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. Large amounts are
11 : : * 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 : : * or radix sort 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 in memory 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 in-memory sorting, 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) 1996-2026, 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 tracks on-disk space,
203 : : * false means in-memory */
204 : : TupSortStatus maxSpaceStatus; /* sort status when maxSpace was reached */
205 : : LogicalTapeSet *tapeset; /* logtape.c object for tapes in a temp file */
206 : :
207 : : /*
208 : : * This array holds the tuples now in sort memory. If we are in state
209 : : * INITIAL, the tuples are in no particular order; if we are in state
210 : : * SORTEDINMEM, the tuples are in final sorted order; in states BUILDRUNS
211 : : * and FINALMERGE, the tuples are organized in "heap" order per Algorithm
212 : : * H. In state SORTEDONTAPE, the array is not used.
213 : : */
214 : : SortTuple *memtuples; /* array of SortTuple structs */
215 : : int memtupcount; /* number of tuples currently present */
216 : : int memtupsize; /* allocated length of memtuples array */
217 : : bool growmemtuples; /* memtuples' growth still underway? */
218 : :
219 : : /*
220 : : * Memory for tuples is sometimes allocated using a simple slab allocator,
221 : : * rather than with palloc(). Currently, we switch to slab allocation
222 : : * when we start merging. Merging only needs to keep a small, fixed
223 : : * number of tuples in memory at any time, so we can avoid the
224 : : * palloc/pfree overhead by recycling a fixed number of fixed-size slots
225 : : * to hold the tuples.
226 : : *
227 : : * For the slab, we use one large allocation, divided into SLAB_SLOT_SIZE
228 : : * slots. The allocation is sized to have one slot per tape, plus one
229 : : * additional slot. We need that many slots to hold all the tuples kept
230 : : * in the heap during merge, plus the one we have last returned from the
231 : : * sort, with tuplesort_gettuple.
232 : : *
233 : : * Initially, all the slots are kept in a linked list of free slots. When
234 : : * a tuple is read from a tape, it is put to the next available slot, if
235 : : * it fits. If the tuple is larger than SLAB_SLOT_SIZE, it is palloc'd
236 : : * instead.
237 : : *
238 : : * When we're done processing a tuple, we return the slot back to the free
239 : : * list, or pfree() if it was palloc'd. We know that a tuple was
240 : : * allocated from the slab, if its pointer value is between
241 : : * slabMemoryBegin and -End.
242 : : *
243 : : * When the slab allocator is used, the USEMEM/LACKMEM mechanism of
244 : : * tracking memory usage is not used.
245 : : */
246 : : bool slabAllocatorUsed;
247 : :
248 : : char *slabMemoryBegin; /* beginning of slab memory arena */
249 : : char *slabMemoryEnd; /* end of slab memory arena */
250 : : SlabSlot *slabFreeHead; /* head of free list */
251 : :
252 : : /* Memory used for input and output tape buffers. */
253 : : size_t tape_buffer_mem;
254 : :
255 : : /*
256 : : * When we return a tuple to the caller in tuplesort_gettuple_XXX, that
257 : : * came from a tape (that is, in TSS_SORTEDONTAPE or TSS_FINALMERGE
258 : : * modes), we remember the tuple in 'lastReturnedTuple', so that we can
259 : : * recycle the memory on next gettuple call.
260 : : */
261 : : void *lastReturnedTuple;
262 : :
263 : : /*
264 : : * While building initial runs, this is the current output run number.
265 : : * Afterwards, it is the number of initial runs we made.
266 : : */
267 : : int currentRun;
268 : :
269 : : /*
270 : : * Logical tapes, for merging.
271 : : *
272 : : * The initial runs are written in the output tapes. In each merge pass,
273 : : * the output tapes of the previous pass become the input tapes, and new
274 : : * output tapes are created as needed. When nInputTapes equals
275 : : * nInputRuns, there is only one merge pass left.
276 : : */
277 : : LogicalTape **inputTapes;
278 : : int nInputTapes;
279 : : int nInputRuns;
280 : :
281 : : LogicalTape **outputTapes;
282 : : int nOutputTapes;
283 : : int nOutputRuns;
284 : :
285 : : LogicalTape *destTape; /* current output tape */
286 : :
287 : : /*
288 : : * These variables are used after completion of sorting to keep track of
289 : : * the next tuple to return. (In the tape case, the tape's current read
290 : : * position is also critical state.)
291 : : */
292 : : LogicalTape *result_tape; /* actual tape of finished output */
293 : : int current; /* array index (only used if SORTEDINMEM) */
294 : : bool eof_reached; /* reached EOF (needed for cursors) */
295 : :
296 : : /* markpos_xxx holds marked position for mark and restore */
297 : : int64 markpos_block; /* tape block# (only used if SORTEDONTAPE) */
298 : : int markpos_offset; /* saved "current", or offset in tape block */
299 : : bool markpos_eof; /* saved "eof_reached" */
300 : :
301 : : /*
302 : : * These variables are used during parallel sorting.
303 : : *
304 : : * worker is our worker identifier. Follows the general convention that
305 : : * -1 value relates to a leader tuplesort, and values >= 0 worker
306 : : * tuplesorts. (-1 can also be a serial tuplesort.)
307 : : *
308 : : * shared is mutable shared memory state, which is used to coordinate
309 : : * parallel sorts.
310 : : *
311 : : * nParticipants is the number of worker Tuplesortstates known by the
312 : : * leader to have actually been launched, which implies that they must
313 : : * finish a run that the leader needs to merge. Typically includes a
314 : : * worker state held by the leader process itself. Set in the leader
315 : : * Tuplesortstate only.
316 : : */
317 : : int worker;
318 : : Sharedsort *shared;
319 : : int nParticipants;
320 : :
321 : : /*
322 : : * Additional state for managing "abbreviated key" sortsupport routines
323 : : * (which currently may be used by all cases except the hash index case).
324 : : * Tracks the intervals at which the optimization's effectiveness is
325 : : * tested.
326 : : */
327 : : int64 abbrevNext; /* Tuple # at which to next check
328 : : * applicability */
329 : :
330 : : /*
331 : : * Resource snapshot for time of sort start.
332 : : */
333 : : PGRUsage ru_start;
334 : : };
335 : :
336 : : /*
337 : : * Private mutable state of tuplesort-parallel-operation. This is allocated
338 : : * in shared memory.
339 : : */
340 : : struct Sharedsort
341 : : {
342 : : /* mutex protects all fields prior to tapes */
343 : : slock_t mutex;
344 : :
345 : : /*
346 : : * currentWorker generates ordinal identifier numbers for parallel sort
347 : : * workers. These start from 0, and are always gapless.
348 : : *
349 : : * Workers increment workersFinished to indicate having finished. If this
350 : : * is equal to state.nParticipants within the leader, leader is ready to
351 : : * merge worker runs.
352 : : */
353 : : int currentWorker;
354 : : int workersFinished;
355 : :
356 : : /* Temporary file space */
357 : : SharedFileSet fileset;
358 : :
359 : : /* Size of tapes flexible array */
360 : : int nTapes;
361 : :
362 : : /*
363 : : * Tapes array used by workers to report back information needed by the
364 : : * leader to concatenate all worker tapes into one for merging
365 : : */
366 : : TapeShare tapes[FLEXIBLE_ARRAY_MEMBER];
367 : : };
368 : :
369 : : /*
370 : : * Is the given tuple allocated from the slab memory arena?
371 : : */
372 : : #define IS_SLAB_SLOT(state, tuple) \
373 : : ((char *) (tuple) >= (state)->slabMemoryBegin && \
374 : : (char *) (tuple) < (state)->slabMemoryEnd)
375 : :
376 : : /*
377 : : * Return the given tuple to the slab memory free list, or free it
378 : : * if it was palloc'd.
379 : : */
380 : : #define RELEASE_SLAB_SLOT(state, tuple) \
381 : : do { \
382 : : SlabSlot *buf = (SlabSlot *) tuple; \
383 : : \
384 : : if (IS_SLAB_SLOT((state), buf)) \
385 : : { \
386 : : buf->nextfree = (state)->slabFreeHead; \
387 : : (state)->slabFreeHead = buf; \
388 : : } else \
389 : : pfree(buf); \
390 : : } while(0)
391 : :
392 : : #define REMOVEABBREV(state,stup,count) ((*(state)->base.removeabbrev) (state, stup, count))
393 : : #define COMPARETUP(state,a,b) ((*(state)->base.comparetup) (a, b, state))
394 : : #define WRITETUP(state,tape,stup) ((*(state)->base.writetup) (state, tape, stup))
395 : : #define READTUP(state,stup,tape,len) ((*(state)->base.readtup) (state, stup, tape, len))
396 : : #define FREESTATE(state) ((state)->base.freestate ? (*(state)->base.freestate) (state) : (void) 0)
397 : : #define LACKMEM(state) ((state)->availMem < 0 && !(state)->slabAllocatorUsed)
398 : : #define USEMEM(state,amt) ((state)->availMem -= (amt))
399 : : #define FREEMEM(state,amt) ((state)->availMem += (amt))
400 : : #define SERIAL(state) ((state)->shared == NULL)
401 : : #define WORKER(state) ((state)->shared && (state)->worker != -1)
402 : : #define LEADER(state) ((state)->shared && (state)->worker == -1)
403 : :
404 : : /*
405 : : * NOTES about on-tape representation of tuples:
406 : : *
407 : : * We require the first "unsigned int" of a stored tuple to be the total size
408 : : * on-tape of the tuple, including itself (so it is never zero; an all-zero
409 : : * unsigned int is used to delimit runs). The remainder of the stored tuple
410 : : * may or may not match the in-memory representation of the tuple ---
411 : : * any conversion needed is the job of the writetup and readtup routines.
412 : : *
413 : : * If state->sortopt contains TUPLESORT_RANDOMACCESS, then the stored
414 : : * representation of the tuple must be followed by another "unsigned int" that
415 : : * is a copy of the length --- so the total tape space used is actually
416 : : * sizeof(unsigned int) more than the stored length value. This allows
417 : : * read-backwards. When the random access flag was not specified, the
418 : : * write/read routines may omit the extra length word.
419 : : *
420 : : * writetup is expected to write both length words as well as the tuple
421 : : * data. When readtup is called, the tape is positioned just after the
422 : : * front length word; readtup must read the tuple data and advance past
423 : : * the back length word (if present).
424 : : *
425 : : * The write/read routines can make use of the tuple description data
426 : : * stored in the Tuplesortstate record, if needed. They are also expected
427 : : * to adjust state->availMem by the amount of memory space (not tape space!)
428 : : * released or consumed. There is no error return from either writetup
429 : : * or readtup; they should ereport() on failure.
430 : : *
431 : : *
432 : : * NOTES about memory consumption calculations:
433 : : *
434 : : * We count space allocated for tuples against the workMem limit, plus
435 : : * the space used by the variable-size memtuples array. Fixed-size space
436 : : * is not counted; it's small enough to not be interesting.
437 : : *
438 : : * Note that we count actual space used (as shown by GetMemoryChunkSpace)
439 : : * rather than the originally-requested size. This is important since
440 : : * palloc can add substantial overhead. It's not a complete answer since
441 : : * we won't count any wasted space in palloc allocation blocks, but it's
442 : : * a lot better than what we were doing before 7.3. As of 9.6, a
443 : : * separate memory context is used for caller passed tuples. Resetting
444 : : * it at certain key increments significantly ameliorates fragmentation.
445 : : * readtup routines use the slab allocator (they cannot use
446 : : * the reset context because it gets deleted at the point that merging
447 : : * begins).
448 : : */
449 : :
450 : :
451 : : static void tuplesort_begin_batch(Tuplesortstate *state);
452 : : static bool consider_abort_common(Tuplesortstate *state);
453 : : static void inittapes(Tuplesortstate *state, bool mergeruns);
454 : : static void inittapestate(Tuplesortstate *state, int maxTapes);
455 : : static void selectnewtape(Tuplesortstate *state);
456 : : static void init_slab_allocator(Tuplesortstate *state, int numSlots);
457 : : static void mergeruns(Tuplesortstate *state);
458 : : static void mergeonerun(Tuplesortstate *state);
459 : : static void beginmerge(Tuplesortstate *state);
460 : : static bool mergereadnext(Tuplesortstate *state, LogicalTape *srcTape, SortTuple *stup);
461 : : static void dumptuples(Tuplesortstate *state, bool alltuples);
462 : : static void make_bounded_heap(Tuplesortstate *state);
463 : : static void sort_bounded_heap(Tuplesortstate *state);
464 : : static void tuplesort_sort_memtuples(Tuplesortstate *state);
465 : : static void tuplesort_heap_insert(Tuplesortstate *state, SortTuple *tuple);
466 : : static void tuplesort_heap_replace_top(Tuplesortstate *state, SortTuple *tuple);
467 : : static void tuplesort_heap_delete_top(Tuplesortstate *state);
468 : : static void reversedirection(Tuplesortstate *state);
469 : : static unsigned int getlen(LogicalTape *tape, bool eofOK);
470 : : static void markrunend(LogicalTape *tape);
471 : : static int worker_get_identifier(Tuplesortstate *state);
472 : : static void worker_freeze_result_tape(Tuplesortstate *state);
473 : : static void worker_nomergeruns(Tuplesortstate *state);
474 : : static void leader_takeover_tapes(Tuplesortstate *state);
475 : : static void free_sort_tuple(Tuplesortstate *state, SortTuple *stup);
476 : : static void tuplesort_free(Tuplesortstate *state);
477 : : static void tuplesort_updatemax(Tuplesortstate *state);
478 : :
479 : :
480 : : /*
481 : : * Special versions of qsort just for SortTuple objects. qsort_tuple() sorts
482 : : * any variant of SortTuples, using the appropriate comparetup function.
483 : : * qsort_ssup() is specialized for the case where the comparetup function
484 : : * reduces to ApplySortComparator(), that is single-key MinimalTuple sorts
485 : : * and Datum sorts.
486 : : */
487 : :
488 : : #define ST_SORT qsort_tuple
489 : : #define ST_ELEMENT_TYPE SortTuple
490 : : #define ST_COMPARE_RUNTIME_POINTER
491 : : #define ST_COMPARE_ARG_TYPE Tuplesortstate
492 : : #define ST_CHECK_FOR_INTERRUPTS
493 : : #define ST_SCOPE static
494 : : #define ST_DECLARE
495 : : #define ST_DEFINE
496 : : #include "lib/sort_template.h"
497 : :
498 : : #define ST_SORT qsort_ssup
499 : : #define ST_ELEMENT_TYPE SortTuple
500 : : #define ST_COMPARE(a, b, ssup) \
501 : : ApplySortComparator((a)->datum1, (a)->isnull1, \
502 : : (b)->datum1, (b)->isnull1, (ssup))
503 : : #define ST_COMPARE_ARG_TYPE SortSupportData
504 : : #define ST_CHECK_FOR_INTERRUPTS
505 : : #define ST_SCOPE static
506 : : #define ST_DEFINE
507 : : #include "lib/sort_template.h"
508 : :
509 : : /* state for radix sort */
510 : : typedef struct RadixSortInfo
511 : : {
512 : : union
513 : : {
514 : : size_t count;
515 : : size_t offset;
516 : : };
517 : : size_t next_offset;
518 : : } RadixSortInfo;
519 : :
520 : : /*
521 : : * Threshold below which qsort_tuple() is generally faster than a radix sort.
522 : : */
523 : : #define QSORT_THRESHOLD 40
524 : :
525 : :
526 : : /*
527 : : * tuplesort_begin_xxx
528 : : *
529 : : * Initialize for a tuple sort operation.
530 : : *
531 : : * After calling tuplesort_begin, the caller should call tuplesort_putXXX
532 : : * zero or more times, then call tuplesort_performsort when all the tuples
533 : : * have been supplied. After performsort, retrieve the tuples in sorted
534 : : * order by calling tuplesort_getXXX until it returns false/NULL. (If random
535 : : * access was requested, rescan, markpos, and restorepos can also be called.)
536 : : * Call tuplesort_end to terminate the operation and release memory/disk space.
537 : : *
538 : : * Each variant of tuplesort_begin has a workMem parameter specifying the
539 : : * maximum number of kilobytes of RAM to use before spilling data to disk.
540 : : * (The normal value of this parameter is work_mem, but some callers use
541 : : * other values.) Each variant also has a sortopt which is a bitmask of
542 : : * sort options. See TUPLESORT_* definitions in tuplesort.h
543 : : */
544 : :
545 : : Tuplesortstate *
1441 drowley@postgresql.o 546 :CBC 142805 : tuplesort_begin_common(int workMem, SortCoordinate coordinate, int sortopt)
547 : : {
548 : : Tuplesortstate *state;
549 : : MemoryContext maincontext;
550 : : MemoryContext sortcontext;
551 : : MemoryContext oldcontext;
552 : :
553 : : /* See leader_takeover_tapes() remarks on random access support */
554 [ + + - + ]: 142805 : if (coordinate && (sortopt & TUPLESORT_RANDOMACCESS))
2963 rhaas@postgresql.org 555 [ # # ]:UBC 0 : elog(ERROR, "random access disallowed under parallel sort");
556 : :
557 : : /*
558 : : * Memory context surviving tuplesort_reset. This memory context holds
559 : : * data which is useful to keep while sorting multiple similar batches.
560 : : */
2169 tomas.vondra@postgre 561 :CBC 142805 : maincontext = AllocSetContextCreate(CurrentMemoryContext,
562 : : "TupleSort main",
563 : : ALLOCSET_DEFAULT_SIZES);
564 : :
565 : : /*
566 : : * Create a working memory context for one sort operation. The content of
567 : : * this context is deleted by tuplesort_reset.
568 : : */
569 : 142805 : sortcontext = AllocSetContextCreate(maincontext,
570 : : "TupleSort sort",
571 : : ALLOCSET_DEFAULT_SIZES);
572 : :
573 : : /*
574 : : * Additionally a working memory context for tuples is setup in
575 : : * tuplesort_begin_batch.
576 : : */
577 : :
578 : : /*
579 : : * Make the Tuplesortstate within the per-sortstate context. This way, we
580 : : * don't need a separate pfree() operation for it at shutdown.
581 : : */
582 : 142805 : oldcontext = MemoryContextSwitchTo(maincontext);
583 : :
95 michael@paquier.xyz 584 :GNC 142805 : state = palloc0_object(Tuplesortstate);
585 : :
7468 tgl@sss.pgh.pa.us 586 [ - + ]:CBC 142805 : if (trace_sort)
7468 tgl@sss.pgh.pa.us 587 :UBC 0 : pg_rusage_init(&state->ru_start);
588 : :
1327 akorotkov@postgresql 589 :CBC 142805 : state->base.sortopt = sortopt;
590 : 142805 : state->base.tuples = true;
591 : 142805 : state->abbrevNext = 10;
592 : :
593 : : /*
594 : : * workMem is forced to be at least 64KB, the current minimum valid value
595 : : * for the work_mem GUC. This is a defense against parallel sort callers
596 : : * that divide out memory among many workers in a way that leaves each
597 : : * with very little memory.
598 : : */
2963 rhaas@postgresql.org 599 : 142805 : state->allowedMem = Max(workMem, 64) * (int64) 1024;
1327 akorotkov@postgresql 600 : 142805 : state->base.sortcontext = sortcontext;
601 : 142805 : state->base.maincontext = maincontext;
602 : :
2169 tomas.vondra@postgre 603 : 142805 : state->memtupsize = INITIAL_MEMTUPSIZE;
604 : 142805 : state->memtuples = NULL;
605 : :
606 : : /*
607 : : * After all of the other non-parallel-related state, we setup all of the
608 : : * state needed for each batch.
