Age Owner Branch data TLA Line data Source code
1 : : /*-------------------------------------------------------------------------
2 : : *
3 : : * tuplesort.c
4 : : * Generalized tuple sorting routines.
5 : : *
6 : : * This module provides a generalized facility for tuple sorting, which can be
7 : : * applied to different kinds of sortable objects. Implementation of
8 : : * the particular sorting variants is given in tuplesortvariants.c.
9 : : * This module works efficiently for both small and large amounts
10 : : * of data. Small amounts are sorted in-memory using qsort(). Large
11 : : * amounts are sorted using temporary files and a standard external sort
12 : : * algorithm.
13 : : *
14 : : * See Knuth, volume 3, for more than you want to know about external
15 : : * sorting algorithms. The algorithm we use is a balanced k-way merge.
16 : : * Before PostgreSQL 15, we used the polyphase merge algorithm (Knuth's
17 : : * Algorithm 5.4.2D), but with modern hardware, a straightforward balanced
18 : : * merge is better. Knuth is assuming that tape drives are expensive
19 : : * beasts, and in particular that there will always be many more runs than
20 : : * tape drives. The polyphase merge algorithm was good at keeping all the
21 : : * tape drives busy, but in our implementation a "tape drive" doesn't cost
22 : : * much more than a few Kb of memory buffers, so we can afford to have
23 : : * lots of them. In particular, if we can have as many tape drives as
24 : : * sorted runs, we can eliminate any repeated I/O at all.
25 : : *
26 : : * Historically, we divided the input into sorted runs using replacement
27 : : * selection, in the form of a priority tree implemented as a heap
28 : : * (essentially Knuth's Algorithm 5.2.3H), but now we always use quicksort
29 : : * for run generation.
30 : : *
31 : : * The approximate amount of memory allowed for any one sort operation
32 : : * is specified in kilobytes by the caller (most pass work_mem). Initially,
33 : : * we absorb tuples and simply store them in an unsorted array as long as
34 : : * we haven't exceeded workMem. If we reach the end of the input without
35 : : * exceeding workMem, we sort the array using qsort() and subsequently return
36 : : * tuples just by scanning the tuple array sequentially. If we do exceed
37 : : * workMem, we begin to emit tuples into sorted runs in temporary tapes.
38 : : * When tuples are dumped in batch after quicksorting, we begin a new run
39 : : * with a new output tape. If we reach the max number of tapes, we write
40 : : * subsequent runs on the existing tapes in a round-robin fashion. We will
41 : : * need multiple merge passes to finish the merge in that case. After the
42 : : * end of the input is reached, we dump out remaining tuples in memory into
43 : : * a final run, then merge the runs.
44 : : *
45 : : * When merging runs, we use a heap containing just the frontmost tuple from
46 : : * each source run; we repeatedly output the smallest tuple and replace it
47 : : * with the next tuple from its source tape (if any). When the heap empties,
48 : : * the merge is complete. The basic merge algorithm thus needs very little
49 : : * memory --- only M tuples for an M-way merge, and M is constrained to a
50 : : * small number. However, we can still make good use of our full workMem
51 : : * allocation by pre-reading additional blocks from each source tape. Without
52 : : * prereading, our access pattern to the temporary file would be very erratic;
53 : : * on average we'd read one block from each of M source tapes during the same
54 : : * time that we're writing M blocks to the output tape, so there is no
55 : : * sequentiality of access at all, defeating the read-ahead methods used by
56 : : * most Unix kernels. Worse, the output tape gets written into a very random
57 : : * sequence of blocks of the temp file, ensuring that things will be even
58 : : * worse when it comes time to read that tape. A straightforward merge pass
59 : : * thus ends up doing a lot of waiting for disk seeks. We can improve matters
60 : : * by prereading from each source tape sequentially, loading about workMem/M
61 : : * bytes from each tape in turn, and making the sequential blocks immediately
62 : : * available for reuse. This approach helps to localize both read and write
63 : : * accesses. The pre-reading is handled by logtape.c, we just tell it how
64 : : * much memory to use for the buffers.
65 : : *
66 : : * In the current code we determine the number of input tapes M on the basis
67 : : * of workMem: we want workMem/M to be large enough that we read a fair
68 : : * amount of data each time we read from a tape, so as to maintain the
69 : : * locality of access described above. Nonetheless, with large workMem we
70 : : * can have many tapes. The logical "tapes" are implemented by logtape.c,
71 : : * which avoids space wastage by recycling disk space as soon as each block
72 : : * is read from its "tape".
73 : : *
74 : : * When the caller requests random access to the sort result, we form
75 : : * the final sorted run on a logical tape which is then "frozen", so
76 : : * that we can access it randomly. When the caller does not need random
77 : : * access, we return from tuplesort_performsort() as soon as we are down
78 : : * to one run per logical tape. The final merge is then performed
79 : : * on-the-fly as the caller repeatedly calls tuplesort_getXXX; this
80 : : * saves one cycle of writing all the data out to disk and reading it in.
81 : : *
82 : : * This module supports parallel sorting. Parallel sorts involve coordination
83 : : * among one or more worker processes, and a leader process, each with its own
84 : : * tuplesort state. The leader process (or, more accurately, the
85 : : * Tuplesortstate associated with a leader process) creates a full tapeset
86 : : * consisting of worker tapes with one run to merge; a run for every
87 : : * worker process. This is then merged. Worker processes are guaranteed to
88 : : * produce exactly one output run from their partial input.
89 : : *
90 : : *
91 : : * Portions Copyright (c) 1996-2025, PostgreSQL Global Development Group
92 : : * Portions Copyright (c) 1994, Regents of the University of California
93 : : *
94 : : * IDENTIFICATION
95 : : * src/backend/utils/sort/tuplesort.c
96 : : *
97 : : *-------------------------------------------------------------------------
98 : : */
99 : :
100 : : #include "postgres.h"
101 : :
102 : : #include <limits.h>
103 : :
104 : : #include "commands/tablespace.h"
105 : : #include "miscadmin.h"
106 : : #include "pg_trace.h"
107 : : #include "storage/shmem.h"
108 : : #include "utils/guc.h"
109 : : #include "utils/memutils.h"
110 : : #include "utils/pg_rusage.h"
111 : : #include "utils/tuplesort.h"
112 : :
113 : : /*
114 : : * Initial size of memtuples array. This must be more than
115 : : * ALLOCSET_SEPARATE_THRESHOLD; see comments in grow_memtuples(). Clamp at
116 : : * 1024 elements to avoid excessive reallocs.
117 : : */
118 : : #define INITIAL_MEMTUPSIZE Max(1024, \
119 : : ALLOCSET_SEPARATE_THRESHOLD / sizeof(SortTuple) + 1)
120 : :
121 : : /* GUC variables */
122 : : bool trace_sort = false;
123 : :
124 : : #ifdef DEBUG_BOUNDED_SORT
125 : : bool optimize_bounded_sort = true;
126 : : #endif
127 : :
128 : :
129 : : /*
130 : : * During merge, we use a pre-allocated set of fixed-size slots to hold
131 : : * tuples. To avoid palloc/pfree overhead.
132 : : *
133 : : * Merge doesn't require a lot of memory, so we can afford to waste some,
134 : : * by using gratuitously-sized slots. If a tuple is larger than 1 kB, the
135 : : * palloc() overhead is not significant anymore.
136 : : *
137 : : * 'nextfree' is valid when this chunk is in the free list. When in use, the
138 : : * slot holds a tuple.
139 : : */
140 : : #define SLAB_SLOT_SIZE 1024
141 : :
142 : : typedef union SlabSlot
143 : : {
144 : : union SlabSlot *nextfree;
145 : : char buffer[SLAB_SLOT_SIZE];
146 : : } SlabSlot;
147 : :
148 : : /*
149 : : * Possible states of a Tuplesort object. These denote the states that
150 : : * persist between calls of Tuplesort routines.
151 : : */
152 : : typedef enum
153 : : {
154 : : TSS_INITIAL, /* Loading tuples; still within memory limit */
155 : : TSS_BOUNDED, /* Loading tuples into bounded-size heap */
156 : : TSS_BUILDRUNS, /* Loading tuples; writing to tape */
157 : : TSS_SORTEDINMEM, /* Sort completed entirely in memory */
158 : : TSS_SORTEDONTAPE, /* Sort completed, final run is on tape */
159 : : TSS_FINALMERGE, /* Performing final merge on-the-fly */
160 : : } TupSortStatus;
161 : :
162 : : /*
163 : : * Parameters for calculation of number of tapes to use --- see inittapes()
164 : : * and tuplesort_merge_order().
165 : : *
166 : : * In this calculation we assume that each tape will cost us about 1 blocks
167 : : * worth of buffer space. This ignores the overhead of all the other data
168 : : * structures needed for each tape, but it's probably close enough.
169 : : *
170 : : * MERGE_BUFFER_SIZE is how much buffer space we'd like to allocate for each
171 : : * input tape, for pre-reading (see discussion at top of file). This is *in
172 : : * addition to* the 1 block already included in TAPE_BUFFER_OVERHEAD.
173 : : */
174 : : #define MINORDER 6 /* minimum merge order */
175 : : #define MAXORDER 500 /* maximum merge order */
176 : : #define TAPE_BUFFER_OVERHEAD BLCKSZ
177 : : #define MERGE_BUFFER_SIZE (BLCKSZ * 32)
178 : :
179 : :
180 : : /*
181 : : * Private state of a Tuplesort operation.
182 : : */
183 : : struct Tuplesortstate
184 : : {
185 : : TuplesortPublic base;
186 : : TupSortStatus status; /* enumerated value as shown above */
187 : : bool bounded; /* did caller specify a maximum number of
188 : : * tuples to return? */
189 : : bool boundUsed; /* true if we made use of a bounded heap */
190 : : int bound; /* if bounded, the maximum number of tuples */
191 : : int64 tupleMem; /* memory consumed by individual tuples.
192 : : * storing this separately from what we track
193 : : * in availMem allows us to subtract the
194 : : * memory consumed by all tuples when dumping
195 : : * tuples to tape */
196 : : int64 availMem; /* remaining memory available, in bytes */
197 : : int64 allowedMem; /* total memory allowed, in bytes */
198 : : int maxTapes; /* max number of input tapes to merge in each
199 : : * pass */
200 : : int64 maxSpace; /* maximum amount of space occupied among sort
201 : : * of groups, either in-memory or on-disk */
202 : : bool isMaxSpaceDisk; /* true when maxSpace is value for on-disk
203 : : * space, false when its value for in-memory
204 : : * space */
205 : : TupSortStatus maxSpaceStatus; /* sort status when maxSpace was reached */
206 : : LogicalTapeSet *tapeset; /* logtape.c object for tapes in a temp file */
207 : :
208 : : /*
209 : : * This array holds the tuples now in sort memory. If we are in state
210 : : * INITIAL, the tuples are in no particular order; if we are in state
211 : : * SORTEDINMEM, the tuples are in final sorted order; in states BUILDRUNS
212 : : * and FINALMERGE, the tuples are organized in "heap" order per Algorithm
213 : : * H. In state SORTEDONTAPE, the array is not used.
214 : : */
215 : : SortTuple *memtuples; /* array of SortTuple structs */
216 : : int memtupcount; /* number of tuples currently present */
217 : : int memtupsize; /* allocated length of memtuples array */
218 : : bool growmemtuples; /* memtuples' growth still underway? */
219 : :
220 : : /*
221 : : * Memory for tuples is sometimes allocated using a simple slab allocator,
222 : : * rather than with palloc(). Currently, we switch to slab allocation
223 : : * when we start merging. Merging only needs to keep a small, fixed
224 : : * number of tuples in memory at any time, so we can avoid the
225 : : * palloc/pfree overhead by recycling a fixed number of fixed-size slots
226 : : * to hold the tuples.
227 : : *
228 : : * For the slab, we use one large allocation, divided into SLAB_SLOT_SIZE
229 : : * slots. The allocation is sized to have one slot per tape, plus one
230 : : * additional slot. We need that many slots to hold all the tuples kept
231 : : * in the heap during merge, plus the one we have last returned from the
232 : : * sort, with tuplesort_gettuple.
233 : : *
234 : : * Initially, all the slots are kept in a linked list of free slots. When
235 : : * a tuple is read from a tape, it is put to the next available slot, if
236 : : * it fits. If the tuple is larger than SLAB_SLOT_SIZE, it is palloc'd
237 : : * instead.
238 : : *
239 : : * When we're done processing a tuple, we return the slot back to the free
240 : : * list, or pfree() if it was palloc'd. We know that a tuple was
241 : : * allocated from the slab, if its pointer value is between
242 : : * slabMemoryBegin and -End.
243 : : *
244 : : * When the slab allocator is used, the USEMEM/LACKMEM mechanism of
245 : : * tracking memory usage is not used.
246 : : */
247 : : bool slabAllocatorUsed;
248 : :
249 : : char *slabMemoryBegin; /* beginning of slab memory arena */
250 : : char *slabMemoryEnd; /* end of slab memory arena */
251 : : SlabSlot *slabFreeHead; /* head of free list */
252 : :
253 : : /* Memory used for input and output tape buffers. */
254 : : size_t tape_buffer_mem;
255 : :
256 : : /*
257 : : * When we return a tuple to the caller in tuplesort_gettuple_XXX, that
258 : : * came from a tape (that is, in TSS_SORTEDONTAPE or TSS_FINALMERGE
259 : : * modes), we remember the tuple in 'lastReturnedTuple', so that we can
260 : : * recycle the memory on next gettuple call.
261 : : */
262 : : void *lastReturnedTuple;
263 : :
264 : : /*
265 : : * While building initial runs, this is the current output run number.
266 : : * Afterwards, it is the number of initial runs we made.
267 : : */
268 : : int currentRun;
269 : :
270 : : /*
271 : : * Logical tapes, for merging.
272 : : *
273 : : * The initial runs are written in the output tapes. In each merge pass,
274 : : * the output tapes of the previous pass become the input tapes, and new
275 : : * output tapes are created as needed. When nInputTapes equals
276 : : * nInputRuns, there is only one merge pass left.
277 : : */
278 : : LogicalTape **inputTapes;
279 : : int nInputTapes;
280 : : int nInputRuns;
281 : :
282 : : LogicalTape **outputTapes;
283 : : int nOutputTapes;
284 : : int nOutputRuns;
285 : :
286 : : LogicalTape *destTape; /* current output tape */
287 : :
288 : : /*
289 : : * These variables are used after completion of sorting to keep track of
290 : : * the next tuple to return. (In the tape case, the tape's current read
291 : : * position is also critical state.)
292 : : */
293 : : LogicalTape *result_tape; /* actual tape of finished output */
294 : : int current; /* array index (only used if SORTEDINMEM) */
295 : : bool eof_reached; /* reached EOF (needed for cursors) */
296 : :
297 : : /* markpos_xxx holds marked position for mark and restore */
298 : : int64 markpos_block; /* tape block# (only used if SORTEDONTAPE) */
299 : : int markpos_offset; /* saved "current", or offset in tape block */
300 : : bool markpos_eof; /* saved "eof_reached" */
301 : :
302 : : /*
303 : : * These variables are used during parallel sorting.
304 : : *
305 : : * worker is our worker identifier. Follows the general convention that
306 : : * -1 value relates to a leader tuplesort, and values >= 0 worker
307 : : * tuplesorts. (-1 can also be a serial tuplesort.)
308 : : *
309 : : * shared is mutable shared memory state, which is used to coordinate
310 : : * parallel sorts.
311 : : *
312 : : * nParticipants is the number of worker Tuplesortstates known by the
313 : : * leader to have actually been launched, which implies that they must
314 : : * finish a run that the leader needs to merge. Typically includes a
315 : : * worker state held by the leader process itself. Set in the leader
316 : : * Tuplesortstate only.
317 : : */
318 : : int worker;
319 : : Sharedsort *shared;
320 : : int nParticipants;
321 : :
322 : : /*
323 : : * Additional state for managing "abbreviated key" sortsupport routines
324 : : * (which currently may be used by all cases except the hash index case).
325 : : * Tracks the intervals at which the optimization's effectiveness is
326 : : * tested.
327 : : */
328 : : int64 abbrevNext; /* Tuple # at which to next check
329 : : * applicability */
330 : :
331 : : /*
332 : : * Resource snapshot for time of sort start.
333 : : */
334 : : PGRUsage ru_start;
335 : : };
336 : :
337 : : /*
338 : : * Private mutable state of tuplesort-parallel-operation. This is allocated
339 : : * in shared memory.
340 : : */
341 : : struct Sharedsort
342 : : {
343 : : /* mutex protects all fields prior to tapes */
344 : : slock_t mutex;
345 : :
346 : : /*
347 : : * currentWorker generates ordinal identifier numbers for parallel sort
348 : : * workers. These start from 0, and are always gapless.
349 : : *
350 : : * Workers increment workersFinished to indicate having finished. If this
351 : : * is equal to state.nParticipants within the leader, leader is ready to
352 : : * merge worker runs.
353 : : */
354 : : int currentWorker;
355 : : int workersFinished;
356 : :
357 : : /* Temporary file space */
358 : : SharedFileSet fileset;
359 : :
360 : : /* Size of tapes flexible array */
361 : : int nTapes;
362 : :
363 : : /*
364 : : * Tapes array used by workers to report back information needed by the
365 : : * leader to concatenate all worker tapes into one for merging
366 : : */
367 : : TapeShare tapes[FLEXIBLE_ARRAY_MEMBER];
368 : : };
369 : :
370 : : /*
371 : : * Is the given tuple allocated from the slab memory arena?
372 : : */
373 : : #define IS_SLAB_SLOT(state, tuple) \
374 : : ((char *) (tuple) >= (state)->slabMemoryBegin && \
375 : : (char *) (tuple) < (state)->slabMemoryEnd)
376 : :
377 : : /*
378 : : * Return the given tuple to the slab memory free list, or free it
379 : : * if it was palloc'd.
380 : : */
381 : : #define RELEASE_SLAB_SLOT(state, tuple) \
382 : : do { \
383 : : SlabSlot *buf = (SlabSlot *) tuple; \
384 : : \
385 : : if (IS_SLAB_SLOT((state), buf)) \
386 : : { \
387 : : buf->nextfree = (state)->slabFreeHead; \
388 : : (state)->slabFreeHead = buf; \
389 : : } else \
390 : : pfree(buf); \
391 : : } while(0)
392 : :
393 : : #define REMOVEABBREV(state,stup,count) ((*(state)->base.removeabbrev) (state, stup, count))
394 : : #define COMPARETUP(state,a,b) ((*(state)->base.comparetup) (a, b, state))
395 : : #define WRITETUP(state,tape,stup) ((*(state)->base.writetup) (state, tape, stup))
396 : : #define READTUP(state,stup,tape,len) ((*(state)->base.readtup) (state, stup, tape, len))
397 : : #define FREESTATE(state) ((state)->base.freestate ? (*(state)->base.freestate) (state) : (void) 0)
398 : : #define LACKMEM(state) ((state)->availMem < 0 && !(state)->slabAllocatorUsed)
399 : : #define USEMEM(state,amt) ((state)->availMem -= (amt))
400 : : #define FREEMEM(state,amt) ((state)->availMem += (amt))
401 : : #define SERIAL(state) ((state)->shared == NULL)
402 : : #define WORKER(state) ((state)->shared && (state)->worker != -1)
403 : : #define LEADER(state) ((state)->shared && (state)->worker == -1)
404 : :
405 : : /*
406 : : * NOTES about on-tape representation of tuples:
407 : : *
408 : : * We require the first "unsigned int" of a stored tuple to be the total size
409 : : * on-tape of the tuple, including itself (so it is never zero; an all-zero
410 : : * unsigned int is used to delimit runs). The remainder of the stored tuple
411 : : * may or may not match the in-memory representation of the tuple ---
412 : : * any conversion needed is the job of the writetup and readtup routines.
