xref: /dports/databases/postgresql96-docs/postgresql-9.6.24/src/backend/utils/sort/tuplesort.c

/*-------------------------------------------------------------------------
 *
 * tuplesort.c
 *	  Generalized tuple sorting routines.
 *
 * This module handles sorting of heap tuples, index tuples, or single
 * Datums (and could easily support other kinds of sortable objects,
 * if necessary).  It works efficiently for both small and large amounts
 * of data.  Small amounts are sorted in-memory using qsort().  Large
 * amounts are sorted using temporary files and a standard external sort
 * algorithm.
 *
 * See Knuth, volume 3, for more than you want to know about the external
 * sorting algorithm.  Historically, we divided the input into sorted runs
 * using replacement selection, in the form of a priority tree implemented
 * as a heap (essentially his Algorithm 5.2.3H), but now we only do that
 * for the first run, and only if the run would otherwise end up being very
 * short.  We merge the runs using polyphase merge, Knuth's Algorithm
 * 5.4.2D.  The logical "tapes" used by Algorithm D are implemented by
 * logtape.c, which avoids space wastage by recycling disk space as soon
 * as each block is read from its "tape".
 *
 * We do not use Knuth's recommended data structure (Algorithm 5.4.1R) for
 * the replacement selection, because it uses a fixed number of records
 * in memory at all times.  Since we are dealing with tuples that may vary
 * considerably in size, we want to be able to vary the number of records
 * kept in memory to ensure full utilization of the allowed sort memory
 * space.  So, we keep the tuples in a variable-size heap, with the next
 * record to go out at the top of the heap.  Like Algorithm 5.4.1R, each
 * record is stored with the run number that it must go into, and we use
 * (run number, key) as the ordering key for the heap.  When the run number
 * at the top of the heap changes, we know that no more records of the prior
 * run are left in the heap.  Note that there are in practice only ever two
 * distinct run numbers, because since PostgreSQL 9.6, we only use
 * replacement selection to form the first run.
 *
 * In PostgreSQL 9.6, a heap (based on Knuth's Algorithm H, with some small
 * customizations) is only used with the aim of producing just one run,
 * thereby avoiding all merging.  Only the first run can use replacement
 * selection, which is why there are now only two possible valid run
 * numbers, and why heapification is customized to not distinguish between
 * tuples in the second run (those will be quicksorted).  We generally
 * prefer a simple hybrid sort-merge strategy, where runs are sorted in much
 * the same way as the entire input of an internal sort is sorted (using
 * qsort()).  The replacement_sort_tuples GUC controls the limited remaining
 * use of replacement selection for the first run.
 *
 * There are several reasons to favor a hybrid sort-merge strategy.
 * Maintaining a priority tree/heap has poor CPU cache characteristics.
 * Furthermore, the growth in main memory sizes has greatly diminished the
 * value of having runs that are larger than available memory, even in the
 * case where there is partially sorted input and runs can be made far
 * larger by using a heap.  In most cases, a single-pass merge step is all
 * that is required even when runs are no larger than available memory.
 * Avoiding multiple merge passes was traditionally considered to be the
 * major advantage of using replacement selection.
 *
 * The approximate amount of memory allowed for any one sort operation
 * is specified in kilobytes by the caller (most pass work_mem).  Initially,
 * we absorb tuples and simply store them in an unsorted array as long as
 * we haven't exceeded workMem.  If we reach the end of the input without
 * exceeding workMem, we sort the array using qsort() and subsequently return
 * tuples just by scanning the tuple array sequentially.  If we do exceed
 * workMem, we begin to emit tuples into sorted runs in temporary tapes.
 * When tuples are dumped in batch after quicksorting, we begin a new run
 * with a new output tape (selected per Algorithm D).  After the end of the
 * input is reached, we dump out remaining tuples in memory into a final run
 * (or two, when replacement selection is still used), then merge the runs
 * using Algorithm D.
 *
 * When merging runs, we use a heap containing just the frontmost tuple from
 * each source run; we repeatedly output the smallest tuple and insert the
 * next tuple from its source tape (if any).  When the heap empties, the merge
 * is complete.  The basic merge algorithm thus needs very little memory ---
 * only M tuples for an M-way merge, and M is constrained to a small number.
 * However, we can still make good use of our full workMem allocation by
 * pre-reading additional tuples from each source tape.  Without prereading,
 * our access pattern to the temporary file would be very erratic; on average
 * we'd read one block from each of M source tapes during the same time that
 * we're writing M blocks to the output tape, so there is no sequentiality of
 * access at all, defeating the read-ahead methods used by most Unix kernels.
 * Worse, the output tape gets written into a very random sequence of blocks
 * of the temp file, ensuring that things will be even worse when it comes
 * time to read that tape.  A straightforward merge pass thus ends up doing a
 * lot of waiting for disk seeks.  We can improve matters by prereading from
 * each source tape sequentially, loading about workMem/M bytes from each tape
 * in turn.  Then we run the merge algorithm, writing but not reading until
 * one of the preloaded tuple series runs out.  Then we switch back to preread
 * mode, fill memory again, and repeat.  This approach helps to localize both
 * read and write accesses.
 *
 * When the caller requests random access to the sort result, we form
 * the final sorted run on a logical tape which is then "frozen", so
 * that we can access it randomly.  When the caller does not need random
 * access, we return from tuplesort_performsort() as soon as we are down
 * to one run per logical tape.  The final merge is then performed
 * on-the-fly as the caller repeatedly calls tuplesort_getXXX; this
 * saves one cycle of writing all the data out to disk and reading it in.
 *
 * Before Postgres 8.2, we always used a seven-tape polyphase merge, on the
 * grounds that 7 is the "sweet spot" on the tapes-to-passes curve according
 * to Knuth's figure 70 (section 5.4.2).  However, Knuth is assuming that
 * tape drives are expensive beasts, and in particular that there will always
 * be many more runs than tape drives.  In our implementation a "tape drive"
 * doesn't cost much more than a few Kb of memory buffers, so we can afford
 * to have lots of them.  In particular, if we can have as many tape drives
 * as sorted runs, we can eliminate any repeated I/O at all.  In the current
 * code we determine the number of tapes M on the basis of workMem: we want
 * workMem/M to be large enough that we read a fair amount of data each time
 * we preread from a tape, so as to maintain the locality of access described
 * above.  Nonetheless, with large workMem we can have many tapes.
 *
 *
 * Portions Copyright (c) 1996-2016, PostgreSQL Global Development Group
 * Portions Copyright (c) 1994, Regents of the University of California
 *
 * IDENTIFICATION
 *	  src/backend/utils/sort/tuplesort.c
 *
 *-------------------------------------------------------------------------
 */

#include "postgres.h"

#include <limits.h>

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


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

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

#ifdef DEBUG_BOUNDED_SORT
bool		optimize_bounded_sort = true;
#endif


/*
 * The objects we actually sort are SortTuple structs.  These contain
 * a pointer to the tuple proper (might be a MinimalTuple or IndexTuple),
 * which is a separate palloc chunk --- we assume it is just one chunk and
 * can be freed by a simple pfree() (except during final on-the-fly merge,
 * when memory is used in batch).  SortTuples also contain the tuple's
 * first key column in Datum/nullflag format, and an index integer.
 *
 * Storing the first key column lets us save heap_getattr or index_getattr
 * calls during tuple comparisons.  We could extract and save all the key
 * columns not just the first, but this would increase code complexity and
 * overhead, and wouldn't actually save any comparison cycles in the common
 * case where the first key determines the comparison result.  Note that
 * for a pass-by-reference datatype, datum1 points into the "tuple" storage.
 *
 * There is one special case: when the sort support infrastructure provides an
 * "abbreviated key" representation, where the key is (typically) a pass by
 * value proxy for a pass by reference type.  In this case, the abbreviated key
 * is stored in datum1 in place of the actual first key column.
 *
 * When sorting single Datums, the data value is represented directly by
 * datum1/isnull1 for pass by value types (or null values).  If the datatype is
 * pass-by-reference and isnull1 is false, then "tuple" points to a separately
 * palloc'd data value, otherwise "tuple" is NULL.  The value of datum1 is then
 * either the same pointer as "tuple", or is an abbreviated key value as
 * described above.  Accordingly, "tuple" is always used in preference to
 * datum1 as the authoritative value for pass-by-reference cases.
 *
 * While building initial runs, tupindex holds the tuple's run number.
 * Historically, the run number could meaningfully distinguish many runs, but
 * it now only distinguishes RUN_FIRST and HEAP_RUN_NEXT, since replacement
 * selection is always abandoned after the first run; no other run number
 * should be represented here.  During merge passes, we re-use it to hold the
 * input tape number that each tuple in the heap was read from, or to hold the
 * index of the next tuple pre-read from the same tape in the case of pre-read
 * entries.  tupindex goes unused if the sort occurs entirely in memory.
 */
typedef struct
{
	void	   *tuple;			/* the tuple itself */
	Datum		datum1;			/* value of first key column */
	bool		isnull1;		/* is first key column NULL? */
	int			tupindex;		/* see notes above */
} SortTuple;