609 : : */
610 : 142805 : tuplesort_begin_batch(state);
611 : :
612 : : /*
613 : : * Initialize parallel-related state based on coordination information
614 : : * from caller
615 : : */
2963 rhaas@postgresql.org 616 [ + + ]: 142805 : if (!coordinate)
617 : : {
618 : : /* Serial sort */
619 : 142379 : state->shared = NULL;
620 : 142379 : state->worker = -1;
621 : 142379 : state->nParticipants = -1;
622 : : }
623 [ + + ]: 426 : else if (coordinate->isWorker)
624 : : {
625 : : /* Parallel worker produces exactly one final run from all input */
626 : 290 : state->shared = coordinate->sharedsort;
627 : 290 : state->worker = worker_get_identifier(state);
628 : 290 : state->nParticipants = -1;
629 : : }
630 : : else
631 : : {
632 : : /* Parallel leader state only used for final merge */
633 : 136 : state->shared = coordinate->sharedsort;
634 : 136 : state->worker = -1;
635 : 136 : state->nParticipants = coordinate->nParticipants;
636 [ - + ]: 136 : Assert(state->nParticipants >= 1);
637 : : }
638 : :
7322 tgl@sss.pgh.pa.us 639 : 142805 : MemoryContextSwitchTo(oldcontext);
640 : :
9646 641 : 142805 : return state;
642 : : }
643 : :
644 : : /*
645 : : * tuplesort_begin_batch
646 : : *
647 : : * Setup, or reset, all state need for processing a new set of tuples with this
648 : : * sort state. Called both from tuplesort_begin_common (the first time sorting
649 : : * with this sort state) and tuplesort_reset (for subsequent usages).
650 : : */
651 : : static void
2169 tomas.vondra@postgre 652 : 144399 : tuplesort_begin_batch(Tuplesortstate *state)
653 : : {
654 : : MemoryContext oldcontext;
655 : :
1327 akorotkov@postgresql 656 : 144399 : oldcontext = MemoryContextSwitchTo(state->base.maincontext);
657 : :
658 : : /*
659 : : * Caller tuple (e.g. IndexTuple) memory context.
660 : : *
661 : : * A dedicated child context used exclusively for caller passed tuples
662 : : * eases memory management. Resetting at key points reduces
663 : : * fragmentation. Note that the memtuples array of SortTuples is allocated
664 : : * in the parent context, not this context, because there is no need to
665 : : * free memtuples early. For bounded sorts, tuples may be pfreed in any
666 : : * order, so we use a regular aset.c context so that it can make use of
667 : : * free'd memory. When the sort is not bounded, we make use of a bump.c
668 : : * context as this keeps allocations more compact with less wastage.
669 : : * Allocations are also slightly more CPU efficient.
670 : : */
706 drowley@postgresql.o 671 [ + + ]: 144399 : if (TupleSortUseBumpTupleCxt(state->base.sortopt))
672 : 143707 : state->base.tuplecontext = BumpContextCreate(state->base.sortcontext,
673 : : "Caller tuples",
674 : : ALLOCSET_DEFAULT_SIZES);
675 : : else
1327 akorotkov@postgresql 676 : 692 : state->base.tuplecontext = AllocSetContextCreate(state->base.sortcontext,
677 : : "Caller tuples",
678 : : ALLOCSET_DEFAULT_SIZES);
679 : :
680 : :
2169 tomas.vondra@postgre 681 : 144399 : state->status = TSS_INITIAL;
682 : 144399 : state->bounded = false;
683 : 144399 : state->boundUsed = false;
684 : :
685 : 144399 : state->availMem = state->allowedMem;
686 : :
687 : 144399 : state->tapeset = NULL;
688 : :
689 : 144399 : state->memtupcount = 0;
690 : :
691 : 144399 : state->growmemtuples = true;
692 : 144399 : state->slabAllocatorUsed = false;
693 [ + + + + ]: 144399 : if (state->memtuples != NULL && state->memtupsize != INITIAL_MEMTUPSIZE)
694 : : {
2169 tomas.vondra@postgre 695 :GBC 36 : pfree(state->memtuples);
696 : 36 : state->memtuples = NULL;
697 : 36 : state->memtupsize = INITIAL_MEMTUPSIZE;
698 : : }
2169 tomas.vondra@postgre 699 [ + + ]:CBC 144399 : if (state->memtuples == NULL)
700 : : {
701 : 142841 : state->memtuples = (SortTuple *) palloc(state->memtupsize * sizeof(SortTuple));
702 : 142841 : USEMEM(state, GetMemoryChunkSpace(state->memtuples));
703 : : }
704 : :
705 : : /* workMem must be large enough for the minimal memtuples array */
706 [ - + - - ]: 144399 : if (LACKMEM(state))
2169 tomas.vondra@postgre 707 [ # # ]:UBC 0 : elog(ERROR, "insufficient memory allowed for sort");
708 : :
2169 tomas.vondra@postgre 709 :CBC 144399 : state->currentRun = 0;
710 : :
711 : : /*
712 : : * Tape variables (inputTapes, outputTapes, etc.) will be initialized by
713 : : * inittapes(), if needed.
714 : : */
715 : :
1609 heikki.linnakangas@i 716 : 144399 : state->result_tape = NULL; /* flag that result tape has not been formed */
717 : :
2169 tomas.vondra@postgre 718 : 144399 : MemoryContextSwitchTo(oldcontext);
719 : 144399 : }
720 : :
721 : : /*
722 : : * tuplesort_set_bound
723 : : *
724 : : * Advise tuplesort that at most the first N result tuples are required.
725 : : *
726 : : * Must be called before inserting any tuples. (Actually, we could allow it
727 : : * as long as the sort hasn't spilled to disk, but there seems no need for
728 : : * delayed calls at the moment.)
729 : : *
730 : : * This is a hint only. The tuplesort may still return more tuples than
731 : : * requested. Parallel leader tuplesorts will always ignore the hint.
732 : : */
733 : : void
6890 tgl@sss.pgh.pa.us 734 : 625 : tuplesort_set_bound(Tuplesortstate *state, int64 bound)
735 : : {
736 : : /* Assert we're called before loading any tuples */
2376 alvherre@alvh.no-ip. 737 [ + - - + ]: 625 : Assert(state->status == TSS_INITIAL && state->memtupcount == 0);
738 : : /* Assert we allow bounded sorts */
1327 akorotkov@postgresql 739 [ - + ]: 625 : Assert(state->base.sortopt & TUPLESORT_ALLOWBOUNDED);
740 : : /* Can't set the bound twice, either */
6890 tgl@sss.pgh.pa.us 741 [ - + ]: 625 : Assert(!state->bounded);
742 : : /* Also, this shouldn't be called in a parallel worker */
2963 rhaas@postgresql.org 743 [ - + - - ]: 625 : Assert(!WORKER(state));
744 : :
745 : : /* Parallel leader allows but ignores hint */
2375 tgl@sss.pgh.pa.us 746 [ - + - - ]: 625 : if (LEADER(state))
2375 tgl@sss.pgh.pa.us 747 :UBC 0 : return;
748 : :
749 : : #ifdef DEBUG_BOUNDED_SORT
750 : : /* Honor GUC setting that disables the feature (for easy testing) */
751 : : if (!optimize_bounded_sort)
752 : : return;
753 : : #endif
754 : :
755 : : /* We want to be able to compute bound * 2, so limit the setting */
6695 bruce@momjian.us 756 [ - + ]:CBC 625 : if (bound > (int64) (INT_MAX / 2))
6890 tgl@sss.pgh.pa.us 757 :UBC 0 : return;
758 : :
6890 tgl@sss.pgh.pa.us 759 :CBC 625 : state->bounded = true;
760 : 625 : state->bound = (int) bound;
761 : :
762 : : /*
763 : : * Bounded sorts are not an effective target for abbreviated key
764 : : * optimization. Disable by setting state to be consistent with no
765 : : * abbreviation support.
766 : : */
1327 akorotkov@postgresql 767 : 625 : state->base.sortKeys->abbrev_converter = NULL;
768 [ + + ]: 625 : if (state->base.sortKeys->abbrev_full_comparator)
769 : 8 : state->base.sortKeys->comparator = state->base.sortKeys->abbrev_full_comparator;
770 : :
771 : : /* Not strictly necessary, but be tidy */
772 : 625 : state->base.sortKeys->abbrev_abort = NULL;
773 : 625 : state->base.sortKeys->abbrev_full_comparator = NULL;
774 : : }
775 : :
776 : : /*
777 : : * tuplesort_used_bound
778 : : *
779 : : * Allow callers to find out if the sort state was able to use a bound.
780 : : */
781 : : bool
2169 tomas.vondra@postgre 782 : 190 : tuplesort_used_bound(Tuplesortstate *state)
783 : : {
784 : 190 : return state->boundUsed;
785 : : }
786 : :
787 : : /*
788 : : * tuplesort_free
789 : : *
790 : : * Internal routine for freeing resources of tuplesort.
791 : : */
792 : : static void
793 : 144267 : tuplesort_free(Tuplesortstate *state)
794 : : {
795 : : /* context swap probably not needed, but let's be safe */
1327 akorotkov@postgresql 796 : 144267 : MemoryContext oldcontext = MemoryContextSwitchTo(state->base.sortcontext);
797 : : int64 spaceUsed;
798 : :
9646 tgl@sss.pgh.pa.us 799 [ + + ]: 144267 : if (state->tapeset)
7453 800 : 459 : spaceUsed = LogicalTapeSetBlocks(state->tapeset);
801 : : else
802 : 143808 : spaceUsed = (state->allowedMem - state->availMem + 1023) / 1024;
803 : :
804 : : /*
805 : : * Delete temporary "tape" files, if any.
806 : : *
807 : : * We don't bother to destroy the individual tapes here. They will go away
808 : : * with the sortcontext. (In TSS_FINALMERGE state, we have closed
809 : : * finished tapes already.)
810 : : */
7322 811 [ + + ]: 144267 : if (state->tapeset)
812 : 459 : LogicalTapeSetClose(state->tapeset);
813 : :
7468 814 [ - + ]: 144267 : if (trace_sort)
815 : : {
7453 tgl@sss.pgh.pa.us 816 [ # # ]:UBC 0 : if (state->tapeset)
351 peter@eisentraut.org 817 [ # # # # ]: 0 : elog(LOG, "%s of worker %d ended, %" PRId64 " disk blocks used: %s",
818 : : SERIAL(state) ? "external sort" : "parallel external sort",
819 : : state->worker, spaceUsed, pg_rusage_show(&state->ru_start));
820 : : else
821 [ # # # # ]: 0 : elog(LOG, "%s of worker %d ended, %" PRId64 " KB used: %s",
822 : : SERIAL(state) ? "internal sort" : "unperformed parallel sort",
823 : : state->worker, spaceUsed, pg_rusage_show(&state->ru_start));
824 : : }
825 : :
826 : : TRACE_POSTGRESQL_SORT_DONE(state->tapeset != NULL, spaceUsed);
827 : :
1327 akorotkov@postgresql 828 [ + + ]:CBC 144267 : FREESTATE(state);
7322 tgl@sss.pgh.pa.us 829 : 144267 : MemoryContextSwitchTo(oldcontext);
830 : :
831 : : /*
832 : : * Free the per-sort memory context, thereby releasing all working memory.
833 : : */
1327 akorotkov@postgresql 834 : 144267 : MemoryContextReset(state->base.sortcontext);
2169 tomas.vondra@postgre 835 : 144267 : }
836 : :
837 : : /*
838 : : * tuplesort_end
839 : : *
840 : : * Release resources and clean up.
841 : : *
842 : : * NOTE: after calling this, any pointers returned by tuplesort_getXXX are
843 : : * pointing to garbage. Be careful not to attempt to use or free such
844 : : * pointers afterwards!
845 : : */
846 : : void
847 : 142673 : tuplesort_end(Tuplesortstate *state)
848 : : {
849 : 142673 : tuplesort_free(state);
850 : :
851 : : /*
852 : : * Free the main memory context, including the Tuplesortstate struct
853 : : * itself.
854 : : */
1327 akorotkov@postgresql 855 : 142673 : MemoryContextDelete(state->base.maincontext);
2169 tomas.vondra@postgre 856 : 142673 : }
857 : :
858 : : /*
859 : : * tuplesort_updatemax
860 : : *
861 : : * Update maximum resource usage statistics.
862 : : */
863 : : static void
864 : 1792 : tuplesort_updatemax(Tuplesortstate *state)
865 : : {
866 : : int64 spaceUsed;
867 : : bool isSpaceDisk;
868 : :
869 : : /*
870 : : * Note: it might seem we should provide both memory and disk usage for a
871 : : * disk-based sort. However, the current code doesn't track memory space
872 : : * accurately once we have begun to return tuples to the caller (since we
873 : : * don't account for pfree's the caller is expected to do), so we cannot
874 : : * rely on availMem in a disk sort. This does not seem worth the overhead
875 : : * to fix. Is it worth creating an API for the memory context code to
876 : : * tell us how much is actually used in sortcontext?
877 : : */
878 [ + + ]: 1792 : if (state->tapeset)
879 : : {
880 : 3 : isSpaceDisk = true;
881 : 3 : spaceUsed = LogicalTapeSetBlocks(state->tapeset) * BLCKSZ;
882 : : }
883 : : else
884 : : {
885 : 1789 : isSpaceDisk = false;
886 : 1789 : spaceUsed = state->allowedMem - state->availMem;
887 : : }
888 : :
889 : : /*
890 : : * Sort evicts data to the disk when it wasn't able to fit that data into
891 : : * main memory. This is why we assume space used on the disk to be more
892 : : * important for tracking resource usage than space used in memory. Note
893 : : * that the amount of space occupied by some tupleset on the disk might be
894 : : * less than amount of space occupied by the same tupleset in memory due
895 : : * to more compact representation.
896 : : */
897 [ + + - + ]: 1792 : if ((isSpaceDisk && !state->isMaxSpaceDisk) ||
898 [ + - + + ]: 1789 : (isSpaceDisk == state->isMaxSpaceDisk && spaceUsed > state->maxSpace))
899 : : {
900 : 252 : state->maxSpace = spaceUsed;
901 : 252 : state->isMaxSpaceDisk = isSpaceDisk;
902 : 252 : state->maxSpaceStatus = state->status;
903 : : }
904 : 1792 : }
905 : :
906 : : /*
907 : : * tuplesort_reset
908 : : *
909 : : * Reset the tuplesort. Reset all the data in the tuplesort, but leave the
910 : : * meta-information in. After tuplesort_reset, tuplesort is ready to start
911 : : * a new sort. This allows avoiding recreation of tuple sort states (and
912 : : * save resources) when sorting multiple small batches.
913 : : */
914 : : void
915 : 1594 : tuplesort_reset(Tuplesortstate *state)
916 : : {
917 : 1594 : tuplesort_updatemax(state);
918 : 1594 : tuplesort_free(state);
919 : :
920 : : /*
921 : : * After we've freed up per-batch memory, re-setup all of the state common
922 : : * to both the first batch and any subsequent batch.
923 : : */
924 : 1594 : tuplesort_begin_batch(state);
925 : :
926 : 1594 : state->lastReturnedTuple = NULL;
927 : 1594 : state->slabMemoryBegin = NULL;
928 : 1594 : state->slabMemoryEnd = NULL;
929 : 1594 : state->slabFreeHead = NULL;
7322 tgl@sss.pgh.pa.us 930 : 1594 : }
931 : :
932 : : /*
933 : : * Grow the memtuples[] array, if possible within our memory constraint. We
934 : : * must not exceed INT_MAX tuples in memory or the caller-provided memory
935 : : * limit. Return true if we were able to enlarge the array, false if not.
936 : : *
937 : : * Normally, at each increment we double the size of the array. When doing
938 : : * that would exceed a limit, we attempt one last, smaller increase (and then
939 : : * clear the growmemtuples flag so we don't try any more). That allows us to
940 : : * use memory as fully as permitted; sticking to the pure doubling rule could
941 : : * result in almost half going unused. Because availMem moves around with
942 : : * tuple addition/removal, we need some rule to prevent making repeated small
943 : : * increases in memtupsize, which would just be useless thrashing. The
944 : : * growmemtuples flag accomplishes that and also prevents useless
945 : : * recalculations in this function.
946 : : */
947 : : static bool
948 : 4591 : grow_memtuples(Tuplesortstate *state)
949 : : {
950 : : int newmemtupsize;
4805 951 : 4591 : int memtupsize = state->memtupsize;
4637 noah@leadboat.com 952 : 4591 : int64 memNowUsed = state->allowedMem - state->availMem;
953 : :
954 : : /* Forget it if we've already maxed out memtuples, per comment above */
4805 tgl@sss.pgh.pa.us 955 [ + + ]: 4591 : if (!state->growmemtuples)
956 : 70 : return false;
957 : :
958 : : /* Select new value of memtupsize */
959 [ + + ]: 4521 : if (memNowUsed <= state->availMem)
960 : : {
961 : : /*
962 : : * We've used no more than half of allowedMem; double our usage,
963 : : * clamping at INT_MAX tuples.
964 : : */
4644 noah@leadboat.com 965 [ + - ]: 4449 : if (memtupsize < INT_MAX / 2)
966 : 4449 : newmemtupsize = memtupsize * 2;
967 : : else
968 : : {
4644 noah@leadboat.com 969 :UBC 0 : newmemtupsize = INT_MAX;
970 : 0 : state->growmemtuples = false;
971 : : }
972 : : }
973 : : else
974 : : {
975 : : /*
976 : : * This will be the last increment of memtupsize. Abandon doubling
977 : : * strategy and instead increase as much as we safely can.
978 : : *
979 : : * To stay within allowedMem, we can't increase memtupsize by more
980 : : * than availMem / sizeof(SortTuple) elements. In practice, we want
981 : : * to increase it by considerably less, because we need to leave some
982 : : * space for the tuples to which the new array slots will refer. We
983 : : * assume the new tuples will be about the same size as the tuples
984 : : * we've already seen, and thus we can extrapolate from the space
985 : : * consumption so far to estimate an appropriate new size for the
986 : : * memtuples array. The optimal value might be higher or lower than
987 : : * this estimate, but it's hard to know that in advance. We again
988 : : * clamp at INT_MAX tuples.
989 : : *
990 : : * This calculation is safe against enlarging the array so much that
991 : : * LACKMEM becomes true, because the memory currently used includes
992 : : * the present array; thus, there would be enough allowedMem for the
993 : : * new array elements even if no other memory were currently used.
994 : : *
995 : : * We do the arithmetic in float8, because otherwise the product of
996 : : * memtupsize and allowedMem could overflow. Any inaccuracy in the
997 : : * result should be insignificant; but even if we computed a
998 : : * completely insane result, the checks below will prevent anything
999 : : * really bad from happening.
1000 : : */
1001 : : double grow_ratio;
1002 : :
4805 tgl@sss.pgh.pa.us 1003 :CBC 72 : grow_ratio = (double) state->allowedMem / (double) memNowUsed;
4644 noah@leadboat.com 1004 [ + - ]: 72 : if (memtupsize * grow_ratio < INT_MAX)
1005 : 72 : newmemtupsize = (int) (memtupsize * grow_ratio);
1006 : : else
4644 noah@leadboat.com 1007 :UBC 0 : newmemtupsize = INT_MAX;
1008 : :
1009 : : /* We won't make any further enlargement attempts */
4805 tgl@sss.pgh.pa.us 1010 :CBC 72 : state->growmemtuples = false;
1011 : : }
1012 : :
1013 : : /* Must enlarge array by at least one element, else report failure */
1014 [ - + ]: 4521 : if (newmemtupsize <= memtupsize)
4805 tgl@sss.pgh.pa.us 1015 :UBC 0 : goto noalloc;
1016 : :
1017 : : /*
1018 : : * On a 32-bit machine, allowedMem could exceed MaxAllocHugeSize. Clamp
1019 : : * to ensure our request won't be rejected. Note that we can easily
1020 : : * exhaust address space before facing this outcome. (This is presently
1021 : : * impossible due to guc.c's MAX_KILOBYTES limitation on work_mem, but
1022 : : * don't rely on that at this distance.)