413 : : *
414 : : * If state->sortopt contains TUPLESORT_RANDOMACCESS, then the stored
415 : : * representation of the tuple must be followed by another "unsigned int" that
416 : : * is a copy of the length --- so the total tape space used is actually
417 : : * sizeof(unsigned int) more than the stored length value. This allows
418 : : * read-backwards. When the random access flag was not specified, the
419 : : * write/read routines may omit the extra length word.
420 : : *
421 : : * writetup is expected to write both length words as well as the tuple
422 : : * data. When readtup is called, the tape is positioned just after the
423 : : * front length word; readtup must read the tuple data and advance past
424 : : * the back length word (if present).
425 : : *
426 : : * The write/read routines can make use of the tuple description data
427 : : * stored in the Tuplesortstate record, if needed. They are also expected
428 : : * to adjust state->availMem by the amount of memory space (not tape space!)
429 : : * released or consumed. There is no error return from either writetup
430 : : * or readtup; they should ereport() on failure.
431 : : *
432 : : *
433 : : * NOTES about memory consumption calculations:
434 : : *
435 : : * We count space allocated for tuples against the workMem limit, plus
436 : : * the space used by the variable-size memtuples array. Fixed-size space
437 : : * is not counted; it's small enough to not be interesting.
438 : : *
439 : : * Note that we count actual space used (as shown by GetMemoryChunkSpace)
440 : : * rather than the originally-requested size. This is important since
441 : : * palloc can add substantial overhead. It's not a complete answer since
442 : : * we won't count any wasted space in palloc allocation blocks, but it's
443 : : * a lot better than what we were doing before 7.3. As of 9.6, a
444 : : * separate memory context is used for caller passed tuples. Resetting
445 : : * it at certain key increments significantly ameliorates fragmentation.
446 : : * readtup routines use the slab allocator (they cannot use
447 : : * the reset context because it gets deleted at the point that merging
448 : : * begins).
449 : : */
450 : :
451 : :
452 : : static void tuplesort_begin_batch(Tuplesortstate *state);
453 : : static bool consider_abort_common(Tuplesortstate *state);
454 : : static void inittapes(Tuplesortstate *state, bool mergeruns);
455 : : static void inittapestate(Tuplesortstate *state, int maxTapes);
456 : : static void selectnewtape(Tuplesortstate *state);
457 : : static void init_slab_allocator(Tuplesortstate *state, int numSlots);
458 : : static void mergeruns(Tuplesortstate *state);
459 : : static void mergeonerun(Tuplesortstate *state);
460 : : static void beginmerge(Tuplesortstate *state);
461 : : static bool mergereadnext(Tuplesortstate *state, LogicalTape *srcTape, SortTuple *stup);
462 : : static void dumptuples(Tuplesortstate *state, bool alltuples);
463 : : static void make_bounded_heap(Tuplesortstate *state);
464 : : static void sort_bounded_heap(Tuplesortstate *state);
465 : : static void tuplesort_sort_memtuples(Tuplesortstate *state);
466 : : static void tuplesort_heap_insert(Tuplesortstate *state, SortTuple *tuple);
467 : : static void tuplesort_heap_replace_top(Tuplesortstate *state, SortTuple *tuple);
468 : : static void tuplesort_heap_delete_top(Tuplesortstate *state);
469 : : static void reversedirection(Tuplesortstate *state);
470 : : static unsigned int getlen(LogicalTape *tape, bool eofOK);
471 : : static void markrunend(LogicalTape *tape);
472 : : static int worker_get_identifier(Tuplesortstate *state);
473 : : static void worker_freeze_result_tape(Tuplesortstate *state);
474 : : static void worker_nomergeruns(Tuplesortstate *state);
475 : : static void leader_takeover_tapes(Tuplesortstate *state);
476 : : static void free_sort_tuple(Tuplesortstate *state, SortTuple *stup);
477 : : static void tuplesort_free(Tuplesortstate *state);
478 : : static void tuplesort_updatemax(Tuplesortstate *state);
479 : :
480 : : /*
481 : : * Specialized comparators that we can inline into specialized sorts. The goal
482 : : * is to try to sort two tuples without having to follow the pointers to the
483 : : * comparator or the tuple.
484 : : *
485 : : * XXX: For now, there is no specialization for cases where datum1 is
486 : : * authoritative and we don't even need to fall back to a callback at all (that
487 : : * would be true for types like int4/int8/timestamp/date, but not true for
488 : : * abbreviations of text or multi-key sorts. There could be! Is it worth it?
489 : : */
490 : :
491 : : /* Used if first key's comparator is ssup_datum_unsigned_cmp */
492 : : static pg_attribute_always_inline int
1355 john.naylor@postgres 493 :CBC 23267917 : qsort_tuple_unsigned_compare(SortTuple *a, SortTuple *b, Tuplesortstate *state)
494 : : {
495 : : int compare;
496 : :
497 : 23267917 : compare = ApplyUnsignedSortComparator(a->datum1, a->isnull1,
498 : 23267917 : b->datum1, b->isnull1,
499 : : &state->base.sortKeys[0]);
500 [ + + ]: 23267917 : if (compare != 0)
501 : 20984054 : return compare;
502 : :
503 : : /*
504 : : * No need to waste effort calling the tiebreak function when there are no
505 : : * other keys to sort on.
506 : : */
1239 akorotkov@postgresql 507 [ - + ]: 2283863 : if (state->base.onlyKey != NULL)
1335 drowley@postgresql.o 508 :UBC 0 : return 0;
509 : :
854 john.naylor@postgres 510 :CBC 2283863 : return state->base.comparetup_tiebreak(a, b, state);
511 : : }
512 : :
513 : : /* Used if first key's comparator is ssup_datum_signed_cmp */
514 : : static pg_attribute_always_inline int
1355 515 : 4682505 : qsort_tuple_signed_compare(SortTuple *a, SortTuple *b, Tuplesortstate *state)
516 : : {
517 : : int compare;
518 : :
519 : 4682505 : compare = ApplySignedSortComparator(a->datum1, a->isnull1,
520 : 4682505 : b->datum1, b->isnull1,
521 : : &state->base.sortKeys[0]);
522 : :
523 [ + + ]: 4682505 : if (compare != 0)
524 : 4645497 : return compare;
525 : :
526 : : /*
527 : : * No need to waste effort calling the tiebreak function when there are no
528 : : * other keys to sort on.
529 : : */
1239 akorotkov@postgresql 530 [ + + ]: 37008 : if (state->base.onlyKey != NULL)
1335 drowley@postgresql.o 531 : 29757 : return 0;
532 : :
854 john.naylor@postgres 533 : 7251 : return state->base.comparetup_tiebreak(a, b, state);
534 : : }
535 : :
536 : : /* Used if first key's comparator is ssup_datum_int32_cmp */
537 : : static pg_attribute_always_inline int
1355 538 : 28058825 : qsort_tuple_int32_compare(SortTuple *a, SortTuple *b, Tuplesortstate *state)
539 : : {
540 : : int compare;
541 : :
542 : 28058825 : compare = ApplyInt32SortComparator(a->datum1, a->isnull1,
1315 tgl@sss.pgh.pa.us 543 : 28058825 : b->datum1, b->isnull1,
544 : : &state->base.sortKeys[0]);
545 : :
1355 john.naylor@postgres 546 [ + + ]: 28058825 : if (compare != 0)
547 : 20056098 : return compare;
548 : :
549 : : /*
550 : : * No need to waste effort calling the tiebreak function when there are no
551 : : * other keys to sort on.
552 : : */
1239 akorotkov@postgresql 553 [ + + ]: 8002727 : if (state->base.onlyKey != NULL)
1335 drowley@postgresql.o 554 : 1137784 : return 0;
555 : :
854 john.naylor@postgres 556 : 6864943 : return state->base.comparetup_tiebreak(a, b, state);
557 : : }
558 : :
559 : : /*
560 : : * Special versions of qsort just for SortTuple objects. qsort_tuple() sorts
561 : : * any variant of SortTuples, using the appropriate comparetup function.
562 : : * qsort_ssup() is specialized for the case where the comparetup function
563 : : * reduces to ApplySortComparator(), that is single-key MinimalTuple sorts
564 : : * and Datum sorts. qsort_tuple_{unsigned,signed,int32} are specialized for
565 : : * common comparison functions on pass-by-value leading datums.
566 : : */
567 : :
568 : : #define ST_SORT qsort_tuple_unsigned
569 : : #define ST_ELEMENT_TYPE SortTuple
570 : : #define ST_COMPARE(a, b, state) qsort_tuple_unsigned_compare(a, b, state)
571 : : #define ST_COMPARE_ARG_TYPE Tuplesortstate
572 : : #define ST_CHECK_FOR_INTERRUPTS
573 : : #define ST_SCOPE static
574 : : #define ST_DEFINE
575 : : #include "lib/sort_template.h"
576 : :
577 : : #define ST_SORT qsort_tuple_signed
578 : : #define ST_ELEMENT_TYPE SortTuple
579 : : #define ST_COMPARE(a, b, state) qsort_tuple_signed_compare(a, b, state)
580 : : #define ST_COMPARE_ARG_TYPE Tuplesortstate
581 : : #define ST_CHECK_FOR_INTERRUPTS
582 : : #define ST_SCOPE static
583 : : #define ST_DEFINE
584 : : #include "lib/sort_template.h"
585 : :
586 : : #define ST_SORT qsort_tuple_int32
587 : : #define ST_ELEMENT_TYPE SortTuple
588 : : #define ST_COMPARE(a, b, state) qsort_tuple_int32_compare(a, b, state)
589 : : #define ST_COMPARE_ARG_TYPE Tuplesortstate
590 : : #define ST_CHECK_FOR_INTERRUPTS
591 : : #define ST_SCOPE static
592 : : #define ST_DEFINE
593 : : #include "lib/sort_template.h"
594 : :
595 : : #define ST_SORT qsort_tuple
596 : : #define ST_ELEMENT_TYPE SortTuple
597 : : #define ST_COMPARE_RUNTIME_POINTER
598 : : #define ST_COMPARE_ARG_TYPE Tuplesortstate
599 : : #define ST_CHECK_FOR_INTERRUPTS
600 : : #define ST_SCOPE static
601 : : #define ST_DECLARE
602 : : #define ST_DEFINE
603 : : #include "lib/sort_template.h"
604 : :
605 : : #define ST_SORT qsort_ssup
606 : : #define ST_ELEMENT_TYPE SortTuple
607 : : #define ST_COMPARE(a, b, ssup) \
608 : : ApplySortComparator((a)->datum1, (a)->isnull1, \
609 : : (b)->datum1, (b)->isnull1, (ssup))
610 : : #define ST_COMPARE_ARG_TYPE SortSupportData
611 : : #define ST_CHECK_FOR_INTERRUPTS
612 : : #define ST_SCOPE static
613 : : #define ST_DEFINE
614 : : #include "lib/sort_template.h"
615 : :
616 : : /*
617 : : * tuplesort_begin_xxx
618 : : *
619 : : * Initialize for a tuple sort operation.
620 : : *
621 : : * After calling tuplesort_begin, the caller should call tuplesort_putXXX
622 : : * zero or more times, then call tuplesort_performsort when all the tuples
623 : : * have been supplied. After performsort, retrieve the tuples in sorted
624 : : * order by calling tuplesort_getXXX until it returns false/NULL. (If random
625 : : * access was requested, rescan, markpos, and restorepos can also be called.)
626 : : * Call tuplesort_end to terminate the operation and release memory/disk space.
627 : : *
628 : : * Each variant of tuplesort_begin has a workMem parameter specifying the
629 : : * maximum number of kilobytes of RAM to use before spilling data to disk.
630 : : * (The normal value of this parameter is work_mem, but some callers use
631 : : * other values.) Each variant also has a sortopt which is a bitmask of
632 : : * sort options. See TUPLESORT_* definitions in tuplesort.h
633 : : */
634 : :
635 : : Tuplesortstate *
1353 drowley@postgresql.o 636 : 137730 : tuplesort_begin_common(int workMem, SortCoordinate coordinate, int sortopt)
637 : : {
638 : : Tuplesortstate *state;
639 : : MemoryContext maincontext;
640 : : MemoryContext sortcontext;
641 : : MemoryContext oldcontext;
642 : :
643 : : /* See leader_takeover_tapes() remarks on random access support */
644 [ + + - + ]: 137730 : if (coordinate && (sortopt & TUPLESORT_RANDOMACCESS))
2875 rhaas@postgresql.org 645 [ # # ]:UBC 0 : elog(ERROR, "random access disallowed under parallel sort");
646 : :
647 : : /*
648 : : * Memory context surviving tuplesort_reset. This memory context holds
649 : : * data which is useful to keep while sorting multiple similar batches.
650 : : */
2081 tomas.vondra@postgre 651 :CBC 137730 : maincontext = AllocSetContextCreate(CurrentMemoryContext,
652 : : "TupleSort main",
653 : : ALLOCSET_DEFAULT_SIZES);
654 : :
655 : : /*
656 : : * Create a working memory context for one sort operation. The content of
657 : : * this context is deleted by tuplesort_reset.
658 : : */
659 : 137730 : sortcontext = AllocSetContextCreate(maincontext,
660 : : "TupleSort sort",
661 : : ALLOCSET_DEFAULT_SIZES);
662 : :
663 : : /*
664 : : * Additionally a working memory context for tuples is setup in
665 : : * tuplesort_begin_batch.
666 : : */
667 : :
668 : : /*
669 : : * Make the Tuplesortstate within the per-sortstate context. This way, we
670 : : * don't need a separate pfree() operation for it at shutdown.
671 : : */
672 : 137730 : oldcontext = MemoryContextSwitchTo(maincontext);
673 : :
7 michael@paquier.xyz 674 :GNC 137730 : state = palloc0_object(Tuplesortstate);
675 : :
7380 tgl@sss.pgh.pa.us 676 [ - + ]:CBC 137730 : if (trace_sort)
7380 tgl@sss.pgh.pa.us 677 :UBC 0 : pg_rusage_init(&state->ru_start);
678 : :
1239 akorotkov@postgresql 679 :CBC 137730 : state->base.sortopt = sortopt;
680 : 137730 : state->base.tuples = true;
681 : 137730 : state->abbrevNext = 10;
682 : :
683 : : /*
684 : : * workMem is forced to be at least 64KB, the current minimum valid value
685 : : * for the work_mem GUC. This is a defense against parallel sort callers
686 : : * that divide out memory among many workers in a way that leaves each
687 : : * with very little memory.
688 : : */
2875 rhaas@postgresql.org 689 : 137730 : state->allowedMem = Max(workMem, 64) * (int64) 1024;
1239 akorotkov@postgresql 690 : 137730 : state->base.sortcontext = sortcontext;
691 : 137730 : state->base.maincontext = maincontext;
692 : :
2081 tomas.vondra@postgre 693 : 137730 : state->memtupsize = INITIAL_MEMTUPSIZE;
694 : 137730 : state->memtuples = NULL;
695 : :
696 : : /*
697 : : * After all of the other non-parallel-related state, we setup all of the
698 : : * state needed for each batch.
699 : : */
700 : 137730 : tuplesort_begin_batch(state);
701 : :
702 : : /*
703 : : * Initialize parallel-related state based on coordination information
704 : : * from caller
705 : : */
2875 rhaas@postgresql.org 706 [ + + ]: 137730 : if (!coordinate)
707 : : {
708 : : /* Serial sort */
709 : 137380 : state->shared = NULL;
710 : 137380 : state->worker = -1;
711 : 137380 : state->nParticipants = -1;
712 : : }
713 [ + + ]: 350 : else if (coordinate->isWorker)
714 : : {
715 : : /* Parallel worker produces exactly one final run from all input */
716 : 234 : state->shared = coordinate->sharedsort;
717 : 234 : state->worker = worker_get_identifier(state);
718 : 234 : state->nParticipants = -1;
719 : : }
720 : : else
721 : : {
722 : : /* Parallel leader state only used for final merge */
723 : 116 : state->shared = coordinate->sharedsort;
724 : 116 : state->worker = -1;
725 : 116 : state->nParticipants = coordinate->nParticipants;
726 [ - + ]: 116 : Assert(state->nParticipants >= 1);
727 : : }
728 : :
7234 tgl@sss.pgh.pa.us 729 : 137730 : MemoryContextSwitchTo(oldcontext);
730 : :
9558 731 : 137730 : return state;
732 : : }
733 : :
734 : : /*
735 : : * tuplesort_begin_batch
736 : : *
737 : : * Setup, or reset, all state need for processing a new set of tuples with this
738 : : * sort state. Called both from tuplesort_begin_common (the first time sorting
739 : : * with this sort state) and tuplesort_reset (for subsequent usages).
740 : : */
741 : : static void
2081 tomas.vondra@postgre 742 : 139399 : tuplesort_begin_batch(Tuplesortstate *state)
743 : : {
744 : : MemoryContext oldcontext;
745 : :
1239 akorotkov@postgresql 746 : 139399 : oldcontext = MemoryContextSwitchTo(state->base.maincontext);
747 : :
748 : : /*
749 : : * Caller tuple (e.g. IndexTuple) memory context.
750 : : *
751 : : * A dedicated child context used exclusively for caller passed tuples
752 : : * eases memory management. Resetting at key points reduces
753 : : * fragmentation. Note that the memtuples array of SortTuples is allocated
754 : : * in the parent context, not this context, because there is no need to
755 : : * free memtuples early. For bounded sorts, tuples may be pfreed in any
756 : : * order, so we use a regular aset.c context so that it can make use of
757 : : * free'd memory. When the sort is not bounded, we make use of a bump.c
758 : : * context as this keeps allocations more compact with less wastage.
759 : : * Allocations are also slightly more CPU efficient.
760 : : */
618 drowley@postgresql.o 761 [ + + ]: 139399 : if (TupleSortUseBumpTupleCxt(state->base.sortopt))
762 : 138715 : state->base.tuplecontext = BumpContextCreate(state->base.sortcontext,
763 : : "Caller tuples",
764 : : ALLOCSET_DEFAULT_SIZES);
765 : : else
1239 akorotkov@postgresql 766 : 684 : state->base.tuplecontext = AllocSetContextCreate(state->base.sortcontext,
767 : : "Caller tuples",
768 : : ALLOCSET_DEFAULT_SIZES);
769 : :
770 : :
2081 tomas.vondra@postgre 771 : 139399 : state->status = TSS_INITIAL;
772 : 139399 : state->bounded = false;
773 : 139399 : state->boundUsed = false;
774 : :
775 : 139399 : state->availMem = state->allowedMem;
776 : :
777 : 139399 : state->tapeset = NULL;
778 : :
779 : 139399 : state->memtupcount = 0;
780 : :
781 : 139399 : state->growmemtuples = true;
782 : 139399 : state->slabAllocatorUsed = false;
783 [ + + + + ]: 139399 : if (state->memtuples != NULL && state->memtupsize != INITIAL_MEMTUPSIZE)
784 : : {
2081 tomas.vondra@postgre 785 :GBC 36 : pfree(state->memtuples);
786 : 36 : state->memtuples = NULL;
787 : 36 : state->memtupsize = INITIAL_MEMTUPSIZE;
788 : : }
2081 tomas.vondra@postgre 789 [ + + ]:CBC 139399 : if (state->memtuples == NULL)
790 : : {
791 : 137766 : state->memtuples = (SortTuple *) palloc(state->memtupsize * sizeof(SortTuple));
792 : 137766 : USEMEM(state, GetMemoryChunkSpace(state->memtuples));
793 : : }
794 : :
795 : : /* workMem must be large enough for the minimal memtuples array */
796 [ - + - - ]: 139399 : if (LACKMEM(state))
2081 tomas.vondra@postgre 797 [ # # ]:UBC 0 : elog(ERROR, "insufficient memory allowed for sort");
798 : :
2081 tomas.vondra@postgre 799 :CBC 139399 : state->currentRun = 0;
800 : :
801 : : /*
802 : : * Tape variables (inputTapes, outputTapes, etc.) will be initialized by
803 : : * inittapes(), if needed.