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

/*
 * Parameters for calculation of number of tapes to use --- see inittapes()
 * and tuplesort_merge_order().
 *
 * In this calculation we assume that each tape will cost us about 3 blocks
 * worth of buffer space (which is an underestimate for very large data
 * volumes, but it's probably close enough --- see logtape.c).
 *
 * MERGE_BUFFER_SIZE is how much data we'd like to read from each input
 * tape during a preread cycle (see discussion at top of file).
 */
#define MINORDER		6		/* minimum merge order */
#define TAPE_BUFFER_OVERHEAD		(BLCKSZ * 3)
#define MERGE_BUFFER_SIZE			(BLCKSZ * 32)

 /*
  * Run numbers, used during external sort operations.
  *
  * HEAP_RUN_NEXT is only used for SortTuple.tupindex, never state.currentRun.
  */
#define RUN_FIRST		0
#define HEAP_RUN_NEXT	INT_MAX
#define RUN_SECOND		1

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

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

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

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

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

	/*
	 * Function to read a stored tuple from tape back into memory. 'len' is
	 * the already-read length of the stored tuple.  Create a palloc'd copy,
	 * initialize tuple/datum1/isnull1 in the target SortTuple struct, and
	 * decrease state->availMem by the amount of memory space consumed. (See
	 * batchUsed notes for details on how memory is handled when incremental
	 * accounting is abandoned.)
	 */
	void		(*readtup) (Tuplesortstate *state, SortTuple *stup,
										int tapenum, unsigned int len);

	/*
	 * Function to move a caller tuple.  This is usually implemented as a
	 * memmove() shim, but function may also perform additional fix-up of
	 * caller tuple where needed.  Batch memory support requires the movement
	 * of caller tuples from one location in memory to another.
	 */
	void		(*movetup) (void *dest, void *src, unsigned int len);

	/*
	 * This array holds the tuples now in sort memory.  If we are in state
	 * INITIAL, the tuples are in no particular order; if we are in state
	 * SORTEDINMEM, the tuples are in final sorted order; in states BUILDRUNS
	 * and FINALMERGE, the tuples are organized in "heap" order per Algorithm
	 * H.  (Note that memtupcount only counts the tuples that are part of the
	 * heap --- during merge passes, memtuples[] entries beyond tapeRange are
	 * never in the heap and are used to hold pre-read tuples.)  In state
	 * SORTEDONTAPE, the array is not used.
	 */
	SortTuple  *memtuples;		/* array of SortTuple structs */
	int			memtupcount;	/* number of tuples currently present */
	int			memtupsize;		/* allocated length of memtuples array */
	bool		growmemtuples;	/* memtuples' growth still underway? */

	/*
	 * Memory for tuples is sometimes allocated in batch, rather than
	 * incrementally.  This implies that incremental memory accounting has
	 * been abandoned.  Currently, this only happens for the final on-the-fly
	 * merge step.  Large batch allocations can store tuples (e.g.
	 * IndexTuples) without palloc() fragmentation and other overhead.
	 */
	bool		batchUsed;

	/*
	 * While building initial runs, this indicates if the replacement
	 * selection strategy is in use.  When it isn't, then a simple hybrid
	 * sort-merge strategy is in use instead (runs are quicksorted).
	 */
	bool		replaceActive;

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

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

	/*
	 * These variables are only used during merge passes.  mergeactive[i] is
	 * true if we are reading an input run from (actual) tape number i and
	 * have not yet exhausted that run.  mergenext[i] is the memtuples index
	 * of the next pre-read tuple (next to be loaded into the heap) for tape
	 * i, or 0 if we are out of pre-read tuples.  mergelast[i] similarly
	 * points to the last pre-read tuple from each tape.  mergeavailslots[i]
	 * is the number of unused memtuples[] slots reserved for tape i, and
	 * mergeavailmem[i] is the amount of unused space allocated for tape i.
	 * mergefreelist and mergefirstfree keep track of unused locations in the
	 * memtuples[] array.  The memtuples[].tupindex fields link together
	 * pre-read tuples for each tape as well as recycled locations in
	 * mergefreelist. It is OK to use 0 as a null link in these lists, because
	 * memtuples[0] is part of the merge heap and is never a pre-read tuple.
	 */
	bool	   *mergeactive;	/* active input run source? */
	int		   *mergenext;		/* first preread tuple for each source */
	int		   *mergelast;		/* last preread tuple for each source */
	int		   *mergeavailslots;	/* slots left for prereading each tape */
	int64	   *mergeavailmem;	/* availMem for prereading each tape */
	int			mergefreelist;	/* head of freelist of recycled slots */
	int			mergefirstfree; /* first slot never used in this merge */

	/*
	 * Per-tape batch state, when final on-the-fly merge consumes memory from
	 * just a few large allocations.
	 *
	 * Aside from the general benefits of performing fewer individual retail
	 * palloc() calls, this also helps make merging more cache efficient,
	 * since each tape's tuples must naturally be accessed sequentially (in
	 * sorted order).
	 */
	int64		spacePerTape;	/* Space (memory) for tuples (not slots) */
	char	  **mergetuples;	/* Each tape's memory allocation */
	char	  **mergecurrent;	/* Current offset into each tape's memory */
	char	  **mergetail;		/* Last item's start point for each tape */
	char	  **mergeoverflow;	/* Retail palloc() "overflow" for each tape */

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

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

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

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

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

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

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

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

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

	/* These are specific to the index_hash subcase: */
	uint32		hash_mask;		/* mask for sortable part of hash code */

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

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

#define COMPARETUP(state,a,b)	((*(state)->comparetup) (a, b, state))
#define COPYTUP(state,stup,tup) ((*(state)->copytup) (state, stup, tup))
#define WRITETUP(state,tape,stup)	((*(state)->writetup) (state, tape, stup))
#define READTUP(state,stup,tape,len) ((*(state)->readtup) (state, stup, tape, len))
#define MOVETUP(dest,src,len) ((*(state)->movetup) (dest, src, len))
#define LACKMEM(state)		((state)->availMem < 0 && !(state)->batchUsed)
#define USEMEM(state,amt)	((state)->availMem -= (amt))
#define FREEMEM(state,amt)	((state)->availMem += (amt))

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

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


static Tuplesortstate *tuplesort_begin_common(int workMem, bool randomAccess);
static void puttuple_common(Tuplesortstate *state, SortTuple *tuple);
static bool consider_abort_common(Tuplesortstate *state);
static bool useselection(Tuplesortstate *state);
static void inittapes(Tuplesortstate *state);
static void selectnewtape(Tuplesortstate *state);
static void mergeruns(Tuplesortstate *state);
static void mergeonerun(Tuplesortstate *state);
static void beginmerge(Tuplesortstate *state, bool finalMergeBatch);
static void batchmemtuples(Tuplesortstate *state);
static void mergebatch(Tuplesortstate *state, int64 spacePerTape);
static void mergebatchone(Tuplesortstate *state, int srcTape,
			  SortTuple *stup, bool *should_free);
static void mergebatchfreetape(Tuplesortstate *state, int srcTape,
				   SortTuple *rtup, bool *should_free);
static void *mergebatchalloc(Tuplesortstate *state, int tapenum, Size tuplen);
static void mergepreread(Tuplesortstate *state);
static void mergeprereadone(Tuplesortstate *state, int srcTape);
static void dumptuples(Tuplesortstate *state, bool alltuples);
static void dumpbatch(Tuplesortstate *state, bool alltuples);
static void make_bounded_heap(Tuplesortstate *state);
static void sort_bounded_heap(Tuplesortstate *state);
static void tuplesort_sort_memtuples(Tuplesortstate *state);
static void tuplesort_heap_insert(Tuplesortstate *state, SortTuple *tuple,
					  int tupleindex, bool checkIndex);
static void tuplesort_heap_siftup(Tuplesortstate *state, bool checkIndex);
static void reversedirection(Tuplesortstate *state);
static unsigned int getlen(Tuplesortstate *state, int tapenum, bool eofOK);
static void markrunend(Tuplesortstate *state, int tapenum);
static void *readtup_alloc(Tuplesortstate *state, int tapenum, Size tuplen);
static int comparetup_heap(const SortTuple *a, const SortTuple *b,
				Tuplesortstate *state);
static void copytup_heap(Tuplesortstate *state, SortTuple *stup, void *tup);
static void writetup_heap(Tuplesortstate *state, int tapenum,
			  SortTuple *stup);
static void readtup_heap(Tuplesortstate *state, SortTuple *stup,
			 int tapenum, unsigned int len);
static void movetup_heap(void *dest, void *src, unsigned int len);
static int comparetup_cluster(const SortTuple *a, const SortTuple *b,
				   Tuplesortstate *state);
static void copytup_cluster(Tuplesortstate *state, SortTuple *stup, void *tup);
static void writetup_cluster(Tuplesortstate *state, int tapenum,
				 SortTuple *stup);
static void readtup_cluster(Tuplesortstate *state, SortTuple *stup,
				int tapenum, unsigned int len);
static void movetup_cluster(void *dest, void *src, unsigned int len);
static int comparetup_index_btree(const SortTuple *a, const SortTuple *b,
					   Tuplesortstate *state);
static int comparetup_index_hash(const SortTuple *a, const SortTuple *b,
					  Tuplesortstate *state);
static void copytup_index(Tuplesortstate *state, SortTuple *stup, void *tup);
static void writetup_index(Tuplesortstate *state, int tapenum,
			   SortTuple *stup);
static void readtup_index(Tuplesortstate *state, SortTuple *stup,
			  int tapenum, unsigned int len);
static void movetup_index(void *dest, void *src, unsigned int len);
static int comparetup_datum(const SortTuple *a, const SortTuple *b,
				 Tuplesortstate *state);
static void copytup_datum(Tuplesortstate *state, SortTuple *stup, void *tup);
static void writetup_datum(Tuplesortstate *state, int tapenum,
			   SortTuple *stup);
static void readtup_datum(Tuplesortstate *state, SortTuple *stup,
			  int tapenum, unsigned int len);
static void movetup_datum(void *dest, void *src, unsigned int len);
static void free_sort_tuple(Tuplesortstate *state, SortTuple *stup);

