/*-------------------------------------------------------------------------
 *
 * tuplesort.h
 *	  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.  Parallel sorts use a variant of this external sort
 * algorithm, and are typically only used for large amounts of data.
 *
 * Portions Copyright (c) 1996-2026, PostgreSQL Global Development Group
 * Portions Copyright (c) 1994, Regents of the University of California
 *
 * src/include/utils/tuplesort.h
 *
 *-------------------------------------------------------------------------
 */
#ifndef TUPLESORT_H
#define TUPLESORT_H

#include "access/itup.h"
#include "executor/instrument_node.h"
#include "executor/tuptable.h"
#include "storage/dsm.h"
#include "utils/logtape.h"
#include "utils/relcache.h"
#include "utils/sortsupport.h"

/* We don't want this file to depend on AM-specific header files */
typedef struct BrinTuple BrinTuple;
typedef struct GinTuple GinTuple;

/*
 * Tuplesortstate and Sharedsort are opaque types whose details are not
 * known outside tuplesort.c.
 */
typedef struct Tuplesortstate Tuplesortstate;
typedef struct Sharedsort Sharedsort;

/*
 * Tuplesort parallel coordination state, allocated by each participant in
 * local memory.  Participant caller initializes everything.  See usage notes
 * below.
 */
typedef struct SortCoordinateData
{
	/* Worker process?  If not, must be leader. */
	bool		isWorker;

	/*
	 * Leader-process-passed number of participants known launched (workers
	 * set this to -1).  Includes state within leader needed for it to
	 * participate as a worker, if any.
	 */
	int			nParticipants;

	/* Private opaque state (points to shared memory) */
	Sharedsort *sharedsort;
} SortCoordinateData;

typedef struct SortCoordinateData *SortCoordinate;

/* Bitwise option flags for tuple sorts */
#define TUPLESORT_NONE					0

/* specifies whether non-sequential access to the sort result is required */
#define	TUPLESORT_RANDOMACCESS			(1 << 0)

/* specifies if the tuplesort is able to support bounded sorts */
#define TUPLESORT_ALLOWBOUNDED			(1 << 1)

/*
 * For bounded sort, tuples get pfree'd when they fall outside of the bound.
 * When bounded sorts are not required, we can use a bump context for tuple
 * allocation as there's no risk that pfree will ever be called for a tuple.
 * Define a macro to make it easier for code to figure out if we're using a
 * bump allocator.
 */
#define TupleSortUseBumpTupleCxt(opt) (((opt) & TUPLESORT_ALLOWBOUNDED) == 0)

/*
 * The objects we actually sort are SortTuple structs.  These contain
 * a pointer to the tuple proper (might be a MinimalTuple or IndexTuple),
 * which is a separate palloc chunk --- we assume it is just one chunk and
 * can be freed by a simple pfree() (except during merge, where we use a
 * simple slab allocator, and during a non-bounded sort where we use a bump
 * allocator).  SortTuples also contain the tuple's first key column in
 * Datum/nullflag format, and a source/input tape number that tracks which
 * tape each heap element/slot belongs to during merging.
 *
 * 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.
 */
typedef struct
{
	void	   *tuple;			/* the tuple itself */
	Datum		datum1;			/* value of first key column */
	bool		isnull1;		/* is first key column NULL? */
	uint8		curbyte;		/* chunk of datum1 for current radix sort pass */
	int			srctape;		/* source tape number */
} SortTuple;

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

/*
 * The public part of a Tuple sort operation state.  This data structure
 * contains the definition of sort-variant-specific interface methods and
 * the part of Tuple sort operation state required by their implementations.
 */
typedef struct
{
	/*
	 * 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;

	/*
	 * Fall back to the full tuple for comparison, but only compare the first
	 * sortkey if it was abbreviated. Otherwise, only compare second and later
	 * sortkeys.
	 */
	SortTupleComparator comparetup_tiebreak;

	/*
	 * Alter datum1 representation in the SortTuple's array back from the
	 * abbreviated key to the first column value.
	 */
	void		(*removeabbrev) (Tuplesortstate *state, SortTuple *stups,
								 int count);