1023 : : */
4644 noah@leadboat.com 1024 [ - + ]:CBC 4521 : if ((Size) newmemtupsize >= MaxAllocHugeSize / sizeof(SortTuple))
1025 : : {
4644 noah@leadboat.com 1026 :UBC 0 : newmemtupsize = (int) (MaxAllocHugeSize / sizeof(SortTuple));
4805 tgl@sss.pgh.pa.us 1027 : 0 : state->growmemtuples = false; /* can't grow any more */
1028 : : }
1029 : :
1030 : : /*
1031 : : * We need to be sure that we do not cause LACKMEM to become true, else
1032 : : * the space management algorithm will go nuts. The code above should
1033 : : * never generate a dangerous request, but to be safe, check explicitly
1034 : : * that the array growth fits within availMem. (We could still cause
1035 : : * LACKMEM if the memory chunk overhead associated with the memtuples
1036 : : * array were to increase. That shouldn't happen because we chose the
1037 : : * initial array size large enough to ensure that palloc will be treating
1038 : : * both old and new arrays as separate chunks. But we'll check LACKMEM
1039 : : * explicitly below just in case.)
1040 : : */
4637 noah@leadboat.com 1041 [ - + ]:CBC 4521 : if (state->availMem < (int64) ((newmemtupsize - memtupsize) * sizeof(SortTuple)))
4805 tgl@sss.pgh.pa.us 1042 :UBC 0 : goto noalloc;
1043 : :
1044 : : /* OK, do it */
7322 tgl@sss.pgh.pa.us 1045 :CBC 4521 : FREEMEM(state, GetMemoryChunkSpace(state->memtuples));
4805 1046 : 4521 : state->memtupsize = newmemtupsize;
7322 1047 : 4521 : state->memtuples = (SortTuple *)
4644 noah@leadboat.com 1048 : 4521 : repalloc_huge(state->memtuples,
1049 : 4521 : state->memtupsize * sizeof(SortTuple));
7322 tgl@sss.pgh.pa.us 1050 : 4521 : USEMEM(state, GetMemoryChunkSpace(state->memtuples));
1051 [ - + - - ]: 4521 : if (LACKMEM(state))
3876 tgl@sss.pgh.pa.us 1052 [ # # ]:UBC 0 : elog(ERROR, "unexpected out-of-memory situation in tuplesort");
7322 tgl@sss.pgh.pa.us 1053 :CBC 4521 : return true;
1054 : :
4805 tgl@sss.pgh.pa.us 1055 :UBC 0 : noalloc:
1056 : : /* If for any reason we didn't realloc, shut off future attempts */
1057 : 0 : state->growmemtuples = false;
1058 : 0 : return false;
1059 : : }
1060 : :
1061 : : /*
1062 : : * Shared code for tuple and datum cases.
1063 : : */
1064 : : void
706 drowley@postgresql.o 1065 :CBC 16481151 : tuplesort_puttuple_common(Tuplesortstate *state, SortTuple *tuple,
1066 : : bool useAbbrev, Size tuplen)
1067 : : {
1327 akorotkov@postgresql 1068 : 16481151 : MemoryContext oldcontext = MemoryContextSwitchTo(state->base.sortcontext);
1069 : :
2963 rhaas@postgresql.org 1070 [ + + - + ]: 16481151 : Assert(!LEADER(state));
1071 : :
1072 : : /* account for the memory used for this tuple */
706 drowley@postgresql.o 1073 : 16481151 : USEMEM(state, tuplen);
1074 : 16481151 : state->tupleMem += tuplen;
1075 : :
1327 akorotkov@postgresql 1076 [ + + ]: 16481151 : if (!useAbbrev)
1077 : : {
1078 : : /*
1079 : : * Leave ordinary Datum representation, or NULL value. If there is a
1080 : : * converter it won't expect NULL values, and cost model is not
1081 : : * required to account for NULL, so in that case we avoid calling
1082 : : * converter and just set datum1 to zeroed representation (to be
1083 : : * consistent, and to support cheap inequality tests for NULL
1084 : : * abbreviated keys).
1085 : : */
1086 : : }
1087 [ + + ]: 2223215 : else if (!consider_abort_common(state))
1088 : : {
1089 : : /* Store abbreviated key representation */
1090 : 2223167 : tuple->datum1 = state->base.sortKeys->abbrev_converter(tuple->datum1,
1091 : : state->base.sortKeys);
1092 : : }
1093 : : else
1094 : : {
1095 : : /*
1096 : : * Set state to be consistent with never trying abbreviation.
1097 : : *
1098 : : * Alter datum1 representation in already-copied tuples, so as to
1099 : : * ensure a consistent representation (current tuple was just
1100 : : * handled). It does not matter if some dumped tuples are already
1101 : : * sorted on tape, since serialized tuples lack abbreviated keys
1102 : : * (TSS_BUILDRUNS state prevents control reaching here in any case).
1103 : : */
1104 : 48 : REMOVEABBREV(state, state->memtuples, state->memtupcount);
1105 : : }
1106 : :
9646 tgl@sss.pgh.pa.us 1107 [ + + + - ]: 16481151 : switch (state->status)
1108 : : {
8907 bruce@momjian.us 1109 : 14053141 : case TSS_INITIAL:
1110 : :
1111 : : /*
1112 : : * Save the tuple into the unsorted array. First, grow the array
1113 : : * as needed. Note that we try to grow the array when there is
1114 : : * still one free slot remaining --- if we fail, there'll still be
1115 : : * room to store the incoming tuple, and then we'll switch to
1116 : : * tape-based operation.
1117 : : */
7322 tgl@sss.pgh.pa.us 1118 [ + + ]: 14053141 : if (state->memtupcount >= state->memtupsize - 1)
1119 : : {
1120 : 4591 : (void) grow_memtuples(state);
1121 [ - + ]: 4591 : Assert(state->memtupcount < state->memtupsize);
1122 : : }
1123 : 14053141 : state->memtuples[state->memtupcount++] = *tuple;
1124 : :
1125 : : /*
1126 : : * Check if it's time to switch over to a bounded heapsort. We do
1127 : : * so if the input tuple count exceeds twice the desired tuple
1128 : : * count (this is a heuristic for where heapsort becomes cheaper
1129 : : * than a quicksort), or if we've just filled workMem and have
1130 : : * enough tuples to meet the bound.
1131 : : *
1132 : : * Note that once we enter TSS_BOUNDED state we will always try to
1133 : : * complete the sort that way. In the worst case, if later input
1134 : : * tuples are larger than earlier ones, this might cause us to
1135 : : * exceed workMem significantly.
1136 : : */
6890 1137 [ + + ]: 14053141 : if (state->bounded &&
1138 [ + + ]: 30948 : (state->memtupcount > state->bound * 2 ||
1139 [ + + - + : 30737 : (state->memtupcount > state->bound && LACKMEM(state))))
- - ]
1140 : : {
1141 [ - + ]: 211 : if (trace_sort)
6890 tgl@sss.pgh.pa.us 1142 [ # # ]:UBC 0 : elog(LOG, "switching to bounded heapsort at %d tuples: %s",
1143 : : state->memtupcount,
1144 : : pg_rusage_show(&state->ru_start));
6890 tgl@sss.pgh.pa.us 1145 :CBC 211 : make_bounded_heap(state);
1327 akorotkov@postgresql 1146 : 211 : MemoryContextSwitchTo(oldcontext);
6890 tgl@sss.pgh.pa.us 1147 : 211 : return;
1148 : : }
1149 : :
1150 : : /*
1151 : : * Done if we still fit in available memory and have array slots.
1152 : : */
7322 1153 [ + + - + : 14052930 : if (state->memtupcount < state->memtupsize && !LACKMEM(state))
- - ]
1154 : : {
1327 akorotkov@postgresql 1155 : 14052860 : MemoryContextSwitchTo(oldcontext);
9646 tgl@sss.pgh.pa.us 1156 : 14052860 : return;
1157 : : }
1158 : :
1159 : : /*
1160 : : * Nope; time to switch to tape-based operation.
1161 : : */
2963 rhaas@postgresql.org 1162 : 70 : inittapes(state, true);
1163 : :
1164 : : /*
1165 : : * Dump all tuples.
1166 : : */
9646 tgl@sss.pgh.pa.us 1167 : 70 : dumptuples(state, false);
1168 : 70 : break;
1169 : :
6890 1170 : 1871803 : case TSS_BOUNDED:
1171 : :
1172 : : /*
1173 : : * We don't want to grow the array here, so check whether the new
1174 : : * tuple can be discarded before putting it in. This should be a
1175 : : * good speed optimization, too, since when there are many more
1176 : : * input tuples than the bound, most input tuples can be discarded
1177 : : * with just this one comparison. Note that because we currently
1178 : : * have the sort direction reversed, we must check for <= not >=.
1179 : : */
1180 [ + + ]: 1871803 : if (COMPARETUP(state, tuple, &state->memtuples[0]) <= 0)
1181 : : {
1182 : : /* new tuple <= top of the heap, so we can discard it */
1183 : 1620474 : free_sort_tuple(state, tuple);
5108 rhaas@postgresql.org 1184 [ + + ]: 1620474 : CHECK_FOR_INTERRUPTS();
1185 : : }
1186 : : else
1187 : : {
1188 : : /* discard top of heap, replacing it with the new tuple */
6890 tgl@sss.pgh.pa.us 1189 : 251329 : free_sort_tuple(state, &state->memtuples[0]);
3089 rhaas@postgresql.org 1190 : 251329 : tuplesort_heap_replace_top(state, tuple);
1191 : : }
6890 tgl@sss.pgh.pa.us 1192 : 1871803 : break;
1193 : :
9646 1194 : 556207 : case TSS_BUILDRUNS:
1195 : :
1196 : : /*
1197 : : * Save the tuple into the unsorted array (there must be space)
1198 : : */
3089 rhaas@postgresql.org 1199 : 556207 : state->memtuples[state->memtupcount++] = *tuple;
1200 : :
1201 : : /*
1202 : : * If we are over the memory limit, dump all tuples.
1203 : : */
9646 tgl@sss.pgh.pa.us 1204 : 556207 : dumptuples(state, false);
1205 : 556207 : break;
1206 : :
9646 tgl@sss.pgh.pa.us 1207 :UBC 0 : default:
8269 1208 [ # # ]: 0 : elog(ERROR, "invalid tuplesort state");
1209 : : break;
1210 : : }
1327 akorotkov@postgresql 1211 :CBC 2428080 : MemoryContextSwitchTo(oldcontext);
1212 : : }
1213 : :
1214 : : static bool
4073 rhaas@postgresql.org 1215 : 2223215 : consider_abort_common(Tuplesortstate *state)
1216 : : {
1327 akorotkov@postgresql 1217 [ - + ]: 2223215 : Assert(state->base.sortKeys[0].abbrev_converter != NULL);
1218 [ - + ]: 2223215 : Assert(state->base.sortKeys[0].abbrev_abort != NULL);
1219 [ - + ]: 2223215 : Assert(state->base.sortKeys[0].abbrev_full_comparator != NULL);
1220 : :
1221 : : /*
1222 : : * Check effectiveness of abbreviation optimization. Consider aborting
1223 : : * when still within memory limit.
1224 : : */
4073 rhaas@postgresql.org 1225 [ + + ]: 2223215 : if (state->status == TSS_INITIAL &&
1226 [ + + ]: 1986985 : state->memtupcount >= state->abbrevNext)
1227 : : {
1228 : 2580 : state->abbrevNext *= 2;
1229 : :
1230 : : /*
1231 : : * Check opclass-supplied abbreviation abort routine. It may indicate
1232 : : * that abbreviation should not proceed.
1233 : : */
1327 akorotkov@postgresql 1234 [ + + ]: 2580 : if (!state->base.sortKeys->abbrev_abort(state->memtupcount,
1235 : : state->base.sortKeys))
4073 rhaas@postgresql.org 1236 : 2532 : return false;
1237 : :
1238 : : /*
1239 : : * Finally, restore authoritative comparator, and indicate that
1240 : : * abbreviation is not in play by setting abbrev_converter to NULL
1241 : : */
1327 akorotkov@postgresql 1242 : 48 : state->base.sortKeys[0].comparator = state->base.sortKeys[0].abbrev_full_comparator;
1243 : 48 : state->base.sortKeys[0].abbrev_converter = NULL;
1244 : : /* Not strictly necessary, but be tidy */
1245 : 48 : state->base.sortKeys[0].abbrev_abort = NULL;
1246 : 48 : state->base.sortKeys[0].abbrev_full_comparator = NULL;
1247 : :
1248 : : /* Give up - expect original pass-by-value representation */
4073 rhaas@postgresql.org 1249 : 48 : return true;
1250 : : }
1251 : :
1252 : 2220635 : return false;
1253 : : }
1254 : :
1255 : : /*
1256 : : * All tuples have been provided; finish the sort.
1257 : : */
1258 : : void
9646 tgl@sss.pgh.pa.us 1259 : 122917 : tuplesort_performsort(Tuplesortstate *state)
1260 : : {
1327 akorotkov@postgresql 1261 : 122917 : MemoryContext oldcontext = MemoryContextSwitchTo(state->base.sortcontext);
1262 : :
7468 tgl@sss.pgh.pa.us 1263 [ - + ]: 122917 : if (trace_sort)
2691 pg@bowt.ie 1264 [ # # ]:UBC 0 : elog(LOG, "performsort of worker %d starting: %s",
1265 : : state->worker, pg_rusage_show(&state->ru_start));
1266 : :
9646 tgl@sss.pgh.pa.us 1267 [ + + + - ]:CBC 122917 : switch (state->status)
1268 : : {
8907 bruce@momjian.us 1269 : 122636 : case TSS_INITIAL:
1270 : :
1271 : : /*
1272 : : * We were able to accumulate all the tuples within the allowed
1273 : : * amount of memory, or leader to take over worker tapes
1274 : : */
2963 rhaas@postgresql.org 1275 [ + + ]: 122636 : if (SERIAL(state))
1276 : : {
1277 : : /* Sort in memory and we're done */
1278 : 122247 : tuplesort_sort_memtuples(state);
1279 : 122202 : state->status = TSS_SORTEDINMEM;
1280 : : }
1281 [ + - + + ]: 389 : else if (WORKER(state))
1282 : : {
1283 : : /*
1284 : : * Parallel workers must still dump out tuples to tape. No
1285 : : * merge is required to produce single output run, though.
1286 : : */
1287 : 290 : inittapes(state, false);
1288 : 290 : dumptuples(state, true);
1289 : 290 : worker_nomergeruns(state);
1290 : 290 : state->status = TSS_SORTEDONTAPE;
1291 : : }
1292 : : else
1293 : : {
1294 : : /*
1295 : : * Leader will take over worker tapes and merge worker runs.
1296 : : * Note that mergeruns sets the correct state->status.
1297 : : */
1298 : 99 : leader_takeover_tapes(state);
1299 : 99 : mergeruns(state);
1300 : : }
9646 tgl@sss.pgh.pa.us 1301 : 122591 : state->current = 0;
1302 : 122591 : state->eof_reached = false;
2963 rhaas@postgresql.org 1303 : 122591 : state->markpos_block = 0L;
9646 tgl@sss.pgh.pa.us 1304 : 122591 : state->markpos_offset = 0;
1305 : 122591 : state->markpos_eof = false;
1306 : 122591 : break;
1307 : :
6890 1308 : 211 : case TSS_BOUNDED:
1309 : :
1310 : : /*
1311 : : * We were able to accumulate all the tuples required for output
1312 : : * in memory, using a heap to eliminate excess tuples. Now we
1313 : : * have to transform the heap to a properly-sorted array. Note
1314 : : * that sort_bounded_heap sets the correct state->status.
1315 : : */
6770 1316 : 211 : sort_bounded_heap(state);
6890 1317 : 211 : state->current = 0;
1318 : 211 : state->eof_reached = false;
1319 : 211 : state->markpos_offset = 0;
1320 : 211 : state->markpos_eof = false;
1321 : 211 : break;
1322 : :
9646 1323 : 70 : case TSS_BUILDRUNS:
1324 : :
1325 : : /*
1326 : : * Finish tape-based sort. First, flush all tuples remaining in
1327 : : * memory out to tape; then merge until we have a single remaining
1328 : : * run (or, if !randomAccess and !WORKER(), one run per tape).
1329 : : * Note that mergeruns sets the correct state->status.
1330 : : */
1331 : 70 : dumptuples(state, true);
1332 : 70 : mergeruns(state);
1333 : 70 : state->eof_reached = false;
1334 : 70 : state->markpos_block = 0L;
1335 : 70 : state->markpos_offset = 0;
1336 : 70 : state->markpos_eof = false;
1337 : 70 : break;
1338 : :
9646 tgl@sss.pgh.pa.us 1339 :UBC 0 : default:
8269 1340 [ # # ]: 0 : elog(ERROR, "invalid tuplesort state");
1341 : : break;
1342 : : }
1343 : :
7468 tgl@sss.pgh.pa.us 1344 [ - + ]:CBC 122872 : if (trace_sort)
1345 : : {
7312 tgl@sss.pgh.pa.us 1346 [ # # ]:UBC 0 : if (state->status == TSS_FINALMERGE)
2691 pg@bowt.ie 1347 [ # # ]: 0 : elog(LOG, "performsort of worker %d done (except %d-way final merge): %s",
1348 : : state->worker, state->nInputTapes,
1349 : : pg_rusage_show(&state->ru_start));
1350 : : else
1351 [ # # ]: 0 : elog(LOG, "performsort of worker %d done: %s",
1352 : : state->worker, pg_rusage_show(&state->ru_start));
1353 : : }
1354 : :
7322 tgl@sss.pgh.pa.us 1355 :CBC 122872 : MemoryContextSwitchTo(oldcontext);
9646 1356 : 122872 : }
1357 : :
1358 : : /*
1359 : : * Internal routine to fetch the next tuple in either forward or back
1360 : : * direction into *stup. Returns false if no more tuples.
1361 : : * Returned tuple belongs to tuplesort memory context, and must not be freed
1362 : : * by caller. Note that fetched tuple is stored in memory that may be
1363 : : * recycled by any future fetch.
1364 : : */
1365 : : bool
7322 1366 : 15298549 : tuplesort_gettuple_common(Tuplesortstate *state, bool forward,
1367 : : SortTuple *stup)
1368 : : {
1369 : : unsigned int tuplen;
1370 : : size_t nmoved;
1371 : :
2963 rhaas@postgresql.org 1372 [ + + - + ]: 15298549 : Assert(!WORKER(state));
1373 : :
9646 tgl@sss.pgh.pa.us 1374 [ + + + - ]: 15298549 : switch (state->status)
1375 : : {
1376 : 12803491 : case TSS_SORTEDINMEM:
1327 akorotkov@postgresql 1377 [ + + - + ]: 12803491 : Assert(forward || state->base.sortopt & TUPLESORT_RANDOMACCESS);
3450 heikki.linnakangas@i 1378 [ - + ]: 12803491 : Assert(!state->slabAllocatorUsed);
9646 tgl@sss.pgh.pa.us 1379 [ + + ]: 12803491 : if (forward)
1380 : : {
1381 [ + + ]: 12803458 : if (state->current < state->memtupcount)
1382 : : {
7322 1383 : 12681788 : *stup = state->memtuples[state->current++];
1384 : 12681788 : return true;
1385 : : }
9646 1386 : 121670 : state->eof_reached = true;
1387 : :
1388 : : /*
1389 : : * Complain if caller tries to retrieve more tuples than
1390 : : * originally asked for in a bounded sort. This is because
1391 : : * returning EOF here might be the wrong thing.
1392 : : */
6890 1393 [ + + - + ]: 121670 : if (state->bounded && state->current >= state->bound)
6890 tgl@sss.pgh.pa.us 1394 [ # # ]:UBC 0 : elog(ERROR, "retrieved too many tuples in a bounded sort");
1395 : :
7322 tgl@sss.pgh.pa.us 1396 :CBC 121670 : return false;
1397 : : }
1398 : : else
1399 : : {
9646 1400 [ - + ]: 33 : if (state->current <= 0)
7322 tgl@sss.pgh.pa.us 1401 :UBC 0 : return false;
1402 : :
1403 : : /*
1404 : : * if all tuples are fetched already then we return last
1405 : : * tuple, else - tuple before last returned.
