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From: Tomas Vondra <[email protected]>
Subject: [PATCH 2/2] pick MCV items by relative error
Date: Sat, 22 Jun 2019 15:37:40 +0200

---
 src/backend/statistics/mcv.c | 149 +++++++++++++++++++++++++----------
 1 file changed, 109 insertions(+), 40 deletions(-)

diff --git a/src/backend/statistics/mcv.c b/src/backend/statistics/mcv.c
index 04a4f17b01..3056b659e7 100644
--- a/src/backend/statistics/mcv.c
+++ b/src/backend/statistics/mcv.c
@@ -78,6 +78,8 @@ static MultiSortSupport build_mss(VacAttrStats **stats, int numattrs);
 static SortItem *build_distinct_groups(int numrows, SortItem *items,
 									   MultiSortSupport mss, int *ndistinct);
 
+static int sort_item_compare(const void *a, const void *b, void *arg);
+
 static SortItem **build_column_frequencies(SortItem *groups, int ngroups,
 										   MultiSortSupport mss, int *ncounts);
 
@@ -147,6 +149,63 @@ get_mincount_for_mcv_list(int samplerows, double totalrows)
 	return numer / denom;
 }
 
+/*
+ * Represents a group of values, with both the observed and base frequency
+ * (as expected from product of individual columns).
+ */
+typedef struct SortGroup {
+	Datum  *values;
+	bool   *isnull;
+	double	frequency;
+	double	base_frequency;
+} SortGroup;
+
+/*
+ * compare_relative_error
+ *		compare MCV groups by relative estimation error
+ *
+ * We simply compute relative estimation error
+ *
+ *     Max(estimate/actual, actual/estimate)
+ *
+ * and then use that to pick the most mis-estimated groups.
+ */
+static int
+compare_relative_error(const void *a, const void *b)
+{
+	SortGroup  *sa = (SortGroup	*) a;
+	SortGroup  *sb = (SortGroup	*) b;
+
+	double		ea = Max(sa->frequency / sa->base_frequency,
+						 sa->base_frequency / sa->frequency),
+				eb = Max(sb->frequency / sb->base_frequency,
+						 sb->base_frequency / sb->frequency);
+/*
+	double		ea = sa->frequency * abs(sa->base_frequency - sa->base_frequency),
+				eb = sb->frequency * abs(sb->base_frequency - sb->base_frequency);
+*/
+	if (ea > eb)
+		return -1;
+	else if (ea < eb)
+		return 1;
+
+	return 0;
+}
+
+static int
+compare_frequency(const void *a, const void *b)
+{
+	SortGroup  *sa = (SortGroup	*) a;
+	SortGroup  *sb = (SortGroup	*) b;
+
+	if (sa->frequency > sb->frequency)
+		return -1;
+	else if (sa->frequency < sb->frequency)
+		return 1;
+
+	return 0;
+}
+
 /*
  * Builds MCV list from the set of sampled rows.
  *
@@ -177,6 +236,13 @@ statext_mcv_build(int numrows, HeapTuple *rows, Bitmapset *attrs,
 	MultiSortSupport mss;
 	SortItem  **freqs;
 	int		   *nfreqs;
+	SortGroup  *sort_groups;
+	int			nsort_groups;
+	SortItem	key;
+
+		/* space for search key */
+	key.values = palloc(sizeof(Datum));
+	key.isnull = palloc(sizeof(bool));
 
 	attnums = build_attnums_array(attrs, &numattrs);
 
@@ -229,20 +295,55 @@ statext_mcv_build(int numrows, HeapTuple *rows, Bitmapset *attrs,
 	 */
 	mincount = get_mincount_for_mcv_list(numrows, totalrows);
 
