/*-------------------------------------------------------------------------
 *
 * ts_selfuncs.c
 *	  Selectivity estimation functions for text search operators.
 *
 * Portions Copyright (c) 1996-2014, PostgreSQL Global Development Group
 *
 *
 * IDENTIFICATION
 *	  src/backend/tsearch/ts_selfuncs.c
 *
 *-------------------------------------------------------------------------
 */
#include "postgres.h"

#include "access/htup_details.h"
#include "catalog/pg_statistic.h"
#include "catalog/pg_type.h"
#include "miscadmin.h"
#include "nodes/nodes.h"
#include "tsearch/ts_type.h"
#include "utils/lsyscache.h"
#include "utils/selfuncs.h"
#include "utils/syscache.h"


/*
 * The default text search selectivity is chosen to be small enough to
 * encourage indexscans for typical table densities.  See selfuncs.h and
 * DEFAULT_EQ_SEL for details.
 */
#define DEFAULT_TS_MATCH_SEL 0.005

/* lookup table type for binary searching through MCELEMs */
typedef struct
{
	text	   *element;
	float4		frequency;
} TextFreq;

/* type of keys for bsearch'ing through an array of TextFreqs */
typedef struct
{
	char	   *lexeme;
	int			length;
} LexemeKey;

static Selectivity tsquerysel(VariableStatData *vardata, Datum constval);
static Selectivity mcelem_tsquery_selec(TSQuery query,
					 Datum *mcelem, int nmcelem,
					 float4 *numbers, int nnumbers);
static Selectivity tsquery_opr_selec(QueryItem *item, char *operand,
				  TextFreq *lookup, int length, float4 minfreq);
static int	compare_lexeme_textfreq(const void *e1, const void *e2);

#define tsquery_opr_selec_no_stats(query) \
	tsquery_opr_selec(GETQUERY(query), GETOPERAND(query), NULL, 0, 0)


/*
 *	tsmatchsel -- Selectivity of "@@"
 *
 * restriction selectivity function for tsvector @@ tsquery and
 * tsquery @@ tsvector
 */
Datum
tsmatchsel(PG_FUNCTION_ARGS)
{
	PlannerInfo *root = (PlannerInfo *) PG_GETARG_POINTER(0);

#ifdef NOT_USED
	Oid			operator = PG_GETARG_OID(1);
#endif
	List	   *args = (List *) PG_GETARG_POINTER(2);
	int			varRelid = PG_GETARG_INT32(3);
	VariableStatData vardata;
	Node	   *other;
	bool		varonleft;
	Selectivity selec;

	/*
	 * If expression is not variable = something or something = variable, then
	 * punt and return a default estimate.
	 */
	if (!get_restriction_variable(root, args, varRelid,
								  &vardata, &other, &varonleft))
		PG_RETURN_FLOAT8(DEFAULT_TS_MATCH_SEL);

	/*
	 * Can't do anything useful if the something is not a constant, either.
	 */
	if (!IsA(other, Const))
	{
		ReleaseVariableStats(vardata);
		PG_RETURN_FLOAT8(DEFAULT_TS_MATCH_SEL);
	}

	/*
	 * The "@@" operator is strict, so we can cope with NULL right away
	 */
	if (((Const *) other)->constisnull)
	{
		ReleaseVariableStats(vardata);
		PG_RETURN_FLOAT8(0.0);
	}

	/*
	 * OK, there's a Var and a Const we're dealing with here.  We need the
	 * Const to be a TSQuery, else we can't do anything useful.  We have to
	 * check this because the Var might be the TSQuery not the TSVector.
	 */
	if (((Const *) other)->consttype == TSQUERYOID)
	{
		/* tsvector @@ tsquery or the other way around */
		Assert(vardata.vartype == TSVECTOROID);

		selec = tsquerysel(&vardata, ((Const *) other)->constvalue);
	}
	else
	{
		/* If we can't see the query structure, must punt */
		selec = DEFAULT_TS_MATCH_SEL;
	}

	ReleaseVariableStats(vardata);

	CLAMP_PROBABILITY(selec);

	PG_RETURN_FLOAT8((float8) selec);
}


/*
 *	tsmatchjoinsel -- join selectivity of "@@"
 *
 * join selectivity function for tsvector @@ tsquery and tsquery @@ tsvector
 */
Datum
tsmatchjoinsel(PG_FUNCTION_ARGS)
{
	/* for the moment we just punt */
	PG_RETURN_FLOAT8(DEFAULT_TS_MATCH_SEL);
}


/*
 * @@ selectivity for tsvector var vs tsquery constant
 */
static Selectivity
tsquerysel(VariableStatData *vardata, Datum constval)
{
	Selectivity selec;
	TSQuery		query;

	/* The caller made sure the const is a TSQuery, so get it now */
	query = DatumGetTSQuery(constval);