1406 : : */
9646 tgl@sss.pgh.pa.us 1407 [ + + ]:CBC 33 : if (state->eof_reached)
1408 : 6 : state->eof_reached = false;
1409 : : else
1410 : : {
9468 bruce@momjian.us 1411 : 27 : state->current--; /* last returned tuple */
9646 tgl@sss.pgh.pa.us 1412 [ + + ]: 27 : if (state->current <= 0)
7322 1413 : 3 : return false;
1414 : : }
1415 : 30 : *stup = state->memtuples[state->current - 1];
1416 : 30 : return true;
1417 : : }
1418 : : break;
1419 : :
9646 1420 : 151500 : case TSS_SORTEDONTAPE:
1327 akorotkov@postgresql 1421 [ + + - + ]: 151500 : Assert(forward || state->base.sortopt & TUPLESORT_RANDOMACCESS);
3450 heikki.linnakangas@i 1422 [ - + ]: 151500 : Assert(state->slabAllocatorUsed);
1423 : :
1424 : : /*
1425 : : * The slot that held the tuple that we returned in previous
1426 : : * gettuple call can now be reused.
1427 : : */
1428 [ + + ]: 151500 : if (state->lastReturnedTuple)
1429 : : {
1430 [ + - + - ]: 76425 : RELEASE_SLAB_SLOT(state, state->lastReturnedTuple);
1431 : 76425 : state->lastReturnedTuple = NULL;
1432 : : }
1433 : :
9646 tgl@sss.pgh.pa.us 1434 [ + + ]: 151500 : if (forward)
1435 : : {
1436 [ - + ]: 151485 : if (state->eof_reached)
7322 tgl@sss.pgh.pa.us 1437 :UBC 0 : return false;
1438 : :
1609 heikki.linnakangas@i 1439 [ + + ]:CBC 151485 : if ((tuplen = getlen(state->result_tape, true)) != 0)
1440 : : {
7322 tgl@sss.pgh.pa.us 1441 : 151470 : READTUP(state, stup, state->result_tape, tuplen);
1442 : :
1443 : : /*
1444 : : * Remember the tuple we return, so that we can recycle
1445 : : * its memory on next call. (This can be NULL, in the
1446 : : * !state->tuples case).
1447 : : */
3450 heikki.linnakangas@i 1448 : 151470 : state->lastReturnedTuple = stup->tuple;
1449 : :
7322 tgl@sss.pgh.pa.us 1450 : 151470 : return true;
1451 : : }
1452 : : else
1453 : : {
9646 1454 : 15 : state->eof_reached = true;
7322 1455 : 15 : return false;
1456 : : }
1457 : : }
1458 : :
1459 : : /*
1460 : : * Backward.
1461 : : *
1462 : : * if all tuples are fetched already then we return last tuple,
1463 : : * else - tuple before last returned.
1464 : : */
9646 1465 [ + + ]: 15 : if (state->eof_reached)
1466 : : {
1467 : : /*
1468 : : * Seek position is pointing just past the zero tuplen at the
1469 : : * end of file; back up to fetch last tuple's ending length
1470 : : * word. If seek fails we must have a completely empty file.
1471 : : */
1609 heikki.linnakangas@i 1472 : 6 : nmoved = LogicalTapeBackspace(state->result_tape,
1473 : : 2 * sizeof(unsigned int));
3370 1474 [ - + ]: 6 : if (nmoved == 0)
7322 tgl@sss.pgh.pa.us 1475 :UBC 0 : return false;
3370 heikki.linnakangas@i 1476 [ - + ]:CBC 6 : else if (nmoved != 2 * sizeof(unsigned int))
3370 heikki.linnakangas@i 1477 [ # # ]:UBC 0 : elog(ERROR, "unexpected tape position");
9646 tgl@sss.pgh.pa.us 1478 :CBC 6 : state->eof_reached = false;
1479 : : }
1480 : : else
1481 : : {
1482 : : /*
1483 : : * Back up and fetch previously-returned tuple's ending length
1484 : : * word. If seek fails, assume we are at start of file.
1485 : : */
1609 heikki.linnakangas@i 1486 : 9 : nmoved = LogicalTapeBackspace(state->result_tape,
1487 : : sizeof(unsigned int));
3370 1488 [ - + ]: 9 : if (nmoved == 0)
7322 tgl@sss.pgh.pa.us 1489 :UBC 0 : return false;
3370 heikki.linnakangas@i 1490 [ - + ]:CBC 9 : else if (nmoved != sizeof(unsigned int))
3370 heikki.linnakangas@i 1491 [ # # ]:UBC 0 : elog(ERROR, "unexpected tape position");
1609 heikki.linnakangas@i 1492 :CBC 9 : tuplen = getlen(state->result_tape, false);
1493 : :
1494 : : /*
1495 : : * Back up to get ending length word of tuple before it.
1496 : : */
1497 : 9 : nmoved = LogicalTapeBackspace(state->result_tape,
1498 : : tuplen + 2 * sizeof(unsigned int));
3370 1499 [ + + ]: 9 : if (nmoved == tuplen + sizeof(unsigned int))
1500 : : {
1501 : : /*
1502 : : * We backed up over the previous tuple, but there was no
1503 : : * ending length word before it. That means that the prev
1504 : : * tuple is the first tuple in the file. It is now the
1505 : : * next to read in forward direction (not obviously right,
1506 : : * but that is what in-memory case does).
1507 : : */
7322 tgl@sss.pgh.pa.us 1508 : 3 : return false;
1509 : : }
3370 heikki.linnakangas@i 1510 [ - + ]: 6 : else if (nmoved != tuplen + 2 * sizeof(unsigned int))
3370 heikki.linnakangas@i 1511 [ # # ]:UBC 0 : elog(ERROR, "bogus tuple length in backward scan");
1512 : : }
1513 : :
1609 heikki.linnakangas@i 1514 :CBC 12 : tuplen = getlen(state->result_tape, false);
1515 : :
1516 : : /*
1517 : : * Now we have the length of the prior tuple, back up and read it.
1518 : : * Note: READTUP expects we are positioned after the initial
1519 : : * length word of the tuple, so back up to that point.
1520 : : */
1521 : 12 : nmoved = LogicalTapeBackspace(state->result_tape,
1522 : : tuplen);
3370 1523 [ - + ]: 12 : if (nmoved != tuplen)
8269 tgl@sss.pgh.pa.us 1524 [ # # ]:UBC 0 : elog(ERROR, "bogus tuple length in backward scan");
7322 tgl@sss.pgh.pa.us 1525 :CBC 12 : READTUP(state, stup, state->result_tape, tuplen);
1526 : :
1527 : : /*
1528 : : * Remember the tuple we return, so that we can recycle its memory
1529 : : * on next call. (This can be NULL, in the Datum case).
1530 : : */
3450 heikki.linnakangas@i 1531 : 12 : state->lastReturnedTuple = stup->tuple;
1532 : :
7322 tgl@sss.pgh.pa.us 1533 : 12 : return true;
1534 : :
9646 1535 : 2343558 : case TSS_FINALMERGE:
1536 [ - + ]: 2343558 : Assert(forward);
1537 : : /* We are managing memory ourselves, with the slab allocator. */
3450 heikki.linnakangas@i 1538 [ - + ]: 2343558 : Assert(state->slabAllocatorUsed);
1539 : :
1540 : : /*
1541 : : * The slab slot holding the tuple that we returned in previous
1542 : : * gettuple call can now be reused.
1543 : : */
1544 [ + + ]: 2343558 : if (state->lastReturnedTuple)
1545 : : {
1546 [ + - + + ]: 2283385 : RELEASE_SLAB_SLOT(state, state->lastReturnedTuple);
1547 : 2283385 : state->lastReturnedTuple = NULL;
1548 : : }
1549 : :
1550 : : /*
1551 : : * This code should match the inner loop of mergeonerun().
1552 : : */
9633 tgl@sss.pgh.pa.us 1553 [ + + ]: 2343558 : if (state->memtupcount > 0)
1554 : : {
1609 heikki.linnakangas@i 1555 : 2343409 : int srcTapeIndex = state->memtuples[0].srctape;
1556 : 2343409 : LogicalTape *srcTape = state->inputTapes[srcTapeIndex];
1557 : : SortTuple newtup;
1558 : :
3450 1559 : 2343409 : *stup = state->memtuples[0];
1560 : :
1561 : : /*
1562 : : * Remember the tuple we return, so that we can recycle its
1563 : : * memory on next call. (This can be NULL, in the Datum case).
1564 : : */
1565 : 2343409 : state->lastReturnedTuple = stup->tuple;
1566 : :
1567 : : /*
1568 : : * Pull next tuple from tape, and replace the returned tuple
1569 : : * at top of the heap with it.
1570 : : */
1571 [ + + ]: 2343409 : if (!mergereadnext(state, srcTape, &newtup))
1572 : : {
1573 : : /*
1574 : : * If no more data, we've reached end of run on this tape.
1575 : : * Remove the top node from the heap.
1576 : : */
3089 rhaas@postgresql.org 1577 : 225 : tuplesort_heap_delete_top(state);
1609 heikki.linnakangas@i 1578 : 225 : state->nInputRuns--;
1579 : :
1580 : : /*
1581 : : * Close the tape. It'd go away at the end of the sort
1582 : : * anyway, but better to release the memory early.
1583 : : */
1327 akorotkov@postgresql 1584 : 225 : LogicalTapeClose(srcTape);
1585 : 225 : return true;
1586 : : }
1587 : 2343184 : newtup.srctape = srcTapeIndex;
1588 : 2343184 : tuplesort_heap_replace_top(state, &newtup);
1589 : 2343184 : return true;
1590 : : }
1591 : 149 : return false;
1592 : :
1327 akorotkov@postgresql 1593 :UBC 0 : default:
1594 [ # # ]: 0 : elog(ERROR, "invalid tuplesort state");
1595 : : return false; /* keep compiler quiet */
1596 : : }
1597 : : }
1598 : :
1599 : :
1600 : : /*
1601 : : * Advance over N tuples in either forward or back direction,
1602 : : * without returning any data. N==0 is a no-op.
1603 : : * Returns true if successful, false if ran out of tuples.
1604 : : */
1605 : : bool
4465 tgl@sss.pgh.pa.us 1606 :CBC 196 : tuplesort_skiptuples(Tuplesortstate *state, int64 ntuples, bool forward)
1607 : : {
1608 : : MemoryContext oldcontext;
1609 : :
1610 : : /*
1611 : : * We don't actually support backwards skip yet, because no callers need
1612 : : * it. The API is designed to allow for that later, though.
1613 : : */
1614 [ - + ]: 196 : Assert(forward);
1615 [ - + ]: 196 : Assert(ntuples >= 0);
2963 rhaas@postgresql.org 1616 [ - + - - ]: 196 : Assert(!WORKER(state));
1617 : :
4465 tgl@sss.pgh.pa.us 1618 [ + + - ]: 196 : switch (state->status)
1619 : : {
1620 : 184 : case TSS_SORTEDINMEM:
1621 [ + - ]: 184 : if (state->memtupcount - state->current >= ntuples)
1622 : : {
1623 : 184 : state->current += ntuples;
1624 : 184 : return true;
1625 : : }
4465 tgl@sss.pgh.pa.us 1626 :UBC 0 : state->current = state->memtupcount;
1627 : 0 : state->eof_reached = true;
1628 : :
1629 : : /*
1630 : : * Complain if caller tries to retrieve more tuples than
1631 : : * originally asked for in a bounded sort. This is because
1632 : : * returning EOF here might be the wrong thing.
1633 : : */
1634 [ # # # # ]: 0 : if (state->bounded && state->current >= state->bound)
1635 [ # # ]: 0 : elog(ERROR, "retrieved too many tuples in a bounded sort");
1636 : :
1637 : 0 : return false;
1638 : :
4465 tgl@sss.pgh.pa.us 1639 :CBC 12 : case TSS_SORTEDONTAPE:
1640 : : case TSS_FINALMERGE:
1641 : :
1642 : : /*
1643 : : * We could probably optimize these cases better, but for now it's
1644 : : * not worth the trouble.
1645 : : */
1327 akorotkov@postgresql 1646 : 12 : oldcontext = MemoryContextSwitchTo(state->base.sortcontext);
4465 tgl@sss.pgh.pa.us 1647 [ + + ]: 120066 : while (ntuples-- > 0)
1648 : : {
1649 : : SortTuple stup;
1650 : :
3380 rhaas@postgresql.org 1651 [ - + ]: 120054 : if (!tuplesort_gettuple_common(state, forward, &stup))
1652 : : {
4464 tgl@sss.pgh.pa.us 1653 :UBC 0 : MemoryContextSwitchTo(oldcontext);
4465 1654 : 0 : return false;
1655 : : }
4465 tgl@sss.pgh.pa.us 1656 [ - + ]:CBC 120054 : CHECK_FOR_INTERRUPTS();
1657 : : }
4464 1658 : 12 : MemoryContextSwitchTo(oldcontext);
4465 1659 : 12 : return true;
1660 : :
4465 tgl@sss.pgh.pa.us 1661 :UBC 0 : default:
1662 [ # # ]: 0 : elog(ERROR, "invalid tuplesort state");
1663 : : return false; /* keep compiler quiet */
1664 : : }
1665 : : }
1666 : :
1667 : : /*
1668 : : * tuplesort_merge_order - report merge order we'll use for given memory
1669 : : * (note: "merge order" just means the number of input tapes in the merge).
1670 : : *
1671 : : * This is exported for use by the planner. allowedMem is in bytes.
1672 : : */
1673 : : int
4637 noah@leadboat.com 1674 :CBC 11869 : tuplesort_merge_order(int64 allowedMem)
1675 : : {
1676 : : int mOrder;
1677 : :
1678 : : /*----------
1679 : : * In the merge phase, we need buffer space for each input and output tape.
1680 : : * Each pass in the balanced merge algorithm reads from M input tapes, and
1681 : : * writes to N output tapes. Each tape consumes TAPE_BUFFER_OVERHEAD bytes
1682 : : * of memory. In addition to that, we want MERGE_BUFFER_SIZE workspace per
1683 : : * input tape.
1684 : : *
1685 : : * totalMem = M * (TAPE_BUFFER_OVERHEAD + MERGE_BUFFER_SIZE) +
1686 : : * N * TAPE_BUFFER_OVERHEAD
1687 : : *
1688 : : * Except for the last and next-to-last merge passes, where there can be
1689 : : * fewer tapes left to process, M = N. We choose M so that we have the
1690 : : * desired amount of memory available for the input buffers
1691 : : * (TAPE_BUFFER_OVERHEAD + MERGE_BUFFER_SIZE), given the total memory
1692 : : * available for the tape buffers (allowedMem).
1693 : : *
1694 : : * Note: you might be thinking we need to account for the memtuples[]
1695 : : * array in this calculation, but we effectively treat that as part of the
1696 : : * MERGE_BUFFER_SIZE workspace.
1697 : : *----------
1698 : : */
1609 heikki.linnakangas@i 1699 : 11869 : mOrder = allowedMem /
1700 : : (2 * TAPE_BUFFER_OVERHEAD + MERGE_BUFFER_SIZE);
1701 : :
1702 : : /*
1703 : : * Even in minimum memory, use at least a MINORDER merge. On the other
1704 : : * hand, even when we have lots of memory, do not use more than a MAXORDER
1705 : : * merge. Tapes are pretty cheap, but they're not entirely free. Each
1706 : : * additional tape reduces the amount of memory available to build runs,
1707 : : * which in turn can cause the same sort to need more runs, which makes
1708 : : * merging slower even if it can still be done in a single pass. Also,
1709 : : * high order merges are quite slow due to CPU cache effects; it can be
1710 : : * faster to pay the I/O cost of a multi-pass merge than to perform a
1711 : : * single merge pass across many hundreds of tapes.
1712 : : */
7322 tgl@sss.pgh.pa.us 1713 : 11869 : mOrder = Max(mOrder, MINORDER);
3407 rhaas@postgresql.org 1714 : 11869 : mOrder = Min(mOrder, MAXORDER);
1715 : :
7322 tgl@sss.pgh.pa.us 1716 : 11869 : return mOrder;
1717 : : }
1718 : :
1719 : : /*
1720 : : * Helper function to calculate how much memory to allocate for the read buffer
1721 : : * of each input tape in a merge pass.
1722 : : *
1723 : : * 'avail_mem' is the amount of memory available for the buffers of all the
1724 : : * tapes, both input and output.
1725 : : * 'nInputTapes' and 'nInputRuns' are the number of input tapes and runs.
1726 : : * 'maxOutputTapes' is the max. number of output tapes we should produce.
1727 : : */
1728 : : static int64
1609 heikki.linnakangas@i 1729 : 184 : merge_read_buffer_size(int64 avail_mem, int nInputTapes, int nInputRuns,
1730 : : int maxOutputTapes)
1731 : : {
1732 : : int nOutputRuns;
1733 : : int nOutputTapes;
1734 : :
1735 : : /*
1736 : : * How many output tapes will we produce in this pass?
1737 : : *
1738 : : * This is nInputRuns / nInputTapes, rounded up.
1739 : : */
1740 : 184 : nOutputRuns = (nInputRuns + nInputTapes - 1) / nInputTapes;
1741 : :
1742 : 184 : nOutputTapes = Min(nOutputRuns, maxOutputTapes);
1743 : :
1744 : : /*
1745 : : * Each output tape consumes TAPE_BUFFER_OVERHEAD bytes of memory. All
1746 : : * remaining memory is divided evenly between the input tapes.
1747 : : *
1748 : : * This also follows from the formula in tuplesort_merge_order, but here
1749 : : * we derive the input buffer size from the amount of memory available,
1750 : : * and M and N.
1751 : : */
1752 : 184 : return Max((avail_mem - TAPE_BUFFER_OVERHEAD * nOutputTapes) / nInputTapes, 0);
1753 : : }
1754 : :
1755 : : /*
1756 : : * inittapes - initialize for tape sorting.
1757 : : *
1758 : : * This is called only if we have found we won't sort in memory.
1759 : : */
1760 : : static void
2963 rhaas@postgresql.org 1761 : 360 : inittapes(Tuplesortstate *state, bool mergeruns)
1762 : : {
1763 [ + + - + ]: 360 : Assert(!LEADER(state));
1764 : :
1765 [ + + ]: 360 : if (mergeruns)
1766 : : {
1767 : : /* Compute number of input tapes to use when merging */
1609 heikki.linnakangas@i 1768 : 70 : state->maxTapes = tuplesort_merge_order(state->allowedMem);
1769 : : }
1770 : : else
1771 : : {
1772 : : /* Workers can sometimes produce single run, output without merge */
2963 rhaas@postgresql.org 1773 [ + - - + ]: 290 : Assert(WORKER(state));
1609 heikki.linnakangas@i 1774 : 290 : state->maxTapes = MINORDER;
1775 : : }
1776 : :
7468 tgl@sss.pgh.pa.us 1777 [ - + ]: 360 : if (trace_sort)
2691 pg@bowt.ie 1778 [ # # ]:UBC 0 : elog(LOG, "worker %d switching to external sort with %d tapes: %s",
1779 : : state->worker, state->maxTapes, pg_rusage_show(&state->ru_start));
1780 : :
1781 : : /* Create the tape set */
1609 heikki.linnakangas@i 1782 :CBC 360 : inittapestate(state, state->maxTapes);
2963 rhaas@postgresql.org 1783 : 360 : state->tapeset =
1609 heikki.linnakangas@i 1784 : 360 : LogicalTapeSetCreate(false,
2963 rhaas@postgresql.org 1785 [ + + ]: 360 : state->shared ? &state->shared->fileset : NULL,
1786 : : state->worker);
1787 : :
3089 1788 : 360 : state->currentRun = 0;
1789 : :
1790 : : /*
1791 : : * Initialize logical tape arrays.
