 /* recycle the slot of the tuple we just wrote out, for the next read */
2813 if (state->memtuples[0].tuple)
2814 RELEASE_SLAB_SLOT(state, state->memtuples[0].tuple);
2817 * pull next tuple from the tape, and replace the written-out tuple in
2820 if (mergereadnext(state, srcTape, &stup))
2822 stup.tupindex = srcTape;
2823 tuplesort_heap_replace_top(state, &stup, false);
2827 tuplesort_heap_delete_top(state, false);
2831 * When the heap empties, we're done. Write an end-of-run marker on the
2832 * output tape, and increment its count of real runs.
2834 markrunend(state, destTape);
2835 state->tp_runs[state->tapeRange]++;
2839 elog(LOG, "finished %d-way merge step: %s", state->activeTapes,
2840 pg_rusage_show(&state->ru_start));
2845 * beginmerge - initialize for a merge pass
2847 * We decrease the counts of real and dummy runs for each tape, and mark
2848 * which tapes contain active input runs in mergeactive[]. Then, fill the
2849 * merge heap with the first tuple from each active tape.
2852 beginmerge(Tuplesortstate *state)
2858 /* Heap should be empty here */
2859 Assert(state->memtupcount == 0);
2861 /* Adjust run counts and mark the active tapes */
2862 memset(state->mergeactive, 0,
2863 state->maxTapes * sizeof(*state->mergeactive));
2865 for (tapenum = 0; tapenum < state->tapeRange; tapenum++)
2867 if (state->tp_dummy[tapenum] > 0)
2868 state->tp_dummy[tapenum]--;
2871 Assert(state->tp_runs[tapenum] > 0);
2872 state->tp_runs[tapenum]--;
2873 srcTape = state->tp_tapenum[tapenum];
2874 state->mergeactive[srcTape] = true;
2878 Assert(activeTapes > 0);
2879 state->activeTapes = activeTapes;
2881 /* Load the merge heap with the first tuple from each input tape */
2882 for (srcTape = 0; srcTape < state->maxTapes; srcTape++)
2886 if (mergereadnext(state, srcTape, &tup))
2888 tup.tupindex = srcTape;
2889 tuplesort_heap_insert(state, &tup, false);
2895 * mergereadnext - read next tuple from one merge input tape
2897 * Returns false on EOF.
2900 mergereadnext(Tuplesortstate *state, int srcTape, SortTuple *stup)
2902 unsigned int tuplen;
2904 if (!state->mergeactive[srcTape])
2905 return false; /* tape's run is already exhausted */
2907 /* read next tuple, if any */
2908 if ((tuplen = getlen(state, srcTape, true)) == 0)
2910 state->mergeactive[srcTape] = false;
2913 READTUP(state, stup, srcTape, tuplen);
2919 * dumptuples - remove tuples from memtuples and write to tape
2921 * This is used during initial-run building, but not during merging.
2923 * When alltuples = false and replacement selection is still active, dump
2924 * only enough tuples to get under the availMem limit (and leave at least
2925 * one tuple in memtuples, since puttuple will then assume it is a heap that
2926 * has a tuple to compare to). We always insist there be at least one free
2927 * slot in the memtuples[] array.
2929 * When alltuples = true, dump everything currently in memory. (This
2930 * case is only used at end of input data, although in practice only the
2931 * first run could fail to dump all tuples when we LACKMEM(), and only
2932 * when replacement selection is active.)
2934 * If, when replacement selection is active, we see that the tuple run
2935 * number at the top of the heap has changed, start a new run. This must be
2936 * the first run, because replacement selection is always abandoned for all
2940 dumptuples(Tuplesortstate *state, bool alltuples)
2943 (LACKMEM(state) && state->memtupcount > 1) ||
2944 state->memtupcount >= state->memtupsize)
2946 if (state->replaceActive)
2949 * Still holding out for a case favorable to replacement
2950 * selection. Still incrementally spilling using heap.
2952 * Dump the heap's frontmost entry, and remove it from the heap.
2954 Assert(state->memtupcount > 0);
2955 WRITETUP(state, state->tp_tapenum[state->destTape],
2956 &state->memtuples[0]);
2957 tuplesort_heap_delete_top(state, true);
2962 * Once committed to quicksorting runs, never incrementally spill
2964 dumpbatch(state, alltuples);
2969 * If top run number has changed, we've finished the current run (this
2970 * can only be the first run), and will no longer spill incrementally.
2972 if (state->memtupcount == 0 ||
2973 state->memtuples[0].tupindex == HEAP_RUN_NEXT)
2975 markrunend(state, state->tp_tapenum[state->destTape]);
2976 Assert(state->currentRun == RUN_FIRST);
2977 state->currentRun++;
2978 state->tp_runs[state->destTape]++;
2979 state->tp_dummy[state->destTape]--; /* per Alg D step D2 */
2983 elog(LOG, "finished incrementally writing %s run %d to tape %d: %s",
2984 (state->memtupcount == 0) ? "only" : "first",
2985 state->currentRun, state->destTape,
2986 pg_rusage_show(&state->ru_start));
2990 * Done if heap is empty, which is possible when there is only one
2993 Assert(state->currentRun == RUN_SECOND);
2994 if (state->memtupcount == 0)
2997 * Replacement selection best case; no final merge required,
2998 * because there was only one initial run (second run has no
2999 * tuples). See RUN_SECOND case in mergeruns().
3005 * Abandon replacement selection for second run (as well as any
3008 state->replaceActive = false;
3011 * First tuple of next run should not be heapified, and so will
3012 * bear placeholder run number. In practice this must actually be
3013 * the second run, which just became the currentRun, so we're
3014 * clear to quicksort and dump the tuples in batch next time
3015 * memtuples becomes full.
3017 Assert(state->memtuples[0].tupindex == HEAP_RUN_NEXT);
3018 selectnewtape(state);
3024 * dumpbatch - sort and dump all memtuples, forming one run on tape
3026 * Second or subsequent runs are never heapified by this module (although
3027 * heapification still respects run number differences between the first and
3028 * second runs), and a heap (replacement selection priority queue) is often
3029 * avoided in the first place.