	/*
	 * 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.
	 */
	void		(*writetup) (Tuplesortstate *state, LogicalTape *tape,
							 SortTuple *stup);

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

	/*
	 * Function to do some specific release of resources for the sort variant.
	 * In particular, this function should free everything stored in the "arg"
	 * field, which wouldn't be cleared on reset of the Tuple sort memory
	 * contexts.  This can be NULL if nothing specific needs to be done.
	 */
	void		(*freestate) (Tuplesortstate *state);

	/*
	 * The subsequent fields are used in the implementations of the functions
	 * above.
	 */
	MemoryContext maincontext;	/* memory context for tuple sort metadata that
								 * persists across multiple batches */
	MemoryContext sortcontext;	/* memory context holding most sort data */
	MemoryContext tuplecontext; /* sub-context of sortcontext for tuple data */

	/*
	 * Whether SortTuple's datum1 and isnull1 members are maintained by the
	 * above routines.  If not, some sort specializations are disabled.
	 */
	bool		haveDatum1;

	/*
	 * 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.
	 */
	int			nKeys;			/* number of columns in sort key */
	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.  The
	 * presence of a value in this field is also checked by various sort
	 * specialization functions as an optimization when comparing the leading
	 * key in a tiebreak situation to determine if there are any subsequent
	 * keys to sort on.
	 */
	SortSupport onlyKey;

	int			sortopt;		/* Bitmask of flags used to setup sort */

	bool		tuples;			/* Can SortTuple.tuple ever be set? */

	void	   *arg;			/* Specific information for the sort variant */
} TuplesortPublic;

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

#define TuplesortstateGetPublic(state) ((TuplesortPublic *) state)