804 : : */
805 : :
1521 heikki.linnakangas@i 806 : 139399 : state->result_tape = NULL; /* flag that result tape has not been formed */
807 : :
2081 tomas.vondra@postgre 808 : 139399 : MemoryContextSwitchTo(oldcontext);
809 : 139399 : }
810 : :
811 : : /*
812 : : * tuplesort_set_bound
813 : : *
814 : : * Advise tuplesort that at most the first N result tuples are required.
815 : : *
816 : : * Must be called before inserting any tuples. (Actually, we could allow it
817 : : * as long as the sort hasn't spilled to disk, but there seems no need for
818 : : * delayed calls at the moment.)
819 : : *
820 : : * This is a hint only. The tuplesort may still return more tuples than
821 : : * requested. Parallel leader tuplesorts will always ignore the hint.
822 : : */
823 : : void
6802 tgl@sss.pgh.pa.us 824 : 617 : tuplesort_set_bound(Tuplesortstate *state, int64 bound)
825 : : {
826 : : /* Assert we're called before loading any tuples */
2288 alvherre@alvh.no-ip. 827 [ + - - + ]: 617 : Assert(state->status == TSS_INITIAL && state->memtupcount == 0);
828 : : /* Assert we allow bounded sorts */
1239 akorotkov@postgresql 829 [ - + ]: 617 : Assert(state->base.sortopt & TUPLESORT_ALLOWBOUNDED);
830 : : /* Can't set the bound twice, either */
6802 tgl@sss.pgh.pa.us 831 [ - + ]: 617 : Assert(!state->bounded);
832 : : /* Also, this shouldn't be called in a parallel worker */
2875 rhaas@postgresql.org 833 [ - + - - ]: 617 : Assert(!WORKER(state));
834 : :
835 : : /* Parallel leader allows but ignores hint */
2287 tgl@sss.pgh.pa.us 836 [ - + - - ]: 617 : if (LEADER(state))
2287 tgl@sss.pgh.pa.us 837 :UBC 0 : return;
838 : :
839 : : #ifdef DEBUG_BOUNDED_SORT
840 : : /* Honor GUC setting that disables the feature (for easy testing) */
841 : : if (!optimize_bounded_sort)
842 : : return;
843 : : #endif
844 : :
845 : : /* We want to be able to compute bound * 2, so limit the setting */
6607 bruce@momjian.us 846 [ - + ]:CBC 617 : if (bound > (int64) (INT_MAX / 2))
6802 tgl@sss.pgh.pa.us 847 :UBC 0 : return;
848 : :
6802 tgl@sss.pgh.pa.us 849 :CBC 617 : state->bounded = true;
850 : 617 : state->bound = (int) bound;
851 : :
852 : : /*
853 : : * Bounded sorts are not an effective target for abbreviated key
854 : : * optimization. Disable by setting state to be consistent with no
855 : : * abbreviation support.
856 : : */
1239 akorotkov@postgresql 857 : 617 : state->base.sortKeys->abbrev_converter = NULL;
858 [ + + ]: 617 : if (state->base.sortKeys->abbrev_full_comparator)
859 : 8 : state->base.sortKeys->comparator = state->base.sortKeys->abbrev_full_comparator;
860 : :
861 : : /* Not strictly necessary, but be tidy */
862 : 617 : state->base.sortKeys->abbrev_abort = NULL;
863 : 617 : state->base.sortKeys->abbrev_full_comparator = NULL;
864 : : }
865 : :
866 : : /*
867 : : * tuplesort_used_bound
868 : : *
869 : : * Allow callers to find out if the sort state was able to use a bound.
870 : : */
871 : : bool
2081 tomas.vondra@postgre 872 : 190 : tuplesort_used_bound(Tuplesortstate *state)
873 : : {
874 : 190 : return state->boundUsed;
875 : : }
876 : :
877 : : /*
878 : : * tuplesort_free
879 : : *
880 : : * Internal routine for freeing resources of tuplesort.
881 : : */
882 : : static void
883 : 139268 : tuplesort_free(Tuplesortstate *state)
884 : : {
885 : : /* context swap probably not needed, but let's be safe */
1239 akorotkov@postgresql 886 : 139268 : MemoryContext oldcontext = MemoryContextSwitchTo(state->base.sortcontext);
887 : : int64 spaceUsed;
888 : :
9558 tgl@sss.pgh.pa.us 889 [ + + ]: 139268 : if (state->tapeset)
7365 890 : 385 : spaceUsed = LogicalTapeSetBlocks(state->tapeset);
891 : : else
892 : 138883 : spaceUsed = (state->allowedMem - state->availMem + 1023) / 1024;
893 : :
894 : : /*
895 : : * Delete temporary "tape" files, if any.
896 : : *
897 : : * We don't bother to destroy the individual tapes here. They will go away
898 : : * with the sortcontext. (In TSS_FINALMERGE state, we have closed
899 : : * finished tapes already.)
900 : : */
7234 901 [ + + ]: 139268 : if (state->tapeset)
902 : 385 : LogicalTapeSetClose(state->tapeset);
903 : :
7380 904 [ - + ]: 139268 : if (trace_sort)
905 : : {
7365 tgl@sss.pgh.pa.us 906 [ # # ]:UBC 0 : if (state->tapeset)
263 peter@eisentraut.org 907 [ # # # # ]: 0 : elog(LOG, "%s of worker %d ended, %" PRId64 " disk blocks used: %s",
908 : : SERIAL(state) ? "external sort" : "parallel external sort",
909 : : state->worker, spaceUsed, pg_rusage_show(&state->ru_start));
910 : : else
911 [ # # # # ]: 0 : elog(LOG, "%s of worker %d ended, %" PRId64 " KB used: %s",
912 : : SERIAL(state) ? "internal sort" : "unperformed parallel sort",
913 : : state->worker, spaceUsed, pg_rusage_show(&state->ru_start));
914 : : }
915 : :
916 : : TRACE_POSTGRESQL_SORT_DONE(state->tapeset != NULL, spaceUsed);
917 : :
1239 akorotkov@postgresql 918 [ + + ]:CBC 139268 : FREESTATE(state);
7234 tgl@sss.pgh.pa.us 919 : 139268 : MemoryContextSwitchTo(oldcontext);
920 : :
921 : : /*
922 : : * Free the per-sort memory context, thereby releasing all working memory.
923 : : */
1239 akorotkov@postgresql 924 : 139268 : MemoryContextReset(state->base.sortcontext);
2081 tomas.vondra@postgre 925 : 139268 : }
926 : :
927 : : /*
928 : : * tuplesort_end
929 : : *
930 : : * Release resources and clean up.
931 : : *
932 : : * NOTE: after calling this, any pointers returned by tuplesort_getXXX are
933 : : * pointing to garbage. Be careful not to attempt to use or free such
934 : : * pointers afterwards!
935 : : */
936 : : void
937 : 137599 : tuplesort_end(Tuplesortstate *state)
938 : : {
939 : 137599 : tuplesort_free(state);
940 : :
941 : : /*
942 : : * Free the main memory context, including the Tuplesortstate struct
943 : : * itself.
944 : : */
1239 akorotkov@postgresql 945 : 137599 : MemoryContextDelete(state->base.maincontext);
2081 tomas.vondra@postgre 946 : 137599 : }
947 : :
948 : : /*
949 : : * tuplesort_updatemax
950 : : *
951 : : * Update maximum resource usage statistics.
952 : : */
953 : : static void
954 : 1867 : tuplesort_updatemax(Tuplesortstate *state)
955 : : {
956 : : int64 spaceUsed;
957 : : bool isSpaceDisk;
958 : :
959 : : /*
960 : : * Note: it might seem we should provide both memory and disk usage for a
961 : : * disk-based sort. However, the current code doesn't track memory space
962 : : * accurately once we have begun to return tuples to the caller (since we
963 : : * don't account for pfree's the caller is expected to do), so we cannot
964 : : * rely on availMem in a disk sort. This does not seem worth the overhead
965 : : * to fix. Is it worth creating an API for the memory context code to
966 : : * tell us how much is actually used in sortcontext?
967 : : */
968 [ + + ]: 1867 : if (state->tapeset)
969 : : {
970 : 3 : isSpaceDisk = true;
971 : 3 : spaceUsed = LogicalTapeSetBlocks(state->tapeset) * BLCKSZ;
972 : : }
973 : : else
974 : : {
975 : 1864 : isSpaceDisk = false;
976 : 1864 : spaceUsed = state->allowedMem - state->availMem;
977 : : }
978 : :
979 : : /*
980 : : * Sort evicts data to the disk when it wasn't able to fit that data into
981 : : * main memory. This is why we assume space used on the disk to be more
982 : : * important for tracking resource usage than space used in memory. Note
983 : : * that the amount of space occupied by some tupleset on the disk might be
984 : : * less than amount of space occupied by the same tupleset in memory due
985 : : * to more compact representation.
986 : : */
987 [ + + - + ]: 1867 : if ((isSpaceDisk && !state->isMaxSpaceDisk) ||
988 [ + - + + ]: 1864 : (isSpaceDisk == state->isMaxSpaceDisk && spaceUsed > state->maxSpace))
989 : : {
990 : 253 : state->maxSpace = spaceUsed;
991 : 253 : state->isMaxSpaceDisk = isSpaceDisk;
992 : 253 : state->maxSpaceStatus = state->status;
993 : : }
994 : 1867 : }
995 : :
996 : : /*
997 : : * tuplesort_reset
998 : : *
999 : : * Reset the tuplesort. Reset all the data in the tuplesort, but leave the
1000 : : * meta-information in. After tuplesort_reset, tuplesort is ready to start
1001 : : * a new sort. This allows avoiding recreation of tuple sort states (and
1002 : : * save resources) when sorting multiple small batches.
1003 : : */
1004 : : void
1005 : 1669 : tuplesort_reset(Tuplesortstate *state)
1006 : : {
1007 : 1669 : tuplesort_updatemax(state);
1008 : 1669 : tuplesort_free(state);
1009 : :
1010 : : /*
1011 : : * After we've freed up per-batch memory, re-setup all of the state common
1012 : : * to both the first batch and any subsequent batch.
1013 : : */
1014 : 1669 : tuplesort_begin_batch(state);
1015 : :
1016 : 1669 : state->lastReturnedTuple = NULL;
1017 : 1669 : state->slabMemoryBegin = NULL;
1018 : 1669 : state->slabMemoryEnd = NULL;
1019 : 1669 : state->slabFreeHead = NULL;
7234 tgl@sss.pgh.pa.us 1020 : 1669 : }
1021 : :
1022 : : /*
1023 : : * Grow the memtuples[] array, if possible within our memory constraint. We
1024 : : * must not exceed INT_MAX tuples in memory or the caller-provided memory
1025 : : * limit. Return true if we were able to enlarge the array, false if not.
1026 : : *
1027 : : * Normally, at each increment we double the size of the array. When doing
1028 : : * that would exceed a limit, we attempt one last, smaller increase (and then
1029 : : * clear the growmemtuples flag so we don't try any more). That allows us to
1030 : : * use memory as fully as permitted; sticking to the pure doubling rule could
1031 : : * result in almost half going unused. Because availMem moves around with
1032 : : * tuple addition/removal, we need some rule to prevent making repeated small
1033 : : * increases in memtupsize, which would just be useless thrashing. The
1034 : : * growmemtuples flag accomplishes that and also prevents useless
1035 : : * recalculations in this function.
1036 : : */
1037 : : static bool
1038 : 4265 : grow_memtuples(Tuplesortstate *state)
1039 : : {
1040 : : int newmemtupsize;
4717 1041 : 4265 : int memtupsize = state->memtupsize;
4549 noah@leadboat.com 1042 : 4265 : int64 memNowUsed = state->allowedMem - state->availMem;
1043 : :
1044 : : /* Forget it if we've already maxed out memtuples, per comment above */
4717 tgl@sss.pgh.pa.us 1045 [ + + ]: 4265 : if (!state->growmemtuples)
1046 : 70 : return false;
1047 : :
1048 : : /* Select new value of memtupsize */
1049 [ + + ]: 4195 : if (memNowUsed <= state->availMem)
1050 : : {
1051 : : /*
1052 : : * We've used no more than half of allowedMem; double our usage,
1053 : : * clamping at INT_MAX tuples.
1054 : : */
4556 noah@leadboat.com 1055 [ + - ]: 4121 : if (memtupsize < INT_MAX / 2)
1056 : 4121 : newmemtupsize = memtupsize * 2;
1057 : : else
1058 : : {
4556 noah@leadboat.com 1059 :UBC 0 : newmemtupsize = INT_MAX;
1060 : 0 : state->growmemtuples = false;
1061 : : }
1062 : : }
1063 : : else
1064 : : {
1065 : : /*
1066 : : * This will be the last increment of memtupsize. Abandon doubling
1067 : : * strategy and instead increase as much as we safely can.
1068 : : *
1069 : : * To stay within allowedMem, we can't increase memtupsize by more
1070 : : * than availMem / sizeof(SortTuple) elements. In practice, we want
1071 : : * to increase it by considerably less, because we need to leave some
1072 : : * space for the tuples to which the new array slots will refer. We
1073 : : * assume the new tuples will be about the same size as the tuples
1074 : : * we've already seen, and thus we can extrapolate from the space
1075 : : * consumption so far to estimate an appropriate new size for the
1076 : : * memtuples array. The optimal value might be higher or lower than
1077 : : * this estimate, but it's hard to know that in advance. We again
1078 : : * clamp at INT_MAX tuples.
1079 : : *
1080 : : * This calculation is safe against enlarging the array so much that
1081 : : * LACKMEM becomes true, because the memory currently used includes
1082 : : * the present array; thus, there would be enough allowedMem for the
1083 : : * new array elements even if no other memory were currently used.
1084 : : *
1085 : : * We do the arithmetic in float8, because otherwise the product of
1086 : : * memtupsize and allowedMem could overflow. Any inaccuracy in the
1087 : : * result should be insignificant; but even if we computed a
1088 : : * completely insane result, the checks below will prevent anything
1089 : : * really bad from happening.
1090 : : */
1091 : : double grow_ratio;
1092 : :
4717 tgl@sss.pgh.pa.us 1093 :CBC 74 : grow_ratio = (double) state->allowedMem / (double) memNowUsed;
4556 noah@leadboat.com 1094 [ + - ]: 74 : if (memtupsize * grow_ratio < INT_MAX)
1095 : 74 : newmemtupsize = (int) (memtupsize * grow_ratio);
1096 : : else
4556 noah@leadboat.com 1097 :UBC 0 : newmemtupsize = INT_MAX;
1098 : :
1099 : : /* We won't make any further enlargement attempts */
4717 tgl@sss.pgh.pa.us 1100 :CBC 74 : state->growmemtuples = false;
1101 : : }
1102 : :
1103 : : /* Must enlarge array by at least one element, else report failure */
1104 [ - + ]: 4195 : if (newmemtupsize <= memtupsize)
4717 tgl@sss.pgh.pa.us 1105 :UBC 0 : goto noalloc;
1106 : :
1107 : : /*
1108 : : * On a 32-bit machine, allowedMem could exceed MaxAllocHugeSize. Clamp
1109 : : * to ensure our request won't be rejected. Note that we can easily
1110 : : * exhaust address space before facing this outcome. (This is presently
1111 : : * impossible due to guc.c's MAX_KILOBYTES limitation on work_mem, but
1112 : : * don't rely on that at this distance.)
1113 : : */
4556 noah@leadboat.com 1114 [ - + ]:CBC 4195 : if ((Size) newmemtupsize >= MaxAllocHugeSize / sizeof(SortTuple))
1115 : : {
4556 noah@leadboat.com 1116 :UBC 0 : newmemtupsize = (int) (MaxAllocHugeSize / sizeof(SortTuple));
4717 tgl@sss.pgh.pa.us 1117 : 0 : state->growmemtuples = false; /* can't grow any more */
1118 : : }
1119 : :
1120 : : /*
1121 : : * We need to be sure that we do not cause LACKMEM to become true, else
1122 : : * the space management algorithm will go nuts. The code above should
1123 : : * never generate a dangerous request, but to be safe, check explicitly
1124 : : * that the array growth fits within availMem. (We could still cause
1125 : : * LACKMEM if the memory chunk overhead associated with the memtuples
1126 : : * array were to increase. That shouldn't happen because we chose the
1127 : : * initial array size large enough to ensure that palloc will be treating
1128 : : * both old and new arrays as separate chunks. But we'll check LACKMEM
1129 : : * explicitly below just in case.)
1130 : : */
4549 noah@leadboat.com 1131 [ - + ]:CBC 4195 : if (state->availMem < (int64) ((newmemtupsize - memtupsize) * sizeof(SortTuple)))
4717 tgl@sss.pgh.pa.us 1132 :UBC 0 : goto noalloc;
1133 : :
1134 : : /* OK, do it */
7234 tgl@sss.pgh.pa.us 1135 :CBC 4195 : FREEMEM(state, GetMemoryChunkSpace(state->memtuples));
4717 1136 : 4195 : state->memtupsize = newmemtupsize;
7234 1137 : 4195 : state->memtuples = (SortTuple *)
4556 noah@leadboat.com 1138 : 4195 : repalloc_huge(state->memtuples,
1139 : 4195 : state->memtupsize * sizeof(SortTuple));
7234 tgl@sss.pgh.pa.us 1140 : 4195 : USEMEM(state, GetMemoryChunkSpace(state->memtuples));
1141 [ - + - - ]: 4195 : if (LACKMEM(state))
3788 tgl@sss.pgh.pa.us 1142 [ # # ]:UBC 0 : elog(ERROR, "unexpected out-of-memory situation in tuplesort");
7234 tgl@sss.pgh.pa.us 1143 :CBC 4195 : return true;
1144 : :
4717 tgl@sss.pgh.pa.us 1145 :UBC 0 : noalloc:
1146 : : /* If for any reason we didn't realloc, shut off future attempts */
1147 : 0 : state->growmemtuples = false;
1148 : 0 : return false;
1149 : : }
1150 : :
1151 : : /*
1152 : : * Shared code for tuple and datum cases.
1153 : : */
1154 : : void
618 drowley@postgresql.o 1155 :CBC 15507214 : tuplesort_puttuple_common(Tuplesortstate *state, SortTuple *tuple,
1156 : : bool useAbbrev, Size tuplen)
1157 : : {
1239 akorotkov@postgresql 1158 : 15507214 : MemoryContext oldcontext = MemoryContextSwitchTo(state->base.sortcontext);
1159 : :
2875 rhaas@postgresql.org 1160 [ + + - + ]: 15507214 : Assert(!LEADER(state));
1161 : :
1162 : : /* account for the memory used for this tuple */
618 drowley@postgresql.o 1163 : 15507214 : USEMEM(state, tuplen);
1164 : 15507214 : state->tupleMem += tuplen;
1165 : :
1239 akorotkov@postgresql 1166 [ + + ]: 15507214 : if (!useAbbrev)
1167 : : {
1168 : : /*
1169 : : * Leave ordinary Datum representation, or NULL value. If there is a
1170 : : * converter it won't expect NULL values, and cost model is not
1171 : : * required to account for NULL, so in that case we avoid calling
1172 : : * converter and just set datum1 to zeroed representation (to be
1173 : : * consistent, and to support cheap inequality tests for NULL
1174 : : * abbreviated keys).
1175 : : */
1176 : : }
1177 [ + + ]: 2221541 : else if (!consider_abort_common(state))
1178 : : {
1179 : : /* Store abbreviated key representation */
1180 : 2221493 : tuple->datum1 = state->base.sortKeys->abbrev_converter(tuple->datum1,
1181 : : state->base.sortKeys);
1182 : : }
1183 : : else
1184 : : {
1185 : : /*
1186 : : * Set state to be consistent with never trying abbreviation.
1187 : : *
1188 : : * Alter datum1 representation in already-copied tuples, so as to
1189 : : * ensure a consistent representation (current tuple was just
1190 : : * handled). It does not matter if some dumped tuples are already
1191 : : * sorted on tape, since serialized tuples lack abbreviated keys
1192 : : * (TSS_BUILDRUNS state prevents control reaching here in any case).