3032 dumpbatch(Tuplesortstate *state, bool alltuples)
3038 * Final call might require no sorting, in rare cases where we just so
3039 * happen to have previously LACKMEM()'d at the point where exactly all
3040 * remaining tuples are loaded into memory, just before input was
3043 * In general, short final runs are quite possible. Rather than allowing
3044 * a special case where there was a superfluous selectnewtape() call (i.e.
3045 * a call with no subsequent run actually written to destTape), we prefer
3046 * to write out a 0 tuple run.
3048 * mergereadnext() is prepared for 0 tuple runs, and will reliably mark
3049 * the tape inactive for the merge when called from beginmerge(). This
3050 * case is therefore similar to the case where mergeonerun() finds a dummy
3051 * run for the tape, and so doesn't need to merge a run from the tape (or
3052 * conceptually "merges" the dummy run, if you prefer). According to
3053 * Knuth, Algorithm D "isn't strictly optimal" in its method of
3054 * distribution and dummy run assignment; this edge case seems very
3055 * unlikely to make that appreciably worse.
3057 Assert(state->status == TSS_BUILDRUNS);
3060 * It seems unlikely that this limit will ever be exceeded, but take no
3063 if (state->currentRun == INT_MAX)
3065 (errcode(ERRCODE_PROGRAM_LIMIT_EXCEEDED),
3066 errmsg("cannot have more than %d runs for an external sort",
3069 state->currentRun++;
3073 elog(LOG, "starting quicksort of run %d: %s",
3074 state->currentRun, pg_rusage_show(&state->ru_start));
3078 * Sort all tuples accumulated within the allowed amount of memory for
3079 * this run using quicksort
3081 tuplesort_sort_memtuples(state);
3085 elog(LOG, "finished quicksort of run %d: %s",
3086 state->currentRun, pg_rusage_show(&state->ru_start));
3089 memtupwrite = state->memtupcount;
3090 for (i = 0; i < memtupwrite; i++)
3092 WRITETUP(state, state->tp_tapenum[state->destTape],
3093 &state->memtuples[i]);
3094 state->memtupcount--;
3098 * Reset tuple memory. We've freed all of the tuples that we previously
3099 * allocated. It's important to avoid fragmentation when there is a stark
3100 * change in the sizes of incoming tuples. Fragmentation due to
3101 * AllocSetFree's bucketing by size class might be particularly bad if
3102 * this step wasn't taken.
3104 MemoryContextReset(state->tuplecontext);
3106 markrunend(state, state->tp_tapenum[state->destTape]);
3107 state->tp_runs[state->destTape]++;
3108 state->tp_dummy[state->destTape]--; /* per Alg D step D2 */
3112 elog(LOG, "finished writing run %d to tape %d: %s",
3113 state->currentRun, state->destTape,
3114 pg_rusage_show(&state->ru_start));
3118 selectnewtape(state);
3122 * tuplesort_rescan - rewind and replay the scan
3125 tuplesort_rescan(Tuplesortstate *state)
3127 MemoryContext oldcontext = MemoryContextSwitchTo(state->sortcontext);
3129 Assert(state->randomAccess);
3131 switch (state->status)
3133 case TSS_SORTEDINMEM:
3135 state->eof_reached = false;
3136 state->markpos_offset = 0;
3137 state->markpos_eof = false;
3139 case TSS_SORTEDONTAPE:
3140 LogicalTapeRewindForRead(state->tapeset,
3143 state->eof_reached = false;
3144 state->markpos_block = 0L;
3145 state->markpos_offset = 0;
3146 state->markpos_eof = false;
3149 elog(ERROR, "invalid tuplesort state");
3153 MemoryContextSwitchTo(oldcontext);
3157 * tuplesort_markpos - saves current position in the merged sort file
3160 tuplesort_markpos(Tuplesortstate *state)
3162 MemoryContext oldcontext = MemoryContextSwitchTo(state->sortcontext);
3164 Assert(state->randomAccess);
3166 switch (state->status)
3168 case TSS_SORTEDINMEM:
3169 state->markpos_offset = state->current;
3170 state->markpos_eof = state->eof_reached;
3172 case TSS_SORTEDONTAPE:
3173 LogicalTapeTell(state->tapeset,
3175 &state->markpos_block,
3176 &state->markpos_offset);
3177 state->markpos_eof = state->eof_reached;
3180 elog(ERROR, "invalid tuplesort state");
3184 MemoryContextSwitchTo(oldcontext);
3188 * tuplesort_restorepos - restores current position in merged sort file to
3189 * last saved position
3192 tuplesort_restorepos(Tuplesortstate *state)
3194 MemoryContext oldcontext = MemoryContextSwitchTo(state->sortcontext);
3196 Assert(state->randomAccess);
3198 switch (state->status)
3200 case TSS_SORTEDINMEM:
3201 state->current = state->markpos_offset;
3202 state->eof_reached = state->markpos_eof;
3204 case TSS_SORTEDONTAPE:
3205 LogicalTapeSeek(state->tapeset,
3207 state->markpos_block,
3208 state->markpos_offset);
3209 state->eof_reached = state->markpos_eof;
3212 elog(ERROR, "invalid tuplesort state");
3216 MemoryContextSwitchTo(oldcontext);
3220 * tuplesort_get_stats - extract summary statistics
3222 * This can be called after tuplesort_performsort() finishes to obtain
3223 * printable summary information about how the sort was performed.
3224 * spaceUsed is measured in kilobytes.
3227 tuplesort_get_stats(Tuplesortstate *state,
3228 const char **sortMethod,
3229 const char **spaceType,
3233 * Note: it might seem we should provide both memory and disk usage for a
3234 * disk-based sort. However, the current code doesn't track memory space
3235 * accurately once we have begun to return tuples to the caller (since we
3236 * don't account for pfree's the caller is expected to do), so we cannot
3237 * rely on availMem in a disk sort. This does not seem worth the overhead
3238 * to fix. Is it worth creating an API for the memory context code to
3239 * tell us how much is actually used in sortcontext?