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


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

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

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

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

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

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

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

	state->status = TSS_INITIAL;
	state->randomAccess = randomAccess;
	state->bounded = false;
	state->tuples = true;
	state->boundUsed = false;
	state->allowedMem = workMem * (int64) 1024;
	state->availMem = state->allowedMem;
	state->sortcontext = sortcontext;
	state->tuplecontext = tuplecontext;
	state->tapeset = NULL;

	state->memtupcount = 0;

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

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

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

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

	state->currentRun = RUN_FIRST;

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

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

	MemoryContextSwitchTo(oldcontext);

	return state;
}

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

	oldcontext = MemoryContextSwitchTo(state->sortcontext);

	AssertArg(nkeys > 0);

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

	state->nKeys = nkeys;

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

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

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

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

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

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

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

		PrepareSortSupportFromOrderingOp(sortOperators[i], sortKey);
	}

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

	MemoryContextSwitchTo(oldcontext);

	return state;
}

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

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

	oldcontext = MemoryContextSwitchTo(state->sortcontext);

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

	state->nKeys = RelationGetNumberOfAttributes(indexRel);

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

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

	state->indexInfo = BuildIndexInfo(indexRel);

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

	indexScanKey = _bt_mkscankey_nodata(indexRel);

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

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

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

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

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

		AssertState(sortKey->ssup_attno != 0);

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

		PrepareSortSupportFromIndexRel(indexRel, strategy, sortKey);
	}

	_bt_freeskey(indexScanKey);

	MemoryContextSwitchTo(oldcontext);

	return state;
}

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

	oldcontext = MemoryContextSwitchTo(state->sortcontext);

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

	state->nKeys = RelationGetNumberOfAttributes(indexRel);

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

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

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

	indexScanKey = _bt_mkscankey_nodata(indexRel);
	state->nKeys = RelationGetNumberOfAttributes(indexRel);

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

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

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

		AssertState(sortKey->ssup_attno != 0);

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

		PrepareSortSupportFromIndexRel(indexRel, strategy, sortKey);
	}

	_bt_freeskey(indexScanKey);

	MemoryContextSwitchTo(oldcontext);

	return state;
}

Tuplesortstate *
tuplesort_begin_index_hash(Relation heapRel,
						   Relation indexRel,
						   uint32 hash_mask,
						   int workMem, bool randomAccess)
{
	Tuplesortstate *state = tuplesort_begin_common(workMem, randomAccess);
	MemoryContext oldcontext;

	oldcontext = MemoryContextSwitchTo(state->sortcontext);

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

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

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

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

	state->hash_mask = hash_mask;

	MemoryContextSwitchTo(oldcontext);

	return state;
}

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

	oldcontext = MemoryContextSwitchTo(state->sortcontext);

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

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

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

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

	state->datumType = datumType;

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

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

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

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

	PrepareSortSupportFromOrderingOp(sortOperator, state->sortKeys);

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

	MemoryContextSwitchTo(oldcontext);

	return state;
}

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

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

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

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

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

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

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

#ifdef TRACE_SORT
	long		spaceUsed;

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

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

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

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

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

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

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

	MemoryContextSwitchTo(oldcontext);

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

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

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

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

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

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

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

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

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

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

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

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

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

	puttuple_common(state, &stup);

	MemoryContextSwitchTo(oldcontext);
}

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

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

	puttuple_common(state, &stup);

	MemoryContextSwitchTo(oldcontext);
}

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

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

	MemoryContextSwitchTo(state->sortcontext);

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

		stup.datum1 = original;

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

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

	puttuple_common(state, &stup);

	MemoryContextSwitchTo(oldcontext);
}

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

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

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

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

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

			stup.datum1 = original;

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

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

	puttuple_common(state, &stup);

	MemoryContextSwitchTo(oldcontext);
}

/*
 * Shared code for tuple and datum cases.
 */
static void
puttuple_common(Tuplesortstate *state, SortTuple *tuple)
{
	switch (state->status)
	{
		case TSS_INITIAL:

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

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

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

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

			/*
			 * Dump tuples until we are back under the limit.
			 */
			dumptuples(state, false);
			break;

		case TSS_BOUNDED:

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

		case TSS_BUILDRUNS:

			/*
			 * Insert the tuple into the heap, with run number currentRun if
			 * it can go into the current run, else HEAP_RUN_NEXT.  The tuple
			 * can go into the current run if it is >= the first
			 * not-yet-output tuple.  (Actually, it could go into the current
			 * run if it is >= the most recently output tuple ... but that
			 * would require keeping around the tuple we last output, and it's
			 * simplest to let writetup free each tuple as soon as it's
			 * written.)
			 *
			 * Note that this only applies when:
			 *
			 * - currentRun is RUN_FIRST
			 *
			 * - Replacement selection is in use (typically it is never used).
			 *
			 * When these two conditions are not both true, all tuples are
			 * appended indifferently, much like the TSS_INITIAL case.
			 *
			 * There should always be room to store the incoming tuple.
			 */
			Assert(!state->replaceActive || state->memtupcount > 0);
			if (state->replaceActive &&
				COMPARETUP(state, tuple, &state->memtuples[0]) >= 0)
			{
				Assert(state->currentRun == RUN_FIRST);

				/*
				 * Insert tuple into first, fully heapified run.
				 *
				 * Unlike classic replacement selection, which this module was
				 * previously based on, only RUN_FIRST tuples are fully
				 * heapified.  Any second/next run tuples are appended
				 * indifferently.  While HEAP_RUN_NEXT tuples may be sifted
				 * out of the way of first run tuples, COMPARETUP() will never
				 * be called for the run's tuples during sifting (only our
				 * initial COMPARETUP() call is required for the tuple, to
				 * determine that the tuple does not belong in RUN_FIRST).
				 */
				tuplesort_heap_insert(state, tuple, state->currentRun, true);
			}
			else
			{
				/*
				 * Tuple was determined to not belong to heapified RUN_FIRST,
				 * or replacement selection not in play.  Append the tuple to
				 * memtuples indifferently.
				 *
				 * dumptuples() does not trust that the next run's tuples are
				 * heapified.  Anything past the first run will always be
				 * quicksorted even when replacement selection is initially
				 * used.  (When it's never used, every tuple still takes this
				 * path.)
				 */
				tuple->tupindex = HEAP_RUN_NEXT;
				state->memtuples[state->memtupcount++] = *tuple;
			}

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

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

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

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

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

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

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

	return false;
}

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

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

	switch (state->status)
	{
		case TSS_INITIAL:

			/*
			 * We were able to accumulate all the tuples within the allowed
			 * amount of memory.  Just qsort 'em and we're done.
			 */
			tuplesort_sort_memtuples(state);
			state->current = 0;
			state->eof_reached = false;
			state->markpos_offset = 0;
			state->markpos_eof = false;
			state->status = TSS_SORTEDINMEM;
			break;

		case TSS_BOUNDED:

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

		case TSS_BUILDRUNS:

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

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

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

	MemoryContextSwitchTo(oldcontext);
}

/*
 * Internal routine to fetch the next tuple in either forward or back
 * direction into *stup.  Returns FALSE if no more tuples.
 * If *should_free is set, the caller must pfree stup.tuple when done with it.
 * Otherwise, caller should not use tuple following next call here.
 *
 * Note:  Public tuplesort fetch routine callers cannot rely on tuple being
 * allocated in their own memory context when should_free is TRUE.  It may be
 * necessary to create a new copy of the tuple to meet the requirements of
 * public fetch routine callers.
 */
static bool
tuplesort_gettuple_common(Tuplesortstate *state, bool forward,
						  SortTuple *stup, bool *should_free)
{
	unsigned int tuplen;

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

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

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

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

		case TSS_SORTEDONTAPE:
			Assert(forward || state->randomAccess);
			Assert(!state->batchUsed);
			*should_free = true;
			if (forward)
			{
				if (state->eof_reached)
					return false;
				if ((tuplen = getlen(state, state->result_tape, true)) != 0)
				{
					READTUP(state, stup, state->result_tape, tuplen);
					return true;
				}
				else
				{
					state->eof_reached = true;
					return false;
				}
			}