1193 : : */
1194 : 48 : REMOVEABBREV(state, state->memtuples, state->memtupcount);
1195 : : }
1196 : :
9558 tgl@sss.pgh.pa.us 1197 [ + + + - ]: 15507214 : switch (state->status)
1198 : : {
8819 bruce@momjian.us 1199 : 13079419 : case TSS_INITIAL:
1200 : :
1201 : : /*
1202 : : * Save the tuple into the unsorted array. First, grow the array
1203 : : * as needed. Note that we try to grow the array when there is
1204 : : * still one free slot remaining --- if we fail, there'll still be
1205 : : * room to store the incoming tuple, and then we'll switch to
1206 : : * tape-based operation.
1207 : : */
7234 tgl@sss.pgh.pa.us 1208 [ + + ]: 13079419 : if (state->memtupcount >= state->memtupsize - 1)
1209 : : {
1210 : 4265 : (void) grow_memtuples(state);
1211 [ - + ]: 4265 : Assert(state->memtupcount < state->memtupsize);
1212 : : }
1213 : 13079419 : state->memtuples[state->memtupcount++] = *tuple;
1214 : :
1215 : : /*
1216 : : * Check if it's time to switch over to a bounded heapsort. We do
1217 : : * so if the input tuple count exceeds twice the desired tuple
1218 : : * count (this is a heuristic for where heapsort becomes cheaper
1219 : : * than a quicksort), or if we've just filled workMem and have
1220 : : * enough tuples to meet the bound.
1221 : : *
1222 : : * Note that once we enter TSS_BOUNDED state we will always try to
1223 : : * complete the sort that way. In the worst case, if later input
1224 : : * tuples are larger than earlier ones, this might cause us to
1225 : : * exceed workMem significantly.
1226 : : */
6802 1227 [ + + ]: 13079419 : if (state->bounded &&
1228 [ + + ]: 29155 : (state->memtupcount > state->bound * 2 ||
1229 [ + + - + : 28942 : (state->memtupcount > state->bound && LACKMEM(state))))
- - ]
1230 : : {
1231 [ - + ]: 213 : if (trace_sort)
6802 tgl@sss.pgh.pa.us 1232 [ # # ]:UBC 0 : elog(LOG, "switching to bounded heapsort at %d tuples: %s",
1233 : : state->memtupcount,
1234 : : pg_rusage_show(&state->ru_start));
6802 tgl@sss.pgh.pa.us 1235 :CBC 213 : make_bounded_heap(state);
1239 akorotkov@postgresql 1236 : 213 : MemoryContextSwitchTo(oldcontext);
6802 tgl@sss.pgh.pa.us 1237 : 213 : return;
1238 : : }
1239 : :
1240 : : /*
1241 : : * Done if we still fit in available memory and have array slots.
1242 : : */
7234 1243 [ + + - + : 13079206 : if (state->memtupcount < state->memtupsize && !LACKMEM(state))
- - ]
1244 : : {
1239 akorotkov@postgresql 1245 : 13079136 : MemoryContextSwitchTo(oldcontext);
9558 tgl@sss.pgh.pa.us 1246 : 13079136 : return;
1247 : : }
1248 : :
1249 : : /*
1250 : : * Nope; time to switch to tape-based operation.
1251 : : */
2875 rhaas@postgresql.org 1252 : 70 : inittapes(state, true);
1253 : :
1254 : : /*
1255 : : * Dump all tuples.
1256 : : */
9558 tgl@sss.pgh.pa.us 1257 : 70 : dumptuples(state, false);
1258 : 70 : break;
1259 : :
6802 1260 : 1871588 : case TSS_BOUNDED:
1261 : :
1262 : : /*
1263 : : * We don't want to grow the array here, so check whether the new
1264 : : * tuple can be discarded before putting it in. This should be a
1265 : : * good speed optimization, too, since when there are many more
1266 : : * input tuples than the bound, most input tuples can be discarded
1267 : : * with just this one comparison. Note that because we currently
1268 : : * have the sort direction reversed, we must check for <= not >=.
1269 : : */
1270 [ + + ]: 1871588 : if (COMPARETUP(state, tuple, &state->memtuples[0]) <= 0)
1271 : : {
1272 : : /* new tuple <= top of the heap, so we can discard it */
1273 : 1620186 : free_sort_tuple(state, tuple);
5020 rhaas@postgresql.org 1274 [ + + ]: 1620186 : CHECK_FOR_INTERRUPTS();
1275 : : }
1276 : : else
1277 : : {
1278 : : /* discard top of heap, replacing it with the new tuple */
6802 tgl@sss.pgh.pa.us 1279 : 251402 : free_sort_tuple(state, &state->memtuples[0]);
3001 rhaas@postgresql.org 1280 : 251402 : tuplesort_heap_replace_top(state, tuple);
1281 : : }
6802 tgl@sss.pgh.pa.us 1282 : 1871588 : break;
1283 : :
9558 1284 : 556207 : case TSS_BUILDRUNS:
1285 : :
1286 : : /*
1287 : : * Save the tuple into the unsorted array (there must be space)
1288 : : */
3001 rhaas@postgresql.org 1289 : 556207 : state->memtuples[state->memtupcount++] = *tuple;
1290 : :
1291 : : /*
1292 : : * If we are over the memory limit, dump all tuples.
1293 : : */
9558 tgl@sss.pgh.pa.us 1294 : 556207 : dumptuples(state, false);
1295 : 556207 : break;
1296 : :
9558 tgl@sss.pgh.pa.us 1297 :UBC 0 : default:
8181 1298 [ # # ]: 0 : elog(ERROR, "invalid tuplesort state");
1299 : : break;
1300 : : }
1239 akorotkov@postgresql 1301 :CBC 2427865 : MemoryContextSwitchTo(oldcontext);
1302 : : }
1303 : :
1304 : : static bool
3985 rhaas@postgresql.org 1305 : 2221541 : consider_abort_common(Tuplesortstate *state)
1306 : : {
1239 akorotkov@postgresql 1307 [ - + ]: 2221541 : Assert(state->base.sortKeys[0].abbrev_converter != NULL);
1308 [ - + ]: 2221541 : Assert(state->base.sortKeys[0].abbrev_abort != NULL);
1309 [ - + ]: 2221541 : Assert(state->base.sortKeys[0].abbrev_full_comparator != NULL);
1310 : :
1311 : : /*
1312 : : * Check effectiveness of abbreviation optimization. Consider aborting
1313 : : * when still within memory limit.
1314 : : */
3985 rhaas@postgresql.org 1315 [ + + ]: 2221541 : if (state->status == TSS_INITIAL &&
1316 [ + + ]: 1985311 : state->memtupcount >= state->abbrevNext)
1317 : : {
1318 : 2564 : state->abbrevNext *= 2;
1319 : :
1320 : : /*
1321 : : * Check opclass-supplied abbreviation abort routine. It may indicate
1322 : : * that abbreviation should not proceed.
1323 : : */
1239 akorotkov@postgresql 1324 [ + + ]: 2564 : if (!state->base.sortKeys->abbrev_abort(state->memtupcount,
1325 : : state->base.sortKeys))
3985 rhaas@postgresql.org 1326 : 2516 : return false;
1327 : :
1328 : : /*
1329 : : * Finally, restore authoritative comparator, and indicate that
1330 : : * abbreviation is not in play by setting abbrev_converter to NULL
1331 : : */
1239 akorotkov@postgresql 1332 : 48 : state->base.sortKeys[0].comparator = state->base.sortKeys[0].abbrev_full_comparator;
1333 : 48 : state->base.sortKeys[0].abbrev_converter = NULL;
1334 : : /* Not strictly necessary, but be tidy */
1335 : 48 : state->base.sortKeys[0].abbrev_abort = NULL;
1336 : 48 : state->base.sortKeys[0].abbrev_full_comparator = NULL;
1337 : :
1338 : : /* Give up - expect original pass-by-value representation */
3985 rhaas@postgresql.org 1339 : 48 : return true;
1340 : : }
1341 : :
1342 : 2218977 : return false;
1343 : : }
1344 : :
1345 : : /*
1346 : : * All tuples have been provided; finish the sort.
1347 : : */
1348 : : void
9558 tgl@sss.pgh.pa.us 1349 : 118235 : tuplesort_performsort(Tuplesortstate *state)
1350 : : {
1239 akorotkov@postgresql 1351 : 118235 : MemoryContext oldcontext = MemoryContextSwitchTo(state->base.sortcontext);
1352 : :
7380 tgl@sss.pgh.pa.us 1353 [ - + ]: 118235 : if (trace_sort)
2603 pg@bowt.ie 1354 [ # # ]:UBC 0 : elog(LOG, "performsort of worker %d starting: %s",
1355 : : state->worker, pg_rusage_show(&state->ru_start));
1356 : :
9558 tgl@sss.pgh.pa.us 1357 [ + + + - ]:CBC 118235 : switch (state->status)
1358 : : {
8819 bruce@momjian.us 1359 : 117952 : case TSS_INITIAL:
1360 : :
1361 : : /*
1362 : : * We were able to accumulate all the tuples within the allowed
1363 : : * amount of memory, or leader to take over worker tapes
1364 : : */
2875 rhaas@postgresql.org 1365 [ + + ]: 117952 : if (SERIAL(state))
1366 : : {
1367 : : /* Just qsort 'em and we're done */
1368 : 117637 : tuplesort_sort_memtuples(state);
1369 : 117592 : state->status = TSS_SORTEDINMEM;
1370 : : }
1371 [ + - + + ]: 315 : else if (WORKER(state))
1372 : : {
1373 : : /*
1374 : : * Parallel workers must still dump out tuples to tape. No
1375 : : * merge is required to produce single output run, though.
1376 : : */
1377 : 234 : inittapes(state, false);
1378 : 234 : dumptuples(state, true);
1379 : 234 : worker_nomergeruns(state);
1380 : 234 : state->status = TSS_SORTEDONTAPE;
1381 : : }
1382 : : else
1383 : : {
1384 : : /*
1385 : : * Leader will take over worker tapes and merge worker runs.
1386 : : * Note that mergeruns sets the correct state->status.
1387 : : */
1388 : 81 : leader_takeover_tapes(state);
1389 : 81 : mergeruns(state);
1390 : : }
9558 tgl@sss.pgh.pa.us 1391 : 117907 : state->current = 0;
1392 : 117907 : state->eof_reached = false;
2875 rhaas@postgresql.org 1393 : 117907 : state->markpos_block = 0L;
9558 tgl@sss.pgh.pa.us 1394 : 117907 : state->markpos_offset = 0;
1395 : 117907 : state->markpos_eof = false;
1396 : 117907 : break;
1397 : :
6802 1398 : 213 : case TSS_BOUNDED:
1399 : :
1400 : : /*
1401 : : * We were able to accumulate all the tuples required for output
1402 : : * in memory, using a heap to eliminate excess tuples. Now we
1403 : : * have to transform the heap to a properly-sorted array. Note
1404 : : * that sort_bounded_heap sets the correct state->status.
1405 : : */
6682 1406 : 213 : sort_bounded_heap(state);
6802 1407 : 213 : state->current = 0;
1408 : 213 : state->eof_reached = false;
1409 : 213 : state->markpos_offset = 0;
1410 : 213 : state->markpos_eof = false;
1411 : 213 : break;
1412 : :
9558 1413 : 70 : case TSS_BUILDRUNS:
1414 : :
1415 : : /*
1416 : : * Finish tape-based sort. First, flush all tuples remaining in
1417 : : * memory out to tape; then merge until we have a single remaining
1418 : : * run (or, if !randomAccess and !WORKER(), one run per tape).
1419 : : * Note that mergeruns sets the correct state->status.
1420 : : */
1421 : 70 : dumptuples(state, true);
1422 : 70 : mergeruns(state);
1423 : 70 : state->eof_reached = false;
1424 : 70 : state->markpos_block = 0L;
1425 : 70 : state->markpos_offset = 0;
1426 : 70 : state->markpos_eof = false;
1427 : 70 : break;
1428 : :
9558 tgl@sss.pgh.pa.us 1429 :UBC 0 : default:
8181 1430 [ # # ]: 0 : elog(ERROR, "invalid tuplesort state");
1431 : : break;
1432 : : }
1433 : :
7380 tgl@sss.pgh.pa.us 1434 [ - + ]:CBC 118190 : if (trace_sort)
1435 : : {
7224 tgl@sss.pgh.pa.us 1436 [ # # ]:UBC 0 : if (state->status == TSS_FINALMERGE)
2603 pg@bowt.ie 1437 [ # # ]: 0 : elog(LOG, "performsort of worker %d done (except %d-way final merge): %s",
1438 : : state->worker, state->nInputTapes,
1439 : : pg_rusage_show(&state->ru_start));
1440 : : else
1441 [ # # ]: 0 : elog(LOG, "performsort of worker %d done: %s",
1442 : : state->worker, pg_rusage_show(&state->ru_start));
1443 : : }
1444 : :
7234 tgl@sss.pgh.pa.us 1445 :CBC 118190 : MemoryContextSwitchTo(oldcontext);
9558 1446 : 118190 : }
1447 : :
1448 : : /*
1449 : : * Internal routine to fetch the next tuple in either forward or back
1450 : : * direction into *stup. Returns false if no more tuples.
1451 : : * Returned tuple belongs to tuplesort memory context, and must not be freed
1452 : : * by caller. Note that fetched tuple is stored in memory that may be
1453 : : * recycled by any future fetch.
1454 : : */
1455 : : bool
7234 1456 : 14317533 : tuplesort_gettuple_common(Tuplesortstate *state, bool forward,
1457 : : SortTuple *stup)
1458 : : {
1459 : : unsigned int tuplen;
1460 : : size_t nmoved;
1461 : :
2875 rhaas@postgresql.org 1462 [ + + - + ]: 14317533 : Assert(!WORKER(state));
1463 : :
9558 tgl@sss.pgh.pa.us 1464 [ + + + - ]: 14317533 : switch (state->status)
1465 : : {
1466 : 11843705 : case TSS_SORTEDINMEM:
1239 akorotkov@postgresql 1467 [ + + - + ]: 11843705 : Assert(forward || state->base.sortopt & TUPLESORT_RANDOMACCESS);
3362 heikki.linnakangas@i 1468 [ - + ]: 11843705 : Assert(!state->slabAllocatorUsed);
9558 tgl@sss.pgh.pa.us 1469 [ + + ]: 11843705 : if (forward)
1470 : : {
1471 [ + + ]: 11843672 : if (state->current < state->memtupcount)
1472 : : {
7234 1473 : 11726500 : *stup = state->memtuples[state->current++];
1474 : 11726500 : return true;
1475 : : }
9558 1476 : 117172 : state->eof_reached = true;
1477 : :
1478 : : /*
1479 : : * Complain if caller tries to retrieve more tuples than
1480 : : * originally asked for in a bounded sort. This is because
1481 : : * returning EOF here might be the wrong thing.
1482 : : */
6802 1483 [ + + - + ]: 117172 : if (state->bounded && state->current >= state->bound)
6802 tgl@sss.pgh.pa.us 1484 [ # # ]:UBC 0 : elog(ERROR, "retrieved too many tuples in a bounded sort");
1485 : :
7234 tgl@sss.pgh.pa.us 1486 :CBC 117172 : return false;
1487 : : }
1488 : : else
1489 : : {
9558 1490 [ - + ]: 33 : if (state->current <= 0)
7234 tgl@sss.pgh.pa.us 1491 :UBC 0 : return false;
1492 : :
1493 : : /*
1494 : : * if all tuples are fetched already then we return last
1495 : : * tuple, else - tuple before last returned.
1496 : : */
9558 tgl@sss.pgh.pa.us 1497 [ + + ]:CBC 33 : if (state->eof_reached)
1498 : 6 : state->eof_reached = false;
1499 : : else
1500 : : {
9380 bruce@momjian.us 1501 : 27 : state->current--; /* last returned tuple */
9558 tgl@sss.pgh.pa.us 1502 [ + + ]: 27 : if (state->current <= 0)
7234 1503 : 3 : return false;
1504 : : }
1505 : 30 : *stup = state->memtuples[state->current - 1];
1506 : 30 : return true;
1507 : : }
1508 : : break;
1509 : :
9558 1510 : 151500 : case TSS_SORTEDONTAPE:
1239 akorotkov@postgresql 1511 [ + + - + ]: 151500 : Assert(forward || state->base.sortopt & TUPLESORT_RANDOMACCESS);
3362 heikki.linnakangas@i 1512 [ - + ]: 151500 : Assert(state->slabAllocatorUsed);
1513 : :
1514 : : /*
1515 : : * The slot that held the tuple that we returned in previous
1516 : : * gettuple call can now be reused.
1517 : : */
1518 [ + + ]: 151500 : if (state->lastReturnedTuple)
1519 : : {
1520 [ + - + - ]: 76425 : RELEASE_SLAB_SLOT(state, state->lastReturnedTuple);
1521 : 76425 : state->lastReturnedTuple = NULL;
1522 : : }
1523 : :
9558 tgl@sss.pgh.pa.us 1524 [ + + ]: 151500 : if (forward)
1525 : : {
1526 [ - + ]: 151485 : if (state->eof_reached)
7234 tgl@sss.pgh.pa.us 1527 :UBC 0 : return false;
1528 : :
1521 heikki.linnakangas@i 1529 [ + + ]:CBC 151485 : if ((tuplen = getlen(state->result_tape, true)) != 0)
1530 : : {
7234 tgl@sss.pgh.pa.us 1531 : 151470 : READTUP(state, stup, state->result_tape, tuplen);
1532 : :
1533 : : /*
1534 : : * Remember the tuple we return, so that we can recycle
1535 : : * its memory on next call. (This can be NULL, in the
1536 : : * !state->tuples case).
1537 : : */
3362 heikki.linnakangas@i 1538 : 151470 : state->lastReturnedTuple = stup->tuple;
1539 : :
7234 tgl@sss.pgh.pa.us 1540 : 151470 : return true;
1541 : : }
1542 : : else
1543 : : {
9558 1544 : 15 : state->eof_reached = true;
7234 1545 : 15 : return false;
1546 : : }
1547 : : }
1548 : :
1549 : : /*
1550 : : * Backward.
1551 : : *
1552 : : * if all tuples are fetched already then we return last tuple,
1553 : : * else - tuple before last returned.
1554 : : */
9558 1555 [ + + ]: 15 : if (state->eof_reached)
1556 : : {
1557 : : /*
1558 : : * Seek position is pointing just past the zero tuplen at the
1559 : : * end of file; back up to fetch last tuple's ending length
1560 : : * word. If seek fails we must have a completely empty file.
1561 : : */
1521 heikki.linnakangas@i 1562 : 6 : nmoved = LogicalTapeBackspace(state->result_tape,
1563 : : 2 * sizeof(unsigned int));
3282 1564 [ - + ]: 6 : if (nmoved == 0)
7234 tgl@sss.pgh.pa.us 1565 :UBC 0 : return false;
3282 heikki.linnakangas@i 1566 [ - + ]:CBC 6 : else if (nmoved != 2 * sizeof(unsigned int))
3282 heikki.linnakangas@i 1567 [ # # ]:UBC 0 : elog(ERROR, "unexpected tape position");
9558 tgl@sss.pgh.pa.us 1568 :CBC 6 : state->eof_reached = false;
1569 : : }
1570 : : else
1571 : : {
1572 : : /*
1573 : : * Back up and fetch previously-returned tuple's ending length
1574 : : * word. If seek fails, assume we are at start of file.
1575 : : */
1521 heikki.linnakangas@i 1576 : 9 : nmoved = LogicalTapeBackspace(state->result_tape,
1577 : : sizeof(unsigned int));
3282 1578 [ - + ]: 9 : if (nmoved == 0)
7234 tgl@sss.pgh.pa.us 1579 :UBC 0 : return false;
3282 heikki.linnakangas@i 1580 [ - + ]:CBC 9 : else if (nmoved != sizeof(unsigned int))
3282 heikki.linnakangas@i 1581 [ # # ]:UBC 0 : elog(ERROR, "unexpected tape position");
1521 heikki.linnakangas@i 1582 :CBC 9 : tuplen = getlen(state->result_tape, false);
1583 : :
1584 : : /*
1585 : : * Back up to get ending length word of tuple before it.