3243 *spaceType = "Disk";
3244 *spaceUsed = LogicalTapeSetBlocks(state->tapeset) * (BLCKSZ / 1024);
3248 *spaceType = "Memory";
3249 *spaceUsed = (state->allowedMem - state->availMem + 1023) / 1024;
3252 switch (state->status)
3254 case TSS_SORTEDINMEM:
3255 if (state->boundUsed)
3256 *sortMethod = "top-N heapsort";
3258 *sortMethod = "quicksort";
3260 case TSS_SORTEDONTAPE:
3261 *sortMethod = "external sort";
3263 case TSS_FINALMERGE:
3264 *sortMethod = "external merge";
3267 *sortMethod = "still in progress";
3274 * Heap manipulation routines, per Knuth's Algorithm 5.2.3H.
3276 * Compare two SortTuples. If checkIndex is true, use the tuple index
3277 * as the front of the sort key; otherwise, no.
3279 * Note that for checkIndex callers, the heap invariant is never
3280 * maintained beyond the first run, and so there are no COMPARETUP()
3281 * calls needed to distinguish tuples in HEAP_RUN_NEXT.
3284 #define HEAPCOMPARE(tup1,tup2) \
3285 (checkIndex && ((tup1)->tupindex != (tup2)->tupindex || \
3286 (tup1)->tupindex == HEAP_RUN_NEXT) ? \
3287 ((tup1)->tupindex) - ((tup2)->tupindex) : \
3288 COMPARETUP(state, tup1, tup2))
3291 * Convert the existing unordered array of SortTuples to a bounded heap,
3292 * discarding all but the smallest "state->bound" tuples.
3294 * When working with a bounded heap, we want to keep the largest entry
3295 * at the root (array entry zero), instead of the smallest as in the normal
3296 * sort case. This allows us to discard the largest entry cheaply.
3297 * Therefore, we temporarily reverse the sort direction.
3299 * We assume that all entries in a bounded heap will always have tupindex
3300 * zero; it therefore doesn't matter that HEAPCOMPARE() doesn't reverse
3301 * the direction of comparison for tupindexes.
3304 make_bounded_heap(Tuplesortstate *state)
3306 int tupcount = state->memtupcount;
3309 Assert(state->status == TSS_INITIAL);
3310 Assert(state->bounded);
3311 Assert(tupcount >= state->bound);
3313 /* Reverse sort direction so largest entry will be at root */
3314 reversedirection(state);
3316 state->memtupcount = 0; /* make the heap empty */
3317 for (i = 0; i < tupcount; i++)
3319 if (state->memtupcount < state->bound)
3321 /* Insert next tuple into heap */
3322 /* Must copy source tuple to avoid possible overwrite */
3323 SortTuple stup = state->memtuples[i];
3325 stup.tupindex = 0; /* not used */
3326 tuplesort_heap_insert(state, &stup, false);
3331 * The heap is full. Replace the largest entry with the new
3332 * tuple, or just discard it, if it's larger than anything already
3335 if (COMPARETUP(state, &state->memtuples[i], &state->memtuples[0]) <= 0)
3337 free_sort_tuple(state, &state->memtuples[i]);
3338 CHECK_FOR_INTERRUPTS();
3341 tuplesort_heap_replace_top(state, &state->memtuples[i], false);
3345 Assert(state->memtupcount == state->bound);
3346 state->status = TSS_BOUNDED;
3350 * Convert the bounded heap to a properly-sorted array
3353 sort_bounded_heap(Tuplesortstate *state)
3355 int tupcount = state->memtupcount;
3357 Assert(state->status == TSS_BOUNDED);
3358 Assert(state->bounded);
3359 Assert(tupcount == state->bound);
3362 * We can unheapify in place because each delete-top call will remove the
3363 * largest entry, which we can promptly store in the newly freed slot at
3364 * the end. Once we're down to a single-entry heap, we're done.
3366 while (state->memtupcount > 1)
3368 SortTuple stup = state->memtuples[0];
3370 /* this sifts-up the next-largest entry and decreases memtupcount */
3371 tuplesort_heap_delete_top(state, false);
3372 state->memtuples[state->memtupcount] = stup;
3374 state->memtupcount = tupcount;
3377 * Reverse sort direction back to the original state. This is not
3378 * actually necessary but seems like a good idea for tidiness.
3380 reversedirection(state);
3382 state->status = TSS_SORTEDINMEM;
3383 state->boundUsed = true;
3387 * Sort all memtuples using specialized qsort() routines.
3389 * Quicksort is used for small in-memory sorts. Quicksort is also generally
3390 * preferred to replacement selection for generating runs during external sort
3391 * operations, although replacement selection is sometimes used for the first
3395 tuplesort_sort_memtuples(Tuplesortstate *state)
3397 if (state->memtupcount > 1)
3399 /* Can we use the single-key sort function? */
3400 if (state->onlyKey != NULL)
3401 qsort_ssup(state->memtuples, state->memtupcount,
3404 qsort_tuple(state->memtuples,
3412 * Insert a new tuple into an empty or existing heap, maintaining the
3413 * heap invariant. Caller is responsible for ensuring there's room.
3415 * Note: For some callers, tuple points to a memtuples[] entry above the
3416 * end of the heap. This is safe as long as it's not immediately adjacent
3417 * to the end of the heap (ie, in the [memtupcount] array entry) --- if it
3418 * is, it might get overwritten before being moved into the heap!
3421 tuplesort_heap_insert(Tuplesortstate *state, SortTuple *tuple,
3424 SortTuple *memtuples;
3427 memtuples = state->memtuples;
3428 Assert(state->memtupcount < state->memtupsize);
3429 Assert(!checkIndex || tuple->tupindex == RUN_FIRST);
3431 CHECK_FOR_INTERRUPTS();
3434 * Sift-up the new entry, per Knuth 5.2.3 exercise 16. Note that Knuth is
3435 * using 1-based array indexes, not 0-based.