+	nsort_groups = 0;
+	sort_groups = (SortGroup *) palloc(sizeof(SortGroup) * ngroups);
+
 	/*
 	 * Walk the groups until we find the first group with a count below the
 	 * mincount threshold (the index of that group is the number of groups we
-	 * want to keep).
+	 * will consider to keep).
 	 */
-	for (i = 0; i < nitems; i++)
+	for (i = 0; i < ngroups; i++)
 	{
+		int	j;
+
 		if (groups[i].count < mincount)
-		{
-			nitems = i;
 			break;
+
+		sort_groups[i].values = groups[i].values;
+		sort_groups[i].isnull = groups[i].isnull;
+		sort_groups[i].frequency = (double) groups[i].count / numrows;
+
+		/* base frequency, if the attributes were independent */
+		sort_groups[i].base_frequency = 1.0;
+		for (j = 0; j < numattrs; j++)
+		{
+			SortItem   *freq;
+
+			/* fill search key */
+			key.values[0] = groups[i].values[j];
+			key.isnull[0] = groups[i].isnull[j];
+
+			freq = (SortItem *) bsearch_arg(&key, freqs[j], nfreqs[j],
+											sizeof(SortItem),
+											sort_item_compare, &mss->ssup[j]);
+
+			sort_groups[i].base_frequency *= ((double) freq->count) / numrows;
 		}
+
+		nsort_groups = i;
 	}
 
+	/* sort the groups by relative error */
+	pg_qsort(sort_groups, nsort_groups, sizeof(SortGroup), compare_relative_error);
+
+	/* make sure we only consider groups that are frequent enough */
+	if (nitems > nsort_groups)
+		nitems = nsort_groups;
+
+	/* sort the first groups by frequency (descending) */
+	pg_qsort(sort_groups, nitems, sizeof(SortGroup), compare_frequency);
+
 	/*
 	 * At this point we know the number of items for the MCV list. There might
 	 * be none (for uniform distribution with many groups), and in that case
@@ -250,18 +351,6 @@ statext_mcv_build(int numrows, HeapTuple *rows, Bitmapset *attrs,
 	 */
 	if (nitems > 0)
 	{
-		int			j;
-		SortItem	key;
-		MultiSortSupport	tmp;
-
-		/* used to search values */
-		tmp = (MultiSortSupport) palloc(offsetof(MultiSortSupportData, ssup)
-										+ sizeof(SortSupportData));
-
-		/* space for search key */
-		key.values = palloc(sizeof(Datum));
-		key.isnull = palloc(sizeof(bool));
-
 		/*
 		 * Allocate the MCV list structure, set the global parameters.
 		 */
@@ -287,35 +376,15 @@ statext_mcv_build(int numrows, HeapTuple *rows, Bitmapset *attrs,
 			item->isnull = (bool *) palloc(sizeof(bool) * numattrs);
 
 			/* copy values for the group */
-			memcpy(item->values, groups[i].values, sizeof(Datum) * numattrs);
-			memcpy(item->isnull, groups[i].isnull, sizeof(bool) * numattrs);
+			memcpy(item->values, sort_groups[i].values, sizeof(Datum) * numattrs);
+			memcpy(item->isnull, sort_groups[i].isnull, sizeof(bool) * numattrs);
 
 			/* groups should be sorted by frequency in descending order */
 			Assert((i == 0) || (groups[i - 1].count >= groups[i].count));
 
 			/* group frequency */
-			item->frequency = (double) groups[i].count / numrows;
-
-			/* base frequency, if the attributes were independent */
-			item->base_frequency = 1.0;
-			for (j = 0; j < numattrs; j++)
-			{
-				SortItem   *freq;
-
-				/* single dimension */
-				tmp->ndims = 1;
-				tmp->ssup[0] = mss->ssup[j];
-
-				/* fill search key */
-				key.values[0] = groups[i].values[j];
-				key.isnull[0] = groups[i].isnull[j];
-
-				freq = (SortItem *) bsearch_arg(&key, freqs[j], nfreqs[j],
-												sizeof(SortItem),
-												multi_sort_compare, tmp);
-
-				item->base_frequency *= ((double) freq->count) / numrows;
-			}
+			item->frequency = sort_groups[i].frequency;
+			item->base_frequency = sort_groups[i].base_frequency;
 		}
 	}
 
-- 
2.20.1


--jxg27ui63xsucoks--





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