	/* Empty query matches nothing */
	if (query->size == 0)
		return (Selectivity) 0.0;

	if (HeapTupleIsValid(vardata->statsTuple))
	{
		Form_pg_statistic stats;
		Datum	   *values;
		int			nvalues;
		float4	   *numbers;
		int			nnumbers;

		stats = (Form_pg_statistic) GETSTRUCT(vardata->statsTuple);

		/* MCELEM will be an array of TEXT elements for a tsvector column */
		if (get_attstatsslot(vardata->statsTuple,
							 TEXTOID, -1,
							 STATISTIC_KIND_MCELEM, InvalidOid,
							 NULL,
							 &values, &nvalues,
							 &numbers, &nnumbers))
		{
			/*
			 * There is a most-common-elements slot for the tsvector Var, so
			 * use that.
			 */
			selec = mcelem_tsquery_selec(query, values, nvalues,
										 numbers, nnumbers);
			free_attstatsslot(TEXTOID, values, nvalues, numbers, nnumbers);
		}
		else
		{
			/* No most-common-elements info, so do without */
			selec = tsquery_opr_selec_no_stats(query);
		}

		/*
		 * MCE stats count only non-null rows, so adjust for null rows.
		 */
		selec *= (1.0 - stats->stanullfrac);
	}
	else
	{
		/* No stats at all, so do without */
		selec = tsquery_opr_selec_no_stats(query);
		/* we assume no nulls here, so no stanullfrac correction */
	}

	return selec;
}

/*
 * Extract data from the pg_statistic arrays into useful format.
 */
static Selectivity
mcelem_tsquery_selec(TSQuery query, Datum *mcelem, int nmcelem,
					 float4 *numbers, int nnumbers)
{
	float4		minfreq;
	TextFreq   *lookup;
	Selectivity selec;
	int			i;

	/*
	 * There should be two more Numbers than Values, because the last two
	 * cells are taken for minimal and maximal frequency.  Punt if not.
	 *
	 * (Note: the MCELEM statistics slot definition allows for a third extra
	 * number containing the frequency of nulls, but we're not expecting that
	 * to appear for a tsvector column.)
	 */
	if (nnumbers != nmcelem + 2)
		return tsquery_opr_selec_no_stats(query);

	/*
	 * Transpose the data into a single array so we can use bsearch().
	 */
	lookup = (TextFreq *) palloc(sizeof(TextFreq) * nmcelem);
	for (i = 0; i < nmcelem; i++)
	{
		/*
		 * The text Datums came from an array, so it cannot be compressed or
		 * stored out-of-line -- it's safe to use VARSIZE_ANY*.
		 */
		Assert(!VARATT_IS_COMPRESSED(mcelem[i]) && !VARATT_IS_EXTERNAL(mcelem[i]));
		lookup[i].element = (text *) DatumGetPointer(mcelem[i]);
		lookup[i].frequency = numbers[i];
	}

	/*
	 * Grab the lowest frequency. compute_tsvector_stats() stored it for us in
	 * the one before the last cell of the Numbers array. See ts_typanalyze.c
	 */
	minfreq = numbers[nnumbers - 2];

	selec = tsquery_opr_selec(GETQUERY(query), GETOPERAND(query), lookup,
							  nmcelem, minfreq);

	pfree(lookup);

	return selec;
}

/*
 * Traverse the tsquery in preorder, calculating selectivity as:
 *
 *	 selec(left_oper) * selec(right_oper) in AND nodes,
 *
 *	 selec(left_oper) + selec(right_oper) -
 *		selec(left_oper) * selec(right_oper) in OR nodes,
 *
 *	 1 - select(oper) in NOT nodes
 *
 *	 histogram-based estimation in prefix VAL nodes
 *
 *	 freq[val] in exact VAL nodes, if the value is in MCELEM
 *	 min(freq[MCELEM]) / 2 in VAL nodes, if it is not
 *
 * The MCELEM array is already sorted (see ts_typanalyze.c), so we can use
 * binary search for determining freq[MCELEM].
 *
 * If we don't have stats for the tsvector, we still use this logic,
 * except we use default estimates for VAL nodes.  This case is signaled
 * by lookup == NULL.
 */
static Selectivity
tsquery_opr_selec(QueryItem *item, char *operand,
				  TextFreq *lookup, int length, float4 minfreq)
{
	Selectivity selec;

	/* since this function recurses, it could be driven to stack overflow */
	check_stack_depth();

	if (item->type == QI_VAL)
	{
		QueryOperand *oper = (QueryOperand *) item;
		LexemeKey	key;

		/*
		 * Prepare the key for bsearch().
		 */
		key.lexeme = operand + oper->distance;
		key.length = oper->length;

		if (oper->prefix)
		{
			/* Prefix match, ie the query item is lexeme:* */
			Selectivity matched,
						allmces;
			int			i,
						n_matched;