3437 j = state->memtupcount++;
3440 int i = (j - 1) >> 1;
3442 if (HEAPCOMPARE(tuple, &memtuples[i]) >= 0)
3444 memtuples[j] = memtuples[i];
3447 memtuples[j] = *tuple;
3451 * Remove the tuple at state->memtuples[0] from the heap. Decrement
3452 * memtupcount, and sift up to maintain the heap invariant.
3454 * The caller has already free'd the tuple the top node points to,
3458 tuplesort_heap_delete_top(Tuplesortstate *state, bool checkIndex)
3460 SortTuple *memtuples = state->memtuples;
3463 Assert(!checkIndex || state->currentRun == RUN_FIRST);
3464 if (--state->memtupcount <= 0)
3468 * Remove the last tuple in the heap, and re-insert it, by replacing the
3469 * current top node with it.
3471 tuple = &memtuples[state->memtupcount];
3472 tuplesort_heap_replace_top(state, tuple, checkIndex);
3476 * Replace the tuple at state->memtuples[0] with a new tuple. Sift up to
3477 * maintain the heap invariant.
3479 * This corresponds to Knuth's "sift-up" algorithm (Algorithm 5.2.3H,
3480 * Heapsort, steps H3-H8).
3483 tuplesort_heap_replace_top(Tuplesortstate *state, SortTuple *tuple,
3486 SortTuple *memtuples = state->memtuples;
3490 Assert(!checkIndex || state->currentRun == RUN_FIRST);
3491 Assert(state->memtupcount >= 1);
3493 CHECK_FOR_INTERRUPTS();
3495 n = state->memtupcount;
3496 i = 0; /* i is where the "hole" is */
3504 HEAPCOMPARE(&memtuples[j], &memtuples[j + 1]) > 0)
3506 if (HEAPCOMPARE(tuple, &memtuples[j]) <= 0)
3508 memtuples[i] = memtuples[j];
3511 memtuples[i] = *tuple;
3515 * Function to reverse the sort direction from its current state
3517 * It is not safe to call this when performing hash tuplesorts
3520 reversedirection(Tuplesortstate *state)
3522 SortSupport sortKey = state->sortKeys;
3525 for (nkey = 0; nkey < state->nKeys; nkey++, sortKey++)
3527 sortKey->ssup_reverse = !sortKey->ssup_reverse;
3528 sortKey->ssup_nulls_first = !sortKey->ssup_nulls_first;
3534 * Tape interface routines
3538 getlen(Tuplesortstate *state, int tapenum, bool eofOK)
3542 if (LogicalTapeRead(state->tapeset, tapenum,
3543 &len, sizeof(len)) != sizeof(len))
3544 elog(ERROR, "unexpected end of tape");
3545 if (len == 0 && !eofOK)
3546 elog(ERROR, "unexpected end of data");
3551 markrunend(Tuplesortstate *state, int tapenum)
3553 unsigned int len = 0;
3555 LogicalTapeWrite(state->tapeset, tapenum, (void *) &len, sizeof(len));
3559 * Get memory for tuple from within READTUP() routine.
3561 * We use next free slot from the slab allocator, or palloc() if the tuple
3562 * is too large for that.
3565 readtup_alloc(Tuplesortstate *state, Size tuplen)
3570 * We pre-allocate enough slots in the slab arena that we should never run
3573 Assert(state->slabFreeHead);
3575 if (tuplen > SLAB_SLOT_SIZE || !state->slabFreeHead)
3576 return MemoryContextAlloc(state->sortcontext, tuplen);
3579 buf = state->slabFreeHead;
3580 /* Reuse this slot */
3581 state->slabFreeHead = buf->nextfree;
3589 * Routines specialized for HeapTuple (actually MinimalTuple) case
3593 comparetup_heap(const SortTuple *a, const SortTuple *b, Tuplesortstate *state)
3595 SortSupport sortKey = state->sortKeys;
3608 /* Compare the leading sort key */
3609 compare = ApplySortComparator(a->datum1, a->isnull1,
3610 b->datum1, b->isnull1,
3615 /* Compare additional sort keys */
3616 ltup.t_len = ((MinimalTuple) a->tuple)->t_len + MINIMAL_TUPLE_OFFSET;
3617 ltup.t_data = (HeapTupleHeader) ((char *) a->tuple - MINIMAL_TUPLE_OFFSET);
3618 rtup.t_len = ((MinimalTuple) b->tuple)->t_len + MINIMAL_TUPLE_OFFSET;
3619 rtup.t_data = (HeapTupleHeader) ((char *) b->tuple - MINIMAL_TUPLE_OFFSET);
3620 tupDesc = state->tupDesc;
3622 if (sortKey->abbrev_converter)
3624 attno = sortKey->ssup_attno;
3626 datum1 = heap_getattr(<up, attno, tupDesc, &isnull1);
3627 datum2 = heap_getattr(&rtup, attno, tupDesc, &isnull2);
3629 compare = ApplySortAbbrevFullComparator(datum1, isnull1,
3637 for (nkey = 1; nkey < state->nKeys; nkey++, sortKey++)
3639 attno = sortKey->ssup_attno;
3641 datum1 = heap_getattr(<up, attno, tupDesc, &isnull1);
3642 datum2 = heap_getattr(&rtup, attno, tupDesc, &isnull2);
3644 compare = ApplySortComparator(datum1, isnull1,
3655 copytup_heap(Tuplesortstate *state, SortTuple *stup, void *tup)
3658 * We expect the passed "tup" to be a TupleTableSlot, and form a
3659 * MinimalTuple using the exported interface for that.