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

/*
 * We provide multiple interfaces to what is essentially the same code,
 * since different callers have different data to be sorted and want to
 * specify the sort key information differently.  There are two APIs for
 * sorting HeapTuples and two more for sorting IndexTuples.  Yet another
 * API supports sorting bare Datums.
 *
 * Serial sort callers should pass NULL for their coordinate argument.
 *
 * The "heap" API actually stores/sorts MinimalTuples, which means it doesn't
 * preserve the system columns (tuple identity and transaction visibility
 * info).  The sort keys are specified by column numbers within the tuples
 * and sort operator OIDs.  We save some cycles by passing and returning the
 * tuples in TupleTableSlots, rather than forming actual HeapTuples (which'd
 * have to be converted to MinimalTuples).  This API works well for sorts
 * executed as parts of plan trees.
 *
 * The "cluster" API stores/sorts full HeapTuples including all visibility
 * info. The sort keys are specified by reference to a btree index that is
 * defined on the relation to be sorted.  Note that putheaptuple/getheaptuple
 * go with this API, not the "begin_heap" one!
 *
 * The "index_btree" API stores/sorts IndexTuples (preserving all their
 * header fields).  The sort keys are specified by a btree index definition.
 *
 * The "index_hash" API is similar to index_btree, but the tuples are
 * actually sorted by their hash codes not the raw data.
 *
 * The "index_brin" API is similar to index_btree, but the tuples are
 * BrinTuple and are sorted by their block number not the raw data.
 *
 * Parallel sort callers are required to coordinate multiple tuplesort states
 * in a leader process and one or more worker processes.  The leader process
 * must launch workers, and have each perform an independent "partial"
 * tuplesort, typically fed by the parallel heap interface.  The leader later
 * produces the final output (internally, it merges runs output by workers).
 *
 * Callers must do the following to perform a sort in parallel using multiple
 * worker processes:
 *
 * 1. Request tuplesort-private shared memory for n workers.  Use
 *    tuplesort_estimate_shared() to get the required size.
 * 2. Have leader process initialize allocated shared memory using
 *    tuplesort_initialize_shared().  Launch workers.
 * 3. Initialize a coordinate argument within both the leader process, and
 *    for each worker process.  This has a pointer to the shared
 *    tuplesort-private structure, as well as some caller-initialized fields.
 *    Leader's coordinate argument reliably indicates number of workers
 *    launched (this is unused by workers).
 * 4. Begin a tuplesort using some appropriate tuplesort_begin* routine,
 *    (passing the coordinate argument) within each worker.  The workMem
 *    arguments need not be identical.  All other arguments should match
 *    exactly, though.
 * 5. tuplesort_attach_shared() should be called by all workers.  Feed tuples
 *    to each worker, and call tuplesort_performsort() within each when input
 *    is exhausted.
 * 6. Call tuplesort_end() in each worker process.  Worker processes can shut
 *    down once tuplesort_end() returns.
 * 7. Begin a tuplesort in the leader using the same tuplesort_begin*
 *    routine, passing a leader-appropriate coordinate argument (this can
 *    happen as early as during step 3, actually, since we only need to know
 *    the number of workers successfully launched).  The leader must now wait
 *    for workers to finish.  Caller must use own mechanism for ensuring that
 *    next step isn't reached until all workers have called and returned from
 *    tuplesort_performsort().  (Note that it's okay if workers have already
 *    also called tuplesort_end() by then.)
 * 8. Call tuplesort_performsort() in leader.  Consume output using the
 *    appropriate tuplesort_get* routine.  Leader can skip this step if
 *    tuplesort turns out to be unnecessary.
 * 9. Call tuplesort_end() in leader.
 *
 * This division of labor assumes nothing about how input tuples are produced,
 * but does require that caller combine the state of multiple tuplesorts for
 * any purpose other than producing the final output.  For example, callers
 * must consider that tuplesort_get_stats() reports on only one worker's role
 * in a sort (or the leader's role), and not statistics for the sort as a
 * whole.
 *
 * Note that callers may use the leader process to sort runs as if it was an
 * independent worker process (prior to the process performing a leader sort
 * to produce the final sorted output).  Doing so only requires a second
 * "partial" tuplesort within the leader process, initialized like that of a
 * worker process.  The steps above don't touch on this directly.  The only
 * difference is that the tuplesort_attach_shared() call is never needed within
 * leader process, because the backend as a whole holds the shared fileset
 * reference.  A worker Tuplesortstate in leader is expected to do exactly the
 * same amount of total initial processing work as a worker process
 * Tuplesortstate, since the leader process has nothing else to do before
 * workers finish.
 *
 * Note that only a very small amount of memory will be allocated prior to
 * the leader state first consuming input, and that workers will free the
 * vast majority of their memory upon returning from tuplesort_performsort().
 * Callers can rely on this to arrange for memory to be used in a way that
 * respects a workMem-style budget across an entire parallel sort operation.
 *
 * Callers are responsible for parallel safety in general.  However, they
 * can at least rely on there being no parallel safety hazards within
 * tuplesort, because tuplesort thinks of the sort as several independent
 * sorts whose results are combined.  Since, in general, the behavior of
 * sort operators is immutable, caller need only worry about the parallel
 * safety of whatever the process is through which input tuples are
 * generated (typically, caller uses a parallel heap scan).
 */


extern Tuplesortstate *tuplesort_begin_common(int workMem,
											  SortCoordinate coordinate,
											  int sortopt);
extern void tuplesort_set_bound(Tuplesortstate *state, int64 bound);
extern bool tuplesort_used_bound(Tuplesortstate *state);
extern void tuplesort_puttuple_common(Tuplesortstate *state,
									  SortTuple *tuple, bool useAbbrev,
									  Size tuplen);
extern void tuplesort_performsort(Tuplesortstate *state);
extern bool tuplesort_gettuple_common(Tuplesortstate *state, bool forward,
									  SortTuple *stup);
extern bool tuplesort_skiptuples(Tuplesortstate *state, int64 ntuples,
								 bool forward);
extern void tuplesort_end(Tuplesortstate *state);
extern void tuplesort_reset(Tuplesortstate *state);

extern void tuplesort_get_stats(Tuplesortstate *state,
								TuplesortInstrumentation *stats);
extern const char *tuplesort_method_name(TuplesortMethod m);
extern const char *tuplesort_space_type_name(TuplesortSpaceType t);

extern int	tuplesort_merge_order(int64 allowedMem);

extern Size tuplesort_estimate_shared(int nWorkers);
extern void tuplesort_initialize_shared(Sharedsort *shared, int nWorkers,
										dsm_segment *seg);
extern void tuplesort_attach_shared(Sharedsort *shared, dsm_segment *seg);