1586 : : */
1587 : 9 : nmoved = LogicalTapeBackspace(state->result_tape,
1588 : : tuplen + 2 * sizeof(unsigned int));
3282 1589 [ + + ]: 9 : if (nmoved == tuplen + sizeof(unsigned int))
1590 : : {
1591 : : /*
1592 : : * We backed up over the previous tuple, but there was no
1593 : : * ending length word before it. That means that the prev
1594 : : * tuple is the first tuple in the file. It is now the
1595 : : * next to read in forward direction (not obviously right,
1596 : : * but that is what in-memory case does).
1597 : : */
7234 tgl@sss.pgh.pa.us 1598 : 3 : return false;
1599 : : }
3282 heikki.linnakangas@i 1600 [ - + ]: 6 : else if (nmoved != tuplen + 2 * sizeof(unsigned int))
3282 heikki.linnakangas@i 1601 [ # # ]:UBC 0 : elog(ERROR, "bogus tuple length in backward scan");
1602 : : }
1603 : :
1521 heikki.linnakangas@i 1604 :CBC 12 : tuplen = getlen(state->result_tape, false);
1605 : :
1606 : : /*
1607 : : * Now we have the length of the prior tuple, back up and read it.
1608 : : * Note: READTUP expects we are positioned after the initial
1609 : : * length word of the tuple, so back up to that point.
1610 : : */
1611 : 12 : nmoved = LogicalTapeBackspace(state->result_tape,
1612 : : tuplen);
3282 1613 [ - + ]: 12 : if (nmoved != tuplen)
8181 tgl@sss.pgh.pa.us 1614 [ # # ]:UBC 0 : elog(ERROR, "bogus tuple length in backward scan");
7234 tgl@sss.pgh.pa.us 1615 :CBC 12 : READTUP(state, stup, state->result_tape, tuplen);
1616 : :
1617 : : /*
1618 : : * Remember the tuple we return, so that we can recycle its memory
1619 : : * on next call. (This can be NULL, in the Datum case).
1620 : : */
3362 heikki.linnakangas@i 1621 : 12 : state->lastReturnedTuple = stup->tuple;
1622 : :
7234 tgl@sss.pgh.pa.us 1623 : 12 : return true;
1624 : :
9558 1625 : 2322328 : case TSS_FINALMERGE:
1626 [ - + ]: 2322328 : Assert(forward);
1627 : : /* We are managing memory ourselves, with the slab allocator. */
3362 heikki.linnakangas@i 1628 [ - + ]: 2322328 : Assert(state->slabAllocatorUsed);
1629 : :
1630 : : /*
1631 : : * The slab slot holding the tuple that we returned in previous
1632 : : * gettuple call can now be reused.
1633 : : */
1634 [ + + ]: 2322328 : if (state->lastReturnedTuple)
1635 : : {
1636 [ + - + - ]: 2262173 : RELEASE_SLAB_SLOT(state, state->lastReturnedTuple);
1637 : 2262173 : state->lastReturnedTuple = NULL;
1638 : : }
1639 : :
1640 : : /*
1641 : : * This code should match the inner loop of mergeonerun().
1642 : : */
9545 tgl@sss.pgh.pa.us 1643 [ + + ]: 2322328 : if (state->memtupcount > 0)
1644 : : {
1521 heikki.linnakangas@i 1645 : 2322197 : int srcTapeIndex = state->memtuples[0].srctape;
1646 : 2322197 : LogicalTape *srcTape = state->inputTapes[srcTapeIndex];
1647 : : SortTuple newtup;
1648 : :
3362 1649 : 2322197 : *stup = state->memtuples[0];
1650 : :
1651 : : /*
1652 : : * Remember the tuple we return, so that we can recycle its
1653 : : * memory on next call. (This can be NULL, in the Datum case).
1654 : : */
1655 : 2322197 : state->lastReturnedTuple = stup->tuple;
1656 : :
1657 : : /*
1658 : : * Pull next tuple from tape, and replace the returned tuple
1659 : : * at top of the heap with it.
1660 : : */
1661 [ + + ]: 2322197 : if (!mergereadnext(state, srcTape, &newtup))
1662 : : {
1663 : : /*
1664 : : * If no more data, we've reached end of run on this tape.
1665 : : * Remove the top node from the heap.
1666 : : */
3001 rhaas@postgresql.org 1667 : 197 : tuplesort_heap_delete_top(state);
1521 heikki.linnakangas@i 1668 : 197 : state->nInputRuns--;
1669 : :
1670 : : /*
1671 : : * Close the tape. It'd go away at the end of the sort
1672 : : * anyway, but better to release the memory early.
1673 : : */
1239 akorotkov@postgresql 1674 : 197 : LogicalTapeClose(srcTape);
1675 : 197 : return true;
1676 : : }
1677 : 2322000 : newtup.srctape = srcTapeIndex;
1678 : 2322000 : tuplesort_heap_replace_top(state, &newtup);
1679 : 2322000 : return true;
1680 : : }
1681 : 131 : return false;
1682 : :
1239 akorotkov@postgresql 1683 :UBC 0 : default:
1684 [ # # ]: 0 : elog(ERROR, "invalid tuplesort state");
1685 : : return false; /* keep compiler quiet */
1686 : : }
1687 : : }
1688 : :
1689 : :
1690 : : /*
1691 : : * Advance over N tuples in either forward or back direction,
1692 : : * without returning any data. N==0 is a no-op.
1693 : : * Returns true if successful, false if ran out of tuples.
1694 : : */
1695 : : bool
4377 tgl@sss.pgh.pa.us 1696 :CBC 196 : tuplesort_skiptuples(Tuplesortstate *state, int64 ntuples, bool forward)
1697 : : {
1698 : : MemoryContext oldcontext;
1699 : :
1700 : : /*
1701 : : * We don't actually support backwards skip yet, because no callers need
1702 : : * it. The API is designed to allow for that later, though.
1703 : : */
1704 [ - + ]: 196 : Assert(forward);
1705 [ - + ]: 196 : Assert(ntuples >= 0);
2875 rhaas@postgresql.org 1706 [ - + - - ]: 196 : Assert(!WORKER(state));
1707 : :
4377 tgl@sss.pgh.pa.us 1708 [ + + - ]: 196 : switch (state->status)
1709 : : {
1710 : 184 : case TSS_SORTEDINMEM:
1711 [ + - ]: 184 : if (state->memtupcount - state->current >= ntuples)
1712 : : {
1713 : 184 : state->current += ntuples;
1714 : 184 : return true;
1715 : : }
4377 tgl@sss.pgh.pa.us 1716 :UBC 0 : state->current = state->memtupcount;
1717 : 0 : state->eof_reached = true;
1718 : :
1719 : : /*
1720 : : * Complain if caller tries to retrieve more tuples than
1721 : : * originally asked for in a bounded sort. This is because
1722 : : * returning EOF here might be the wrong thing.
1723 : : */
1724 [ # # # # ]: 0 : if (state->bounded && state->current >= state->bound)
1725 [ # # ]: 0 : elog(ERROR, "retrieved too many tuples in a bounded sort");
1726 : :
1727 : 0 : return false;
1728 : :
4377 tgl@sss.pgh.pa.us 1729 :CBC 12 : case TSS_SORTEDONTAPE:
1730 : : case TSS_FINALMERGE:
1731 : :
1732 : : /*
1733 : : * We could probably optimize these cases better, but for now it's
1734 : : * not worth the trouble.
1735 : : */
1239 akorotkov@postgresql 1736 : 12 : oldcontext = MemoryContextSwitchTo(state->base.sortcontext);
4377 tgl@sss.pgh.pa.us 1737 [ + + ]: 120066 : while (ntuples-- > 0)
1738 : : {
1739 : : SortTuple stup;
1740 : :
3292 rhaas@postgresql.org 1741 [ - + ]: 120054 : if (!tuplesort_gettuple_common(state, forward, &stup))
1742 : : {
4376 tgl@sss.pgh.pa.us 1743 :UBC 0 : MemoryContextSwitchTo(oldcontext);
4377 1744 : 0 : return false;
1745 : : }
4377 tgl@sss.pgh.pa.us 1746 [ - + ]:CBC 120054 : CHECK_FOR_INTERRUPTS();
1747 : : }
4376 1748 : 12 : MemoryContextSwitchTo(oldcontext);
4377 1749 : 12 : return true;
1750 : :
4377 tgl@sss.pgh.pa.us 1751 :UBC 0 : default:
1752 [ # # ]: 0 : elog(ERROR, "invalid tuplesort state");
1753 : : return false; /* keep compiler quiet */
1754 : : }
1755 : : }
1756 : :
1757 : : /*
1758 : : * tuplesort_merge_order - report merge order we'll use for given memory
1759 : : * (note: "merge order" just means the number of input tapes in the merge).
1760 : : *
1761 : : * This is exported for use by the planner. allowedMem is in bytes.
1762 : : */
1763 : : int
4549 noah@leadboat.com 1764 :CBC 9388 : tuplesort_merge_order(int64 allowedMem)
1765 : : {
1766 : : int mOrder;
1767 : :
1768 : : /*----------
1769 : : * In the merge phase, we need buffer space for each input and output tape.
1770 : : * Each pass in the balanced merge algorithm reads from M input tapes, and
1771 : : * writes to N output tapes. Each tape consumes TAPE_BUFFER_OVERHEAD bytes
1772 : : * of memory. In addition to that, we want MERGE_BUFFER_SIZE workspace per
1773 : : * input tape.
1774 : : *
1775 : : * totalMem = M * (TAPE_BUFFER_OVERHEAD + MERGE_BUFFER_SIZE) +
1776 : : * N * TAPE_BUFFER_OVERHEAD
1777 : : *
1778 : : * Except for the last and next-to-last merge passes, where there can be
1779 : : * fewer tapes left to process, M = N. We choose M so that we have the
1780 : : * desired amount of memory available for the input buffers
1781 : : * (TAPE_BUFFER_OVERHEAD + MERGE_BUFFER_SIZE), given the total memory
1782 : : * available for the tape buffers (allowedMem).
1783 : : *
1784 : : * Note: you might be thinking we need to account for the memtuples[]
1785 : : * array in this calculation, but we effectively treat that as part of the
1786 : : * MERGE_BUFFER_SIZE workspace.
1787 : : *----------
1788 : : */
1521 heikki.linnakangas@i 1789 : 9388 : mOrder = allowedMem /
1790 : : (2 * TAPE_BUFFER_OVERHEAD + MERGE_BUFFER_SIZE);
1791 : :
1792 : : /*
1793 : : * Even in minimum memory, use at least a MINORDER merge. On the other
1794 : : * hand, even when we have lots of memory, do not use more than a MAXORDER
1795 : : * merge. Tapes are pretty cheap, but they're not entirely free. Each
1796 : : * additional tape reduces the amount of memory available to build runs,
1797 : : * which in turn can cause the same sort to need more runs, which makes
1798 : : * merging slower even if it can still be done in a single pass. Also,
1799 : : * high order merges are quite slow due to CPU cache effects; it can be
1800 : : * faster to pay the I/O cost of a multi-pass merge than to perform a
1801 : : * single merge pass across many hundreds of tapes.
1802 : : */
7234 tgl@sss.pgh.pa.us 1803 : 9388 : mOrder = Max(mOrder, MINORDER);
3319 rhaas@postgresql.org 1804 : 9388 : mOrder = Min(mOrder, MAXORDER);
1805 : :
7234 tgl@sss.pgh.pa.us 1806 : 9388 : return mOrder;
1807 : : }
1808 : :
1809 : : /*
1810 : : * Helper function to calculate how much memory to allocate for the read buffer
1811 : : * of each input tape in a merge pass.
1812 : : *
1813 : : * 'avail_mem' is the amount of memory available for the buffers of all the
1814 : : * tapes, both input and output.
1815 : : * 'nInputTapes' and 'nInputRuns' are the number of input tapes and runs.
1816 : : * 'maxOutputTapes' is the max. number of output tapes we should produce.
1817 : : */
1818 : : static int64
1521 heikki.linnakangas@i 1819 : 166 : merge_read_buffer_size(int64 avail_mem, int nInputTapes, int nInputRuns,
1820 : : int maxOutputTapes)
1821 : : {
1822 : : int nOutputRuns;
1823 : : int nOutputTapes;
1824 : :
1825 : : /*
1826 : : * How many output tapes will we produce in this pass?
1827 : : *
1828 : : * This is nInputRuns / nInputTapes, rounded up.
1829 : : */
1830 : 166 : nOutputRuns = (nInputRuns + nInputTapes - 1) / nInputTapes;
1831 : :
1832 : 166 : nOutputTapes = Min(nOutputRuns, maxOutputTapes);
1833 : :
1834 : : /*
1835 : : * Each output tape consumes TAPE_BUFFER_OVERHEAD bytes of memory. All
1836 : : * remaining memory is divided evenly between the input tapes.
1837 : : *
1838 : : * This also follows from the formula in tuplesort_merge_order, but here
1839 : : * we derive the input buffer size from the amount of memory available,
1840 : : * and M and N.
1841 : : */
1842 : 166 : return Max((avail_mem - TAPE_BUFFER_OVERHEAD * nOutputTapes) / nInputTapes, 0);
1843 : : }
1844 : :
1845 : : /*
1846 : : * inittapes - initialize for tape sorting.
1847 : : *
1848 : : * This is called only if we have found we won't sort in memory.
1849 : : */
1850 : : static void
2875 rhaas@postgresql.org 1851 : 304 : inittapes(Tuplesortstate *state, bool mergeruns)
1852 : : {
1853 [ + + - + ]: 304 : Assert(!LEADER(state));
1854 : :
1855 [ + + ]: 304 : if (mergeruns)
1856 : : {
1857 : : /* Compute number of input tapes to use when merging */
1521 heikki.linnakangas@i 1858 : 70 : state->maxTapes = tuplesort_merge_order(state->allowedMem);
1859 : : }
1860 : : else
1861 : : {
1862 : : /* Workers can sometimes produce single run, output without merge */
2875 rhaas@postgresql.org 1863 [ + - - + ]: 234 : Assert(WORKER(state));
1521 heikki.linnakangas@i 1864 : 234 : state->maxTapes = MINORDER;
1865 : : }
1866 : :
7380 tgl@sss.pgh.pa.us 1867 [ - + ]: 304 : if (trace_sort)
2603 pg@bowt.ie 1868 [ # # ]:UBC 0 : elog(LOG, "worker %d switching to external sort with %d tapes: %s",
1869 : : state->worker, state->maxTapes, pg_rusage_show(&state->ru_start));
1870 : :
1871 : : /* Create the tape set */
1521 heikki.linnakangas@i 1872 :CBC 304 : inittapestate(state, state->maxTapes);
2875 rhaas@postgresql.org 1873 : 304 : state->tapeset =
1521 heikki.linnakangas@i 1874 : 304 : LogicalTapeSetCreate(false,
2875 rhaas@postgresql.org 1875 [ + + ]: 304 : state->shared ? &state->shared->fileset : NULL,
1876 : : state->worker);
1877 : :
3001 1878 : 304 : state->currentRun = 0;
1879 : :
1880 : : /*
1881 : : * Initialize logical tape arrays.
1882 : : */
1521 heikki.linnakangas@i 1883 : 304 : state->inputTapes = NULL;
1884 : 304 : state->nInputTapes = 0;
1885 : 304 : state->nInputRuns = 0;
1886 : :
1887 : 304 : state->outputTapes = palloc0(state->maxTapes * sizeof(LogicalTape *));
1888 : 304 : state->nOutputTapes = 0;
1889 : 304 : state->nOutputRuns = 0;
1890 : :
9558 tgl@sss.pgh.pa.us 1891 : 304 : state->status = TSS_BUILDRUNS;
1892 : :
1521 heikki.linnakangas@i 1893 : 304 : selectnewtape(state);
9558 tgl@sss.pgh.pa.us 1894 : 304 : }
1895 : :
1896 : : /*
1897 : : * inittapestate - initialize generic tape management state
1898 : : */
1899 : : static void
2875 rhaas@postgresql.org 1900 : 385 : inittapestate(Tuplesortstate *state, int maxTapes)
1901 : : {
1902 : : int64 tapeSpace;
1903 : :
1904 : : /*
1905 : : * Decrease availMem to reflect the space needed for tape buffers; but
1906 : : * don't decrease it to the point that we have no room for tuples. (That
1907 : : * case is only likely to occur if sorting pass-by-value Datums; in all
1908 : : * other scenarios the memtuples[] array is unlikely to occupy more than
1909 : : * half of allowedMem. In the pass-by-value case it's not important to
1910 : : * account for tuple space, so we don't care if LACKMEM becomes
1911 : : * inaccurate.)
1912 : : */
1913 : 385 : tapeSpace = (int64) maxTapes * TAPE_BUFFER_OVERHEAD;
1914 : :
1915 [ + + ]: 385 : if (tapeSpace + GetMemoryChunkSpace(state->memtuples) < state->allowedMem)
1916 : 324 : USEMEM(state, tapeSpace);
1917 : :
1918 : : /*
1919 : : * Make sure that the temp file(s) underlying the tape set are created in
1920 : : * suitable temp tablespaces. For parallel sorts, this should have been
1921 : : * called already, but it doesn't matter if it is called a second time.
1922 : : */
1923 : 385 : PrepareTempTablespaces();
1924 : 385 : }
1925 : :
1926 : : /*
1927 : : * selectnewtape -- select next tape to output to.
1928 : : *
1929 : : * This is called after finishing a run when we know another run
1930 : : * must be started. This is used both when building the initial
1931 : : * runs, and during merge passes.
1932 : : */
1933 : : static void
9558 tgl@sss.pgh.pa.us 1934 : 856 : selectnewtape(Tuplesortstate *state)
1935 : : {
1936 : : /*
1937 : : * At the beginning of each merge pass, nOutputTapes and nOutputRuns are
1938 : : * both zero. On each call, we create a new output tape to hold the next
1939 : : * run, until maxTapes is reached. After that, we assign new runs to the
1940 : : * existing tapes in a round robin fashion.
1941 : : */
1514 heikki.linnakangas@i 1942 [ + + ]: 856 : if (state->nOutputTapes < state->maxTapes)
1943 : : {
1944 : : /* Create a new tape to hold the next run */
1521 1945 [ - + ]: 565 : Assert(state->outputTapes[state->nOutputRuns] == NULL);
1946 [ - + ]: 565 : Assert(state->nOutputRuns == state->nOutputTapes);
1947 : 565 : state->destTape = LogicalTapeCreate(state->tapeset);
1514 1948 : 565 : state->outputTapes[state->nOutputTapes] = state->destTape;
1521 1949 : 565 : state->nOutputTapes++;
1950 : 565 : state->nOutputRuns++;
1951 : : }
1952 : : else
1953 : : {
1954 : : /*
1955 : : * We have reached the max number of tapes. Append to an existing
1956 : : * tape.
1957 : : */
1958 : 291 : state->destTape = state->outputTapes[state->nOutputRuns % state->nOutputTapes];
1959 : 291 : state->nOutputRuns++;
1960 : : }
9558 tgl@sss.pgh.pa.us 1961 : 856 : }
1962 : :
1963 : : /*
1964 : : * Initialize the slab allocation arena, for the given number of slots.