3661 TupleTableSlot *slot = (TupleTableSlot *) tup;
3665 MemoryContext oldcontext = MemoryContextSwitchTo(state->tuplecontext);
3667 /* copy the tuple into sort storage */
3668 tuple = ExecCopySlotMinimalTuple(slot);
3669 stup->tuple = (void *) tuple;
3670 USEMEM(state, GetMemoryChunkSpace(tuple));
3671 /* set up first-column key value */
3672 htup.t_len = tuple->t_len + MINIMAL_TUPLE_OFFSET;
3673 htup.t_data = (HeapTupleHeader) ((char *) tuple - MINIMAL_TUPLE_OFFSET);
3674 original = heap_getattr(&htup,
3675 state->sortKeys[0].ssup_attno,
3679 MemoryContextSwitchTo(oldcontext);
3681 if (!state->sortKeys->abbrev_converter || stup->isnull1)
3684 * Store ordinary Datum representation, or NULL value. If there is a
3685 * converter it won't expect NULL values, and cost model is not
3686 * required to account for NULL, so in that case we avoid calling
3687 * converter and just set datum1 to zeroed representation (to be
3688 * consistent, and to support cheap inequality tests for NULL
3689 * abbreviated keys).
3691 stup->datum1 = original;
3693 else if (!consider_abort_common(state))
3695 /* Store abbreviated key representation */
3696 stup->datum1 = state->sortKeys->abbrev_converter(original,
3701 /* Abort abbreviation */
3704 stup->datum1 = original;
3707 * Set state to be consistent with never trying abbreviation.
3709 * Alter datum1 representation in already-copied tuples, so as to
3710 * ensure a consistent representation (current tuple was just
3711 * handled). It does not matter if some dumped tuples are already
3712 * sorted on tape, since serialized tuples lack abbreviated keys
3713 * (TSS_BUILDRUNS state prevents control reaching here in any case).
3715 for (i = 0; i < state->memtupcount; i++)
3717 SortTuple *mtup = &state->memtuples[i];
3719 htup.t_len = ((MinimalTuple) mtup->tuple)->t_len +
3720 MINIMAL_TUPLE_OFFSET;
3721 htup.t_data = (HeapTupleHeader) ((char *) mtup->tuple -
3722 MINIMAL_TUPLE_OFFSET);
3724 mtup->datum1 = heap_getattr(&htup,
3725 state->sortKeys[0].ssup_attno,
3733 writetup_heap(Tuplesortstate *state, int tapenum, SortTuple *stup)
3735 MinimalTuple tuple = (MinimalTuple) stup->tuple;
3737 /* the part of the MinimalTuple we'll write: */
3738 char *tupbody = (char *) tuple + MINIMAL_TUPLE_DATA_OFFSET;
3739 unsigned int tupbodylen = tuple->t_len - MINIMAL_TUPLE_DATA_OFFSET;
3741 /* total on-disk footprint: */
3742 unsigned int tuplen = tupbodylen + sizeof(int);
3744 LogicalTapeWrite(state->tapeset, tapenum,
3745 (void *) &tuplen, sizeof(tuplen));
3746 LogicalTapeWrite(state->tapeset, tapenum,
3747 (void *) tupbody, tupbodylen);
3748 if (state->randomAccess) /* need trailing length word? */
3749 LogicalTapeWrite(state->tapeset, tapenum,
3750 (void *) &tuplen, sizeof(tuplen));
3752 if (!state->slabAllocatorUsed)
3754 FREEMEM(state, GetMemoryChunkSpace(tuple));
3755 heap_free_minimal_tuple(tuple);
3760 readtup_heap(Tuplesortstate *state, SortTuple *stup,
3761 int tapenum, unsigned int len)
3763 unsigned int tupbodylen = len - sizeof(int);
3764 unsigned int tuplen = tupbodylen + MINIMAL_TUPLE_DATA_OFFSET;
3765 MinimalTuple tuple = (MinimalTuple) readtup_alloc(state, tuplen);
3766 char *tupbody = (char *) tuple + MINIMAL_TUPLE_DATA_OFFSET;
3769 /* read in the tuple proper */
3770 tuple->t_len = tuplen;
3771 LogicalTapeReadExact(state->tapeset, tapenum,
3772 tupbody, tupbodylen);
3773 if (state->randomAccess) /* need trailing length word? */
3774 LogicalTapeReadExact(state->tapeset, tapenum,
3775 &tuplen, sizeof(tuplen));
3776 stup->tuple = (void *) tuple;
3777 /* set up first-column key value */
3778 htup.t_len = tuple->t_len + MINIMAL_TUPLE_OFFSET;
3779 htup.t_data = (HeapTupleHeader) ((char *) tuple - MINIMAL_TUPLE_OFFSET);
3780 stup->datum1 = heap_getattr(&htup,
3781 state->sortKeys[0].ssup_attno,
3787 * Routines specialized for the CLUSTER case (HeapTuple data, with
3788 * comparisons per a btree index definition)
3792 comparetup_cluster(const SortTuple *a, const SortTuple *b,
3793 Tuplesortstate *state)
3795 SortSupport sortKey = state->sortKeys;
3805 AttrNumber leading = state->indexInfo->ii_KeyAttrNumbers[0];
3807 /* Be prepared to compare additional sort keys */
3808 ltup = (HeapTuple) a->tuple;
3809 rtup = (HeapTuple) b->tuple;
3810 tupDesc = state->tupDesc;
3812 /* Compare the leading sort key, if it's simple */
3815 compare = ApplySortComparator(a->datum1, a->isnull1,
3816 b->datum1, b->isnull1,
3821 if (sortKey->abbrev_converter)
3823 datum1 = heap_getattr(ltup, leading, tupDesc, &isnull1);
3824 datum2 = heap_getattr(rtup, leading, tupDesc, &isnull2);
3826 compare = ApplySortAbbrevFullComparator(datum1, isnull1,
3830 if (compare != 0 || state->nKeys == 1)
3832 /* Compare additional columns the hard way */
3838 /* Must compare all keys the hard way */
3842 if (state->indexInfo->ii_Expressions == NULL)
3844 /* If not expression index, just compare the proper heap attrs */
3846 for (; nkey < state->nKeys; nkey++, sortKey++)
3848 AttrNumber attno = state->indexInfo->ii_KeyAttrNumbers[nkey];
3850 datum1 = heap_getattr(ltup, attno, tupDesc, &isnull1);
3851 datum2 = heap_getattr(rtup, attno, tupDesc, &isnull2);
3853 compare = ApplySortComparator(datum1, isnull1,
3863 * In the expression index case, compute the whole index tuple and
3864 * then compare values. It would perhaps be faster to compute only as
3865 * many columns as we need to compare, but that would require
3866 * duplicating all the logic in FormIndexDatum.