/*
 * These routines may only be called if TUPLESORT_RANDOMACCESS was specified
 * during tuplesort_begin_*.  Additionally backwards scan in gettuple/getdatum
 * also require TUPLESORT_RANDOMACCESS.  Note that parallel sorts do not
 * support random access.
 */
extern void tuplesort_rescan(Tuplesortstate *state);
extern void tuplesort_markpos(Tuplesortstate *state);
extern void tuplesort_restorepos(Tuplesortstate *state);

extern void *tuplesort_readtup_alloc(Tuplesortstate *state, Size tuplen);


/* tuplesortvariants.c */

extern Tuplesortstate *tuplesort_begin_heap(TupleDesc tupDesc,
											int nkeys, AttrNumber *attNums,
											Oid *sortOperators, Oid *sortCollations,
											bool *nullsFirstFlags,
											int workMem, SortCoordinate coordinate,
											int sortopt);
extern Tuplesortstate *tuplesort_begin_cluster(TupleDesc tupDesc,
											   Relation indexRel, int workMem,
											   SortCoordinate coordinate,
											   int sortopt);
extern Tuplesortstate *tuplesort_begin_index_btree(Relation heapRel,
												   Relation indexRel,
												   bool enforceUnique,
												   bool uniqueNullsNotDistinct,
												   int workMem, SortCoordinate coordinate,
												   int sortopt);
extern Tuplesortstate *tuplesort_begin_index_hash(Relation heapRel,
												  Relation indexRel,
												  uint32 high_mask,
												  uint32 low_mask,
												  uint32 max_buckets,
												  int workMem, SortCoordinate coordinate,
												  int sortopt);
extern Tuplesortstate *tuplesort_begin_index_gist(Relation heapRel,
												  Relation indexRel,
												  int workMem, SortCoordinate coordinate,
												  int sortopt);
extern Tuplesortstate *tuplesort_begin_index_brin(int workMem, SortCoordinate coordinate,
												  int sortopt);
extern Tuplesortstate *tuplesort_begin_index_gin(Relation heapRel,
												 Relation indexRel,
												 int workMem, SortCoordinate coordinate,
												 int sortopt);
extern Tuplesortstate *tuplesort_begin_datum(Oid datumType,
											 Oid sortOperator, Oid sortCollation,
											 bool nullsFirstFlag,
											 int workMem, SortCoordinate coordinate,
											 int sortopt);

extern void tuplesort_puttupleslot(Tuplesortstate *state,
								   TupleTableSlot *slot);
extern void tuplesort_putheaptuple(Tuplesortstate *state, HeapTuple tup);
extern void tuplesort_putindextuplevalues(Tuplesortstate *state,
										  Relation rel, const ItemPointerData *self,
										  const Datum *values, const bool *isnull);
extern void tuplesort_putbrintuple(Tuplesortstate *state, BrinTuple *tuple, Size size);
extern void tuplesort_putgintuple(Tuplesortstate *state, GinTuple *tuple, Size size);
extern void tuplesort_putdatum(Tuplesortstate *state, Datum val,
							   bool isNull);

extern bool tuplesort_gettupleslot(Tuplesortstate *state, bool forward,
								   bool copy, TupleTableSlot *slot, Datum *abbrev);
extern HeapTuple tuplesort_getheaptuple(Tuplesortstate *state, bool forward);
extern IndexTuple tuplesort_getindextuple(Tuplesortstate *state, bool forward);
extern BrinTuple *tuplesort_getbrintuple(Tuplesortstate *state, Size *len,
										 bool forward);
extern GinTuple *tuplesort_getgintuple(Tuplesortstate *state, Size *len,
									   bool forward);
extern bool tuplesort_getdatum(Tuplesortstate *state, bool forward, bool copy,
							   Datum *val, bool *isNull, Datum *abbrev);


#endif							/* TUPLESORT_H */