1965 : : */
1966 : : static void
3362 heikki.linnakangas@i 1967 : 151 : init_slab_allocator(Tuplesortstate *state, int numSlots)
1968 : : {
1969 [ + + ]: 151 : if (numSlots > 0)
1970 : : {
1971 : : char *p;
1972 : : int i;
1973 : :
1974 : 137 : state->slabMemoryBegin = palloc(numSlots * SLAB_SLOT_SIZE);
1975 : 137 : state->slabMemoryEnd = state->slabMemoryBegin +
1976 : 137 : numSlots * SLAB_SLOT_SIZE;
1977 : 137 : state->slabFreeHead = (SlabSlot *) state->slabMemoryBegin;
1978 : 137 : USEMEM(state, numSlots * SLAB_SLOT_SIZE);
1979 : :
1980 : 137 : p = state->slabMemoryBegin;
1981 [ + + ]: 521 : for (i = 0; i < numSlots - 1; i++)
1982 : : {
1983 : 384 : ((SlabSlot *) p)->nextfree = (SlabSlot *) (p + SLAB_SLOT_SIZE);
1984 : 384 : p += SLAB_SLOT_SIZE;
1985 : : }
1986 : 137 : ((SlabSlot *) p)->nextfree = NULL;
1987 : : }
1988 : : else
1989 : : {
1990 : 14 : state->slabMemoryBegin = state->slabMemoryEnd = NULL;
1991 : 14 : state->slabFreeHead = NULL;
1992 : : }
1993 : 151 : state->slabAllocatorUsed = true;
1994 : 151 : }
1995 : :
1996 : : /*
1997 : : * mergeruns -- merge all the completed initial runs.
1998 : : *
1999 : : * This implements the Balanced k-Way Merge Algorithm. All input data has
2000 : : * already been written to initial runs on tape (see dumptuples).
2001 : : */
2002 : : static void
9558 tgl@sss.pgh.pa.us 2003 : 151 : mergeruns(Tuplesortstate *state)
2004 : : {
2005 : : int tapenum;
2006 : :
2007 [ - + ]: 151 : Assert(state->status == TSS_BUILDRUNS);
9545 2008 [ - + ]: 151 : Assert(state->memtupcount == 0);
2009 : :
1239 akorotkov@postgresql 2010 [ + + + + ]: 151 : if (state->base.sortKeys != NULL && state->base.sortKeys->abbrev_converter != NULL)
2011 : : {
2012 : : /*
2013 : : * If there are multiple runs to be merged, when we go to read back
2014 : : * tuples from disk, abbreviated keys will not have been stored, and
2015 : : * we don't care to regenerate them. Disable abbreviation from this
2016 : : * point on.
2017 : : */
2018 : 15 : state->base.sortKeys->abbrev_converter = NULL;
2019 : 15 : state->base.sortKeys->comparator = state->base.sortKeys->abbrev_full_comparator;
2020 : :
2021 : : /* Not strictly necessary, but be tidy */
2022 : 15 : state->base.sortKeys->abbrev_abort = NULL;
2023 : 15 : state->base.sortKeys->abbrev_full_comparator = NULL;
2024 : : }
2025 : :
2026 : : /*
2027 : : * Reset tuple memory. We've freed all the tuples that we previously
2028 : : * allocated. We will use the slab allocator from now on.
2029 : : */
2030 : 151 : MemoryContextResetOnly(state->base.tuplecontext);
2031 : :
2032 : : /*
2033 : : * We no longer need a large memtuples array. (We will allocate a smaller
2034 : : * one for the heap later.)
2035 : : */
3362 heikki.linnakangas@i 2036 : 151 : FREEMEM(state, GetMemoryChunkSpace(state->memtuples));
2037 : 151 : pfree(state->memtuples);
2038 : 151 : state->memtuples = NULL;
2039 : :
2040 : : /*
2041 : : * Initialize the slab allocator. We need one slab slot per input tape,
2042 : : * for the tuples in the heap, plus one to hold the tuple last returned
2043 : : * from tuplesort_gettuple. (If we're sorting pass-by-val Datums,
2044 : : * however, we don't need to do allocate anything.)
2045 : : *
2046 : : * In a multi-pass merge, we could shrink this allocation for the last
2047 : : * merge pass, if it has fewer tapes than previous passes, but we don't
2048 : : * bother.
2049 : : *
2050 : : * From this point on, we no longer use the USEMEM()/LACKMEM() mechanism
2051 : : * to track memory usage of individual tuples.
2052 : : */
1239 akorotkov@postgresql 2053 [ + + ]: 151 : if (state->base.tuples)
1521 heikki.linnakangas@i 2054 : 137 : init_slab_allocator(state, state->nOutputTapes + 1);
2055 : : else
3362 2056 : 14 : init_slab_allocator(state, 0);
2057 : :
2058 : : /*
2059 : : * Allocate a new 'memtuples' array, for the heap. It will hold one tuple
2060 : : * from each input tape.
2061 : : *
2062 : : * We could shrink this, too, between passes in a multi-pass merge, but we
2063 : : * don't bother. (The initial input tapes are still in outputTapes. The
2064 : : * number of input tapes will not increase between passes.)
2065 : : */
1521 2066 : 151 : state->memtupsize = state->nOutputTapes;
1239 akorotkov@postgresql 2067 : 302 : state->memtuples = (SortTuple *) MemoryContextAlloc(state->base.maincontext,
1521 heikki.linnakangas@i 2068 : 151 : state->nOutputTapes * sizeof(SortTuple));
3296 2069 : 151 : USEMEM(state, GetMemoryChunkSpace(state->memtuples));
2070 : :
2071 : : /*
2072 : : * Use all the remaining memory we have available for tape buffers among
2073 : : * all the input tapes. At the beginning of each merge pass, we will
2074 : : * divide this memory between the input and output tapes in the pass.
2075 : : */
1521 2076 : 151 : state->tape_buffer_mem = state->availMem;
1514 2077 : 151 : USEMEM(state, state->tape_buffer_mem);
3353 2078 [ - + ]: 151 : if (trace_sort)
1521 heikki.linnakangas@i 2079 [ # # ]:UBC 0 : elog(LOG, "worker %d using %zu KB of memory for tape buffers",
2080 : : state->worker, state->tape_buffer_mem / 1024);
2081 : :
2082 : : for (;;)
2083 : : {
2084 : : /*
2085 : : * On the first iteration, or if we have read all the runs from the
2086 : : * input tapes in a multi-pass merge, it's time to start a new pass.
2087 : : * Rewind all the output tapes, and make them inputs for the next
2088 : : * pass.
2089 : : */
1521 heikki.linnakangas@i 2090 [ + + ]:CBC 220 : if (state->nInputRuns == 0)
2091 : : {
2092 : : int64 input_buffer_size;
2093 : :
2094 : : /* Close the old, emptied, input tapes */
2095 [ + + ]: 166 : if (state->nInputTapes > 0)
2096 : : {
2097 [ + + ]: 105 : for (tapenum = 0; tapenum < state->nInputTapes; tapenum++)
2098 : 90 : LogicalTapeClose(state->inputTapes[tapenum]);
2099 : 15 : pfree(state->inputTapes);
2100 : : }
2101 : :
2102 : : /* Previous pass's outputs become next pass's inputs. */
2103 : 166 : state->inputTapes = state->outputTapes;
2104 : 166 : state->nInputTapes = state->nOutputTapes;
2105 : 166 : state->nInputRuns = state->nOutputRuns;
2106 : :
2107 : : /*
2108 : : * Reset output tape variables. The actual LogicalTapes will be
2109 : : * created as needed, here we only allocate the array to hold
2110 : : * them.
2111 : : */
2112 : 166 : state->outputTapes = palloc0(state->nInputTapes * sizeof(LogicalTape *));
2113 : 166 : state->nOutputTapes = 0;
2114 : 166 : state->nOutputRuns = 0;
2115 : :
2116 : : /*
2117 : : * Redistribute the memory allocated for tape buffers, among the
2118 : : * new input and output tapes.
2119 : : */
2120 : 166 : input_buffer_size = merge_read_buffer_size(state->tape_buffer_mem,
2121 : : state->nInputTapes,
2122 : : state->nInputRuns,
2123 : : state->maxTapes);
2124 : :
2125 [ - + ]: 166 : if (trace_sort)
1521 heikki.linnakangas@i 2126 [ # # ]:UBC 0 : elog(LOG, "starting merge pass of %d input runs on %d tapes, " INT64_FORMAT " KB of memory for each input tape: %s",
2127 : : state->nInputRuns, state->nInputTapes, input_buffer_size / 1024,
2128 : : pg_rusage_show(&state->ru_start));
2129 : :
2130 : : /* Prepare the new input tapes for merge pass. */
1521 heikki.linnakangas@i 2131 [ + + ]:CBC 650 : for (tapenum = 0; tapenum < state->nInputTapes; tapenum++)
2132 : 484 : LogicalTapeRewindForRead(state->inputTapes[tapenum], input_buffer_size);
2133 : :
2134 : : /*
2135 : : * If there's just one run left on each input tape, then only one
2136 : : * merge pass remains. If we don't have to produce a materialized
2137 : : * sorted tape, we can stop at this point and do the final merge
2138 : : * on-the-fly.
2139 : : */
1239 akorotkov@postgresql 2140 [ + + ]: 166 : if ((state->base.sortopt & TUPLESORT_RANDOMACCESS) == 0
1353 drowley@postgresql.o 2141 [ + + ]: 155 : && state->nInputRuns <= state->nInputTapes
1521 heikki.linnakangas@i 2142 [ + + + - ]: 140 : && !WORKER(state))
2143 : : {
2144 : : /* Tell logtape.c we won't be writing anymore */
7225 tgl@sss.pgh.pa.us 2145 : 140 : LogicalTapeSetForgetFreeSpace(state->tapeset);
2146 : : /* Initialize for the final merge pass */
3362 heikki.linnakangas@i 2147 : 140 : beginmerge(state);
9558 tgl@sss.pgh.pa.us 2148 : 140 : state->status = TSS_FINALMERGE;
2149 : 140 : return;
2150 : : }
2151 : : }
2152 : :
2153 : : /* Select an output tape */
1521 heikki.linnakangas@i 2154 : 80 : selectnewtape(state);
2155 : :
2156 : : /* Merge one run from each input tape. */
2157 : 80 : mergeonerun(state);
2158 : :
2159 : : /*
2160 : : * If the input tapes are empty, and we output only one output run,
2161 : : * we're done. The current output tape contains the final result.
2162 : : */
2163 [ + + + + ]: 80 : if (state->nInputRuns == 0 && state->nOutputRuns <= 1)
2164 : 11 : break;
2165 : : }
2166 : :
2167 : : /*
2168 : : * Done. The result is on a single run on a single tape.
2169 : : */
2170 : 11 : state->result_tape = state->outputTapes[0];
2875 rhaas@postgresql.org 2171 [ - + - - ]: 11 : if (!WORKER(state))
1521 heikki.linnakangas@i 2172 : 11 : LogicalTapeFreeze(state->result_tape, NULL);
2173 : : else
2875 rhaas@postgresql.org 2174 :UBC 0 : worker_freeze_result_tape(state);
9558 tgl@sss.pgh.pa.us 2175 :CBC 11 : state->status = TSS_SORTEDONTAPE;
2176 : :
2177 : : /* Close all the now-empty input tapes, to release their read buffers. */
1521 heikki.linnakangas@i 2178 [ + + ]: 57 : for (tapenum = 0; tapenum < state->nInputTapes; tapenum++)
2179 : 46 : LogicalTapeClose(state->inputTapes[tapenum]);
2180 : : }
2181 : :
2182 : : /*
2183 : : * Merge one run from each input tape.
2184 : : */
2185 : : static void
9558 tgl@sss.pgh.pa.us 2186 : 80 : mergeonerun(Tuplesortstate *state)
2187 : : {
2188 : : int srcTapeIndex;
2189 : : LogicalTape *srcTape;
2190 : :
2191 : : /*
2192 : : * Start the merge by loading one tuple from each active source tape into
2193 : : * the heap.
2194 : : */
3362 heikki.linnakangas@i 2195 : 80 : beginmerge(state);
2196 : :
1203 drowley@postgresql.o 2197 [ - + ]: 80 : Assert(state->slabAllocatorUsed);
2198 : :
2199 : : /*
2200 : : * Execute merge by repeatedly extracting lowest tuple in heap, writing it
2201 : : * out, and replacing it with next tuple from same tape (if there is
2202 : : * another one).
2203 : : */
9545 tgl@sss.pgh.pa.us 2204 [ + + ]: 437796 : while (state->memtupcount > 0)
2205 : : {
2206 : : SortTuple stup;
2207 : :
2208 : : /* write the tuple to destTape */
1521 heikki.linnakangas@i 2209 : 437716 : srcTapeIndex = state->memtuples[0].srctape;
2210 : 437716 : srcTape = state->inputTapes[srcTapeIndex];
2211 : 437716 : WRITETUP(state, state->destTape, &state->memtuples[0]);
2212 : :
2213 : : /* recycle the slot of the tuple we just wrote out, for the next read */
3257 tgl@sss.pgh.pa.us 2214 [ + + ]: 437716 : if (state->memtuples[0].tuple)
2215 [ + - + - ]: 367674 : RELEASE_SLAB_SLOT(state, state->memtuples[0].tuple);
2216 : :
2217 : : /*
2218 : : * pull next tuple from the tape, and replace the written-out tuple in
2219 : : * the heap with it.
2220 : : */
3362 heikki.linnakangas@i 2221 [ + + ]: 437716 : if (mergereadnext(state, srcTape, &stup))
2222 : : {
1521 2223 : 437289 : stup.srctape = srcTapeIndex;
3001 rhaas@postgresql.org 2224 : 437289 : tuplesort_heap_replace_top(state, &stup);
2225 : : }
2226 : : else
2227 : : {
2228 : 427 : tuplesort_heap_delete_top(state);
1521 heikki.linnakangas@i 2229 : 427 : state->nInputRuns--;
2230 : : }
2231 : : }
2232 : :
2233 : : /*
2234 : : * When the heap empties, we're done. Write an end-of-run marker on the
2235 : : * output tape.
2236 : : */
2237 : 80 : markrunend(state->destTape);
9558 tgl@sss.pgh.pa.us 2238 : 80 : }
2239 : :
2240 : : /*
2241 : : * beginmerge - initialize for a merge pass
2242 : : *
2243 : : * Fill the merge heap with the first tuple from each input tape.
2244 : : */
2245 : : static void
3362 heikki.linnakangas@i 2246 : 220 : beginmerge(Tuplesortstate *state)
2247 : : {
2248 : : int activeTapes;
2249 : : int srcTapeIndex;
2250 : :
2251 : : /* Heap should be empty here */
9545 tgl@sss.pgh.pa.us 2252 [ - + ]: 220 : Assert(state->memtupcount == 0);
2253 : :
1521 heikki.linnakangas@i 2254 : 220 : activeTapes = Min(state->nInputTapes, state->nInputRuns);
2255 : :
2256 [ + + ]: 995 : for (srcTapeIndex = 0; srcTapeIndex < activeTapes; srcTapeIndex++)
2257 : : {
2258 : : SortTuple tup;
2259 : :
2260 [ + + ]: 775 : if (mergereadnext(state, state->inputTapes[srcTapeIndex], &tup))
2261 : : {
2262 : 648 : tup.srctape = srcTapeIndex;
3001 rhaas@postgresql.org 2263 : 648 : tuplesort_heap_insert(state, &tup);
2264 : : }
2265 : : }
3562 2266 : 220 : }
2267 : :
2268 : : /*
2269 : : * mergereadnext - read next tuple from one merge input tape
2270 : : *
2271 : : * Returns false on EOF.
2272 : : */
2273 : : static bool
1521 heikki.linnakangas@i 2274 : 2760688 : mergereadnext(Tuplesortstate *state, LogicalTape *srcTape, SortTuple *stup)
2275 : : {
2276 : : unsigned int tuplen;
2277 : :
2278 : : /* read next tuple, if any */
2279 [ + + ]: 2760688 : if ((tuplen = getlen(srcTape, true)) == 0)
3362 2280 : 751 : return false;
2281 : 2759937 : READTUP(state, stup, srcTape, tuplen);
2282 : :
2283 : 2759937 : return true;
2284 : : }
2285 : :
2286 : : /*
2287 : : * dumptuples - remove tuples from memtuples and write initial run to tape
2288 : : *
2289 : : * When alltuples = true, dump everything currently in memory. (This case is
2290 : : * only used at end of input data.)
2291 : : */
2292 : : static void
9558 tgl@sss.pgh.pa.us 2293 : 556581 : dumptuples(Tuplesortstate *state, bool alltuples)
2294 : : {
2295 : : int memtupwrite;
2296 : : int i;
2297 : :
2298 : : /*
2299 : : * Nothing to do if we still fit in available memory and have array slots,
2300 : : * unless this is the final call during initial run generation.
2301 : : */
3001 rhaas@postgresql.org 2302 [ + + + + : 556581 : if (state->memtupcount < state->memtupsize && !LACKMEM(state) &&
- + ]
2303 [ + + ]: 556109 : !alltuples)
2304 : 555805 : return;
2305 : :
2306 : : /*
2307 : : * Final call might require no sorting, in rare cases where we just so
2308 : : * happen to have previously LACKMEM()'d at the point where exactly all
2309 : : * remaining tuples are loaded into memory, just before input was
2310 : : * exhausted. In general, short final runs are quite possible, but avoid
2311 : : * creating a completely empty run. In a worker, though, we must produce
2312 : : * at least one tape, even if it's empty.
2313 : : */
1521 heikki.linnakangas@i 2314 [ + + - + ]: 776 : if (state->memtupcount == 0 && state->currentRun > 0)
1521 heikki.linnakangas@i 2315 :UBC 0 : return;
2316 : :
3540 rhaas@postgresql.org 2317 [ - + ]:CBC 776 : Assert(state->status == TSS_BUILDRUNS);
2318 : :
2319 : : /*
2320 : : * It seems unlikely that this limit will ever be exceeded, but take no
2321 : : * chances
2322 : : */
2323 [ - + ]: 776 : if (state->currentRun == INT_MAX)
3540 rhaas@postgresql.org 2324 [ # # ]:UBC 0 : ereport(ERROR,
2325 : : (errcode(ERRCODE_PROGRAM_LIMIT_EXCEEDED),
2326 : : errmsg("cannot have more than %d runs for an external sort",
2327 : : INT_MAX)));
2328 : :
1521 heikki.linnakangas@i 2329 [ + + ]:CBC 776 : if (state->currentRun > 0)
2330 : 472 : selectnewtape(state);
2331 : :
3540 rhaas@postgresql.org 2332 : 776 : state->currentRun++;
2333 : :
2334 [ - + ]: 776 : if (trace_sort)
2603 pg@bowt.ie 2335 [ # # ]:UBC 0 : elog(LOG, "worker %d starting quicksort of run %d: %s",
2336 : : state->worker, state->currentRun,
2337 : : pg_rusage_show(&state->ru_start));
2338 : :
2339 : : /*
2340 : : * Sort all tuples accumulated within the allowed amount of memory for
2341 : : * this run using quicksort
2342 : : */
3540 rhaas@postgresql.org 2343 :CBC 776 : tuplesort_sort_memtuples(state);
2344 : :
2345 [ - + ]: 776 : if (trace_sort)
2603 pg@bowt.ie 2346 [ # # ]:UBC 0 : elog(LOG, "worker %d finished quicksort of run %d: %s",
2347 : : state->worker, state->currentRun,
2348 : : pg_rusage_show(&state->ru_start));
2349 : :
3540 rhaas@postgresql.org 2350 :CBC 776 : memtupwrite = state->memtupcount;
2351 [ + + ]: 2580599 : for (i = 0; i < memtupwrite; i++)
2352 : : {
1203 drowley@postgresql.o 2353 : 2579823 : SortTuple *stup = &state->memtuples[i];
2354 : :
2355 : 2579823 : WRITETUP(state, state->destTape, stup);
2356 : : }
2357 : :
2358 : 776 : state->memtupcount = 0;
2359 : :
2360 : : /*
2361 : : * Reset tuple memory. We've freed all of the tuples that we previously
2362 : : * allocated. It's important to avoid fragmentation when there is a stark
2363 : : * change in the sizes of incoming tuples. In bounded sorts,
2364 : : * fragmentation due to AllocSetFree's bucketing by size class might be
2365 : : * particularly bad if this step wasn't taken.
2366 : : */
1239 akorotkov@postgresql 2367 : 776 : MemoryContextReset(state->base.tuplecontext);
2368 : :
2369 : : /*
2370 : : * Now update the memory accounting to subtract the memory used by the
2371 : : * tuple.