3868 Datum l_index_values[INDEX_MAX_KEYS];
3869 bool l_index_isnull[INDEX_MAX_KEYS];
3870 Datum r_index_values[INDEX_MAX_KEYS];
3871 bool r_index_isnull[INDEX_MAX_KEYS];
3872 TupleTableSlot *ecxt_scantuple;
3874 /* Reset context each time to prevent memory leakage */
3875 ResetPerTupleExprContext(state->estate);
3877 ecxt_scantuple = GetPerTupleExprContext(state->estate)->ecxt_scantuple;
3879 ExecStoreTuple(ltup, ecxt_scantuple, InvalidBuffer, false);
3880 FormIndexDatum(state->indexInfo, ecxt_scantuple, state->estate,
3881 l_index_values, l_index_isnull);
3883 ExecStoreTuple(rtup, ecxt_scantuple, InvalidBuffer, false);
3884 FormIndexDatum(state->indexInfo, ecxt_scantuple, state->estate,
3885 r_index_values, r_index_isnull);
3887 for (; nkey < state->nKeys; nkey++, sortKey++)
3889 compare = ApplySortComparator(l_index_values[nkey],
3890 l_index_isnull[nkey],
3891 r_index_values[nkey],
3892 r_index_isnull[nkey],
3903 copytup_cluster(Tuplesortstate *state, SortTuple *stup, void *tup)
3905 HeapTuple tuple = (HeapTuple) tup;
3907 MemoryContext oldcontext = MemoryContextSwitchTo(state->tuplecontext);
3909 /* copy the tuple into sort storage */
3910 tuple = heap_copytuple(tuple);
3911 stup->tuple = (void *) tuple;
3912 USEMEM(state, GetMemoryChunkSpace(tuple));
3914 MemoryContextSwitchTo(oldcontext);
3917 * set up first-column key value, and potentially abbreviate, if it's a
3920 if (state->indexInfo->ii_KeyAttrNumbers[0] == 0)
3923 original = heap_getattr(tuple,
3924 state->indexInfo->ii_KeyAttrNumbers[0],
3928 if (!state->sortKeys->abbrev_converter || stup->isnull1)
3931 * Store ordinary Datum representation, or NULL value. If there is a
3932 * converter it won't expect NULL values, and cost model is not
3933 * required to account for NULL, so in that case we avoid calling
3934 * converter and just set datum1 to zeroed representation (to be
3935 * consistent, and to support cheap inequality tests for NULL
3936 * abbreviated keys).
3938 stup->datum1 = original;
3940 else if (!consider_abort_common(state))
3942 /* Store abbreviated key representation */
3943 stup->datum1 = state->sortKeys->abbrev_converter(original,
3948 /* Abort abbreviation */
3951 stup->datum1 = original;
3954 * Set state to be consistent with never trying abbreviation.
3956 * Alter datum1 representation in already-copied tuples, so as to
3957 * ensure a consistent representation (current tuple was just
3958 * handled). It does not matter if some dumped tuples are already
3959 * sorted on tape, since serialized tuples lack abbreviated keys
3960 * (TSS_BUILDRUNS state prevents control reaching here in any case).
3962 for (i = 0; i < state->memtupcount; i++)
3964 SortTuple *mtup = &state->memtuples[i];
3966 tuple = (HeapTuple) mtup->tuple;
3967 mtup->datum1 = heap_getattr(tuple,
3968 state->indexInfo->ii_KeyAttrNumbers[0],
3976 writetup_cluster(Tuplesortstate *state, int tapenum, SortTuple *stup)
3978 HeapTuple tuple = (HeapTuple) stup->tuple;
3979 unsigned int tuplen = tuple->t_len + sizeof(ItemPointerData) + sizeof(int);
3981 /* We need to store t_self, but not other fields of HeapTupleData */
3982 LogicalTapeWrite(state->tapeset, tapenum,
3983 &tuplen, sizeof(tuplen));
3984 LogicalTapeWrite(state->tapeset, tapenum,
3985 &tuple->t_self, sizeof(ItemPointerData));
3986 LogicalTapeWrite(state->tapeset, tapenum,
3987 tuple->t_data, tuple->t_len);
3988 if (state->randomAccess) /* need trailing length word? */
3989 LogicalTapeWrite(state->tapeset, tapenum,
3990 &tuplen, sizeof(tuplen));
3992 if (!state->slabAllocatorUsed)
3994 FREEMEM(state, GetMemoryChunkSpace(tuple));
3995 heap_freetuple(tuple);
4000 readtup_cluster(Tuplesortstate *state, SortTuple *stup,
4001 int tapenum, unsigned int tuplen)
4003 unsigned int t_len = tuplen - sizeof(ItemPointerData) - sizeof(int);
4004 HeapTuple tuple = (HeapTuple) readtup_alloc(state,
4005 t_len + HEAPTUPLESIZE);
4007 /* Reconstruct the HeapTupleData header */
4008 tuple->t_data = (HeapTupleHeader) ((char *) tuple + HEAPTUPLESIZE);
4009 tuple->t_len = t_len;
4010 LogicalTapeReadExact(state->tapeset, tapenum,
4011 &tuple->t_self, sizeof(ItemPointerData));
4012 /* We don't currently bother to reconstruct t_tableOid */
4013 tuple->t_tableOid = InvalidOid;
4014 /* Read in the tuple body */
4015 LogicalTapeReadExact(state->tapeset, tapenum,
4016 tuple->t_data, tuple->t_len);
4017 if (state->randomAccess) /* need trailing length word? */
4018 LogicalTapeReadExact(state->tapeset, tapenum,
4019 &tuplen, sizeof(tuplen));
4020 stup->tuple = (void *) tuple;
4021 /* set up first-column key value, if it's a simple column */
4022 if (state->indexInfo->ii_KeyAttrNumbers[0] != 0)
4023 stup->datum1 = heap_getattr(tuple,
4024 state->indexInfo->ii_KeyAttrNumbers[0],
4030 * Routines specialized for IndexTuple case
4032 * The btree and hash cases require separate comparison functions, but the
4033 * IndexTuple representation is the same so the copy/write/read support
4034 * functions can be shared.