1792 : : */
1609 heikki.linnakangas@i 1793 : 360 : state->inputTapes = NULL;
1794 : 360 : state->nInputTapes = 0;
1795 : 360 : state->nInputRuns = 0;
1796 : :
1797 : 360 : state->outputTapes = palloc0(state->maxTapes * sizeof(LogicalTape *));
1798 : 360 : state->nOutputTapes = 0;
1799 : 360 : state->nOutputRuns = 0;
1800 : :
9646 tgl@sss.pgh.pa.us 1801 : 360 : state->status = TSS_BUILDRUNS;
1802 : :
1609 heikki.linnakangas@i 1803 : 360 : selectnewtape(state);
9646 tgl@sss.pgh.pa.us 1804 : 360 : }
1805 : :
1806 : : /*
1807 : : * inittapestate - initialize generic tape management state
1808 : : */
1809 : : static void
2963 rhaas@postgresql.org 1810 : 459 : inittapestate(Tuplesortstate *state, int maxTapes)
1811 : : {
1812 : : int64 tapeSpace;
1813 : :
1814 : : /*
1815 : : * Decrease availMem to reflect the space needed for tape buffers; but
1816 : : * don't decrease it to the point that we have no room for tuples. (That
1817 : : * case is only likely to occur if sorting pass-by-value Datums; in all
1818 : : * other scenarios the memtuples[] array is unlikely to occupy more than
1819 : : * half of allowedMem. In the pass-by-value case it's not important to
1820 : : * account for tuple space, so we don't care if LACKMEM becomes
1821 : : * inaccurate.)
1822 : : */
1823 : 459 : tapeSpace = (int64) maxTapes * TAPE_BUFFER_OVERHEAD;
1824 : :
1825 [ + + ]: 459 : if (tapeSpace + GetMemoryChunkSpace(state->memtuples) < state->allowedMem)
1826 : 398 : USEMEM(state, tapeSpace);
1827 : :
1828 : : /*
1829 : : * Make sure that the temp file(s) underlying the tape set are created in
1830 : : * suitable temp tablespaces. For parallel sorts, this should have been
1831 : : * called already, but it doesn't matter if it is called a second time.
1832 : : */
1833 : 459 : PrepareTempTablespaces();
1834 : 459 : }
1835 : :
1836 : : /*
1837 : : * selectnewtape -- select next tape to output to.
1838 : : *
1839 : : * This is called after finishing a run when we know another run
1840 : : * must be started. This is used both when building the initial
1841 : : * runs, and during merge passes.
1842 : : */
1843 : : static void
9646 tgl@sss.pgh.pa.us 1844 : 912 : selectnewtape(Tuplesortstate *state)
1845 : : {
1846 : : /*
1847 : : * At the beginning of each merge pass, nOutputTapes and nOutputRuns are
1848 : : * both zero. On each call, we create a new output tape to hold the next
1849 : : * run, until maxTapes is reached. After that, we assign new runs to the
1850 : : * existing tapes in a round robin fashion.
1851 : : */
1602 heikki.linnakangas@i 1852 [ + + ]: 912 : if (state->nOutputTapes < state->maxTapes)
1853 : : {
1854 : : /* Create a new tape to hold the next run */
1609 1855 [ - + ]: 621 : Assert(state->outputTapes[state->nOutputRuns] == NULL);
1856 [ - + ]: 621 : Assert(state->nOutputRuns == state->nOutputTapes);
1857 : 621 : state->destTape = LogicalTapeCreate(state->tapeset);
1602 1858 : 621 : state->outputTapes[state->nOutputTapes] = state->destTape;
1609 1859 : 621 : state->nOutputTapes++;
1860 : 621 : state->nOutputRuns++;
1861 : : }
1862 : : else
1863 : : {
1864 : : /*
1865 : : * We have reached the max number of tapes. Append to an existing
1866 : : * tape.
1867 : : */
1868 : 291 : state->destTape = state->outputTapes[state->nOutputRuns % state->nOutputTapes];
1869 : 291 : state->nOutputRuns++;
1870 : : }
9646 tgl@sss.pgh.pa.us 1871 : 912 : }
1872 : :
1873 : : /*
1874 : : * Initialize the slab allocation arena, for the given number of slots.
1875 : : */
1876 : : static void
3450 heikki.linnakangas@i 1877 : 169 : init_slab_allocator(Tuplesortstate *state, int numSlots)
1878 : : {
1879 [ + + ]: 169 : if (numSlots > 0)
1880 : : {
1881 : : char *p;
1882 : : int i;
1883 : :
1884 : 155 : state->slabMemoryBegin = palloc(numSlots * SLAB_SLOT_SIZE);
1885 : 155 : state->slabMemoryEnd = state->slabMemoryBegin +
1886 : 155 : numSlots * SLAB_SLOT_SIZE;
1887 : 155 : state->slabFreeHead = (SlabSlot *) state->slabMemoryBegin;
1888 : 155 : USEMEM(state, numSlots * SLAB_SLOT_SIZE);
1889 : :
1890 : 155 : p = state->slabMemoryBegin;
1891 [ + + ]: 591 : for (i = 0; i < numSlots - 1; i++)
1892 : : {
1893 : 436 : ((SlabSlot *) p)->nextfree = (SlabSlot *) (p + SLAB_SLOT_SIZE);
1894 : 436 : p += SLAB_SLOT_SIZE;
1895 : : }
1896 : 155 : ((SlabSlot *) p)->nextfree = NULL;
1897 : : }
1898 : : else
1899 : : {
1900 : 14 : state->slabMemoryBegin = state->slabMemoryEnd = NULL;
1901 : 14 : state->slabFreeHead = NULL;
1902 : : }
1903 : 169 : state->slabAllocatorUsed = true;
1904 : 169 : }
1905 : :
1906 : : /*
1907 : : * mergeruns -- merge all the completed initial runs.
1908 : : *
1909 : : * This implements the Balanced k-Way Merge Algorithm. All input data has
1910 : : * already been written to initial runs on tape (see dumptuples).
1911 : : */
1912 : : static void
9646 tgl@sss.pgh.pa.us 1913 : 169 : mergeruns(Tuplesortstate *state)
1914 : : {
1915 : : int tapenum;
1916 : :
1917 [ - + ]: 169 : Assert(state->status == TSS_BUILDRUNS);
9633 1918 [ - + ]: 169 : Assert(state->memtupcount == 0);
1919 : :
1327 akorotkov@postgresql 1920 [ + + + + ]: 169 : if (state->base.sortKeys != NULL && state->base.sortKeys->abbrev_converter != NULL)
1921 : : {
1922 : : /*
1923 : : * If there are multiple runs to be merged, when we go to read back
1924 : : * tuples from disk, abbreviated keys will not have been stored, and
1925 : : * we don't care to regenerate them. Disable abbreviation from this
1926 : : * point on.
1927 : : */
1928 : 15 : state->base.sortKeys->abbrev_converter = NULL;
1929 : 15 : state->base.sortKeys->comparator = state->base.sortKeys->abbrev_full_comparator;
1930 : :
1931 : : /* Not strictly necessary, but be tidy */
1932 : 15 : state->base.sortKeys->abbrev_abort = NULL;
1933 : 15 : state->base.sortKeys->abbrev_full_comparator = NULL;
1934 : : }
1935 : :
1936 : : /*
1937 : : * Reset tuple memory. We've freed all the tuples that we previously
1938 : : * allocated. We will use the slab allocator from now on.
1939 : : */
1940 : 169 : MemoryContextResetOnly(state->base.tuplecontext);
1941 : :
1942 : : /*
1943 : : * We no longer need a large memtuples array. (We will allocate a smaller
1944 : : * one for the heap later.)
1945 : : */
3450 heikki.linnakangas@i 1946 : 169 : FREEMEM(state, GetMemoryChunkSpace(state->memtuples));
1947 : 169 : pfree(state->memtuples);
1948 : 169 : state->memtuples = NULL;
1949 : :
1950 : : /*
1951 : : * Initialize the slab allocator. We need one slab slot per input tape,
1952 : : * for the tuples in the heap, plus one to hold the tuple last returned
1953 : : * from tuplesort_gettuple. (If we're sorting pass-by-val Datums,
1954 : : * however, we don't need to do allocate anything.)
1955 : : *
1956 : : * In a multi-pass merge, we could shrink this allocation for the last
1957 : : * merge pass, if it has fewer tapes than previous passes, but we don't
1958 : : * bother.
1959 : : *
1960 : : * From this point on, we no longer use the USEMEM()/LACKMEM() mechanism
1961 : : * to track memory usage of individual tuples.
1962 : : */
1327 akorotkov@postgresql 1963 [ + + ]: 169 : if (state->base.tuples)
1609 heikki.linnakangas@i 1964 : 155 : init_slab_allocator(state, state->nOutputTapes + 1);
1965 : : else
3450 1966 : 14 : init_slab_allocator(state, 0);
1967 : :
1968 : : /*
1969 : : * Allocate a new 'memtuples' array, for the heap. It will hold one tuple
1970 : : * from each input tape.
1971 : : *
1972 : : * We could shrink this, too, between passes in a multi-pass merge, but we
1973 : : * don't bother. (The initial input tapes are still in outputTapes. The
1974 : : * number of input tapes will not increase between passes.)
1975 : : */
1609 1976 : 169 : state->memtupsize = state->nOutputTapes;
1327 akorotkov@postgresql 1977 : 338 : state->memtuples = (SortTuple *) MemoryContextAlloc(state->base.maincontext,
1609 heikki.linnakangas@i 1978 : 169 : state->nOutputTapes * sizeof(SortTuple));
3384 1979 : 169 : USEMEM(state, GetMemoryChunkSpace(state->memtuples));
1980 : :
1981 : : /*
1982 : : * Use all the remaining memory we have available for tape buffers among
1983 : : * all the input tapes. At the beginning of each merge pass, we will
1984 : : * divide this memory between the input and output tapes in the pass.
1985 : : */
1609 1986 : 169 : state->tape_buffer_mem = state->availMem;
1602 1987 : 169 : USEMEM(state, state->tape_buffer_mem);
3441 1988 [ - + ]: 169 : if (trace_sort)
1609 heikki.linnakangas@i 1989 [ # # ]:UBC 0 : elog(LOG, "worker %d using %zu KB of memory for tape buffers",
1990 : : state->worker, state->tape_buffer_mem / 1024);
1991 : :
1992 : : for (;;)
1993 : : {
1994 : : /*
1995 : : * On the first iteration, or if we have read all the runs from the
1996 : : * input tapes in a multi-pass merge, it's time to start a new pass.
1997 : : * Rewind all the output tapes, and make them inputs for the next
1998 : : * pass.
1999 : : */
1609 heikki.linnakangas@i 2000 [ + + ]:CBC 238 : if (state->nInputRuns == 0)
2001 : : {
2002 : : int64 input_buffer_size;
2003 : :
2004 : : /* Close the old, emptied, input tapes */
2005 [ + + ]: 184 : if (state->nInputTapes > 0)
2006 : : {
2007 [ + + ]: 105 : for (tapenum = 0; tapenum < state->nInputTapes; tapenum++)
2008 : 90 : LogicalTapeClose(state->inputTapes[tapenum]);
2009 : 15 : pfree(state->inputTapes);
2010 : : }
2011 : :
2012 : : /* Previous pass's outputs become next pass's inputs. */
2013 : 184 : state->inputTapes = state->outputTapes;
2014 : 184 : state->nInputTapes = state->nOutputTapes;
2015 : 184 : state->nInputRuns = state->nOutputRuns;
2016 : :
2017 : : /*
2018 : : * Reset output tape variables. The actual LogicalTapes will be
2019 : : * created as needed, here we only allocate the array to hold
2020 : : * them.
2021 : : */
2022 : 184 : state->outputTapes = palloc0(state->nInputTapes * sizeof(LogicalTape *));
2023 : 184 : state->nOutputTapes = 0;
2024 : 184 : state->nOutputRuns = 0;
2025 : :
2026 : : /*
2027 : : * Redistribute the memory allocated for tape buffers, among the
2028 : : * new input and output tapes.
2029 : : */
2030 : 184 : input_buffer_size = merge_read_buffer_size(state->tape_buffer_mem,
2031 : : state->nInputTapes,
2032 : : state->nInputRuns,
2033 : : state->maxTapes);
2034 : :
2035 [ - + ]: 184 : if (trace_sort)
1609 heikki.linnakangas@i 2036 [ # # ]:UBC 0 : elog(LOG, "starting merge pass of %d input runs on %d tapes, " INT64_FORMAT " KB of memory for each input tape: %s",
2037 : : state->nInputRuns, state->nInputTapes, input_buffer_size / 1024,
2038 : : pg_rusage_show(&state->ru_start));
2039 : :
2040 : : /* Prepare the new input tapes for merge pass. */
1609 heikki.linnakangas@i 2041 [ + + ]:CBC 720 : for (tapenum = 0; tapenum < state->nInputTapes; tapenum++)
2042 : 536 : LogicalTapeRewindForRead(state->inputTapes[tapenum], input_buffer_size);
2043 : :
2044 : : /*
2045 : : * If there's just one run left on each input tape, then only one
2046 : : * merge pass remains. If we don't have to produce a materialized
2047 : : * sorted tape, we can stop at this point and do the final merge
2048 : : * on-the-fly.
2049 : : */
1327 akorotkov@postgresql 2050 [ + + ]: 184 : if ((state->base.sortopt & TUPLESORT_RANDOMACCESS) == 0
1441 drowley@postgresql.o 2051 [ + + ]: 173 : && state->nInputRuns <= state->nInputTapes
1609 heikki.linnakangas@i 2052 [ + + + - ]: 158 : && !WORKER(state))
2053 : : {
2054 : : /* Tell logtape.c we won't be writing anymore */
7313 tgl@sss.pgh.pa.us 2055 : 158 : LogicalTapeSetForgetFreeSpace(state->tapeset);
2056 : : /* Initialize for the final merge pass */
3450 heikki.linnakangas@i 2057 : 158 : beginmerge(state);
9646 tgl@sss.pgh.pa.us 2058 : 158 : state->status = TSS_FINALMERGE;
2059 : 158 : return;
2060 : : }
2061 : : }
2062 : :
2063 : : /* Select an output tape */
1609 heikki.linnakangas@i 2064 : 80 : selectnewtape(state);
2065 : :
2066 : : /* Merge one run from each input tape. */
2067 : 80 : mergeonerun(state);
2068 : :
2069 : : /*
2070 : : * If the input tapes are empty, and we output only one output run,
2071 : : * we're done. The current output tape contains the final result.
2072 : : */
2073 [ + + + + ]: 80 : if (state->nInputRuns == 0 && state->nOutputRuns <= 1)
2074 : 11 : break;
2075 : : }
2076 : :
2077 : : /*
2078 : : * Done. The result is on a single run on a single tape.
2079 : : */
2080 : 11 : state->result_tape = state->outputTapes[0];
2963 rhaas@postgresql.org 2081 [ - + - - ]: 11 : if (!WORKER(state))
1609 heikki.linnakangas@i 2082 : 11 : LogicalTapeFreeze(state->result_tape, NULL);
2083 : : else
2963 rhaas@postgresql.org 2084 :UBC 0 : worker_freeze_result_tape(state);
9646 tgl@sss.pgh.pa.us 2085 :CBC 11 : state->status = TSS_SORTEDONTAPE;
2086 : :
2087 : : /* Close all the now-empty input tapes, to release their read buffers. */
1609 heikki.linnakangas@i 2088 [ + + ]: 57 : for (tapenum = 0; tapenum < state->nInputTapes; tapenum++)
2089 : 46 : LogicalTapeClose(state->inputTapes[tapenum]);
2090 : : }
2091 : :
2092 : : /*
2093 : : * Merge one run from each input tape.
2094 : : */
2095 : : static void
9646 tgl@sss.pgh.pa.us 2096 : 80 : mergeonerun(Tuplesortstate *state)
2097 : : {
2098 : : int srcTapeIndex;
2099 : : LogicalTape *srcTape;
2100 : :
2101 : : /*
2102 : : * Start the merge by loading one tuple from each active source tape into
2103 : : * the heap.
2104 : : */
3450 heikki.linnakangas@i 2105 : 80 : beginmerge(state);
2106 : :
1291 drowley@postgresql.o 2107 [ - + ]: 80 : Assert(state->slabAllocatorUsed);
2108 : :
2109 : : /*
2110 : : * Execute merge by repeatedly extracting lowest tuple in heap, writing it
2111 : : * out, and replacing it with next tuple from same tape (if there is
2112 : : * another one).
2113 : : */
9633 tgl@sss.pgh.pa.us 2114 [ + + ]: 437796 : while (state->memtupcount > 0)
2115 : : {
2116 : : SortTuple stup;
2117 : :
2118 : : /* write the tuple to destTape */
1609 heikki.linnakangas@i 2119 : 437716 : srcTapeIndex = state->memtuples[0].srctape;
2120 : 437716 : srcTape = state->inputTapes[srcTapeIndex];
2121 : 437716 : WRITETUP(state, state->destTape, &state->memtuples[0]);
2122 : :
2123 : : /* recycle the slot of the tuple we just wrote out, for the next read */
3345 tgl@sss.pgh.pa.us 2124 [ + + ]: 437716 : if (state->memtuples[0].tuple)
2125 [ + - + - ]: 367674 : RELEASE_SLAB_SLOT(state, state->memtuples[0].tuple);
2126 : :
2127 : : /*
2128 : : * pull next tuple from the tape, and replace the written-out tuple in
2129 : : * the heap with it.
2130 : : */
3450 heikki.linnakangas@i 2131 [ + + ]: 437716 : if (mergereadnext(state, srcTape, &stup))
2132 : : {
1609 2133 : 437289 : stup.srctape = srcTapeIndex;
3089 rhaas@postgresql.org 2134 : 437289 : tuplesort_heap_replace_top(state, &stup);
2135 : : }
2136 : : else
2137 : : {
2138 : 427 : tuplesort_heap_delete_top(state);
1609 heikki.linnakangas@i 2139 : 427 : state->nInputRuns--;
2140 : : }
2141 : : }
2142 : :
2143 : : /*
2144 : : * When the heap empties, we're done. Write an end-of-run marker on the
2145 : : * output tape.
2146 : : */
2147 : 80 : markrunend(state->destTape);
9646 tgl@sss.pgh.pa.us 2148 : 80 : }
2149 : :
2150 : : /*
2151 : : * beginmerge - initialize for a merge pass
2152 : : *
2153 : : * Fill the merge heap with the first tuple from each input tape.
2154 : : */
2155 : : static void
3450 heikki.linnakangas@i 2156 : 238 : beginmerge(Tuplesortstate *state)
2157 : : {
2158 : : int activeTapes;
2159 : : int srcTapeIndex;
2160 : :
2161 : : /* Heap should be empty here */
9633 tgl@sss.pgh.pa.us 2162 [ - + ]: 238 : Assert(state->memtupcount == 0);
2163 : :
1609 heikki.linnakangas@i 2164 : 238 : activeTapes = Min(state->nInputTapes, state->nInputRuns);
2165 : :
2166 [ + + ]: 1065 : for (srcTapeIndex = 0; srcTapeIndex < activeTapes; srcTapeIndex++)
2167 : : {
2168 : : SortTuple tup;
2169 : :
2170 [ + + ]: 827 : if (mergereadnext(state, state->inputTapes[srcTapeIndex], &tup))
2171 : : {
2172 : 676 : tup.srctape = srcTapeIndex;
3089 rhaas@postgresql.org 2173 : 676 : tuplesort_heap_insert(state, &tup);
2174 : : }
2175 : : }
3650 2176 : 238 : }
2177 : :
2178 : : /*
2179 : : * mergereadnext - read next tuple from one merge input tape
2180 : : *
2181 : : * Returns false on EOF.
2182 : : */
2183 : : static bool
1609 heikki.linnakangas@i 2184 : 2781952 : mergereadnext(Tuplesortstate *state, LogicalTape *srcTape, SortTuple *stup)
2185 : : {
2186 : : unsigned int tuplen;
2187 : :
2188 : : /* read next tuple, if any */
2189 [ + + ]: 2781952 : if ((tuplen = getlen(srcTape, true)) == 0)
3450 2190 : 803 : return false;
2191 : 2781149 : READTUP(state, stup, srcTape, tuplen);
2192 : :
2193 : 2781149 : return true;
2194 : : }
2195 : :
2196 : : /*
2197 : : * dumptuples - remove tuples from memtuples and write initial run to tape
2198 : : *
2199 : : * When alltuples = true, dump everything currently in memory. (This case is
2200 : : * only used at end of input data.)