			/*
			 * Our strategy is to scan through the MCELEM list and combine the
			 * frequencies of the ones that match the prefix.  We then
			 * extrapolate the fraction of matching MCELEMs to the remaining
			 * rows, assuming that the MCELEMs are representative of the whole
			 * lexeme population in this respect.  (Compare
			 * histogram_selectivity().)  Note that these are most common
			 * elements not most common values, so they're not mutually
			 * exclusive.  We treat occurrences as independent events.
			 *
			 * This is only a good plan if we have a pretty fair number of
			 * MCELEMs available; we set the threshold at 100.  If no stats or
			 * insufficient stats, arbitrarily use DEFAULT_TS_MATCH_SEL*4.
			 */
			if (lookup == NULL || length < 100)
				return (Selectivity) (DEFAULT_TS_MATCH_SEL * 4);

			matched = allmces = 0;
			n_matched = 0;
			for (i = 0; i < length; i++)
			{
				TextFreq   *t = lookup + i;
				int			tlen = VARSIZE_ANY_EXHDR(t->element);

				if (tlen >= key.length &&
					strncmp(key.lexeme, VARDATA_ANY(t->element),
							key.length) == 0)
				{
					matched += t->frequency - matched * t->frequency;
					n_matched++;
				}
				allmces += t->frequency - allmces * t->frequency;
			}

			/* Clamp to ensure sanity in the face of roundoff error */
			CLAMP_PROBABILITY(matched);
			CLAMP_PROBABILITY(allmces);

			selec = matched + (1.0 - allmces) * ((double) n_matched / length);

			/*
			 * In any case, never believe that a prefix match has selectivity
			 * less than we would assign for a non-MCELEM lexeme.  This
			 * preserves the property that "word:*" should be estimated to
			 * match at least as many rows as "word" would be.
			 */
			selec = Max(Min(DEFAULT_TS_MATCH_SEL, minfreq / 2), selec);
		}
		else
		{
			/* Regular exact lexeme match */
			TextFreq   *searchres;

			/* If no stats for the variable, use DEFAULT_TS_MATCH_SEL */
			if (lookup == NULL)
				return (Selectivity) DEFAULT_TS_MATCH_SEL;

			searchres = (TextFreq *) bsearch(&key, lookup, length,
											 sizeof(TextFreq),
											 compare_lexeme_textfreq);

			if (searchres)
			{
				/*
				 * The element is in MCELEM.  Return precise selectivity (or
				 * at least as precise as ANALYZE could find out).
				 */
				selec = searchres->frequency;
			}
			else
			{
				/*
				 * The element is not in MCELEM.  Punt, but assume that the
				 * selectivity cannot be more than minfreq / 2.
				 */
				selec = Min(DEFAULT_TS_MATCH_SEL, minfreq / 2);
			}
		}
	}
	else
	{
		/* Current TSQuery node is an operator */
		Selectivity s1,
					s2;

		switch (item->qoperator.oper)
		{
			case OP_NOT:
				selec = 1.0 - tsquery_opr_selec(item + 1, operand,
												lookup, length, minfreq);
				break;

			case OP_AND:
				s1 = tsquery_opr_selec(item + 1, operand,
									   lookup, length, minfreq);
				s2 = tsquery_opr_selec(item + item->qoperator.left, operand,
									   lookup, length, minfreq);
				selec = s1 * s2;
				break;

			case OP_OR:
				s1 = tsquery_opr_selec(item + 1, operand,
									   lookup, length, minfreq);
				s2 = tsquery_opr_selec(item + item->qoperator.left, operand,
									   lookup, length, minfreq);
				selec = s1 + s2 - s1 * s2;
				break;

			default:
				elog(ERROR, "unrecognized operator: %d", item->qoperator.oper);
				selec = 0;		/* keep compiler quiet */
				break;
		}
	}

	/* Clamp intermediate results to stay sane despite roundoff error */
	CLAMP_PROBABILITY(selec);

	return selec;
}

/*
 * bsearch() comparator for a lexeme (non-NULL terminated string with length)
 * and a TextFreq. Use length, then byte-for-byte comparison, because that's
 * how ANALYZE code sorted data before storing it in a statistic tuple.
 * See ts_typanalyze.c for details.
 */
static int
compare_lexeme_textfreq(const void *e1, const void *e2)
{
	const LexemeKey *key = (const LexemeKey *) e1;
	const TextFreq *t = (const TextFreq *) e2;
	int			len1,
				len2;

	len1 = key->length;
	len2 = VARSIZE_ANY_EXHDR(t->element);

	/* Compare lengths first, possibly avoiding a strncmp call */
	if (len1 > len2)
		return 1;
	else if (len1 < len2)
		return -1;

	/* Fall back on byte-for-byte comparison */
	return strncmp(key->lexeme, VARDATA_ANY(t->element), len1);
}