4038 comparetup_index_btree(const SortTuple *a, const SortTuple *b,
4039 Tuplesortstate *state)
4042 * This is similar to comparetup_heap(), but expects index tuples. There
4043 * is also special handling for enforcing uniqueness, and special
4044 * treatment for equal keys at the end.
4046 SortSupport sortKey = state->sortKeys;
4051 bool equal_hasnull = false;
4060 /* Compare the leading sort key */
4061 compare = ApplySortComparator(a->datum1, a->isnull1,
4062 b->datum1, b->isnull1,
4067 /* Compare additional sort keys */
4068 tuple1 = (IndexTuple) a->tuple;
4069 tuple2 = (IndexTuple) b->tuple;
4070 keysz = state->nKeys;
4071 tupDes = RelationGetDescr(state->indexRel);
4073 if (sortKey->abbrev_converter)
4075 datum1 = index_getattr(tuple1, 1, tupDes, &isnull1);
4076 datum2 = index_getattr(tuple2, 1, tupDes, &isnull2);
4078 compare = ApplySortAbbrevFullComparator(datum1, isnull1,
4085 /* they are equal, so we only need to examine one null flag */
4087 equal_hasnull = true;
4090 for (nkey = 2; nkey <= keysz; nkey++, sortKey++)
4092 datum1 = index_getattr(tuple1, nkey, tupDes, &isnull1);
4093 datum2 = index_getattr(tuple2, nkey, tupDes, &isnull2);
4095 compare = ApplySortComparator(datum1, isnull1,
4099 return compare; /* done when we find unequal attributes */
4101 /* they are equal, so we only need to examine one null flag */
4103 equal_hasnull = true;
4107 * If btree has asked us to enforce uniqueness, complain if two equal
4108 * tuples are detected (unless there was at least one NULL field).
4110 * It is sufficient to make the test here, because if two tuples are equal
4111 * they *must* get compared at some stage of the sort --- otherwise the
4112 * sort algorithm wouldn't have checked whether one must appear before the
4115 if (state->enforceUnique && !equal_hasnull)
4117 Datum values[INDEX_MAX_KEYS];
4118 bool isnull[INDEX_MAX_KEYS];
4122 * Some rather brain-dead implementations of qsort (such as the one in
4123 * QNX 4) will sometimes call the comparison routine to compare a
4124 * value to itself, but we always use our own implementation, which
4127 Assert(tuple1 != tuple2);
4129 index_deform_tuple(tuple1, tupDes, values, isnull);
4131 key_desc = BuildIndexValueDescription(state->indexRel, values, isnull);
4134 (errcode(ERRCODE_UNIQUE_VIOLATION),
4135 errmsg("could not create unique index \"%s\"",
4136 RelationGetRelationName(state->indexRel)),
4137 key_desc ? errdetail("Key %s is duplicated.", key_desc) :
4138 errdetail("Duplicate keys exist."),
4139 errtableconstraint(state->heapRel,
4140 RelationGetRelationName(state->indexRel))));
4144 * If key values are equal, we sort on ItemPointer. This does not affect
4145 * validity of the finished index, but it may be useful to have index
4146 * scans in physical order.
4149 BlockNumber blk1 = ItemPointerGetBlockNumber(&tuple1->t_tid);
4150 BlockNumber blk2 = ItemPointerGetBlockNumber(&tuple2->t_tid);
4153 return (blk1 < blk2) ? -1 : 1;
4156 OffsetNumber pos1 = ItemPointerGetOffsetNumber(&tuple1->t_tid);
4157 OffsetNumber pos2 = ItemPointerGetOffsetNumber(&tuple2->t_tid);
4160 return (pos1 < pos2) ? -1 : 1;
4167 comparetup_index_hash(const SortTuple *a, const SortTuple *b,
4168 Tuplesortstate *state)
4176 * Fetch hash keys and mask off bits we don't want to sort by. We know
4177 * that the first column of the index tuple is the hash key.
4179 Assert(!a->isnull1);
4180 bucket1 = _hash_hashkey2bucket(DatumGetUInt32(a->datum1),
4181 state->max_buckets, state->high_mask,
4183 Assert(!b->isnull1);
4184 bucket2 = _hash_hashkey2bucket(DatumGetUInt32(b->datum1),
4185 state->max_buckets, state->high_mask,
4187 if (bucket1 > bucket2)
4189 else if (bucket1 < bucket2)
4193 * If hash values are equal, we sort on ItemPointer. This does not affect
4194 * validity of the finished index, but it may be useful to have index
4195 * scans in physical order.
4197 tuple1 = (IndexTuple) a->tuple;
4198 tuple2 = (IndexTuple) b->tuple;
4201 BlockNumber blk1 = ItemPointerGetBlockNumber(&tuple1->t_tid);
4202 BlockNumber blk2 = ItemPointerGetBlockNumber(&tuple2->t_tid);
4205 return (blk1 < blk2) ? -1 : 1;
4208 OffsetNumber pos1 = ItemPointerGetOffsetNumber(&tuple1->t_tid);
4209 OffsetNumber pos2 = ItemPointerGetOffsetNumber(&tuple2->t_tid);
4212 return (pos1 < pos2) ? -1 : 1;
4219 copytup_index(Tuplesortstate *state, SortTuple *stup, void *tup)
4221 IndexTuple tuple = (IndexTuple) tup;
4222 unsigned int tuplen = IndexTupleSize(tuple);
4223 IndexTuple newtuple;
4226 /* copy the tuple into sort storage */
4227 newtuple = (IndexTuple) MemoryContextAlloc(state->tuplecontext, tuplen);
4228 memcpy(newtuple, tuple, tuplen);
4229 USEMEM(state, GetMemoryChunkSpace(newtuple));
4230 stup->tuple = (void *) newtuple;
4231 /* set up first-column key value */
4232 original = index_getattr(newtuple,
4234 RelationGetDescr(state->indexRel),
4237 if (!state->sortKeys->abbrev_converter || stup->isnull1)
4240 * Store ordinary Datum representation, or NULL value. If there is a
4241 * converter it won't expect NULL values, and cost model is not
4242 * required to account for NULL, so in that case we avoid calling
4243 * converter and just set datum1 to zeroed representation (to be
4244 * consistent, and to support cheap inequality tests for NULL
4245 * abbreviated keys).