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

				/*
				 * Back up to get ending length word of tuple before it.
				 */
				if (!LogicalTapeBackspace(state->tapeset,
										  state->result_tape,
										  tuplen + 2 * sizeof(unsigned int)))
				{
					/*
					 * If that fails, presumably the prev tuple is the first
					 * in the file.  Back up so that it becomes next to read
					 * in forward direction (not obviously right, but that is
					 * what in-memory case does).
					 */
					if (!LogicalTapeBackspace(state->tapeset,
											  state->result_tape,
											  tuplen + sizeof(unsigned int)))
						elog(ERROR, "bogus tuple length in backward scan");
					return false;
				}
			}

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

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

		case TSS_FINALMERGE:
			Assert(forward);
			Assert(state->batchUsed || !state->tuples);
			/* For now, assume tuple is stored in tape's batch memory */
			*should_free = false;

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

				/*
				 * Returned tuple is still counted in our memory space most of
				 * the time.  See mergebatchone() for discussion of why caller
				 * may occasionally be required to free returned tuple, and
				 * how preread memory is managed with regard to edge cases
				 * more generally.
				 */
				*stup = state->memtuples[0];
				tuplesort_heap_siftup(state, false);
				if ((tupIndex = state->mergenext[srcTape]) == 0)
				{
					/*
					 * out of preloaded data on this tape, try to read more
					 *
					 * Unlike mergeonerun(), we only preload from the single
					 * tape that's run dry, though not before preparing its
					 * batch memory for a new round of sequential consumption.
					 * See mergepreread() comments.
					 */
					if (state->batchUsed)
						mergebatchone(state, srcTape, stup, should_free);

					mergeprereadone(state, srcTape);

					/*
					 * if still no data, we've reached end of run on this tape
					 */
					if ((tupIndex = state->mergenext[srcTape]) == 0)
					{
						/* Free tape's buffer, avoiding dangling pointer */
						if (state->batchUsed)
							mergebatchfreetape(state, srcTape, stup, should_free);
						return true;
					}
				}
				/* pull next preread tuple from list, insert in heap */
				newtup = &state->memtuples[tupIndex];
				state->mergenext[srcTape] = newtup->tupindex;
				if (state->mergenext[srcTape] == 0)
					state->mergelast[srcTape] = 0;
				tuplesort_heap_insert(state, newtup, srcTape, false);
				/* put the now-unused memtuples entry on the freelist */
				newtup->tupindex = state->mergefreelist;
				state->mergefreelist = tupIndex;
				state->mergeavailslots[srcTape]++;
				return true;
			}
			return false;

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

/*
 * Fetch the next tuple in either forward or back direction.
 * If successful, put tuple in slot and return TRUE; else, clear the slot
 * and return FALSE.
 *
 * Caller may optionally be passed back abbreviated value (on TRUE return
 * value) when abbreviation was used, which can be used to cheaply avoid
 * equality checks that might otherwise be required.  Caller can safely make a
 * determination of "non-equal tuple" based on simple binary inequality.  A
 * NULL value in leading attribute will set abbreviated value to zeroed
 * representation, which caller may rely on in abbreviated inequality check.
 *
 * The slot receives a tuple that's been copied into the caller's memory
 * context, so that it will stay valid regardless of future manipulations of
 * the tuplesort's state (up to and including deleting the tuplesort).
 * This differs from similar routines for other types of tuplesorts.
 */
bool
tuplesort_gettupleslot(Tuplesortstate *state, bool forward,
					   TupleTableSlot *slot, Datum *abbrev)
{
	MemoryContext oldcontext = MemoryContextSwitchTo(state->sortcontext);
	SortTuple	stup;
	bool		should_free;

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

	MemoryContextSwitchTo(oldcontext);

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

		/*
		 * Callers rely on tuple being in their own memory context, which is
		 * not guaranteed by tuplesort_gettuple_common(), even when should_free
		 * is set to TRUE.  We must always copy here, since our interface does
		 * not allow callers to opt into arrangement where tuple memory can go
		 * away on the next call here, or after tuplesort_end() is called.
		 */
		ExecStoreMinimalTuple(heap_copy_minimal_tuple((MinimalTuple) stup.tuple),
							  slot, true);

		/*
		 * Free local copy if needed.  It would be very invasive to get
		 * tuplesort_gettuple_common() to allocate tuple in caller's context
		 * for us, so we just do this instead.
		 */
		if (should_free)
			pfree(stup.tuple);

		return true;
	}
	else
	{
		ExecClearTuple(slot);
		return false;
	}
}

/*
 * Fetch the next tuple in either forward or back direction.
 * Returns NULL if no more tuples.  If *should_free is set, the
 * caller must pfree the returned tuple when done with it.
 * If it is not set, caller should not use tuple following next
 * call here.  It's never okay to use it after tuplesort_end().
 */
HeapTuple
tuplesort_getheaptuple(Tuplesortstate *state, bool forward, bool *should_free)
{
	MemoryContext oldcontext = MemoryContextSwitchTo(state->sortcontext);
	SortTuple	stup;

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

	MemoryContextSwitchTo(oldcontext);

	return stup.tuple;
}

/*
 * Fetch the next index tuple in either forward or back direction.
 * Returns NULL if no more tuples.  If *should_free is set, the
 * caller must pfree the returned tuple when done with it.
 * If it is not set, caller should not use tuple following next
 * call here.  It's never okay to use it after tuplesort_end().
 */
IndexTuple
tuplesort_getindextuple(Tuplesortstate *state, bool forward,
						bool *should_free)
{
	MemoryContext oldcontext = MemoryContextSwitchTo(state->sortcontext);
	SortTuple	stup;

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

	MemoryContextSwitchTo(oldcontext);

	return (IndexTuple) stup.tuple;
}

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

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

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

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

	if (stup.isnull1 || !state->tuples)
	{
		*val = stup.datum1;
		*isNull = stup.isnull1;
	}
	else
	{
		/*
		 * Callers rely on datum being in their own memory context, which is
		 * not guaranteed by tuplesort_gettuple_common(), even when should_free
		 * is set to TRUE.  We must always copy here, since our interface does
		 * not allow callers to opt into arrangement where tuple memory can go
		 * away on the next call here, or after tuplesort_end() is called.
		 *
		 * Use stup.tuple because stup.datum1 may be an abbreviation.
		 */
		*val = datumCopy(PointerGetDatum(stup.tuple), false, state->datumTypeLen);
		*isNull = false;

		/*
		 * Free local copy if needed.  It would be very invasive to get
		 * tuplesort_gettuple_common() to allocate tuple in caller's context
		 * for us, so we just do this instead.
		 */
		if (should_free)
			pfree(stup.tuple);
	}

	return true;
}

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

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

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

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

			return false;

		case TSS_SORTEDONTAPE:
		case TSS_FINALMERGE:

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

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

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

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

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

	/* Even in minimum memory, use at least a MINORDER merge */
	mOrder = Max(mOrder, MINORDER);

	return mOrder;
}

/*
 * useselection - determine algorithm to use to sort first run.
 *
 * It can sometimes be useful to use the replacement selection algorithm if it
 * results in one large run, and there is little available workMem.  See
 * remarks on RUN_SECOND optimization within dumptuples().
 */
static bool
useselection(Tuplesortstate *state)
{
	/*
	 * memtupsize might be noticeably higher than memtupcount here in atypical
	 * cases.  It seems slightly preferable to not allow recent outliers to
	 * impact this determination.  Note that caller's trace_sort output
	 * reports memtupcount instead.
	 */
	if (state->memtupsize <= replacement_sort_tuples)
		return true;

	return false;
}

/*
 * inittapes - initialize for tape sorting.
 *
 * This is called only if we have found we don't have room to sort in memory.
 */
static void
inittapes(Tuplesortstate *state)
{
	int			maxTapes,
				j;
	int64		tapeSpace;

	/* Compute number of tapes to use: merge order plus 1 */
	maxTapes = tuplesort_merge_order(state->allowedMem) + 1;

	/*
	 * We must have at least 2*maxTapes slots in the memtuples[] array, else
	 * we'd not have room for merge heap plus preread.  It seems unlikely that
	 * this case would ever occur, but be safe.
	 */
	maxTapes = Min(maxTapes, state->memtupsize / 2);

	state->maxTapes = maxTapes;
	state->tapeRange = maxTapes - 1;

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

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

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

	/*
	 * Make sure that the temp file(s) underlying the tape set are created in
	 * suitable temp tablespaces.
	 */
	PrepareTempTablespaces();

	/*
	 * Create the tape set and allocate the per-tape data arrays.
	 */
	state->tapeset = LogicalTapeSetCreate(maxTapes);

	state->mergeactive = (bool *) palloc0(maxTapes * sizeof(bool));
	state->mergenext = (int *) palloc0(maxTapes * sizeof(int));
	state->mergelast = (int *) palloc0(maxTapes * sizeof(int));
	state->mergeavailslots = (int *) palloc0(maxTapes * sizeof(int));
	state->mergeavailmem = (int64 *) palloc0(maxTapes * sizeof(int64));
	state->mergetuples = (char **) palloc0(maxTapes * sizeof(char *));
	state->mergecurrent = (char **) palloc0(maxTapes * sizeof(char *));
	state->mergetail = (char **) palloc0(maxTapes * sizeof(char *));
	state->mergeoverflow = (char **) palloc0(maxTapes * sizeof(char *));
	state->tp_fib = (int *) palloc0(maxTapes * sizeof(int));
	state->tp_runs = (int *) palloc0(maxTapes * sizeof(int));
	state->tp_dummy = (int *) palloc0(maxTapes * sizeof(int));
	state->tp_tapenum = (int *) palloc0(maxTapes * sizeof(int));