2201 : : */
2202 : : static void
9646 tgl@sss.pgh.pa.us 2203 : 556637 : dumptuples(Tuplesortstate *state, bool alltuples)
2204 : : {
2205 : : int memtupwrite;
2206 : : int i;
2207 : :
2208 : : /*
2209 : : * Nothing to do if we still fit in available memory and have array slots,
2210 : : * unless this is the final call during initial run generation.
2211 : : */
3089 rhaas@postgresql.org 2212 [ + + + + : 556637 : if (state->memtupcount < state->memtupsize && !LACKMEM(state) &&
- + ]
2213 [ + + ]: 556165 : !alltuples)
2214 : 555805 : return;
2215 : :
2216 : : /*
2217 : : * Final call might require no sorting, in rare cases where we just so
2218 : : * happen to have previously LACKMEM()'d at the point where exactly all
2219 : : * remaining tuples are loaded into memory, just before input was
2220 : : * exhausted. In general, short final runs are quite possible, but avoid
2221 : : * creating a completely empty run. In a worker, though, we must produce
2222 : : * at least one tape, even if it's empty.
2223 : : */
1609 heikki.linnakangas@i 2224 [ + + - + ]: 832 : if (state->memtupcount == 0 && state->currentRun > 0)
1609 heikki.linnakangas@i 2225 :UBC 0 : return;
2226 : :
3628 rhaas@postgresql.org 2227 [ - + ]:CBC 832 : Assert(state->status == TSS_BUILDRUNS);
2228 : :
2229 : : /*
2230 : : * It seems unlikely that this limit will ever be exceeded, but take no
2231 : : * chances
2232 : : */
2233 [ - + ]: 832 : if (state->currentRun == INT_MAX)
3628 rhaas@postgresql.org 2234 [ # # ]:UBC 0 : ereport(ERROR,
2235 : : (errcode(ERRCODE_PROGRAM_LIMIT_EXCEEDED),
2236 : : errmsg("cannot have more than %d runs for an external sort",
2237 : : INT_MAX)));
2238 : :
1609 heikki.linnakangas@i 2239 [ + + ]:CBC 832 : if (state->currentRun > 0)
2240 : 472 : selectnewtape(state);
2241 : :
3628 rhaas@postgresql.org 2242 : 832 : state->currentRun++;
2243 : :
2244 [ - + ]: 832 : if (trace_sort)
2691 pg@bowt.ie 2245 [ # # ]:UBC 0 : elog(LOG, "worker %d starting quicksort of run %d: %s",
2246 : : state->worker, state->currentRun,
2247 : : pg_rusage_show(&state->ru_start));
2248 : :
2249 : : /*
2250 : : * Sort all tuples accumulated within the allowed amount of memory for
2251 : : * this run.
2252 : : */
3628 rhaas@postgresql.org 2253 :CBC 832 : tuplesort_sort_memtuples(state);
2254 : :
2255 [ - + ]: 832 : if (trace_sort)
2691 pg@bowt.ie 2256 [ # # ]:UBC 0 : elog(LOG, "worker %d finished quicksort of run %d: %s",
2257 : : state->worker, state->currentRun,
2258 : : pg_rusage_show(&state->ru_start));
2259 : :
3628 rhaas@postgresql.org 2260 :CBC 832 : memtupwrite = state->memtupcount;
2261 [ + + ]: 2601867 : for (i = 0; i < memtupwrite; i++)
2262 : : {
1291 drowley@postgresql.o 2263 : 2601035 : SortTuple *stup = &state->memtuples[i];
2264 : :
2265 : 2601035 : WRITETUP(state, state->destTape, stup);
2266 : : }
2267 : :
2268 : 832 : state->memtupcount = 0;
2269 : :
2270 : : /*
2271 : : * Reset tuple memory. We've freed all of the tuples that we previously
2272 : : * allocated. It's important to avoid fragmentation when there is a stark
2273 : : * change in the sizes of incoming tuples. In bounded sorts,
2274 : : * fragmentation due to AllocSetFree's bucketing by size class might be
2275 : : * particularly bad if this step wasn't taken.
2276 : : */
1327 akorotkov@postgresql 2277 : 832 : MemoryContextReset(state->base.tuplecontext);
2278 : :
2279 : : /*
2280 : : * Now update the memory accounting to subtract the memory used by the
2281 : : * tuple.
2282 : : */
706 drowley@postgresql.o 2283 : 832 : FREEMEM(state, state->tupleMem);
2284 : 832 : state->tupleMem = 0;
2285 : :
1609 heikki.linnakangas@i 2286 : 832 : markrunend(state->destTape);
2287 : :
3628 rhaas@postgresql.org 2288 [ - + ]: 832 : if (trace_sort)
2691 pg@bowt.ie 2289 [ # # ]:UBC 0 : elog(LOG, "worker %d finished writing run %d to tape %d: %s",
2290 : : state->worker, state->currentRun, (state->currentRun - 1) % state->nOutputTapes + 1,
2291 : : pg_rusage_show(&state->ru_start));
2292 : : }
2293 : :
2294 : : /*
2295 : : * tuplesort_rescan - rewind and replay the scan
2296 : : */
2297 : : void
9646 tgl@sss.pgh.pa.us 2298 :CBC 30 : tuplesort_rescan(Tuplesortstate *state)
2299 : : {
1327 akorotkov@postgresql 2300 : 30 : MemoryContext oldcontext = MemoryContextSwitchTo(state->base.sortcontext);
2301 : :
2302 [ - + ]: 30 : Assert(state->base.sortopt & TUPLESORT_RANDOMACCESS);
2303 : :
9646 tgl@sss.pgh.pa.us 2304 [ + + - ]: 30 : switch (state->status)
2305 : : {
2306 : 26 : case TSS_SORTEDINMEM:
2307 : 26 : state->current = 0;
2308 : 26 : state->eof_reached = false;
2309 : 26 : state->markpos_offset = 0;
2310 : 26 : state->markpos_eof = false;
2311 : 26 : break;
2312 : 4 : case TSS_SORTEDONTAPE:
1609 heikki.linnakangas@i 2313 : 4 : LogicalTapeRewindForRead(state->result_tape, 0);
9646 tgl@sss.pgh.pa.us 2314 : 4 : state->eof_reached = false;
2315 : 4 : state->markpos_block = 0L;
2316 : 4 : state->markpos_offset = 0;
2317 : 4 : state->markpos_eof = false;
2318 : 4 : break;
9646 tgl@sss.pgh.pa.us 2319 :UBC 0 : default:
8269 2320 [ # # ]: 0 : elog(ERROR, "invalid tuplesort state");
2321 : : break;
2322 : : }
2323 : :
7322 tgl@sss.pgh.pa.us 2324 :CBC 30 : MemoryContextSwitchTo(oldcontext);
9646 2325 : 30 : }
2326 : :
2327 : : /*
2328 : : * tuplesort_markpos - saves current position in the merged sort file
2329 : : */
2330 : : void
2331 : 298958 : tuplesort_markpos(Tuplesortstate *state)
2332 : : {
1327 akorotkov@postgresql 2333 : 298958 : MemoryContext oldcontext = MemoryContextSwitchTo(state->base.sortcontext);
2334 : :
2335 [ - + ]: 298958 : Assert(state->base.sortopt & TUPLESORT_RANDOMACCESS);
2336 : :
9646 tgl@sss.pgh.pa.us 2337 [ + + - ]: 298958 : switch (state->status)
2338 : : {
2339 : 294554 : case TSS_SORTEDINMEM:
2340 : 294554 : state->markpos_offset = state->current;
2341 : 294554 : state->markpos_eof = state->eof_reached;
2342 : 294554 : break;
2343 : 4404 : case TSS_SORTEDONTAPE:
1609 heikki.linnakangas@i 2344 : 4404 : LogicalTapeTell(state->result_tape,
2345 : : &state->markpos_block,
2346 : : &state->markpos_offset);
9646 tgl@sss.pgh.pa.us 2347 : 4404 : state->markpos_eof = state->eof_reached;
2348 : 4404 : break;
9646 tgl@sss.pgh.pa.us 2349 :UBC 0 : default:
8269 2350 [ # # ]: 0 : elog(ERROR, "invalid tuplesort state");
2351 : : break;
2352 : : }
2353 : :
7322 tgl@sss.pgh.pa.us 2354 :CBC 298958 : MemoryContextSwitchTo(oldcontext);
9646 2355 : 298958 : }
2356 : :
2357 : : /*
2358 : : * tuplesort_restorepos - restores current position in merged sort file to
2359 : : * last saved position
2360 : : */
2361 : : void
2362 : 19367 : tuplesort_restorepos(Tuplesortstate *state)
2363 : : {
1327 akorotkov@postgresql 2364 : 19367 : MemoryContext oldcontext = MemoryContextSwitchTo(state->base.sortcontext);
2365 : :
2366 [ - + ]: 19367 : Assert(state->base.sortopt & TUPLESORT_RANDOMACCESS);
2367 : :
9646 tgl@sss.pgh.pa.us 2368 [ + + - ]: 19367 : switch (state->status)
2369 : : {
2370 : 16271 : case TSS_SORTEDINMEM:
2371 : 16271 : state->current = state->markpos_offset;
2372 : 16271 : state->eof_reached = state->markpos_eof;
2373 : 16271 : break;
2374 : 3096 : case TSS_SORTEDONTAPE:
1609 heikki.linnakangas@i 2375 : 3096 : LogicalTapeSeek(state->result_tape,
2376 : : state->markpos_block,
2377 : : state->markpos_offset);
9646 tgl@sss.pgh.pa.us 2378 : 3096 : state->eof_reached = state->markpos_eof;
2379 : 3096 : break;
9646 tgl@sss.pgh.pa.us 2380 :UBC 0 : default:
8269 2381 [ # # ]: 0 : elog(ERROR, "invalid tuplesort state");
2382 : : break;
2383 : : }
2384 : :
7322 tgl@sss.pgh.pa.us 2385 :CBC 19367 : MemoryContextSwitchTo(oldcontext);
9646 2386 : 19367 : }
2387 : :
2388 : : /*
2389 : : * tuplesort_get_stats - extract summary statistics
2390 : : *
2391 : : * This can be called after tuplesort_performsort() finishes to obtain
2392 : : * printable summary information about how the sort was performed.
2393 : : */
2394 : : void
6061 2395 : 198 : tuplesort_get_stats(Tuplesortstate *state,
2396 : : TuplesortInstrumentation *stats)
2397 : : {
2398 : : /*
2399 : : * Note: it might seem we should provide both memory and disk usage for a
2400 : : * disk-based sort. However, the current code doesn't track memory space
2401 : : * accurately once we have begun to return tuples to the caller (since we
2402 : : * don't account for pfree's the caller is expected to do), so we cannot
2403 : : * rely on availMem in a disk sort. This does not seem worth the overhead
2404 : : * to fix. Is it worth creating an API for the memory context code to
2405 : : * tell us how much is actually used in sortcontext?
2406 : : */
2169 tomas.vondra@postgre 2407 : 198 : tuplesort_updatemax(state);
2408 : :
2409 [ + + ]: 198 : if (state->isMaxSpaceDisk)
3120 rhaas@postgresql.org 2410 : 3 : stats->spaceType = SORT_SPACE_TYPE_DISK;
2411 : : else
2412 : 195 : stats->spaceType = SORT_SPACE_TYPE_MEMORY;
2169 tomas.vondra@postgre 2413 : 198 : stats->spaceUsed = (state->maxSpace + 1023) / 1024;
2414 : :
2415 [ + - + - ]: 198 : switch (state->maxSpaceStatus)
2416 : : {
6890 tgl@sss.pgh.pa.us 2417 : 195 : case TSS_SORTEDINMEM:
2418 [ + + ]: 195 : if (state->boundUsed)
3120 rhaas@postgresql.org 2419 : 21 : stats->sortMethod = SORT_TYPE_TOP_N_HEAPSORT;
2420 : : else
2421 : 174 : stats->sortMethod = SORT_TYPE_QUICKSORT;
6890 tgl@sss.pgh.pa.us 2422 : 195 : break;
6890 tgl@sss.pgh.pa.us 2423 :UBC 0 : case TSS_SORTEDONTAPE:
3120 rhaas@postgresql.org 2424 : 0 : stats->sortMethod = SORT_TYPE_EXTERNAL_SORT;
6890 tgl@sss.pgh.pa.us 2425 : 0 : break;
6890 tgl@sss.pgh.pa.us 2426 :CBC 3 : case TSS_FINALMERGE:
3120 rhaas@postgresql.org 2427 : 3 : stats->sortMethod = SORT_TYPE_EXTERNAL_MERGE;
6890 tgl@sss.pgh.pa.us 2428 : 3 : break;
6890 tgl@sss.pgh.pa.us 2429 :UBC 0 : default:
3120 rhaas@postgresql.org 2430 : 0 : stats->sortMethod = SORT_TYPE_STILL_IN_PROGRESS;
6890 tgl@sss.pgh.pa.us 2431 : 0 : break;
2432 : : }
6890 tgl@sss.pgh.pa.us 2433 :CBC 198 : }
2434 : :
2435 : : /*
2436 : : * Convert TuplesortMethod to a string.
2437 : : */
2438 : : const char *
3120 rhaas@postgresql.org 2439 : 147 : tuplesort_method_name(TuplesortMethod m)
2440 : : {
2441 [ - + + - : 147 : switch (m)
+ - ]
2442 : : {
3120 rhaas@postgresql.org 2443 :UBC 0 : case SORT_TYPE_STILL_IN_PROGRESS:
2444 : 0 : return "still in progress";
3120 rhaas@postgresql.org 2445 :CBC 21 : case SORT_TYPE_TOP_N_HEAPSORT:
2446 : 21 : return "top-N heapsort";
2447 : 123 : case SORT_TYPE_QUICKSORT:
2448 : 123 : return "quicksort";
3120 rhaas@postgresql.org 2449 :UBC 0 : case SORT_TYPE_EXTERNAL_SORT:
2450 : 0 : return "external sort";
3120 rhaas@postgresql.org 2451 :CBC 3 : case SORT_TYPE_EXTERNAL_MERGE:
2452 : 3 : return "external merge";
2453 : : }
2454 : :
3120 rhaas@postgresql.org 2455 :UBC 0 : return "unknown";
2456 : : }
2457 : :
2458 : : /*
2459 : : * Convert TuplesortSpaceType to a string.
2460 : : */
2461 : : const char *
3120 rhaas@postgresql.org 2462 :CBC 129 : tuplesort_space_type_name(TuplesortSpaceType t)
2463 : : {
2464 [ + + - + ]: 129 : Assert(t == SORT_SPACE_TYPE_DISK || t == SORT_SPACE_TYPE_MEMORY);
2465 [ + + ]: 129 : return t == SORT_SPACE_TYPE_DISK ? "Disk" : "Memory";
2466 : : }
2467 : :
2468 : :
2469 : : /*
2470 : : * Heap manipulation routines, per Knuth's Algorithm 5.2.3H.
2471 : : */
2472 : :
2473 : : /*
2474 : : * Convert the existing unordered array of SortTuples to a bounded heap,
2475 : : * discarding all but the smallest "state->bound" tuples.
2476 : : *
2477 : : * When working with a bounded heap, we want to keep the largest entry
2478 : : * at the root (array entry zero), instead of the smallest as in the normal
2479 : : * sort case. This allows us to discard the largest entry cheaply.
2480 : : * Therefore, we temporarily reverse the sort direction.
2481 : : */
2482 : : static void
6890 tgl@sss.pgh.pa.us 2483 : 211 : make_bounded_heap(Tuplesortstate *state)
2484 : : {
6695 bruce@momjian.us 2485 : 211 : int tupcount = state->memtupcount;
2486 : : int i;
2487 : :
6890 tgl@sss.pgh.pa.us 2488 [ - + ]: 211 : Assert(state->status == TSS_INITIAL);
2489 [ - + ]: 211 : Assert(state->bounded);
2490 [ - + ]: 211 : Assert(tupcount >= state->bound);
2963 rhaas@postgresql.org 2491 [ - + ]: 211 : Assert(SERIAL(state));
2492 : :
2493 : : /* Reverse sort direction so largest entry will be at root */
4146 2494 : 211 : reversedirection(state);
2495 : :
6890 tgl@sss.pgh.pa.us 2496 : 211 : state->memtupcount = 0; /* make the heap empty */
6695 bruce@momjian.us 2497 [ + + ]: 21040 : for (i = 0; i < tupcount; i++)
2498 : : {
3472 heikki.linnakangas@i 2499 [ + + ]: 20829 : if (state->memtupcount < state->bound)
2500 : : {
2501 : : /* Insert next tuple into heap */
2502 : : /* Must copy source tuple to avoid possible overwrite */
6695 bruce@momjian.us 2503 : 10309 : SortTuple stup = state->memtuples[i];
2504 : :
3089 rhaas@postgresql.org 2505 : 10309 : tuplesort_heap_insert(state, &stup);
2506 : : }
2507 : : else
2508 : : {
2509 : : /*
2510 : : * The heap is full. Replace the largest entry with the new
2511 : : * tuple, or just discard it, if it's larger than anything already
2512 : : * in the heap.
2513 : : */
3472 heikki.linnakangas@i 2514 [ + + ]: 10520 : if (COMPARETUP(state, &state->memtuples[i], &state->memtuples[0]) <= 0)
2515 : : {
2516 : 5201 : free_sort_tuple(state, &state->memtuples[i]);
2517 [ - + ]: 5201 : CHECK_FOR_INTERRUPTS();
2518 : : }
2519 : : else
3089 rhaas@postgresql.org 2520 : 5319 : tuplesort_heap_replace_top(state, &state->memtuples[i]);
2521 : : }
2522 : : }
2523 : :
6890 tgl@sss.pgh.pa.us 2524 [ - + ]: 211 : Assert(state->memtupcount == state->bound);
2525 : 211 : state->status = TSS_BOUNDED;
2526 : 211 : }
2527 : :
2528 : : /*
2529 : : * Convert the bounded heap to a properly-sorted array
2530 : : */
2531 : : static void
2532 : 211 : sort_bounded_heap(Tuplesortstate *state)
2533 : : {
6695 bruce@momjian.us 2534 : 211 : int tupcount = state->memtupcount;
2535 : :
6890 tgl@sss.pgh.pa.us 2536 [ - + ]: 211 : Assert(state->status == TSS_BOUNDED);
2537 [ - + ]: 211 : Assert(state->bounded);
2538 [ - + ]: 211 : Assert(tupcount == state->bound);
2963 rhaas@postgresql.org 2539 [ - + ]: 211 : Assert(SERIAL(state));
2540 : :
2541 : : /*
2542 : : * We can unheapify in place because each delete-top call will remove the
2543 : : * largest entry, which we can promptly store in the newly freed slot at
2544 : : * the end. Once we're down to a single-entry heap, we're done.
2545 : : */
6890 tgl@sss.pgh.pa.us 2546 [ + + ]: 10309 : while (state->memtupcount > 1)
2547 : : {
6695 bruce@momjian.us 2548 : 10098 : SortTuple stup = state->memtuples[0];
2549 : :
2550 : : /* this sifts-up the next-largest entry and decreases memtupcount */
3089 rhaas@postgresql.org 2551 : 10098 : tuplesort_heap_delete_top(state);
6890 tgl@sss.pgh.pa.us 2552 : 10098 : state->memtuples[state->memtupcount] = stup;
2553 : : }
2554 : 211 : state->memtupcount = tupcount;
2555 : :
2556 : : /*
2557 : : * Reverse sort direction back to the original state. This is not
2558 : : * actually necessary but seems like a good idea for tidiness.
2559 : : */
4146 rhaas@postgresql.org 2560 : 211 : reversedirection(state);
2561 : :
6890 tgl@sss.pgh.pa.us 2562 : 211 : state->status = TSS_SORTEDINMEM;
2563 : 211 : state->boundUsed = true;
2564 : 211 : }
2565 : :
2566 : :
2567 : : /* radix sort routines */
2568 : :
2569 : : /*
2570 : : * Retrieve byte from datum, indexed by 'level': 0 for MSB, 7 for LSB
2571 : : */
2572 : : static inline uint8
29 john.naylor@postgres 2573 :GNC 28394297 : current_byte(Datum key, int level)
2574 : : {
2575 : 28394297 : int shift = (sizeof(Datum) - 1 - level) * BITS_PER_BYTE;
2576 : :
2577 : 28394297 : return (key >> shift) & 0xFF;
2578 : : }
2579 : :
2580 : : /*
2581 : : * Normalize datum such that unsigned comparison is order-preserving,
2582 : : * taking ASC/DESC into account as well.