4247 stup->datum1 = original;
4249 else if (!consider_abort_common(state))
4251 /* Store abbreviated key representation */
4252 stup->datum1 = state->sortKeys->abbrev_converter(original,
4257 /* Abort abbreviation */
4260 stup->datum1 = original;
4263 * Set state to be consistent with never trying abbreviation.
4265 * Alter datum1 representation in already-copied tuples, so as to
4266 * ensure a consistent representation (current tuple was just
4267 * handled). It does not matter if some dumped tuples are already
4268 * sorted on tape, since serialized tuples lack abbreviated keys
4269 * (TSS_BUILDRUNS state prevents control reaching here in any case).
4271 for (i = 0; i < state->memtupcount; i++)
4273 SortTuple *mtup = &state->memtuples[i];
4275 tuple = (IndexTuple) mtup->tuple;
4276 mtup->datum1 = index_getattr(tuple,
4278 RelationGetDescr(state->indexRel),
4285 writetup_index(Tuplesortstate *state, int tapenum, SortTuple *stup)
4287 IndexTuple tuple = (IndexTuple) stup->tuple;
4288 unsigned int tuplen;
4290 tuplen = IndexTupleSize(tuple) + sizeof(tuplen);
4291 LogicalTapeWrite(state->tapeset, tapenum,
4292 (void *) &tuplen, sizeof(tuplen));
4293 LogicalTapeWrite(state->tapeset, tapenum,
4294 (void *) tuple, IndexTupleSize(tuple));
4295 if (state->randomAccess) /* need trailing length word? */
4296 LogicalTapeWrite(state->tapeset, tapenum,
4297 (void *) &tuplen, sizeof(tuplen));
4299 if (!state->slabAllocatorUsed)
4301 FREEMEM(state, GetMemoryChunkSpace(tuple));
4307 readtup_index(Tuplesortstate *state, SortTuple *stup,
4308 int tapenum, unsigned int len)
4310 unsigned int tuplen = len - sizeof(unsigned int);
4311 IndexTuple tuple = (IndexTuple) readtup_alloc(state, tuplen);
4313 LogicalTapeReadExact(state->tapeset, tapenum,
4315 if (state->randomAccess) /* need trailing length word? */
4316 LogicalTapeReadExact(state->tapeset, tapenum,
4317 &tuplen, sizeof(tuplen));
4318 stup->tuple = (void *) tuple;
4319 /* set up first-column key value */
4320 stup->datum1 = index_getattr(tuple,
4322 RelationGetDescr(state->indexRel),
4327 * Routines specialized for DatumTuple case
4331 comparetup_datum(const SortTuple *a, const SortTuple *b, Tuplesortstate *state)
4335 compare = ApplySortComparator(a->datum1, a->isnull1,
4336 b->datum1, b->isnull1,
4341 /* if we have abbreviations, then "tuple" has the original value */
4343 if (state->sortKeys->abbrev_converter)
4344 compare = ApplySortAbbrevFullComparator(PointerGetDatum(a->tuple), a->isnull1,
4345 PointerGetDatum(b->tuple), b->isnull1,
4352 copytup_datum(Tuplesortstate *state, SortTuple *stup, void *tup)
4354 /* Not currently needed */
4355 elog(ERROR, "copytup_datum() should not be called");
4359 writetup_datum(Tuplesortstate *state, int tapenum, SortTuple *stup)
4362 unsigned int tuplen;
4363 unsigned int writtenlen;
4370 else if (!state->tuples)
4372 waddr = &stup->datum1;
4373 tuplen = sizeof(Datum);
4377 waddr = stup->tuple;
4378 tuplen = datumGetSize(PointerGetDatum(stup->tuple), false, state->datumTypeLen);
4379 Assert(tuplen != 0);
4382 writtenlen = tuplen + sizeof(unsigned int);
4384 LogicalTapeWrite(state->tapeset, tapenum,
4385 (void *) &writtenlen, sizeof(writtenlen));
4386 LogicalTapeWrite(state->tapeset, tapenum,
4388 if (state->randomAccess) /* need trailing length word? */
4389 LogicalTapeWrite(state->tapeset, tapenum,
4390 (void *) &writtenlen, sizeof(writtenlen));
4392 if (!state->slabAllocatorUsed && stup->tuple)
4394 FREEMEM(state, GetMemoryChunkSpace(stup->tuple));
4400 readtup_datum(Tuplesortstate *state, SortTuple *stup,
4401 int tapenum, unsigned int len)
4403 unsigned int tuplen = len - sizeof(unsigned int);
4408 stup->datum1 = (Datum) 0;
4409 stup->isnull1 = true;
4412 else if (!state->tuples)
4414 Assert(tuplen == sizeof(Datum));
4415 LogicalTapeReadExact(state->tapeset, tapenum,
4416 &stup->datum1, tuplen);
4417 stup->isnull1 = false;
4422 void *raddr = readtup_alloc(state, tuplen);
4424 LogicalTapeReadExact(state->tapeset, tapenum,
4426 stup->datum1 = PointerGetDatum(raddr);
4427 stup->isnull1 = false;
4428 stup->tuple = raddr;
4431 if (state->randomAccess) /* need trailing length word? */
4432 LogicalTapeReadExact(state->tapeset, tapenum,
4433 &tuplen, sizeof(tuplen));
4437 * Convenience routine to free a tuple previously loaded into sort memory
4440 free_sort_tuple(Tuplesortstate *state, SortTuple *stup)
4442 FREEMEM(state, GetMemoryChunkSpace(stup->tuple));
projects / postgresql / blob