	/*
	 * Give replacement selection a try based on user setting.  There will be
	 * a switch to a simple hybrid sort-merge strategy after the first run
	 * (iff we could not output one long run).
	 */
	state->replaceActive = useselection(state);

	if (state->replaceActive)
	{
		/*
		 * Convert the unsorted contents of memtuples[] into a heap. Each
		 * tuple is marked as belonging to run number zero.
		 *
		 * NOTE: we pass false for checkIndex since there's no point in
		 * comparing indexes in this step, even though we do intend the
		 * indexes to be part of the sort key...
		 */
		int			ntuples = state->memtupcount;

#ifdef TRACE_SORT
		if (trace_sort)
			elog(LOG, "replacement selection will sort %d first run tuples",
				 state->memtupcount);
#endif
		state->memtupcount = 0; /* make the heap empty */

		for (j = 0; j < ntuples; j++)
		{
			/* Must copy source tuple to avoid possible overwrite */
			SortTuple	stup = state->memtuples[j];

			tuplesort_heap_insert(state, &stup, 0, false);
		}
		Assert(state->memtupcount == ntuples);
	}

	state->currentRun = RUN_FIRST;

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

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

	state->status = TSS_BUILDRUNS;
}

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

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

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

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

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

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

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

	/*
	 * If we produced only one initial run (quite likely if the total data
	 * volume is between 1X and 2X workMem when replacement selection is used,
	 * but something we particular count on when input is presorted), we can
	 * just use that tape as the finished output, rather than doing a useless
	 * merge.  (This obvious optimization is not in Knuth's algorithm.)
	 */
	if (state->currentRun == RUN_SECOND)
	{
		state->result_tape = state->tp_tapenum[state->destTape];
		/* must freeze and rewind the finished output tape */
		LogicalTapeFreeze(state->tapeset, state->result_tape);
		state->status = TSS_SORTEDONTAPE;
		return;
	}

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

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

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

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

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

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

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

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

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

/*
 * Merge one run from each input tape, except ones with dummy runs.
 *
 * This is the inner loop of Algorithm D step D5.  We know that the
 * output tape is TAPE[T].
 */
static void
mergeonerun(Tuplesortstate *state)
{
	int			destTape = state->tp_tapenum[state->tapeRange];
	int			srcTape;
	int			tupIndex;
	SortTuple  *tup;
	int64		priorAvail,
				spaceFreed;

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

	/*
	 * Execute merge by repeatedly extracting lowest tuple in heap, writing it
	 * out, and replacing it with next tuple from same tape (if there is
	 * another one).
	 */
	while (state->memtupcount > 0)
	{
		/* write the tuple to destTape */
		priorAvail = state->availMem;
		srcTape = state->memtuples[0].tupindex;
		WRITETUP(state, destTape, &state->memtuples[0]);
		/* writetup adjusted total free space, now fix per-tape space */
		spaceFreed = state->availMem - priorAvail;
		state->mergeavailmem[srcTape] += spaceFreed;
		/* compact the heap */
		tuplesort_heap_siftup(state, false);
		if ((tupIndex = state->mergenext[srcTape]) == 0)
		{
			/* out of preloaded data on this tape, try to read more */
			mergepreread(state);
			/* if still no data, we've reached end of run on this tape */
			if ((tupIndex = state->mergenext[srcTape]) == 0)
				continue;
		}
		/* pull next preread tuple from list, insert in heap */
		tup = &state->memtuples[tupIndex];
		state->mergenext[srcTape] = tup->tupindex;
		if (state->mergenext[srcTape] == 0)
			state->mergelast[srcTape] = 0;
		tuplesort_heap_insert(state, tup, srcTape, false);
		/* put the now-unused memtuples entry on the freelist */
		tup->tupindex = state->mergefreelist;
		state->mergefreelist = tupIndex;
		state->mergeavailslots[srcTape]++;
	}

	/*
	 * Reset tuple memory.  We've freed all of the tuples that we previously
	 * allocated, but AllocSetFree will have put those chunks of memory on
	 * particular free lists, bucketed by size class.  Thus, although all of
	 * that memory is free, it is effectively fragmented.  Resetting the
	 * context gets us out from under that problem.
	 */
	MemoryContextReset(state->tuplecontext);

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

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

/*
 * beginmerge - initialize for a merge pass
 *
 * We decrease the counts of real and dummy runs for each tape, and mark
 * which tapes contain active input runs in mergeactive[].  Then, load
 * as many tuples as we can from each active input tape, and finally
 * fill the merge heap with the first tuple from each active tape.
 *
 * finalMergeBatch indicates if this is the beginning of a final on-the-fly
 * merge where a batched allocation of tuple memory is required.
 */
static void
beginmerge(Tuplesortstate *state, bool finalMergeBatch)
{
	int			activeTapes;
	int			tapenum;
	int			srcTape;
	int			slotsPerTape;
	int64		spacePerTape;

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

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

	/* Clear merge-pass state variables */
	memset(state->mergenext, 0,
		   state->maxTapes * sizeof(*state->mergenext));
	memset(state->mergelast, 0,
		   state->maxTapes * sizeof(*state->mergelast));
	state->mergefreelist = 0;	/* nothing in the freelist */
	state->mergefirstfree = activeTapes;		/* 1st slot avail for preread */

	if (finalMergeBatch)
	{
		/* Free outright buffers for tape never actually allocated */
		FREEMEM(state, (state->maxTapes - activeTapes) * TAPE_BUFFER_OVERHEAD);

		/*
		 * Grow memtuples one last time, since the palloc() overhead no longer
		 * incurred can make a big difference
		 */
		batchmemtuples(state);
	}

	/*
	 * Initialize space allocation to let each active input tape have an equal
	 * share of preread space.
	 */
	Assert(activeTapes > 0);
	slotsPerTape = (state->memtupsize - state->mergefirstfree) / activeTapes;
	Assert(slotsPerTape > 0);
	spacePerTape = MAXALIGN_DOWN(state->availMem / activeTapes);
	for (srcTape = 0; srcTape < state->maxTapes; srcTape++)
	{
		if (state->mergeactive[srcTape])
		{
			state->mergeavailslots[srcTape] = slotsPerTape;
			state->mergeavailmem[srcTape] = spacePerTape;
		}
	}

	/*
	 * Preallocate tuple batch memory for each tape.  This is the memory used
	 * for tuples themselves (not SortTuples), so it's never used by
	 * pass-by-value datum sorts.  Memory allocation is performed here at most
	 * once per sort, just in advance of the final on-the-fly merge step.
	 */
	if (finalMergeBatch)
		mergebatch(state, spacePerTape);

	/*
	 * Preread as many tuples as possible (and at least one) from each active
	 * tape
	 */
	mergepreread(state);

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

		if (tupIndex)
		{
			tup = &state->memtuples[tupIndex];
			state->mergenext[srcTape] = tup->tupindex;
			if (state->mergenext[srcTape] == 0)
				state->mergelast[srcTape] = 0;
			tuplesort_heap_insert(state, tup, srcTape, false);
			/* put the now-unused memtuples entry on the freelist */
			tup->tupindex = state->mergefreelist;
			state->mergefreelist = tupIndex;
			state->mergeavailslots[srcTape]++;

#ifdef TRACE_SORT
			if (trace_sort && finalMergeBatch)
			{
				int64		perTapeKB = (spacePerTape + 1023) / 1024;
				int64		usedSpaceKB;
				int			usedSlots;

				/*
				 * Report how effective batchmemtuples() was in balancing the
				 * number of slots against the need for memory for the
				 * underlying tuples (e.g. IndexTuples).  The big preread of
				 * all tapes when switching to FINALMERGE state should be
				 * fairly representative of memory utilization during the
				 * final merge step, and in any case is the only point at
				 * which all tapes are guaranteed to have depleted either
				 * their batch memory allowance or slot allowance.  Ideally,
				 * both will be completely depleted for every tape by now.
				 */
				usedSpaceKB = (state->mergecurrent[srcTape] -
							   state->mergetuples[srcTape] + 1023) / 1024;
				usedSlots = slotsPerTape - state->mergeavailslots[srcTape];

				elog(LOG, "tape %d initially used " INT64_FORMAT " KB of "
					 INT64_FORMAT " KB batch (%2.3f) and %d out of %d slots "
					 "(%2.3f)", srcTape,
					 usedSpaceKB, perTapeKB,
					 (double) usedSpaceKB / (double) perTapeKB,
					 usedSlots, slotsPerTape,
					 (double) usedSlots / (double) slotsPerTape);
			}
#endif
		}
	}
}