2372 : : */
618 drowley@postgresql.o 2373 : 776 : FREEMEM(state, state->tupleMem);
2374 : 776 : state->tupleMem = 0;
2375 : :
1521 heikki.linnakangas@i 2376 : 776 : markrunend(state->destTape);
2377 : :
3540 rhaas@postgresql.org 2378 [ - + ]: 776 : if (trace_sort)
2603 pg@bowt.ie 2379 [ # # ]:UBC 0 : elog(LOG, "worker %d finished writing run %d to tape %d: %s",
2380 : : state->worker, state->currentRun, (state->currentRun - 1) % state->nOutputTapes + 1,
2381 : : pg_rusage_show(&state->ru_start));
2382 : : }
2383 : :
2384 : : /*
2385 : : * tuplesort_rescan - rewind and replay the scan
2386 : : */
2387 : : void
9558 tgl@sss.pgh.pa.us 2388 :CBC 30 : tuplesort_rescan(Tuplesortstate *state)
2389 : : {
1239 akorotkov@postgresql 2390 : 30 : MemoryContext oldcontext = MemoryContextSwitchTo(state->base.sortcontext);
2391 : :
2392 [ - + ]: 30 : Assert(state->base.sortopt & TUPLESORT_RANDOMACCESS);
2393 : :
9558 tgl@sss.pgh.pa.us 2394 [ + + - ]: 30 : switch (state->status)
2395 : : {
2396 : 26 : case TSS_SORTEDINMEM:
2397 : 26 : state->current = 0;
2398 : 26 : state->eof_reached = false;
2399 : 26 : state->markpos_offset = 0;
2400 : 26 : state->markpos_eof = false;
2401 : 26 : break;
2402 : 4 : case TSS_SORTEDONTAPE:
1521 heikki.linnakangas@i 2403 : 4 : LogicalTapeRewindForRead(state->result_tape, 0);
9558 tgl@sss.pgh.pa.us 2404 : 4 : state->eof_reached = false;
2405 : 4 : state->markpos_block = 0L;
2406 : 4 : state->markpos_offset = 0;
2407 : 4 : state->markpos_eof = false;
2408 : 4 : break;
9558 tgl@sss.pgh.pa.us 2409 :UBC 0 : default:
8181 2410 [ # # ]: 0 : elog(ERROR, "invalid tuplesort state");
2411 : : break;
2412 : : }
2413 : :
7234 tgl@sss.pgh.pa.us 2414 :CBC 30 : MemoryContextSwitchTo(oldcontext);
9558 2415 : 30 : }
2416 : :
2417 : : /*
2418 : : * tuplesort_markpos - saves current position in the merged sort file
2419 : : */
2420 : : void
2421 : 295167 : tuplesort_markpos(Tuplesortstate *state)
2422 : : {
1239 akorotkov@postgresql 2423 : 295167 : MemoryContext oldcontext = MemoryContextSwitchTo(state->base.sortcontext);
2424 : :
2425 [ - + ]: 295167 : Assert(state->base.sortopt & TUPLESORT_RANDOMACCESS);
2426 : :
9558 tgl@sss.pgh.pa.us 2427 [ + + - ]: 295167 : switch (state->status)
2428 : : {
2429 : 290763 : case TSS_SORTEDINMEM:
2430 : 290763 : state->markpos_offset = state->current;
2431 : 290763 : state->markpos_eof = state->eof_reached;
2432 : 290763 : break;
2433 : 4404 : case TSS_SORTEDONTAPE:
1521 heikki.linnakangas@i 2434 : 4404 : LogicalTapeTell(state->result_tape,
2435 : : &state->markpos_block,
2436 : : &state->markpos_offset);
9558 tgl@sss.pgh.pa.us 2437 : 4404 : state->markpos_eof = state->eof_reached;
2438 : 4404 : break;
9558 tgl@sss.pgh.pa.us 2439 :UBC 0 : default:
8181 2440 [ # # ]: 0 : elog(ERROR, "invalid tuplesort state");
2441 : : break;
2442 : : }
2443 : :
7234 tgl@sss.pgh.pa.us 2444 :CBC 295167 : MemoryContextSwitchTo(oldcontext);
9558 2445 : 295167 : }
2446 : :
2447 : : /*
2448 : : * tuplesort_restorepos - restores current position in merged sort file to
2449 : : * last saved position
2450 : : */
2451 : : void
2452 : 19354 : tuplesort_restorepos(Tuplesortstate *state)
2453 : : {
1239 akorotkov@postgresql 2454 : 19354 : MemoryContext oldcontext = MemoryContextSwitchTo(state->base.sortcontext);
2455 : :
2456 [ - + ]: 19354 : Assert(state->base.sortopt & TUPLESORT_RANDOMACCESS);
2457 : :
9558 tgl@sss.pgh.pa.us 2458 [ + + - ]: 19354 : switch (state->status)
2459 : : {
2460 : 16258 : case TSS_SORTEDINMEM:
2461 : 16258 : state->current = state->markpos_offset;
2462 : 16258 : state->eof_reached = state->markpos_eof;
2463 : 16258 : break;
2464 : 3096 : case TSS_SORTEDONTAPE:
1521 heikki.linnakangas@i 2465 : 3096 : LogicalTapeSeek(state->result_tape,
2466 : : state->markpos_block,
2467 : : state->markpos_offset);
9558 tgl@sss.pgh.pa.us 2468 : 3096 : state->eof_reached = state->markpos_eof;
2469 : 3096 : break;
9558 tgl@sss.pgh.pa.us 2470 :UBC 0 : default:
8181 2471 [ # # ]: 0 : elog(ERROR, "invalid tuplesort state");
2472 : : break;
2473 : : }
2474 : :
7234 tgl@sss.pgh.pa.us 2475 :CBC 19354 : MemoryContextSwitchTo(oldcontext);
9558 2476 : 19354 : }
2477 : :
2478 : : /*
2479 : : * tuplesort_get_stats - extract summary statistics
2480 : : *
2481 : : * This can be called after tuplesort_performsort() finishes to obtain
2482 : : * printable summary information about how the sort was performed.
2483 : : */
2484 : : void
5973 2485 : 198 : tuplesort_get_stats(Tuplesortstate *state,
2486 : : TuplesortInstrumentation *stats)
2487 : : {
2488 : : /*
2489 : : * Note: it might seem we should provide both memory and disk usage for a
2490 : : * disk-based sort. However, the current code doesn't track memory space
2491 : : * accurately once we have begun to return tuples to the caller (since we
2492 : : * don't account for pfree's the caller is expected to do), so we cannot
2493 : : * rely on availMem in a disk sort. This does not seem worth the overhead
2494 : : * to fix. Is it worth creating an API for the memory context code to
2495 : : * tell us how much is actually used in sortcontext?
2496 : : */
2081 tomas.vondra@postgre 2497 : 198 : tuplesort_updatemax(state);
2498 : :
2499 [ + + ]: 198 : if (state->isMaxSpaceDisk)
3032 rhaas@postgresql.org 2500 : 3 : stats->spaceType = SORT_SPACE_TYPE_DISK;
2501 : : else
2502 : 195 : stats->spaceType = SORT_SPACE_TYPE_MEMORY;
2081 tomas.vondra@postgre 2503 : 198 : stats->spaceUsed = (state->maxSpace + 1023) / 1024;
2504 : :
2505 [ + - + - ]: 198 : switch (state->maxSpaceStatus)
2506 : : {
6802 tgl@sss.pgh.pa.us 2507 : 195 : case TSS_SORTEDINMEM:
2508 [ + + ]: 195 : if (state->boundUsed)
3032 rhaas@postgresql.org 2509 : 21 : stats->sortMethod = SORT_TYPE_TOP_N_HEAPSORT;
2510 : : else
2511 : 174 : stats->sortMethod = SORT_TYPE_QUICKSORT;
6802 tgl@sss.pgh.pa.us 2512 : 195 : break;
6802 tgl@sss.pgh.pa.us 2513 :UBC 0 : case TSS_SORTEDONTAPE:
3032 rhaas@postgresql.org 2514 : 0 : stats->sortMethod = SORT_TYPE_EXTERNAL_SORT;
6802 tgl@sss.pgh.pa.us 2515 : 0 : break;
6802 tgl@sss.pgh.pa.us 2516 :CBC 3 : case TSS_FINALMERGE:
3032 rhaas@postgresql.org 2517 : 3 : stats->sortMethod = SORT_TYPE_EXTERNAL_MERGE;
6802 tgl@sss.pgh.pa.us 2518 : 3 : break;
6802 tgl@sss.pgh.pa.us 2519 :UBC 0 : default:
3032 rhaas@postgresql.org 2520 : 0 : stats->sortMethod = SORT_TYPE_STILL_IN_PROGRESS;
6802 tgl@sss.pgh.pa.us 2521 : 0 : break;
2522 : : }
6802 tgl@sss.pgh.pa.us 2523 :CBC 198 : }
2524 : :
2525 : : /*
2526 : : * Convert TuplesortMethod to a string.
2527 : : */
2528 : : const char *
3032 rhaas@postgresql.org 2529 : 147 : tuplesort_method_name(TuplesortMethod m)
2530 : : {
2531 [ - + + - : 147 : switch (m)
+ - ]
2532 : : {
3032 rhaas@postgresql.org 2533 :UBC 0 : case SORT_TYPE_STILL_IN_PROGRESS:
2534 : 0 : return "still in progress";
3032 rhaas@postgresql.org 2535 :CBC 21 : case SORT_TYPE_TOP_N_HEAPSORT:
2536 : 21 : return "top-N heapsort";
2537 : 123 : case SORT_TYPE_QUICKSORT:
2538 : 123 : return "quicksort";
3032 rhaas@postgresql.org 2539 :UBC 0 : case SORT_TYPE_EXTERNAL_SORT:
2540 : 0 : return "external sort";
3032 rhaas@postgresql.org 2541 :CBC 3 : case SORT_TYPE_EXTERNAL_MERGE:
2542 : 3 : return "external merge";
2543 : : }
2544 : :
3032 rhaas@postgresql.org 2545 :UBC 0 : return "unknown";
2546 : : }
2547 : :
2548 : : /*
2549 : : * Convert TuplesortSpaceType to a string.
2550 : : */
2551 : : const char *
3032 rhaas@postgresql.org 2552 :CBC 129 : tuplesort_space_type_name(TuplesortSpaceType t)
2553 : : {
2554 [ + + - + ]: 129 : Assert(t == SORT_SPACE_TYPE_DISK || t == SORT_SPACE_TYPE_MEMORY);
2555 [ + + ]: 129 : return t == SORT_SPACE_TYPE_DISK ? "Disk" : "Memory";
2556 : : }
2557 : :
2558 : :
2559 : : /*
2560 : : * Heap manipulation routines, per Knuth's Algorithm 5.2.3H.
2561 : : */
2562 : :
2563 : : /*
2564 : : * Convert the existing unordered array of SortTuples to a bounded heap,
2565 : : * discarding all but the smallest "state->bound" tuples.
2566 : : *
2567 : : * When working with a bounded heap, we want to keep the largest entry
2568 : : * at the root (array entry zero), instead of the smallest as in the normal
2569 : : * sort case. This allows us to discard the largest entry cheaply.
2570 : : * Therefore, we temporarily reverse the sort direction.
2571 : : */
2572 : : static void
6802 tgl@sss.pgh.pa.us 2573 : 213 : make_bounded_heap(Tuplesortstate *state)
2574 : : {
6607 bruce@momjian.us 2575 : 213 : int tupcount = state->memtupcount;
2576 : : int i;
2577 : :
6802 tgl@sss.pgh.pa.us 2578 [ - + ]: 213 : Assert(state->status == TSS_INITIAL);
2579 [ - + ]: 213 : Assert(state->bounded);
2580 [ - + ]: 213 : Assert(tupcount >= state->bound);
2875 rhaas@postgresql.org 2581 [ - + ]: 213 : Assert(SERIAL(state));
2582 : :
2583 : : /* Reverse sort direction so largest entry will be at root */
4058 2584 : 213 : reversedirection(state);
2585 : :
6802 tgl@sss.pgh.pa.us 2586 : 213 : state->memtupcount = 0; /* make the heap empty */
6607 bruce@momjian.us 2587 [ + + ]: 21078 : for (i = 0; i < tupcount; i++)
2588 : : {
3384 heikki.linnakangas@i 2589 [ + + ]: 20865 : if (state->memtupcount < state->bound)
2590 : : {
2591 : : /* Insert next tuple into heap */
2592 : : /* Must copy source tuple to avoid possible overwrite */
6607 bruce@momjian.us 2593 : 10326 : SortTuple stup = state->memtuples[i];
2594 : :
3001 rhaas@postgresql.org 2595 : 10326 : tuplesort_heap_insert(state, &stup);
2596 : : }
2597 : : else
2598 : : {
2599 : : /*
2600 : : * The heap is full. Replace the largest entry with the new
2601 : : * tuple, or just discard it, if it's larger than anything already
2602 : : * in the heap.
2603 : : */
3384 heikki.linnakangas@i 2604 [ + + ]: 10539 : if (COMPARETUP(state, &state->memtuples[i], &state->memtuples[0]) <= 0)
2605 : : {
2606 : 5229 : free_sort_tuple(state, &state->memtuples[i]);
2607 [ - + ]: 5229 : CHECK_FOR_INTERRUPTS();
2608 : : }
2609 : : else
3001 rhaas@postgresql.org 2610 : 5310 : tuplesort_heap_replace_top(state, &state->memtuples[i]);
2611 : : }
2612 : : }
2613 : :
6802 tgl@sss.pgh.pa.us 2614 [ - + ]: 213 : Assert(state->memtupcount == state->bound);
2615 : 213 : state->status = TSS_BOUNDED;
2616 : 213 : }
2617 : :
2618 : : /*
2619 : : * Convert the bounded heap to a properly-sorted array
2620 : : */
2621 : : static void
2622 : 213 : sort_bounded_heap(Tuplesortstate *state)
2623 : : {
6607 bruce@momjian.us 2624 : 213 : int tupcount = state->memtupcount;
2625 : :
6802 tgl@sss.pgh.pa.us 2626 [ - + ]: 213 : Assert(state->status == TSS_BOUNDED);
2627 [ - + ]: 213 : Assert(state->bounded);
2628 [ - + ]: 213 : Assert(tupcount == state->bound);
2875 rhaas@postgresql.org 2629 [ - + ]: 213 : Assert(SERIAL(state));
2630 : :
2631 : : /*
2632 : : * We can unheapify in place because each delete-top call will remove the
2633 : : * largest entry, which we can promptly store in the newly freed slot at
2634 : : * the end. Once we're down to a single-entry heap, we're done.
2635 : : */
6802 tgl@sss.pgh.pa.us 2636 [ + + ]: 10326 : while (state->memtupcount > 1)
2637 : : {
6607 bruce@momjian.us 2638 : 10113 : SortTuple stup = state->memtuples[0];
2639 : :
2640 : : /* this sifts-up the next-largest entry and decreases memtupcount */
3001 rhaas@postgresql.org 2641 : 10113 : tuplesort_heap_delete_top(state);
6802 tgl@sss.pgh.pa.us 2642 : 10113 : state->memtuples[state->memtupcount] = stup;
2643 : : }
2644 : 213 : state->memtupcount = tupcount;
2645 : :
2646 : : /*
2647 : : * Reverse sort direction back to the original state. This is not
2648 : : * actually necessary but seems like a good idea for tidiness.
2649 : : */
4058 rhaas@postgresql.org 2650 : 213 : reversedirection(state);
2651 : :
6802 tgl@sss.pgh.pa.us 2652 : 213 : state->status = TSS_SORTEDINMEM;
2653 : 213 : state->boundUsed = true;
2654 : 213 : }
2655 : :
2656 : : /*
2657 : : * Sort all memtuples using specialized qsort() routines.
2658 : : *
2659 : : * Quicksort is used for small in-memory sorts, and external sort runs.
2660 : : */
2661 : : static void
3540 rhaas@postgresql.org 2662 : 118413 : tuplesort_sort_memtuples(Tuplesortstate *state)
2663 : : {
2875 2664 [ + + - + ]: 118413 : Assert(!LEADER(state));
2665 : :
3540 2666 [ + + ]: 118413 : if (state->memtupcount > 1)
2667 : : {
2668 : : /*
2669 : : * Do we have the leading column's value or abbreviation in datum1,
2670 : : * and is there a specialization for its comparator?
2671 : : */
1239 akorotkov@postgresql 2672 [ + + + + ]: 34193 : if (state->base.haveDatum1 && state->base.sortKeys)
2673 : : {
2674 [ + + ]: 34173 : if (state->base.sortKeys[0].comparator == ssup_datum_unsigned_cmp)
2675 : : {
1353 tmunro@postgresql.or 2676 : 1761 : qsort_tuple_unsigned(state->memtuples,
2677 : 1761 : state->memtupcount,
2678 : : state);
2679 : 1753 : return;
2680 : : }
1239 akorotkov@postgresql 2681 [ + + ]: 32412 : else if (state->base.sortKeys[0].comparator == ssup_datum_signed_cmp)
2682 : : {
1353 tmunro@postgresql.or 2683 : 671 : qsort_tuple_signed(state->memtuples,
2684 : 671 : state->memtupcount,
2685 : : state);
2686 : 671 : return;
2687 : : }
1239 akorotkov@postgresql 2688 [ + + ]: 31741 : else if (state->base.sortKeys[0].comparator == ssup_datum_int32_cmp)
2689 : : {
1353 tmunro@postgresql.or 2690 : 19958 : qsort_tuple_int32(state->memtuples,
2691 : 19958 : state->memtupcount,
2692 : : state);
2693 : 19928 : return;
2694 : : }
2695 : : }
2696 : :
2697 : : /* Can we use the single-key sort function? */
1239 akorotkov@postgresql 2698 [ + + ]: 11803 : if (state->base.onlyKey != NULL)
2699 : : {
3540 rhaas@postgresql.org 2700 : 5108 : qsort_ssup(state->memtuples, state->memtupcount,
1239 akorotkov@postgresql 2701 : 5108 : state->base.onlyKey);
2702 : : }
2703 : : else
2704 : : {
3540 rhaas@postgresql.org 2705 : 6695 : qsort_tuple(state->memtuples,
2706 : 6695 : state->memtupcount,
2707 : : state->base.comparetup,
2708 : : state);
2709 : : }
2710 : : }
2711 : : }
2712 : :
2713 : : /*
2714 : : * Insert a new tuple into an empty or existing heap, maintaining the
2715 : : * heap invariant. Caller is responsible for ensuring there's room.
2716 : : *
2717 : : * Note: For some callers, tuple points to a memtuples[] entry above the
2718 : : * end of the heap. This is safe as long as it's not immediately adjacent
2719 : : * to the end of the heap (ie, in the [memtupcount] array entry) --- if it
2720 : : * is, it might get overwritten before being moved into the heap!
2721 : : */
2722 : : static void
3001 2723 : 10974 : tuplesort_heap_insert(Tuplesortstate *state, SortTuple *tuple)
2724 : : {
2725 : : SortTuple *memtuples;
2726 : : int j;
2727 : :
9545 tgl@sss.pgh.pa.us 2728 : 10974 : memtuples = state->memtuples;
7234 2729 [ - + ]: 10974 : Assert(state->memtupcount < state->memtupsize);
2730 : :
5020 rhaas@postgresql.org 2731 [ + + ]: 10974 : CHECK_FOR_INTERRUPTS();
2732 : :
2733 : : /*
2734 : : * Sift-up the new entry, per Knuth 5.2.3 exercise 16. Note that Knuth is
2735 : : * using 1-based array indexes, not 0-based.