2583 : : */
2584 : : static inline Datum
2585 : 28394297 : normalize_datum(Datum orig, SortSupport ssup)
2586 : : {
2587 : : Datum norm_datum1;
2588 : :
2589 [ + + ]: 28394297 : if (ssup->comparator == ssup_datum_signed_cmp)
2590 : : {
2591 : 1908618 : norm_datum1 = orig + ((uint64) PG_INT64_MAX) + 1;
2592 : : }
2593 [ + + ]: 26485679 : else if (ssup->comparator == ssup_datum_int32_cmp)
2594 : : {
2595 : : /*
2596 : : * First truncate to uint32. Technically, we don't need to do this,
2597 : : * but it forces the upper half of the datum to be zero regardless of
2598 : : * sign.
2599 : : */
2600 : 20394978 : uint32 u32 = DatumGetUInt32(orig) + ((uint32) PG_INT32_MAX) + 1;
2601 : :
2602 : 20394978 : norm_datum1 = UInt32GetDatum(u32);
2603 : : }
2604 : : else
2605 : : {
2606 [ - + ]: 6090701 : Assert(ssup->comparator == ssup_datum_unsigned_cmp);
2607 : 6090701 : norm_datum1 = orig;
2608 : : }
2609 : :
2610 [ + + ]: 28394297 : if (ssup->ssup_reverse)
2611 : 1615596 : norm_datum1 = ~norm_datum1;
2612 : :
2613 : 28394297 : return norm_datum1;
2614 : : }
2615 : :
2616 : : /*
2617 : : * radix_sort_recursive
2618 : : *
2619 : : * Radix sort by (pass-by-value) datum1, diverting to qsort_tuple()
2620 : : * for tiebreaks.
2621 : : *
2622 : : * This is a modification of
2623 : : * ska_byte_sort() from https://github.com/skarupke/ska_sort
2624 : : * The original copyright notice follows:
2625 : : *
2626 : : * Copyright Malte Skarupke 2016.
2627 : : * Distributed under the Boost Software License, Version 1.0.
2628 : : *
2629 : : * Boost Software License - Version 1.0 - August 17th, 2003
2630 : : *
2631 : : * Permission is hereby granted, free of charge, to any person or organization
2632 : : * obtaining a copy of the software and accompanying documentation covered by
2633 : : * this license (the "Software") to use, reproduce, display, distribute,
2634 : : * execute, and transmit the Software, and to prepare derivative works of the
2635 : : * Software, and to permit third-parties to whom the Software is furnished to
2636 : : * do so, all subject to the following:
2637 : : *
2638 : : * The copyright notices in the Software and this entire statement, including
2639 : : * the above license grant, this restriction and the following disclaimer,
2640 : : * must be included in all copies of the Software, in whole or in part, and
2641 : : * all derivative works of the Software, unless such copies or derivative
2642 : : * works are solely in the form of machine-executable object code generated by
2643 : : * a source language processor.
2644 : : *
2645 : : * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
2646 : : * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
2647 : : * FITNESS FOR A PARTICULAR PURPOSE, TITLE AND NON-INFRINGEMENT. IN NO EVENT
2648 : : * SHALL THE COPYRIGHT HOLDERS OR ANYONE DISTRIBUTING THE SOFTWARE BE LIABLE
2649 : : * FOR ANY DAMAGES OR OTHER LIABILITY, WHETHER IN CONTRACT, TORT OR OTHERWISE,
2650 : : * ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER
2651 : : * DEALINGS IN THE SOFTWARE.
2652 : : */
2653 : : static void
2654 : 32509 : radix_sort_recursive(SortTuple *begin, size_t n_elems, int level, Tuplesortstate *state)
2655 : : {
2656 : 32509 : RadixSortInfo partitions[256] = {0};
2657 : : uint8 remaining_partitions[256];
2658 : 32509 : size_t total = 0;
2659 : 32509 : int num_partitions = 0;
2660 : : int num_remaining;
2661 : 32509 : SortSupport ssup = &state->base.sortKeys[0];
2662 : 32509 : size_t start_offset = 0;
2663 : 32509 : SortTuple *partition_begin = begin;
2664 : :
2665 : : /* count number of occurrences of each byte */
2666 [ + + ]: 28426806 : for (SortTuple *st = begin; st < begin + n_elems; st++)
2667 : : {
2668 : : uint8 this_partition;
2669 : :
2670 : : /* extract the byte for this level from the normalized datum */
2671 : 28394297 : this_partition = current_byte(normalize_datum(st->datum1, ssup),
2672 : : level);
2673 : :
2674 : : /* save it for the permutation step */
2675 : 28394297 : st->curbyte = this_partition;
2676 : :
2677 : 28394297 : partitions[this_partition].count++;
2678 : :
2679 [ + + ]: 28394297 : CHECK_FOR_INTERRUPTS();
2680 : : }
2681 : :
2682 : : /* compute partition offsets */
2683 [ + + ]: 8354813 : for (int i = 0; i < 256; i++)
2684 : : {
2685 : 8322304 : size_t count = partitions[i].count;
2686 : :
2687 [ + + ]: 8322304 : if (count != 0)
2688 : : {
2689 : 1455545 : partitions[i].offset = total;
2690 : 1455545 : total += count;
2691 : 1455545 : remaining_partitions[num_partitions] = i;
2692 : 1455545 : num_partitions++;
2693 : : }
2694 : 8322304 : partitions[i].next_offset = total;
2695 : : }
2696 : :
2697 : : /*
2698 : : * Swap tuples to correct partition.
2699 : : *
2700 : : * In traditional American flag sort, a swap sends the current element to
2701 : : * the correct partition, but the array pointer only advances if the
2702 : : * partner of the swap happens to be an element that belongs in the
2703 : : * current partition. That only requires one pass through the array, but
2704 : : * the disadvantage is we don't know if the pointer can advance until the
2705 : : * swap completes. Here lies the most interesting innovation from the
2706 : : * upstream ska_byte_sort: After initiating the swap, we immediately
2707 : : * proceed to the next element. This makes better use of CPU pipelining,
2708 : : * but also means that we will often need multiple iterations of this
2709 : : * loop. ska_byte_sort() maintains a separate list of which partitions
2710 : : * haven't finished, which is updated every loop iteration. Here we simply
2711 : : * check each partition during every iteration.
2712 : : *
2713 : : * If we started with a single partition, there is nothing to do. If a
2714 : : * previous loop iteration results in only one partition that hasn't been
2715 : : * counted as sorted, we know it's actually sorted and can exit the loop.
2716 : : */
2717 : 32509 : num_remaining = num_partitions;
2718 [ + + ]: 100187 : while (num_remaining > 1)
2719 : : {
2720 : : /* start the count over */
2721 : 67678 : num_remaining = num_partitions;
2722 : :
2723 [ + + ]: 6019479 : for (int i = 0; i < num_partitions; i++)
2724 : : {
2725 : 5951801 : uint8 idx = remaining_partitions[i];
2726 : :
2727 : 5951801 : for (SortTuple *st = begin + partitions[idx].offset;
2728 [ + + ]: 14033595 : st < begin + partitions[idx].next_offset;
2729 : 8081794 : st++)
2730 : : {
2731 : 8081794 : size_t offset = partitions[st->curbyte].offset++;
2732 : : SortTuple tmp;
2733 : :
2734 : : /* swap current tuple with destination position */
2735 [ - + ]: 8081794 : Assert(offset < n_elems);
2736 : 8081794 : tmp = *st;
2737 : 8081794 : *st = begin[offset];
2738 : 8081794 : begin[offset] = tmp;
2739 : :
2740 [ + + ]: 8081794 : CHECK_FOR_INTERRUPTS();
2741 : : };
2742 : :
2743 : : /* Is this partition sorted? */
2744 [ + + ]: 5951801 : if (partitions[idx].offset == partitions[idx].next_offset)
2745 : 4546355 : num_remaining--;
2746 : : }
2747 : : }
2748 : :
2749 : : /* recurse */
2750 : 32509 : for (uint8 *rp = remaining_partitions;
2751 [ + + ]: 1488054 : rp < remaining_partitions + num_partitions;
2752 : 1455545 : rp++)
2753 : : {
2754 : 1455545 : size_t end_offset = partitions[*rp].next_offset;
2755 : 1455545 : SortTuple *partition_end = begin + end_offset;
2756 : 1455545 : size_t num_elements = end_offset - start_offset;
2757 : :
2758 [ + + ]: 1455545 : if (num_elements > 1)
2759 : : {
2760 [ + + ]: 572203 : if (level < sizeof(Datum) - 1)
2761 : : {
2762 [ + + ]: 492735 : if (num_elements < QSORT_THRESHOLD)
2763 : : {
2764 : 461966 : qsort_tuple(partition_begin,
2765 : : num_elements,
2766 : : state->base.comparetup,
2767 : : state);
2768 : : }
2769 : : else
2770 : : {
2771 : 30769 : radix_sort_recursive(partition_begin,
2772 : : num_elements,
2773 : : level + 1,
2774 : : state);
2775 : : }
2776 : : }
2777 [ + + ]: 79468 : else if (state->base.onlyKey == NULL)
2778 : : {
2779 : : /*
2780 : : * We've finished radix sort on all bytes of the pass-by-value
2781 : : * datum (possibly abbreviated), now sort using the tiebreak
2782 : : * comparator.
2783 : : */
2784 : 18206 : qsort_tuple(partition_begin,
2785 : : num_elements,
2786 : : state->base.comparetup_tiebreak,
2787 : : state);
2788 : : }
2789 : : }
2790 : :
2791 : 1455545 : start_offset = end_offset;
2792 : 1455545 : partition_begin = partition_end;
2793 : : }
2794 : 32509 : }
2795 : :
2796 : : /*
2797 : : * Entry point for radix_sort_recursive
2798 : : *
2799 : : * Partition tuples by isnull1, then sort both partitions, using
2800 : : * radix sort on the NOT NULL partition if it's large enough.
2801 : : */
2802 : : static void
2803 : 2869 : radix_sort_tuple(SortTuple *data, size_t n, Tuplesortstate *state)
2804 : : {
2805 : 2869 : bool nulls_first = state->base.sortKeys[0].ssup_nulls_first;
2806 : : SortTuple *null_start;
2807 : : SortTuple *not_null_start;
2808 : 2869 : size_t d1 = 0,
2809 : : d2,
2810 : : null_count,
2811 : : not_null_count;
2812 : :
2813 : : /*
2814 : : * Find the first NOT NULL if NULLS FIRST, or first NULL if NULLS LAST.
2815 : : * This also serves as a quick check for the common case where all tuples
2816 : : * are NOT NULL in the first sort key.
2817 : : */
2818 [ + + + + ]: 7549029 : while (d1 < n && data[d1].isnull1 == nulls_first)
2819 : : {
2820 : 7546160 : d1++;
2821 [ - + ]: 7546160 : CHECK_FOR_INTERRUPTS();
2822 : : }
2823 : :
2824 : : /*
2825 : : * If we have more than one tuple left after the quick check, partition
2826 : : * the remainder using branchless cyclic permutation, based on
2827 : : * https://orlp.net/blog/branchless-lomuto-partitioning/
2828 : : */
2829 [ - + ]: 2869 : Assert(n > 0);
2830 [ + + ]: 2869 : if (d1 < n - 1)
2831 : : {
2832 : 574 : size_t i = d1,
2833 : 574 : j = d1;
2834 : 574 : SortTuple tmp = data[d1]; /* create gap at front */
2835 : :
2836 [ + + ]: 341413 : while (j < n - 1)
2837 : : {
2838 : : /* gap is at j, move i's element to gap */
2839 : 340839 : data[j] = data[i];
2840 : : /* advance j to the first unknown element */
2841 : 340839 : j += 1;
2842 : : /* move the first unknown element back to i */
2843 : 340839 : data[i] = data[j];
2844 : : /* advance i if this element belongs in the left partition */
2845 : 340839 : i += (data[i].isnull1 == nulls_first);
2846 : :
2847 [ - + ]: 340839 : CHECK_FOR_INTERRUPTS();
2848 : : }
2849 : :
2850 : : /* place gap between left and right partitions */
2851 : 574 : data[j] = data[i];
2852 : : /* restore the saved element */
2853 : 574 : data[i] = tmp;
2854 : : /* assign it to the correct partition */
2855 : 574 : i += (data[i].isnull1 == nulls_first);
2856 : :
2857 : : /* d1 is now the number of elements in the left partition */
2858 : 574 : d1 = i;
2859 : : }
2860 : :
2861 : 2869 : d2 = n - d1;
2862 : :
2863 : : /* set pointers and counts for each partition */
2864 [ + + ]: 2869 : if (nulls_first)
2865 : : {
2866 : 491 : null_start = data;
2867 : 491 : null_count = d1;
2868 : 491 : not_null_start = data + d1;
2869 : 491 : not_null_count = d2;
2870 : : }
2871 : : else
2872 : : {
2873 : 2378 : not_null_start = data;
2874 : 2378 : not_null_count = d1;
2875 : 2378 : null_start = data + d1;
2876 : 2378 : null_count = d2;
2877 : : }
2878 : :
2879 : 2869 : for (SortTuple *st = null_start;
2880 [ + + ]: 5079 : st < null_start + null_count;
2881 : 2210 : st++)
2882 [ - + ]: 2210 : Assert(st->isnull1 == true);
2883 : 2869 : for (SortTuple *st = not_null_start;
2884 [ + + ]: 7888235 : st < not_null_start + not_null_count;
2885 : 7885366 : st++)
2886 [ - + ]: 7885366 : Assert(st->isnull1 == false);
2887 : :
2888 : : /*
2889 : : * Sort the NULL partition using tiebreak comparator, if necessary.
2890 : : */
2891 [ + + + + ]: 2869 : if (state->base.onlyKey == NULL && null_count > 1)
2892 : : {
2893 : 87 : qsort_tuple(null_start,
2894 : : null_count,
2895 : : state->base.comparetup_tiebreak,
2896 : : state);
2897 : : }
2898 : :
2899 : : /*
2900 : : * Sort the NOT NULL partition, using radix sort if large enough,
2901 : : * otherwise fall back to quicksort.
2902 : : */
2903 [ + + ]: 2869 : if (not_null_count < QSORT_THRESHOLD)
2904 : : {
2905 : 14 : qsort_tuple(not_null_start,
2906 : : not_null_count,
2907 : : state->base.comparetup,
2908 : : state);
2909 : : }
2910 : : else
2911 : : {
2912 : 2855 : bool presorted = true;
2913 : :
2914 : 2855 : for (SortTuple *st = not_null_start + 1;
2915 [ + + ]: 3981337 : st < not_null_start + not_null_count;
2916 : 3978482 : st++)
2917 : : {
2918 [ + + ]: 3980222 : if (COMPARETUP(state, st - 1, st) > 0)
2919 : : {
2920 : 1740 : presorted = false;
2921 : 1740 : break;
2922 : : }
2923 : :
2924 [ - + ]: 3978482 : CHECK_FOR_INTERRUPTS();
2925 : : }
2926 : :
2927 [ + + ]: 2855 : if (presorted)
2928 : 1115 : return;
2929 : : else
2930 : : {
2931 : 1740 : radix_sort_recursive(not_null_start,
2932 : : not_null_count,
2933 : : 0,
2934 : : state);
2935 : : }
2936 : : }
2937 : : }
2938 : :
2939 : : /* Verify in-memory sort using standard comparator. */
2940 : : static void
2941 : 2869 : verify_memtuples_sorted(Tuplesortstate *state)
2942 : : {
2943 : : #ifdef USE_ASSERT_CHECKING
2944 : 2869 : for (SortTuple *st = state->memtuples + 1;
2945 [ + + ]: 7887576 : st < state->memtuples + state->memtupcount;
2946 : 7884707 : st++)
2947 [ - + ]: 7884707 : Assert(COMPARETUP(state, st - 1, st) <= 0);
2948 : : #endif
2949 : 2869 : }
2950 : :
2951 : : /*
2952 : : * Sort all memtuples using specialized routines.
2953 : : *
2954 : : * Quicksort or radix sort is used for small in-memory sorts,
2955 : : * and external sort runs.
2956 : : */
2957 : : static void
3628 rhaas@postgresql.org 2958 :CBC 123079 : tuplesort_sort_memtuples(Tuplesortstate *state)
2959 : : {
2963 2960 [ + + - + ]: 123079 : Assert(!LEADER(state));
2961 : :
3628 2962 [ + + ]: 123079 : if (state->memtupcount > 1)
2963 : : {
2964 : : /*
2965 : : * Do we have the leading column's value or abbreviation in datum1?
2966 : : */
1327 akorotkov@postgresql 2967 [ + + + + ]: 35608 : if (state->base.haveDatum1 && state->base.sortKeys)
2968 : : {
29 john.naylor@postgres 2969 :GNC 35540 : SortSupport ssup = &state->base.sortKeys[0];
2970 : :
2971 : : /* Does it compare as an integer? */
2972 [ + + ]: 35540 : if (state->memtupcount >= QSORT_THRESHOLD &&
2973 [ + + ]: 7418 : (ssup->comparator == ssup_datum_unsigned_cmp ||
2974 [ + + ]: 7011 : ssup->comparator == ssup_datum_signed_cmp ||
2975 [ + + ]: 6853 : ssup->comparator == ssup_datum_int32_cmp))
2976 : : {
2977 : 2869 : radix_sort_tuple(state->memtuples,
2978 : 2869 : state->memtupcount,
2979 : : state);
2980 : 2869 : verify_memtuples_sorted(state);
1441 tmunro@postgresql.or 2981 :CBC 2869 : return;
2982 : : }
2983 : : }
2984 : :
2985 : : /* Can we use the single-key sort function? */
1327 akorotkov@postgresql 2986 [ + + ]: 32739 : if (state->base.onlyKey != NULL)
2987 : : {
3628 rhaas@postgresql.org 2988 : 21434 : qsort_ssup(state->memtuples, state->memtupcount,
1327 akorotkov@postgresql 2989 : 21434 : state->base.onlyKey);
2990 : : }
2991 : : else
2992 : : {
3628 rhaas@postgresql.org 2993 : 11305 : qsort_tuple(state->memtuples,
2994 : 11305 : state->memtupcount,
2995 : : state->base.comparetup,
2996 : : state);
2997 : : }
2998 : : }
2999 : : }
3000 : :
3001 : : /*
3002 : : * Insert a new tuple into an empty or existing heap, maintaining the
3003 : : * heap invariant. Caller is responsible for ensuring there's room.
3004 : : *
3005 : : * Note: For some callers, tuple points to a memtuples[] entry above the
3006 : : * end of the heap. This is safe as long as it's not immediately adjacent
3007 : : * to the end of the heap (ie, in the [memtupcount] array entry) --- if it
3008 : : * is, it might get overwritten before being moved into the heap!
3009 : : */
3010 : : static void
3089 3011 : 10985 : tuplesort_heap_insert(Tuplesortstate *state, SortTuple *tuple)
3012 : : {
3013 : : SortTuple *memtuples;
3014 : : int j;
3015 : :
9633 tgl@sss.pgh.pa.us 3016 : 10985 : memtuples = state->memtuples;
7322 3017 [ - + ]: 10985 : Assert(state->memtupcount < state->memtupsize);
3018 : :
5108 rhaas@postgresql.org 3019 [ + + ]: 10985 : CHECK_FOR_INTERRUPTS();
3020 : :
3021 : : /*
3022 : : * Sift-up the new entry, per Knuth 5.2.3 exercise 16. Note that Knuth is
3023 : : * using 1-based array indexes, not 0-based.