/*
 * batchmemtuples - grow memtuples without palloc overhead
 *
 * When called, availMem should be approximately the amount of memory we'd
 * require to allocate memtupsize - memtupcount tuples (not SortTuples/slots)
 * that were allocated with palloc() overhead, and in doing so use up all
 * allocated slots.  However, though slots and tuple memory is in balance
 * following the last grow_memtuples() call, that's predicated on the observed
 * average tuple size for the "final" grow_memtuples() call, which includes
 * palloc overhead.  During the final merge pass, where we will arrange to
 * squeeze out the palloc overhead, we might need more slots in the memtuples
 * array.
 *
 * To make that happen, arrange for the amount of remaining memory to be
 * exactly equal to the palloc overhead multiplied by the current size of
 * the memtuples array, force the grow_memtuples flag back to true (it's
 * probably but not necessarily false on entry to this routine), and then
 * call grow_memtuples.  This simulates loading enough tuples to fill the
 * whole memtuples array and then having some space left over because of the
 * elided palloc overhead.  We expect that grow_memtuples() will conclude that
 * it can't double the size of the memtuples array but that it can increase
 * it by some percentage; but if it does decide to double it, that just means
 * that we've never managed to use many slots in the memtuples array, in which
 * case doubling it shouldn't hurt anything anyway.
 */
static void
batchmemtuples(Tuplesortstate *state)
{
	int64		refund;
	int64		availMemLessRefund;
	int			memtupsize = state->memtupsize;

	/* Caller error if we have no tapes */
	Assert(state->activeTapes > 0);

	/* For simplicity, assume no memtuples are actually currently counted */
	Assert(state->memtupcount == 0);

	/*
	 * Refund STANDARDCHUNKHEADERSIZE per tuple.
	 *
	 * This sometimes fails to make memory use perfectly balanced, but it
	 * should never make the situation worse.  Note that Assert-enabled builds
	 * get a larger refund, due to a varying STANDARDCHUNKHEADERSIZE.
	 */
	refund = memtupsize * STANDARDCHUNKHEADERSIZE;
	availMemLessRefund = state->availMem - refund;

	/*
	 * We need to be sure that we do not cause LACKMEM to become true, else
	 * the batch allocation size could be calculated as negative, causing
	 * havoc.  Hence, if availMemLessRefund is negative at this point, we must
	 * do nothing.  Moreover, if it's positive but rather small, there's
	 * little point in proceeding because we could only increase memtuples by
	 * a small amount, not worth the cost of the repalloc's.  We somewhat
	 * arbitrarily set the threshold at ALLOCSET_DEFAULT_INITSIZE per tape.
	 * (Note that this does not represent any assumption about tuple sizes.)
	 */
	if (availMemLessRefund <=
		(int64) state->activeTapes * ALLOCSET_DEFAULT_INITSIZE)
		return;

	/*
	 * To establish balanced memory use after refunding palloc overhead,
	 * temporarily have our accounting indicate that we've allocated all
	 * memory we're allowed to less that refund, and call grow_memtuples() to
	 * have it increase the number of slots.
	 */
	state->growmemtuples = true;
	USEMEM(state, availMemLessRefund);
	(void) grow_memtuples(state);
	state->growmemtuples = false;
	/* availMem must stay accurate for spacePerTape calculation */
	FREEMEM(state, availMemLessRefund);
	if (LACKMEM(state))
		elog(ERROR, "unexpected out-of-memory situation in tuplesort");

#ifdef TRACE_SORT
	if (trace_sort)
	{
		Size		OldKb = (memtupsize * sizeof(SortTuple) + 1023) / 1024;
		Size		NewKb = (state->memtupsize * sizeof(SortTuple) + 1023) / 1024;

		elog(LOG, "grew memtuples %1.2fx from %d (%zu KB) to %d (%zu KB) for final merge",
			 (double) NewKb / (double) OldKb,
			 memtupsize, OldKb,
			 state->memtupsize, NewKb);
	}
#endif
}

/*
 * mergebatch - initialize tuple memory in batch
 *
 * This allows sequential access to sorted tuples buffered in memory from
 * tapes/runs on disk during a final on-the-fly merge step.  Note that the
 * memory is not used for SortTuples, but for the underlying tuples (e.g.
 * MinimalTuples).
 *
 * Note that when batch memory is used, there is a simple division of space
 * into large buffers (one per active tape).  The conventional incremental
 * memory accounting (calling USEMEM() and FREEMEM()) is abandoned.  Instead,
 * when each tape's memory budget is exceeded, a retail palloc() "overflow" is
 * performed, which is then immediately detected in a way that is analogous to
 * LACKMEM().  This keeps each tape's use of memory fair, which is always a
 * goal.
 */
static void
mergebatch(Tuplesortstate *state, int64 spacePerTape)
{
	int			srcTape;

	Assert(state->activeTapes > 0);
	Assert(state->tuples);

	/*
	 * For the purposes of tuplesort's memory accounting, the batch allocation
	 * is special, and regular memory accounting through USEMEM() calls is
	 * abandoned (see mergeprereadone()).
	 */
	for (srcTape = 0; srcTape < state->maxTapes; srcTape++)
	{
		char	   *mergetuples;

		if (!state->mergeactive[srcTape])
			continue;

		/* Allocate buffer for each active tape */
		mergetuples = MemoryContextAllocHuge(state->tuplecontext,
											 spacePerTape);

		/* Initialize state for tape */
		state->mergetuples[srcTape] = mergetuples;
		state->mergecurrent[srcTape] = mergetuples;
		state->mergetail[srcTape] = mergetuples;
		state->mergeoverflow[srcTape] = NULL;
	}

	state->batchUsed = true;
	state->spacePerTape = spacePerTape;
}

/*
 * mergebatchone - prepare batch memory for one merge input tape
 *
 * This is called following the exhaustion of preread tuples for one input
 * tape.  All that actually occurs is that the state for the source tape is
 * reset to indicate that all memory may be reused.
 *
 * This routine must deal with fixing up the tuple that is about to be returned
 * to the client, due to "overflow" allocations.
 */
static void
mergebatchone(Tuplesortstate *state, int srcTape, SortTuple *rtup,
			  bool *should_free)
{
	Assert(state->batchUsed);

	/*
	 * Tuple about to be returned to caller ("stup") is final preread tuple
	 * from tape, just removed from the top of the heap.  Special steps around
	 * memory management must be performed for that tuple, to make sure it
	 * isn't overwritten early.
	 */
	if (!state->mergeoverflow[srcTape])
	{
		Size		tupLen;

		/*
		 * Mark tuple buffer range for reuse, but be careful to move final,
		 * tail tuple to start of space for next run so that it's available to
		 * caller when stup is returned, and remains available at least until
		 * the next tuple is requested.
		 */
		tupLen = state->mergecurrent[srcTape] - state->mergetail[srcTape];
		state->mergecurrent[srcTape] = state->mergetuples[srcTape];
		MOVETUP(state->mergecurrent[srcTape], state->mergetail[srcTape],
				tupLen);

		/* Make SortTuple at top of the merge heap point to new tuple */
		rtup->tuple = (void *) state->mergecurrent[srcTape];

		state->mergetail[srcTape] = state->mergecurrent[srcTape];
		state->mergecurrent[srcTape] += tupLen;
	}
	else
	{
		/*
		 * Handle an "overflow" retail palloc.
		 *
		 * This is needed when we run out of tuple memory for the tape.
		 */
		state->mergecurrent[srcTape] = state->mergetuples[srcTape];
		state->mergetail[srcTape] = state->mergetuples[srcTape];

		if (rtup->tuple)
		{
			Assert(rtup->tuple == (void *) state->mergeoverflow[srcTape]);
			/* Caller should free palloc'd tuple */
			*should_free = true;
		}
		state->mergeoverflow[srcTape] = NULL;
	}
}

/*
 * mergebatchfreetape - handle final clean-up for batch memory once tape is
 * about to become exhausted
 *
 * All tuples are returned from tape, but a single final tuple, *rtup, is to be
 * passed back to caller.  Free tape's batch allocation buffer while ensuring
 * that the final tuple is managed appropriately.
 */
static void
mergebatchfreetape(Tuplesortstate *state, int srcTape, SortTuple *rtup,
				   bool *should_free)
{
	Assert(state->batchUsed);
	Assert(state->status == TSS_FINALMERGE);

	/*
	 * Tuple may or may not already be an overflow allocation from
	 * mergebatchone()
	 */
	if (!*should_free && rtup->tuple)
	{
		/*
		 * Final tuple still in tape's batch allocation.
		 *
		 * Return palloc()'d copy to caller, and have it freed in a similar
		 * manner to overflow allocation.  Otherwise, we'd free batch memory
		 * and pass back a pointer to garbage.  Note that we deliberately
		 * allocate this in the parent tuplesort context, to be on the safe
		 * side.
		 */
		Size		tuplen;
		void	   *oldTuple = rtup->tuple;

		tuplen = state->mergecurrent[srcTape] - state->mergetail[srcTape];
		rtup->tuple = MemoryContextAlloc(state->sortcontext, tuplen);
		MOVETUP(rtup->tuple, oldTuple, tuplen);
		*should_free = true;
	}