2736 : : */
9545 tgl@sss.pgh.pa.us 2737 : 10974 : j = state->memtupcount++;
2738 [ + + ]: 31213 : while (j > 0)
2739 : : {
9380 bruce@momjian.us 2740 : 27781 : int i = (j - 1) >> 1;
2741 : :
3001 rhaas@postgresql.org 2742 [ + + ]: 27781 : if (COMPARETUP(state, tuple, &memtuples[i]) >= 0)
9558 tgl@sss.pgh.pa.us 2743 : 7542 : break;
9545 2744 : 20239 : memtuples[j] = memtuples[i];
9558 2745 : 20239 : j = i;
2746 : : }
7234 2747 : 10974 : memtuples[j] = *tuple;
9558 2748 : 10974 : }
2749 : :
2750 : : /*
2751 : : * Remove the tuple at state->memtuples[0] from the heap. Decrement
2752 : : * memtupcount, and sift up to maintain the heap invariant.
2753 : : *
2754 : : * The caller has already free'd the tuple the top node points to,
2755 : : * if necessary.
2756 : : */
2757 : : static void
3001 rhaas@postgresql.org 2758 : 10737 : tuplesort_heap_delete_top(Tuplesortstate *state)
2759 : : {
7234 tgl@sss.pgh.pa.us 2760 : 10737 : SortTuple *memtuples = state->memtuples;
2761 : : SortTuple *tuple;
2762 : :
9545 2763 [ + + ]: 10737 : if (--state->memtupcount <= 0)
9558 2764 : 151 : return;
2765 : :
2766 : : /*
2767 : : * Remove the last tuple in the heap, and re-insert it, by replacing the
2768 : : * current top node with it.
2769 : : */
3384 heikki.linnakangas@i 2770 : 10586 : tuple = &memtuples[state->memtupcount];
3001 rhaas@postgresql.org 2771 : 10586 : tuplesort_heap_replace_top(state, tuple);
2772 : : }
2773 : :
2774 : : /*
2775 : : * Replace the tuple at state->memtuples[0] with a new tuple. Sift up to
2776 : : * maintain the heap invariant.
2777 : : *
2778 : : * This corresponds to Knuth's "sift-up" algorithm (Algorithm 5.2.3H,
2779 : : * Heapsort, steps H3-H8).
2780 : : */
2781 : : static void
2782 : 3026587 : tuplesort_heap_replace_top(Tuplesortstate *state, SortTuple *tuple)
2783 : : {
3384 heikki.linnakangas@i 2784 : 3026587 : SortTuple *memtuples = state->memtuples;
2785 : : unsigned int i,
2786 : : n;
2787 : :
2788 [ - + ]: 3026587 : Assert(state->memtupcount >= 1);
2789 : :
5020 rhaas@postgresql.org 2790 [ - + ]: 3026587 : CHECK_FOR_INTERRUPTS();
2791 : :
2792 : : /*
2793 : : * state->memtupcount is "int", but we use "unsigned int" for i, j, n.
2794 : : * This prevents overflow in the "2 * i + 1" calculation, since at the top
2795 : : * of the loop we must have i < n <= INT_MAX <= UINT_MAX/2.
2796 : : */
9545 tgl@sss.pgh.pa.us 2797 : 3026587 : n = state->memtupcount;
9558 2798 : 3026587 : i = 0; /* i is where the "hole" is */
2799 : : for (;;)
9545 2800 : 888741 : {
3080 2801 : 3915328 : unsigned int j = 2 * i + 1;
2802 : :
9558 2803 [ + + ]: 3915328 : if (j >= n)
2804 : 563398 : break;
9380 bruce@momjian.us 2805 [ + + + + ]: 4584022 : if (j + 1 < n &&
3001 rhaas@postgresql.org 2806 : 1232092 : COMPARETUP(state, &memtuples[j], &memtuples[j + 1]) > 0)
9558 tgl@sss.pgh.pa.us 2807 : 492406 : j++;
3001 rhaas@postgresql.org 2808 [ + + ]: 3351930 : if (COMPARETUP(state, tuple, &memtuples[j]) <= 0)
9558 tgl@sss.pgh.pa.us 2809 : 2463189 : break;
9545 2810 : 888741 : memtuples[i] = memtuples[j];
9558 2811 : 888741 : i = j;
2812 : : }
7234 2813 : 3026587 : memtuples[i] = *tuple;
9558 2814 : 3026587 : }
2815 : :
2816 : : /*
2817 : : * Function to reverse the sort direction from its current state
2818 : : *
2819 : : * It is not safe to call this when performing hash tuplesorts
2820 : : */
2821 : : static void
4058 rhaas@postgresql.org 2822 : 426 : reversedirection(Tuplesortstate *state)
2823 : : {
1239 akorotkov@postgresql 2824 : 426 : SortSupport sortKey = state->base.sortKeys;
2825 : : int nkey;
2826 : :
2827 [ + + ]: 1032 : for (nkey = 0; nkey < state->base.nKeys; nkey++, sortKey++)
2828 : : {
4058 rhaas@postgresql.org 2829 : 606 : sortKey->ssup_reverse = !sortKey->ssup_reverse;
2830 : 606 : sortKey->ssup_nulls_first = !sortKey->ssup_nulls_first;
2831 : : }
2832 : 426 : }
2833 : :
2834 : :
2835 : : /*
2836 : : * Tape interface routines
2837 : : */
2838 : :
2839 : : static unsigned int
1521 heikki.linnakangas@i 2840 : 2912194 : getlen(LogicalTape *tape, bool eofOK)
2841 : : {
2842 : : unsigned int len;
2843 : :
2844 [ - + ]: 2912194 : if (LogicalTapeRead(tape,
2845 : : &len, sizeof(len)) != sizeof(len))
8181 tgl@sss.pgh.pa.us 2846 [ # # ]:UBC 0 : elog(ERROR, "unexpected end of tape");
9558 tgl@sss.pgh.pa.us 2847 [ + + - + ]:CBC 2912194 : if (len == 0 && !eofOK)
8181 tgl@sss.pgh.pa.us 2848 [ # # ]:UBC 0 : elog(ERROR, "unexpected end of data");
9558 tgl@sss.pgh.pa.us 2849 :CBC 2912194 : return len;
2850 : : }
2851 : :
2852 : : static void
1521 heikki.linnakangas@i 2853 : 856 : markrunend(LogicalTape *tape)
2854 : : {
9380 bruce@momjian.us 2855 : 856 : unsigned int len = 0;
2856 : :
1083 peter@eisentraut.org 2857 : 856 : LogicalTapeWrite(tape, &len, sizeof(len));
9558 tgl@sss.pgh.pa.us 2858 : 856 : }
2859 : :
2860 : : /*
2861 : : * Get memory for tuple from within READTUP() routine.
2862 : : *
2863 : : * We use next free slot from the slab allocator, or palloc() if the tuple
2864 : : * is too large for that.
2865 : : */
2866 : : void *
1239 akorotkov@postgresql 2867 : 2706305 : tuplesort_readtup_alloc(Tuplesortstate *state, Size tuplen)
2868 : : {
2869 : : SlabSlot *buf;
2870 : :
2871 : : /*
2872 : : * We pre-allocate enough slots in the slab arena that we should never run
2873 : : * out.
2874 : : */
3362 heikki.linnakangas@i 2875 [ - + ]: 2706305 : Assert(state->slabFreeHead);
2876 : :
2877 [ + - - + ]: 2706305 : if (tuplen > SLAB_SLOT_SIZE || !state->slabFreeHead)
1239 akorotkov@postgresql 2878 :UBC 0 : return MemoryContextAlloc(state->base.sortcontext, tuplen);
2879 : : else
2880 : : {
3362 heikki.linnakangas@i 2881 :CBC 2706305 : buf = state->slabFreeHead;
2882 : : /* Reuse this slot */
2883 : 2706305 : state->slabFreeHead = buf->nextfree;
2884 : :
2885 : 2706305 : return buf;
2886 : : }
2887 : : }
2888 : :
2889 : :
2890 : : /*
2891 : : * Parallel sort routines
2892 : : */
2893 : :
2894 : : /*
2895 : : * tuplesort_estimate_shared - estimate required shared memory allocation
2896 : : *
2897 : : * nWorkers is an estimate of the number of workers (it's the number that
2898 : : * will be requested).
2899 : : */
2900 : : Size
2875 rhaas@postgresql.org 2901 : 82 : tuplesort_estimate_shared(int nWorkers)
2902 : : {
2903 : : Size tapesSize;
2904 : :
2905 [ - + ]: 82 : Assert(nWorkers > 0);
2906 : :
2907 : : /* Make sure that BufFile shared state is MAXALIGN'd */
2908 : 82 : tapesSize = mul_size(sizeof(TapeShare), nWorkers);
2909 : 82 : tapesSize = MAXALIGN(add_size(tapesSize, offsetof(Sharedsort, tapes)));
2910 : :
2911 : 82 : return tapesSize;
2912 : : }
2913 : :
2914 : : /*
2915 : : * tuplesort_initialize_shared - initialize shared tuplesort state
2916 : : *
2917 : : * Must be called from leader process before workers are launched, to
2918 : : * establish state needed up-front for worker tuplesortstates. nWorkers
2919 : : * should match the argument passed to tuplesort_estimate_shared().
2920 : : */
2921 : : void
2922 : 117 : tuplesort_initialize_shared(Sharedsort *shared, int nWorkers, dsm_segment *seg)
2923 : : {
2924 : : int i;
2925 : :
2926 [ - + ]: 117 : Assert(nWorkers > 0);
2927 : :
2928 : 117 : SpinLockInit(&shared->mutex);
2929 : 117 : shared->currentWorker = 0;
2930 : 117 : shared->workersFinished = 0;
2931 : 117 : SharedFileSetInit(&shared->fileset, seg);
2932 : 117 : shared->nTapes = nWorkers;
2933 [ + + ]: 355 : for (i = 0; i < nWorkers; i++)
2934 : : {
2935 : 238 : shared->tapes[i].firstblocknumber = 0L;
2936 : : }
2937 : 117 : }
2938 : :
2939 : : /*
2940 : : * tuplesort_attach_shared - attach to shared tuplesort state
2941 : : *
2942 : : * Must be called by all worker processes.
2943 : : */
2944 : : void
2945 : 118 : tuplesort_attach_shared(Sharedsort *shared, dsm_segment *seg)
2946 : : {
2947 : : /* Attach to SharedFileSet */
2948 : 118 : SharedFileSetAttach(&shared->fileset, seg);
2949 : 118 : }
2950 : :
2951 : : /*
2952 : : * worker_get_identifier - Assign and return ordinal identifier for worker
2953 : : *
2954 : : * The order in which these are assigned is not well defined, and should not
2955 : : * matter; worker numbers across parallel sort participants need only be
2956 : : * distinct and gapless. logtape.c requires this.
2957 : : *
2958 : : * Note that the identifiers assigned from here have no relation to
2959 : : * ParallelWorkerNumber number, to avoid making any assumption about
2960 : : * caller's requirements. However, we do follow the ParallelWorkerNumber
2961 : : * convention of representing a non-worker with worker number -1. This
2962 : : * includes the leader, as well as serial Tuplesort processes.
2963 : : */
2964 : : static int
2965 : 234 : worker_get_identifier(Tuplesortstate *state)
2966 : : {
2967 : 234 : Sharedsort *shared = state->shared;
2968 : : int worker;
2969 : :
2970 [ + - - + ]: 234 : Assert(WORKER(state));
2971 : :
2972 [ - + ]: 234 : SpinLockAcquire(&shared->mutex);
2973 : 234 : worker = shared->currentWorker++;
2974 : 234 : SpinLockRelease(&shared->mutex);
2975 : :
2976 : 234 : return worker;
2977 : : }
2978 : :
2979 : : /*
2980 : : * worker_freeze_result_tape - freeze worker's result tape for leader
2981 : : *
2982 : : * This is called by workers just after the result tape has been determined,
2983 : : * instead of calling LogicalTapeFreeze() directly. They do so because
2984 : : * workers require a few additional steps over similar serial
2985 : : * TSS_SORTEDONTAPE external sort cases, which also happen here. The extra
2986 : : * steps are around freeing now unneeded resources, and representing to
2987 : : * leader that worker's input run is available for its merge.
2988 : : *
2989 : : * There should only be one final output run for each worker, which consists
2990 : : * of all tuples that were originally input into worker.
2991 : : */
2992 : : static void
2993 : 234 : worker_freeze_result_tape(Tuplesortstate *state)
2994 : : {
2995 : 234 : Sharedsort *shared = state->shared;
2996 : : TapeShare output;
2997 : :
2998 [ + - - + ]: 234 : Assert(WORKER(state));
1521 heikki.linnakangas@i 2999 [ - + ]: 234 : Assert(state->result_tape != NULL);
2875 rhaas@postgresql.org 3000 [ - + ]: 234 : Assert(state->memtupcount == 0);
3001 : :
3002 : : /*
3003 : : * Free most remaining memory, in case caller is sensitive to our holding
3004 : : * on to it. memtuples may not be a tiny merge heap at this point.
3005 : : */
3006 : 234 : pfree(state->memtuples);
3007 : : /* Be tidy */
3008 : 234 : state->memtuples = NULL;
3009 : 234 : state->memtupsize = 0;
3010 : :
3011 : : /*
3012 : : * Parallel worker requires result tape metadata, which is to be stored in
3013 : : * shared memory for leader
3014 : : */
1521 heikki.linnakangas@i 3015 : 234 : LogicalTapeFreeze(state->result_tape, &output);
3016 : :
3017 : : /* Store properties of output tape, and update finished worker count */
2875 rhaas@postgresql.org 3018 [ - + ]: 234 : SpinLockAcquire(&shared->mutex);
3019 : 234 : shared->tapes[state->worker] = output;
3020 : 234 : shared->workersFinished++;
3021 : 234 : SpinLockRelease(&shared->mutex);
3022 : 234 : }
3023 : :
3024 : : /*
3025 : : * worker_nomergeruns - dump memtuples in worker, without merging
3026 : : *
3027 : : * This called as an alternative to mergeruns() with a worker when no
3028 : : * merging is required.
3029 : : */
3030 : : static void
3031 : 234 : worker_nomergeruns(Tuplesortstate *state)
3032 : : {
3033 [ + - - + ]: 234 : Assert(WORKER(state));
1521 heikki.linnakangas@i 3034 [ - + ]: 234 : Assert(state->result_tape == NULL);
3035 [ - + ]: 234 : Assert(state->nOutputRuns == 1);
3036 : :
3037 : 234 : state->result_tape = state->destTape;
2875 rhaas@postgresql.org 3038 : 234 : worker_freeze_result_tape(state);
3039 : 234 : }
3040 : :
3041 : : /*
3042 : : * leader_takeover_tapes - create tapeset for leader from worker tapes
3043 : : *
3044 : : * So far, leader Tuplesortstate has performed no actual sorting. By now, all
3045 : : * sorting has occurred in workers, all of which must have already returned
3046 : : * from tuplesort_performsort().
3047 : : *
3048 : : * When this returns, leader process is left in a state that is virtually
3049 : : * indistinguishable from it having generated runs as a serial external sort
3050 : : * might have.
3051 : : */
3052 : : static void
3053 : 81 : leader_takeover_tapes(Tuplesortstate *state)
3054 : : {
3055 : 81 : Sharedsort *shared = state->shared;
3056 : 81 : int nParticipants = state->nParticipants;
3057 : : int workersFinished;
3058 : : int j;
3059 : :
3060 [ + - - + ]: 81 : Assert(LEADER(state));
3061 [ - + ]: 81 : Assert(nParticipants >= 1);
3062 : :
3063 [ - + ]: 81 : SpinLockAcquire(&shared->mutex);
3064 : 81 : workersFinished = shared->workersFinished;
3065 : 81 : SpinLockRelease(&shared->mutex);
3066 : :
3067 [ - + ]: 81 : if (nParticipants != workersFinished)
2875 rhaas@postgresql.org 3068 [ # # ]:UBC 0 : elog(ERROR, "cannot take over tapes before all workers finish");
3069 : :
3070 : : /*
3071 : : * Create the tapeset from worker tapes, including a leader-owned tape at
3072 : : * the end. Parallel workers are far more expensive than logical tapes,
3073 : : * so the number of tapes allocated here should never be excessive.
3074 : : */
1521 heikki.linnakangas@i 3075 :CBC 81 : inittapestate(state, nParticipants);
3076 : 81 : state->tapeset = LogicalTapeSetCreate(false, &shared->fileset, -1);
3077 : :
3078 : : /*
3079 : : * Set currentRun to reflect the number of runs we will merge (it's not
3080 : : * used for anything, this is just pro forma)
3081 : : */
2875 rhaas@postgresql.org 3082 : 81 : state->currentRun = nParticipants;
3083 : :
3084 : : /*
3085 : : * Initialize the state to look the same as after building the initial
3086 : : * runs.
3087 : : *
3088 : : * There will always be exactly 1 run per worker, and exactly one input
3089 : : * tape per run, because workers always output exactly 1 run, even when
3090 : : * there were no input tuples for workers to sort.
3091 : : */
1521 heikki.linnakangas@i 3092 : 81 : state->inputTapes = NULL;
3093 : 81 : state->nInputTapes = 0;
3094 : 81 : state->nInputRuns = 0;
3095 : :
3096 : 81 : state->outputTapes = palloc0(nParticipants * sizeof(LogicalTape *));
3097 : 81 : state->nOutputTapes = nParticipants;
3098 : 81 : state->nOutputRuns = nParticipants;
3099 : :
3100 [ + + ]: 245 : for (j = 0; j < nParticipants; j++)
3101 : : {
3102 : 164 : state->outputTapes[j] = LogicalTapeImport(state->tapeset, j, &shared->tapes[j]);
3103 : : }
3104 : :
2875 rhaas@postgresql.org 3105 : 81 : state->status = TSS_BUILDRUNS;
3106 : 81 : }
3107 : :
3108 : : /*
3109 : : * Convenience routine to free a tuple previously loaded into sort memory
3110 : : */
3111 : : static void
6802 tgl@sss.pgh.pa.us 3112 : 1876817 : free_sort_tuple(Tuplesortstate *state, SortTuple *stup)
3113 : : {
1618 drowley@postgresql.o 3114 [ + + ]: 1876817 : if (stup->tuple)
3115 : : {
3116 : 1799849 : FREEMEM(state, GetMemoryChunkSpace(stup->tuple));
3117 : 1799849 : pfree(stup->tuple);
3118 : 1799849 : stup->tuple = NULL;
3119 : : }
6802 tgl@sss.pgh.pa.us 3120 : 1876817 : }
3121 : :
3122 : : int
1355 john.naylor@postgres 3123 :UBC 0 : ssup_datum_unsigned_cmp(Datum x, Datum y, SortSupport ssup)
3124 : : {
3125 [ # # ]: 0 : if (x < y)
3126 : 0 : return -1;
3127 [ # # ]: 0 : else if (x > y)
3128 : 0 : return 1;
3129 : : else
3130 : 0 : return 0;
3131 : : }
3132 : :
3133 : : int
1355 john.naylor@postgres 3134 :CBC 592165 : ssup_datum_signed_cmp(Datum x, Datum y, SortSupport ssup)
3135 : : {
1316 drowley@postgresql.o 3136 : 592165 : int64 xx = DatumGetInt64(x);
3137 : 592165 : int64 yy = DatumGetInt64(y);
3138 : :
1355 john.naylor@postgres 3139 [ + + ]: 592165 : if (xx < yy)
3140 : 225721 : return -1;
3141 [ + + ]: 366444 : else if (xx > yy)
3142 : 181919 : return 1;
3143 : : else
3144 : 184525 : return 0;
3145 : : }
3146 : :
3147 : : int
3148 : 97764679 : ssup_datum_int32_cmp(Datum x, Datum y, SortSupport ssup)
3149 : : {
1316 drowley@postgresql.o 3150 : 97764679 : int32 xx = DatumGetInt32(x);
3151 : 97764679 : int32 yy = DatumGetInt32(y);
3152 : :
1355 john.naylor@postgres 3153 [ + + ]: 97764679 : if (xx < yy)
3154 : 23598603 : return -1;
3155 [ + + ]: 74166076 : else if (xx > yy)
3156 : 22389583 : return 1;
3157 : : else
3158 : 51776493 : return 0;
3159 : : }
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