3024 : : */
9633 tgl@sss.pgh.pa.us 3025 : 10985 : j = state->memtupcount++;
3026 [ + + ]: 31178 : while (j > 0)
3027 : : {
9468 bruce@momjian.us 3028 : 27741 : int i = (j - 1) >> 1;
3029 : :
3089 rhaas@postgresql.org 3030 [ + + ]: 27741 : if (COMPARETUP(state, tuple, &memtuples[i]) >= 0)
9646 tgl@sss.pgh.pa.us 3031 : 7548 : break;
9633 3032 : 20193 : memtuples[j] = memtuples[i];
9646 3033 : 20193 : j = i;
3034 : : }
7322 3035 : 10985 : memtuples[j] = *tuple;
9646 3036 : 10985 : }
3037 : :
3038 : : /*
3039 : : * Remove the tuple at state->memtuples[0] from the heap. Decrement
3040 : : * memtupcount, and sift up to maintain the heap invariant.
3041 : : *
3042 : : * The caller has already free'd the tuple the top node points to,
3043 : : * if necessary.
3044 : : */
3045 : : static void
3089 rhaas@postgresql.org 3046 : 10750 : tuplesort_heap_delete_top(Tuplesortstate *state)
3047 : : {
7322 tgl@sss.pgh.pa.us 3048 : 10750 : SortTuple *memtuples = state->memtuples;
3049 : : SortTuple *tuple;
3050 : :
9633 3051 [ + + ]: 10750 : if (--state->memtupcount <= 0)
9646 3052 : 166 : return;
3053 : :
3054 : : /*
3055 : : * Remove the last tuple in the heap, and re-insert it, by replacing the
3056 : : * current top node with it.
3057 : : */
3472 heikki.linnakangas@i 3058 : 10584 : tuple = &memtuples[state->memtupcount];
3089 rhaas@postgresql.org 3059 : 10584 : tuplesort_heap_replace_top(state, tuple);
3060 : : }
3061 : :
3062 : : /*
3063 : : * Replace the tuple at state->memtuples[0] with a new tuple. Sift up to
3064 : : * maintain the heap invariant.
3065 : : *
3066 : : * This corresponds to Knuth's "sift-up" algorithm (Algorithm 5.2.3H,
3067 : : * Heapsort, steps H3-H8).
3068 : : */
3069 : : static void
3070 : 3047705 : tuplesort_heap_replace_top(Tuplesortstate *state, SortTuple *tuple)
3071 : : {
3472 heikki.linnakangas@i 3072 : 3047705 : SortTuple *memtuples = state->memtuples;
3073 : : unsigned int i,
3074 : : n;
3075 : :
3076 [ - + ]: 3047705 : Assert(state->memtupcount >= 1);
3077 : :
5108 rhaas@postgresql.org 3078 [ - + ]: 3047705 : CHECK_FOR_INTERRUPTS();
3079 : :
3080 : : /*
3081 : : * state->memtupcount is "int", but we use "unsigned int" for i, j, n.
3082 : : * This prevents overflow in the "2 * i + 1" calculation, since at the top
3083 : : * of the loop we must have i < n <= INT_MAX <= UINT_MAX/2.
3084 : : */
9633 tgl@sss.pgh.pa.us 3085 : 3047705 : n = state->memtupcount;
9646 3086 : 3047705 : i = 0; /* i is where the "hole" is */
3087 : : for (;;)
9633 3088 : 904773 : {
3168 3089 : 3952478 : unsigned int j = 2 * i + 1;
3090 : :
9646 3091 [ + + ]: 3952478 : if (j >= n)
3092 : 577847 : break;
9468 bruce@momjian.us 3093 [ + + + + ]: 4618182 : if (j + 1 < n &&
3089 rhaas@postgresql.org 3094 : 1243551 : COMPARETUP(state, &memtuples[j], &memtuples[j + 1]) > 0)
9646 tgl@sss.pgh.pa.us 3095 : 498135 : j++;
3089 rhaas@postgresql.org 3096 [ + + ]: 3374631 : if (COMPARETUP(state, tuple, &memtuples[j]) <= 0)
9646 tgl@sss.pgh.pa.us 3097 : 2469858 : break;
9633 3098 : 904773 : memtuples[i] = memtuples[j];
9646 3099 : 904773 : i = j;
3100 : : }
7322 3101 : 3047705 : memtuples[i] = *tuple;
9646 3102 : 3047705 : }
3103 : :
3104 : : /*
3105 : : * Function to reverse the sort direction from its current state
3106 : : *
3107 : : * It is not safe to call this when performing hash tuplesorts
3108 : : */
3109 : : static void
4146 rhaas@postgresql.org 3110 : 422 : reversedirection(Tuplesortstate *state)
3111 : : {
1327 akorotkov@postgresql 3112 : 422 : SortSupport sortKey = state->base.sortKeys;
3113 : : int nkey;
3114 : :
3115 [ + + ]: 1024 : for (nkey = 0; nkey < state->base.nKeys; nkey++, sortKey++)
3116 : : {
4146 rhaas@postgresql.org 3117 : 602 : sortKey->ssup_reverse = !sortKey->ssup_reverse;
3118 : 602 : sortKey->ssup_nulls_first = !sortKey->ssup_nulls_first;
3119 : : }
3120 : 422 : }
3121 : :
3122 : :
3123 : : /*
3124 : : * Tape interface routines
3125 : : */
3126 : :
3127 : : static unsigned int
1609 heikki.linnakangas@i 3128 : 2933458 : getlen(LogicalTape *tape, bool eofOK)
3129 : : {
3130 : : unsigned int len;
3131 : :
3132 [ - + ]: 2933458 : if (LogicalTapeRead(tape,
3133 : : &len, sizeof(len)) != sizeof(len))
8269 tgl@sss.pgh.pa.us 3134 [ # # ]:UBC 0 : elog(ERROR, "unexpected end of tape");
9646 tgl@sss.pgh.pa.us 3135 [ + + - + ]:CBC 2933458 : if (len == 0 && !eofOK)
8269 tgl@sss.pgh.pa.us 3136 [ # # ]:UBC 0 : elog(ERROR, "unexpected end of data");
9646 tgl@sss.pgh.pa.us 3137 :CBC 2933458 : return len;
3138 : : }
3139 : :
3140 : : static void
1609 heikki.linnakangas@i 3141 : 912 : markrunend(LogicalTape *tape)
3142 : : {
9468 bruce@momjian.us 3143 : 912 : unsigned int len = 0;
3144 : :
1171 peter@eisentraut.org 3145 : 912 : LogicalTapeWrite(tape, &len, sizeof(len));
9646 tgl@sss.pgh.pa.us 3146 : 912 : }
3147 : :
3148 : : /*
3149 : : * Get memory for tuple from within READTUP() routine.
3150 : : *
3151 : : * We use next free slot from the slab allocator, or palloc() if the tuple
3152 : : * is too large for that.
3153 : : */
3154 : : void *
1327 akorotkov@postgresql 3155 : 2727517 : tuplesort_readtup_alloc(Tuplesortstate *state, Size tuplen)
3156 : : {
3157 : : SlabSlot *buf;
3158 : :
3159 : : /*
3160 : : * We pre-allocate enough slots in the slab arena that we should never run
3161 : : * out.
3162 : : */
3450 heikki.linnakangas@i 3163 [ - + ]: 2727517 : Assert(state->slabFreeHead);
3164 : :
3165 [ + + - + ]: 2727517 : if (tuplen > SLAB_SLOT_SIZE || !state->slabFreeHead)
1327 akorotkov@postgresql 3166 : 3 : return MemoryContextAlloc(state->base.sortcontext, tuplen);
3167 : : else
3168 : : {
3450 heikki.linnakangas@i 3169 : 2727514 : buf = state->slabFreeHead;
3170 : : /* Reuse this slot */
3171 : 2727514 : state->slabFreeHead = buf->nextfree;
3172 : :
3173 : 2727514 : return buf;
3174 : : }
3175 : : }
3176 : :
3177 : :
3178 : : /*
3179 : : * Parallel sort routines
3180 : : */
3181 : :
3182 : : /*
3183 : : * tuplesort_estimate_shared - estimate required shared memory allocation
3184 : : *
3185 : : * nWorkers is an estimate of the number of workers (it's the number that
3186 : : * will be requested).
3187 : : */
3188 : : Size
2963 rhaas@postgresql.org 3189 : 100 : tuplesort_estimate_shared(int nWorkers)
3190 : : {
3191 : : Size tapesSize;
3192 : :
3193 [ - + ]: 100 : Assert(nWorkers > 0);
3194 : :
3195 : : /* Make sure that BufFile shared state is MAXALIGN'd */
3196 : 100 : tapesSize = mul_size(sizeof(TapeShare), nWorkers);
3197 : 100 : tapesSize = MAXALIGN(add_size(tapesSize, offsetof(Sharedsort, tapes)));
3198 : :
3199 : 100 : return tapesSize;
3200 : : }
3201 : :
3202 : : /*
3203 : : * tuplesort_initialize_shared - initialize shared tuplesort state
3204 : : *
3205 : : * Must be called from leader process before workers are launched, to
3206 : : * establish state needed up-front for worker tuplesortstates. nWorkers
3207 : : * should match the argument passed to tuplesort_estimate_shared().
3208 : : */
3209 : : void
3210 : 137 : tuplesort_initialize_shared(Sharedsort *shared, int nWorkers, dsm_segment *seg)
3211 : : {
3212 : : int i;
3213 : :
3214 [ - + ]: 137 : Assert(nWorkers > 0);
3215 : :
3216 : 137 : SpinLockInit(&shared->mutex);
3217 : 137 : shared->currentWorker = 0;
3218 : 137 : shared->workersFinished = 0;
3219 : 137 : SharedFileSetInit(&shared->fileset, seg);
3220 : 137 : shared->nTapes = nWorkers;
3221 [ + + ]: 431 : for (i = 0; i < nWorkers; i++)
3222 : : {
3223 : 294 : shared->tapes[i].firstblocknumber = 0L;
3224 : : }
3225 : 137 : }
3226 : :
3227 : : /*
3228 : : * tuplesort_attach_shared - attach to shared tuplesort state
3229 : : *
3230 : : * Must be called by all worker processes.
3231 : : */
3232 : : void
3233 : 154 : tuplesort_attach_shared(Sharedsort *shared, dsm_segment *seg)
3234 : : {
3235 : : /* Attach to SharedFileSet */
3236 : 154 : SharedFileSetAttach(&shared->fileset, seg);
3237 : 154 : }
3238 : :
3239 : : /*
3240 : : * worker_get_identifier - Assign and return ordinal identifier for worker
3241 : : *
3242 : : * The order in which these are assigned is not well defined, and should not
3243 : : * matter; worker numbers across parallel sort participants need only be
3244 : : * distinct and gapless. logtape.c requires this.
3245 : : *
3246 : : * Note that the identifiers assigned from here have no relation to
3247 : : * ParallelWorkerNumber number, to avoid making any assumption about
3248 : : * caller's requirements. However, we do follow the ParallelWorkerNumber
3249 : : * convention of representing a non-worker with worker number -1. This
3250 : : * includes the leader, as well as serial Tuplesort processes.
3251 : : */
3252 : : static int
3253 : 290 : worker_get_identifier(Tuplesortstate *state)
3254 : : {
3255 : 290 : Sharedsort *shared = state->shared;
3256 : : int worker;
3257 : :
3258 [ + - - + ]: 290 : Assert(WORKER(state));
3259 : :
3260 [ - + ]: 290 : SpinLockAcquire(&shared->mutex);
3261 : 290 : worker = shared->currentWorker++;
3262 : 290 : SpinLockRelease(&shared->mutex);
3263 : :
3264 : 290 : return worker;
3265 : : }
3266 : :
3267 : : /*
3268 : : * worker_freeze_result_tape - freeze worker's result tape for leader
3269 : : *
3270 : : * This is called by workers just after the result tape has been determined,
3271 : : * instead of calling LogicalTapeFreeze() directly. They do so because
3272 : : * workers require a few additional steps over similar serial
3273 : : * TSS_SORTEDONTAPE external sort cases, which also happen here. The extra
3274 : : * steps are around freeing now unneeded resources, and representing to
3275 : : * leader that worker's input run is available for its merge.
3276 : : *
3277 : : * There should only be one final output run for each worker, which consists
3278 : : * of all tuples that were originally input into worker.
3279 : : */
3280 : : static void
3281 : 290 : worker_freeze_result_tape(Tuplesortstate *state)
3282 : : {
3283 : 290 : Sharedsort *shared = state->shared;
3284 : : TapeShare output;
3285 : :
3286 [ + - - + ]: 290 : Assert(WORKER(state));
1609 heikki.linnakangas@i 3287 [ - + ]: 290 : Assert(state->result_tape != NULL);
2963 rhaas@postgresql.org 3288 [ - + ]: 290 : Assert(state->memtupcount == 0);
3289 : :
3290 : : /*
3291 : : * Free most remaining memory, in case caller is sensitive to our holding
3292 : : * on to it. memtuples may not be a tiny merge heap at this point.
3293 : : */
3294 : 290 : pfree(state->memtuples);
3295 : : /* Be tidy */
3296 : 290 : state->memtuples = NULL;
3297 : 290 : state->memtupsize = 0;
3298 : :
3299 : : /*
3300 : : * Parallel worker requires result tape metadata, which is to be stored in
3301 : : * shared memory for leader
3302 : : */
1609 heikki.linnakangas@i 3303 : 290 : LogicalTapeFreeze(state->result_tape, &output);
3304 : :
3305 : : /* Store properties of output tape, and update finished worker count */
2963 rhaas@postgresql.org 3306 [ - + ]: 290 : SpinLockAcquire(&shared->mutex);
3307 : 290 : shared->tapes[state->worker] = output;
3308 : 290 : shared->workersFinished++;
3309 : 290 : SpinLockRelease(&shared->mutex);
3310 : 290 : }
3311 : :
3312 : : /*
3313 : : * worker_nomergeruns - dump memtuples in worker, without merging
3314 : : *
3315 : : * This called as an alternative to mergeruns() with a worker when no
3316 : : * merging is required.
3317 : : */
3318 : : static void
3319 : 290 : worker_nomergeruns(Tuplesortstate *state)
3320 : : {
3321 [ + - - + ]: 290 : Assert(WORKER(state));
1609 heikki.linnakangas@i 3322 [ - + ]: 290 : Assert(state->result_tape == NULL);
3323 [ - + ]: 290 : Assert(state->nOutputRuns == 1);
3324 : :
3325 : 290 : state->result_tape = state->destTape;
2963 rhaas@postgresql.org 3326 : 290 : worker_freeze_result_tape(state);
3327 : 290 : }
3328 : :
3329 : : /*
3330 : : * leader_takeover_tapes - create tapeset for leader from worker tapes
3331 : : *
3332 : : * So far, leader Tuplesortstate has performed no actual sorting. By now, all
3333 : : * sorting has occurred in workers, all of which must have already returned
3334 : : * from tuplesort_performsort().
3335 : : *
3336 : : * When this returns, leader process is left in a state that is virtually
3337 : : * indistinguishable from it having generated runs as a serial external sort
3338 : : * might have.
3339 : : */
3340 : : static void
3341 : 99 : leader_takeover_tapes(Tuplesortstate *state)
3342 : : {
3343 : 99 : Sharedsort *shared = state->shared;
3344 : 99 : int nParticipants = state->nParticipants;
3345 : : int workersFinished;
3346 : : int j;
3347 : :
3348 [ + - - + ]: 99 : Assert(LEADER(state));
3349 [ - + ]: 99 : Assert(nParticipants >= 1);
3350 : :
3351 [ - + ]: 99 : SpinLockAcquire(&shared->mutex);
3352 : 99 : workersFinished = shared->workersFinished;
3353 : 99 : SpinLockRelease(&shared->mutex);
3354 : :
3355 [ - + ]: 99 : if (nParticipants != workersFinished)
2963 rhaas@postgresql.org 3356 [ # # ]:UBC 0 : elog(ERROR, "cannot take over tapes before all workers finish");
3357 : :
3358 : : /*
3359 : : * Create the tapeset from worker tapes, including a leader-owned tape at
3360 : : * the end. Parallel workers are far more expensive than logical tapes,
3361 : : * so the number of tapes allocated here should never be excessive.
3362 : : */
1609 heikki.linnakangas@i 3363 :CBC 99 : inittapestate(state, nParticipants);
3364 : 99 : state->tapeset = LogicalTapeSetCreate(false, &shared->fileset, -1);
3365 : :
3366 : : /*
3367 : : * Set currentRun to reflect the number of runs we will merge (it's not
3368 : : * used for anything, this is just pro forma)
3369 : : */
2963 rhaas@postgresql.org 3370 : 99 : state->currentRun = nParticipants;
3371 : :
3372 : : /*
3373 : : * Initialize the state to look the same as after building the initial
3374 : : * runs.
3375 : : *
3376 : : * There will always be exactly 1 run per worker, and exactly one input
3377 : : * tape per run, because workers always output exactly 1 run, even when
3378 : : * there were no input tuples for workers to sort.
3379 : : */
1609 heikki.linnakangas@i 3380 : 99 : state->inputTapes = NULL;
3381 : 99 : state->nInputTapes = 0;
3382 : 99 : state->nInputRuns = 0;
3383 : :
3384 : 99 : state->outputTapes = palloc0(nParticipants * sizeof(LogicalTape *));
3385 : 99 : state->nOutputTapes = nParticipants;
3386 : 99 : state->nOutputRuns = nParticipants;
3387 : :
3388 [ + + ]: 315 : for (j = 0; j < nParticipants; j++)
3389 : : {
3390 : 216 : state->outputTapes[j] = LogicalTapeImport(state->tapeset, j, &shared->tapes[j]);
3391 : : }
3392 : :
2963 rhaas@postgresql.org 3393 : 99 : state->status = TSS_BUILDRUNS;
3394 : 99 : }
3395 : :
3396 : : /*
3397 : : * Convenience routine to free a tuple previously loaded into sort memory
3398 : : */
3399 : : static void
6890 tgl@sss.pgh.pa.us 3400 : 1877004 : free_sort_tuple(Tuplesortstate *state, SortTuple *stup)
3401 : : {
1706 drowley@postgresql.o 3402 [ + + ]: 1877004 : if (stup->tuple)
3403 : : {
3404 : 1799843 : FREEMEM(state, GetMemoryChunkSpace(stup->tuple));
3405 : 1799843 : pfree(stup->tuple);
3406 : 1799843 : stup->tuple = NULL;
3407 : : }
6890 tgl@sss.pgh.pa.us 3408 : 1877004 : }
3409 : :
3410 : : int
1443 john.naylor@postgres 3411 :GBC 3709207 : ssup_datum_unsigned_cmp(Datum x, Datum y, SortSupport ssup)
3412 : : {
3413 [ + + ]: 3709207 : if (x < y)
3414 : 1565712 : return -1;
3415 [ + + ]: 2143495 : else if (x > y)
3416 : 562685 : return 1;
3417 : : else
3418 : 1580810 : return 0;
3419 : : }
3420 : :
3421 : : int
1443 john.naylor@postgres 3422 :CBC 2788789 : ssup_datum_signed_cmp(Datum x, Datum y, SortSupport ssup)
3423 : : {
1404 drowley@postgresql.o 3424 : 2788789 : int64 xx = DatumGetInt64(x);
3425 : 2788789 : int64 yy = DatumGetInt64(y);
3426 : :
1443 john.naylor@postgres 3427 [ + + ]: 2788789 : if (xx < yy)
3428 : 2373399 : return -1;
3429 [ + + ]: 415390 : else if (xx > yy)
3430 : 188045 : return 1;
3431 : : else
3432 : 227345 : return 0;
3433 : : }
3434 : :
3435 : : int
3436 : 113596972 : ssup_datum_int32_cmp(Datum x, Datum y, SortSupport ssup)
3437 : : {
1404 drowley@postgresql.o 3438 : 113596972 : int32 xx = DatumGetInt32(x);
3439 : 113596972 : int32 yy = DatumGetInt32(y);
3440 : :
1443 john.naylor@postgres 3441 [ + + ]: 113596972 : if (xx < yy)
3442 : 30421977 : return -1;
3443 [ + + ]: 83174995 : else if (xx > yy)
3444 : 24412270 : return 1;
3445 : : else
3446 : 58762725 : return 0;
3447 : : }
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