	/* Free spacePerTape-sized buffer */
	pfree(state->mergetuples[srcTape]);
}

/*
 * mergebatchalloc - allocate memory for one tuple using a batch memory
 * "logical allocation".
 *
 * This is used for the final on-the-fly merge phase only.  READTUP() routines
 * receive memory from here in place of palloc() and USEMEM() calls.
 *
 * Tuple tapenum is passed, ensuring each tape's tuples are stored in sorted,
 * contiguous order (while allowing safe reuse of memory made available to
 * each tape).  This maximizes locality of access as tuples are returned by
 * final merge.
 *
 * Caller must not subsequently attempt to free memory returned here.  In
 * general, only mergebatch* functions know about how memory returned from
 * here should be freed, and this function's caller must ensure that batch
 * memory management code will definitely have the opportunity to do the right
 * thing during the final on-the-fly merge.
 */
static void *
mergebatchalloc(Tuplesortstate *state, int tapenum, Size tuplen)
{
	Size		reserve_tuplen = MAXALIGN(tuplen);
	char	   *ret;

	/* Should overflow at most once before mergebatchone() call: */
	Assert(state->mergeoverflow[tapenum] == NULL);
	Assert(state->batchUsed);

	/* It should be possible to use precisely spacePerTape memory at once */
	if (state->mergecurrent[tapenum] + reserve_tuplen <=
		state->mergetuples[tapenum] + state->spacePerTape)
	{
		/*
		 * Usual case -- caller is returned pointer into its tape's buffer,
		 * and an offset from that point is recorded as where tape has
		 * consumed up to for current round of preloading.
		 */
		ret = state->mergetail[tapenum] = state->mergecurrent[tapenum];
		state->mergecurrent[tapenum] += reserve_tuplen;
	}
	else
	{
		/*
		 * Allocate memory, and record as tape's overflow allocation.  This
		 * will be detected quickly, in a similar fashion to a LACKMEM()
		 * condition, and should not happen again before a new round of
		 * preloading for caller's tape.  Note that we deliberately allocate
		 * this in the parent tuplesort context, to be on the safe side.
		 *
		 * Sometimes, this does not happen because merging runs out of slots
		 * before running out of memory.
		 */
		ret = state->mergeoverflow[tapenum] =
			MemoryContextAlloc(state->sortcontext, tuplen);
	}

	return ret;
}

/*
 * mergepreread - load tuples from merge input tapes
 *
 * This routine exists to improve sequentiality of reads during a merge pass,
 * as explained in the header comments of this file.  Load tuples from each
 * active source tape until the tape's run is exhausted or it has used up
 * its fair share of available memory.  In any case, we guarantee that there
 * is at least one preread tuple available from each unexhausted input tape.
 *
 * We invoke this routine at the start of a merge pass for initial load,
 * and then whenever any tape's preread data runs out.  Note that we load
 * as much data as possible from all tapes, not just the one that ran out.
 * This is because logtape.c works best with a usage pattern that alternates
 * between reading a lot of data and writing a lot of data, so whenever we
 * are forced to read, we should fill working memory completely.
 *
 * In FINALMERGE state, we *don't* use this routine, but instead just preread
 * from the single tape that ran dry.  There's no read/write alternation in
 * that state and so no point in scanning through all the tapes to fix one.
 * (Moreover, there may be quite a lot of inactive tapes in that state, since
 * we might have had many fewer runs than tapes.  In a regular tape-to-tape
 * merge we can expect most of the tapes to be active.  Plus, only
 * FINALMERGE state has to consider memory management for a batch
 * allocation.)
 */
static void
mergepreread(Tuplesortstate *state)
{
	int			srcTape;

	for (srcTape = 0; srcTape < state->maxTapes; srcTape++)
		mergeprereadone(state, srcTape);
}

/*
 * mergeprereadone - load tuples from one merge input tape
 *
 * Read tuples from the specified tape until it has used up its free memory
 * or array slots; but ensure that we have at least one tuple, if any are
 * to be had.
 */
static void
mergeprereadone(Tuplesortstate *state, int srcTape)
{
	unsigned int tuplen;
	SortTuple	stup;
	int			tupIndex;
	int64		priorAvail,
				spaceUsed;

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

	/*
	 * Manage per-tape availMem.  Only actually matters when batch memory not
	 * in use.
	 */
	priorAvail = state->availMem;
	state->availMem = state->mergeavailmem[srcTape];

	/*
	 * When batch memory is used if final on-the-fly merge, only mergeoverflow
	 * test is relevant; otherwise, only LACKMEM() test is relevant.
	 */
	while ((state->mergeavailslots[srcTape] > 0 &&
			state->mergeoverflow[srcTape] == NULL && !LACKMEM(state)) ||
		   state->mergenext[srcTape] == 0)
	{
		/* read next tuple, if any */
		if ((tuplen = getlen(state, srcTape, true)) == 0)
		{
			state->mergeactive[srcTape] = false;
			break;
		}
		READTUP(state, &stup, srcTape, tuplen);
		/* find a free slot in memtuples[] for it */
		tupIndex = state->mergefreelist;
		if (tupIndex)
			state->mergefreelist = state->memtuples[tupIndex].tupindex;
		else
		{
			tupIndex = state->mergefirstfree++;
			Assert(tupIndex < state->memtupsize);
		}
		state->mergeavailslots[srcTape]--;
		/* store tuple, append to list for its tape */
		stup.tupindex = 0;
		state->memtuples[tupIndex] = stup;
		if (state->mergelast[srcTape])
			state->memtuples[state->mergelast[srcTape]].tupindex = tupIndex;
		else
			state->mergenext[srcTape] = tupIndex;
		state->mergelast[srcTape] = tupIndex;
	}
	/* update per-tape and global availmem counts */
	spaceUsed = state->mergeavailmem[srcTape] - state->availMem;
	state->mergeavailmem[srcTape] = state->availMem;
	state->availMem = priorAvail - spaceUsed;
}

/*
 * dumptuples - remove tuples from memtuples and write to tape
 *
 * This is used during initial-run building, but not during merging.
 *
 * When alltuples = false and replacement selection is still active, dump
 * only enough tuples to get under the availMem limit (and leave at least
 * one tuple in memtuples, since puttuple will then assume it is a heap that
 * has a tuple to compare to).  We always insist there be at least one free
 * slot in the memtuples[] array.
 *
 * When alltuples = true, dump everything currently in memory.  (This
 * case is only used at end of input data, although in practice only the
 * first run could fail to dump all tuples when we LACKMEM(), and only
 * when replacement selection is active.)
 *
 * If, when replacement selection is active, we see that the tuple run
 * number at the top of the heap has changed, start a new run.  This must be
 * the first run, because replacement selection is always abandoned for all
 * further runs.
 */
static void
dumptuples(Tuplesortstate *state, bool alltuples)
{
	while (alltuples ||
		   (LACKMEM(state) && state->memtupcount > 1) ||
		   state->memtupcount >= state->memtupsize)
	{
		if (state->replaceActive)
		{
			/*
			 * Still holding out for a case favorable to replacement
			 * selection. Still incrementally spilling using heap.
			 *
			 * Dump the heap's frontmost entry, and sift up to remove it from
			 * the heap.
			 */
			Assert(state->memtupcount > 0);
			WRITETUP(state, state->tp_tapenum[state->destTape],
					 &state->memtuples[0]);
			tuplesort_heap_siftup(state, true);
		}
		else
		{
			/*
			 * Once committed to quicksorting runs, never incrementally spill
			 */
			dumpbatch(state, alltuples);
			break;
		}

		/*
		 * If top run number has changed, we've finished the current run (this
		 * can only be the first run), and will no longer spill incrementally.
		 */
		if (state->memtupcount == 0 ||
			state->memtuples[0].tupindex == HEAP_RUN_NEXT)
		{
			markrunend(state, state->tp_tapenum[state->destTape]);
			Assert(state->currentRun == RUN_FIRST);
			state->currentRun++;
			state->tp_runs[state->destTape]++;
			state->tp_dummy[state->destTape]--; /* per Alg D step D2 */

#ifdef TRACE_SORT
			if (trace_sort)
				elog(LOG, "finished incrementally writing %s run %d to tape %d: %s",
					 (state->memtupcount == 0) ? "only" : "first",
					 state->currentRun, state->destTape,
					 pg_rusage_show(&state->ru_start));
#endif

			/*
			 * Done if heap is empty, which is possible when there is only one
			 * long run.
			 */
			Assert(state->currentRun == RUN_SECOND);
			if (state->memtupcount == 0)
			{
				/*
				 * Replacement selection best case; no final merge required,
				 * because there was only one initial run (second run has no
				 * tuples).  See RUN_SECOND case in mergeruns().
				 */
				break;
			}

			/*
			 * Abandon replacement selection for second run (as well as any
			 * subsequent runs).
			 */
			state->replaceActive = false;

			/*
			 * First tuple of next run should not be heapified, and so will
			 * bear placeholder run number.  In practice this must actually be
			 * the second run, which just became the currentRun, so we're
			 * clear to quicksort and dump the tuples in batch next time
			 * memtuples becomes full.
			 */
			Assert(state->memtuples[0].tupindex == HEAP_RUN_NEXT);
			selectnewtape(state);
		}
	}
}

/*
 * dumpbatch - sort and dump all memtuples, forming one run on tape
 *
 * Second or subsequent runs are never heapified by this module (although
 * heapification still respects run number differences between the first and
 * second runs), and a heap (replacement selection priority queue) is often
 * avoided in the first place.
 */
static void
dumpbatch(Tuplesortstate *state, bool alltuples)
{
	int			memtupwrite;
	int			i;

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

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

	state->currentRun++;

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

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

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

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

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

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

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

	if (!alltuples)
		selectnewtape(state);
}

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

	Assert(state->randomAccess);

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

	MemoryContextSwitchTo(oldcontext);
}

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

	Assert(state->randomAccess);

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

	MemoryContextSwitchTo(oldcontext);
}

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

	Assert(state->randomAccess);

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

	MemoryContextSwitchTo(oldcontext);
}

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

	switch (state->status)
	{
		case TSS_SORTEDINMEM:
			if (state->boundUsed)
				*sortMethod = "top-N heapsort";
			else
				*sortMethod = "quicksort";
			break;
		case TSS_SORTEDONTAPE:
			*sortMethod = "external sort";
			break;
		case TSS_FINALMERGE:
			*sortMethod = "external merge";
			break;
		default:
			*sortMethod = "still in progress";
			break;
	}
}


/*
 * Heap manipulation routines, per Knuth's Algorithm 5.2.3H.
 *
 * Compare two SortTuples.  If checkIndex is true, use the tuple index
 * as the front of the sort key; otherwise, no.
 *
 * Note that for checkIndex callers, the heap invariant is never
 * maintained beyond the first run, and so there are no COMPARETUP()
 * calls needed to distinguish tuples in HEAP_RUN_NEXT.
 */

#define HEAPCOMPARE(tup1,tup2) \
	(checkIndex && ((tup1)->tupindex != (tup2)->tupindex || \
					(tup1)->tupindex == HEAP_RUN_NEXT) ? \
	 ((tup1)->tupindex) - ((tup2)->tupindex) : \
	 COMPARETUP(state, tup1, tup2))

/*
 * Convert the existing unordered array of SortTuples to a bounded heap,
 * discarding all but the smallest "state->bound" tuples.
 *
 * When working with a bounded heap, we want to keep the largest entry
 * at the root (array entry zero), instead of the smallest as in the normal
 * sort case.  This allows us to discard the largest entry cheaply.
 * Therefore, we temporarily reverse the sort direction.
 *
 * We assume that all entries in a bounded heap will always have tupindex
 * zero; it therefore doesn't matter that HEAPCOMPARE() doesn't reverse
 * the direction of comparison for tupindexes.
 */
static void
make_bounded_heap(Tuplesortstate *state)
{
	int			tupcount = state->memtupcount;
	int			i;

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

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

	state->memtupcount = 0;		/* make the heap empty */
	for (i = 0; i < tupcount; i++)
	{
		if (state->memtupcount >= state->bound &&
		  COMPARETUP(state, &state->memtuples[i], &state->memtuples[0]) <= 0)
		{
			/* New tuple would just get thrown out, so skip it */
			free_sort_tuple(state, &state->memtuples[i]);
			CHECK_FOR_INTERRUPTS();
		}
		else
		{
			/* Insert next tuple into heap */
			/* Must copy source tuple to avoid possible overwrite */
			SortTuple	stup = state->memtuples[i];

			tuplesort_heap_insert(state, &stup, 0, false);

			/* If heap too full, discard largest entry */
			if (state->memtupcount > state->bound)
			{
				free_sort_tuple(state, &state->memtuples[0]);
				tuplesort_heap_siftup(state, false);
			}
		}
	}

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

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

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

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

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

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

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

/*
 * Sort all memtuples using specialized qsort() routines.
 *
 * Quicksort is used for small in-memory sorts.  Quicksort is also generally
 * preferred to replacement selection for generating runs during external sort
 * operations, although replacement selection is sometimes used for the first
 * run.
 */
static void
tuplesort_sort_memtuples(Tuplesortstate *state)
{
	if (state->memtupcount > 1)
	{
		/* Can we use the single-key sort function? */
		if (state->onlyKey != NULL)
			qsort_ssup(state->memtuples, state->memtupcount,
					   state->onlyKey);
		else
			qsort_tuple(state->memtuples,
						state->memtupcount,
						state->comparetup,
						state);
	}
}

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

	/*
	 * Save the tupleindex --- see notes above about writing on *tuple. It's a
	 * historical artifact that tupleindex is passed as a separate argument
	 * and not in *tuple, but it's notationally convenient so let's leave it
	 * that way.
	 */
	tuple->tupindex = tupleindex;

	memtuples = state->memtuples;
	Assert(state->memtupcount < state->memtupsize);
	Assert(!checkIndex || tupleindex == RUN_FIRST);

	CHECK_FOR_INTERRUPTS();

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

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

/*
 * The tuple at state->memtuples[0] has been removed from the heap.
 * Decrement memtupcount, and sift up to maintain the heap invariant.
 */
static void
tuplesort_heap_siftup(Tuplesortstate *state, bool checkIndex)
{
	SortTuple  *memtuples = state->memtuples;
	SortTuple  *tuple;
	unsigned int i,
				n;

	Assert(!checkIndex || state->currentRun == RUN_FIRST);
	if (--state->memtupcount <= 0)
		return;

	CHECK_FOR_INTERRUPTS();

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

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

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

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


/*
 * Tape interface routines
 */

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

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

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

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

/*
 * Get memory for tuple from within READTUP() routine.  Allocate
 * memory and account for that, or consume from tape's batch
 * allocation.
 *
 * Memory returned here in the final on-the-fly merge case is recycled
 * from tape's batch allocation.  Otherwise, callers must pfree() or
 * reset tuple child memory context, and account for that with a
 * FREEMEM().  Currently, this only ever needs to happen in WRITETUP()
 * routines.
 */
static void *
readtup_alloc(Tuplesortstate *state, int tapenum, Size tuplen)
{
	if (state->batchUsed)
	{
		/*
		 * No USEMEM() call, because during final on-the-fly merge accounting
		 * is based on tape-private state. ("Overflow" allocations are
		 * detected as an indication that a new round or preloading is
		 * required. Preloading marks existing contents of tape's batch buffer
		 * for reuse.)
		 */
		return mergebatchalloc(state, tapenum, tuplen);
	}
	else
	{
		char	   *ret;

		/* Batch allocation yet to be performed */
		ret = MemoryContextAlloc(state->tuplecontext, tuplen);
		USEMEM(state, GetMemoryChunkSpace(ret));
		return ret;
	}
}


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

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


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

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

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

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

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

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

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

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

	return 0;
}

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

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

	MemoryContextSwitchTo(oldcontext);

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

		stup->datum1 = original;

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

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

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

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

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

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

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

	FREEMEM(state, GetMemoryChunkSpace(tuple));
	heap_free_minimal_tuple(tuple);
}

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

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

static void
movetup_heap(void *dest, void *src, unsigned int len)
{
	memmove(dest, src, len);
}

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

	return 0;
}

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

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

	MemoryContextSwitchTo(oldcontext);

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

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

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

		stup->datum1 = original;

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

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

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

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

	FREEMEM(state, GetMemoryChunkSpace(tuple));
	heap_freetuple(tuple);
}

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

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

static void
movetup_cluster(void *dest, void *src, unsigned int len)
{
	HeapTuple	tuple;

	memmove(dest, src, len);

	/* Repoint the HeapTupleData header */
	tuple = (HeapTuple) dest;
	tuple->t_data = (HeapTupleHeader) ((char *) tuple + HEAPTUPLESIZE);
}


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

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


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

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

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

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

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

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

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

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

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

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

		index_deform_tuple(tuple1, tupDes, values, isnull);

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

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

	/*
	 * If key values are equal, we sort on ItemPointer.  This does not affect
	 * validity of the finished index, but it may be useful to have index
	 * scans in physical order.
	 */
	{
		BlockNumber blk1 = ItemPointerGetBlockNumber(&tuple1->t_tid);
		BlockNumber blk2 = ItemPointerGetBlockNumber(&tuple2->t_tid);

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

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

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

	return 0;
}

static int
comparetup_index_hash(const SortTuple *a, const SortTuple *b,
					  Tuplesortstate *state)
{
	uint32		hash1;
	uint32		hash2;
	IndexTuple	tuple1;
	IndexTuple	tuple2;

	/*
	 * Fetch hash keys and mask off bits we don't want to sort by. We know
	 * that the first column of the index tuple is the hash key.
	 */
	Assert(!a->isnull1);
	hash1 = DatumGetUInt32(a->datum1) & state->hash_mask;
	Assert(!b->isnull1);
	hash2 = DatumGetUInt32(b->datum1) & state->hash_mask;

	if (hash1 > hash2)
		return 1;
	else if (hash1 < hash2)
		return -1;

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

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

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

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

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

	return 0;
}

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

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

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

		stup->datum1 = original;

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

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

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

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

	FREEMEM(state, GetMemoryChunkSpace(tuple));
	pfree(tuple);
}

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

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

static void
movetup_index(void *dest, void *src, unsigned int len)
{
	memmove(dest, src, len);
}

/*
 * Routines specialized for DatumTuple case
 */

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

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

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

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

	return compare;
}

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

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

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

	writtenlen = tuplen + sizeof(unsigned int);

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

	if (stup->tuple)
	{
		FREEMEM(state, GetMemoryChunkSpace(stup->tuple));
		pfree(stup->tuple);
		stup->tuple = NULL;
	}
}

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

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

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

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

static void
movetup_datum(void *dest, void *src, unsigned int len)
{
	memmove(dest, src, len);
}

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