Add optimizer and executor support for parallel index scans.

In combination with 569174f1be92be93f5366212cc46960d28a5c5cd, which
taught the btree AM how to perform parallel index scans, this allows
parallel index scan plans on btree indexes.  This infrastructure
should be general enough to support parallel index scans for other
index AMs as well, if someone updates them to support parallel
scans.

Amit Kapila, reviewed and tested by Anastasia Lubennikova, Tushar
Ahuja, and Haribabu Kommi, and me.

1 files changed, 49 insertions, 4 deletions

diff --git a/src/backend/optimizer/path/costsize.c b/src/backend/optimizer/path/costsize.c
index a43daa744c7..d01630f8dba 100644
--- a/src/backend/optimizer/path/costsize.c
+++ b/src/backend/optimizer/path/costsize.c
@@ -391,7 +391,8 @@ cost_gather(GatherPath *path, PlannerInfo *root,
  * we have to fetch from the table, so they don't reduce the scan cost.
  */
 void
-cost_index(IndexPath *path, PlannerInfo *root, double loop_count)
+cost_index(IndexPath *path, PlannerInfo *root, double loop_count,
+		   bool partial_path)
 {
 	IndexOptInfo *index = path->indexinfo;
 	RelOptInfo *baserel = index->rel;
@@ -400,6 +401,7 @@ cost_index(IndexPath *path, PlannerInfo *root, double loop_count)
 	List	   *qpquals;
 	Cost		startup_cost = 0;
 	Cost		run_cost = 0;
+	Cost		cpu_run_cost = 0;
 	Cost		indexStartupCost;
 	Cost		indexTotalCost;
 	Selectivity indexSelectivity;
@@ -413,6 +415,8 @@ cost_index(IndexPath *path, PlannerInfo *root, double loop_count)
 	Cost		cpu_per_tuple;
 	double		tuples_fetched;
 	double		pages_fetched;
+	double		rand_heap_pages;
+	double		index_pages;
 
 	/* Should only be applied to base relations */
 	Assert(IsA(baserel, RelOptInfo) &&
@@ -459,7 +463,8 @@ cost_index(IndexPath *path, PlannerInfo *root, double loop_count)
 	amcostestimate = (amcostestimate_function) index->amcostestimate;
 	amcostestimate(root, path, loop_count,
 				   &indexStartupCost, &indexTotalCost,
-				   &indexSelectivity, &indexCorrelation);
+				   &indexSelectivity, &indexCorrelation,
+				   &index_pages);
 
 	/*
 	 * Save amcostestimate's results for possible use in bitmap scan planning.
@@ -526,6 +531,8 @@ cost_index(IndexPath *path, PlannerInfo *root, double loop_count)
 		if (indexonly)
 			pages_fetched = ceil(pages_fetched * (1.0 - baserel->allvisfrac));
 
+		rand_heap_pages = pages_fetched;
+
 		max_IO_cost = (pages_fetched * spc_random_page_cost) / loop_count;
 
 		/*
@@ -564,6 +571,8 @@ cost_index(IndexPath *path, PlannerInfo *root, double loop_count)
 		if (indexonly)
 			pages_fetched = ceil(pages_fetched * (1.0 - baserel->allvisfrac));
 
+		rand_heap_pages = pages_fetched;
+
 		/* max_IO_cost is for the perfectly uncorrelated case (csquared=0) */
 		max_IO_cost = pages_fetched * spc_random_page_cost;
 
@@ -583,6 +592,29 @@ cost_index(IndexPath *path, PlannerInfo *root, double loop_count)
 			min_IO_cost = 0;
 	}
 
+	if (partial_path)
+	{
+		/*
+		 * Estimate the number of parallel workers required to scan index. Use
+		 * the number of heap pages computed considering heap fetches won't be
+		 * sequential as for parallel scans the pages are accessed in random
+		 * order.
+		 */
+		path->path.parallel_workers = compute_parallel_worker(baserel,
+											   (BlockNumber) rand_heap_pages,
+												  (BlockNumber) index_pages);
+
+		/*
+		 * Fall out if workers can't be assigned for parallel scan, because in
+		 * such a case this path will be rejected.  So there is no benefit in
+		 * doing extra computation.
+		 */
+		if (path->path.parallel_workers <= 0)
+			return;
+
+		path->path.parallel_aware = true;
+	}
+
 	/*
 	 * Now interpolate based on estimated index order correlation to get total
 	 * disk I/O cost for main table accesses.
@@ -602,11 +634,24 @@ cost_index(IndexPath *path, PlannerInfo *root, double loop_count)
 	startup_cost += qpqual_cost.startup;
 	cpu_per_tuple = cpu_tuple_cost + qpqual_cost.per_tuple;
 
-	run_cost += cpu_per_tuple * tuples_fetched;
+	cpu_run_cost += cpu_per_tuple * tuples_fetched;
 
 	/* tlist eval costs are paid per output row, not per tuple scanned */
 	startup_cost += path->path.pathtarget->cost.startup;
-	run_cost += path->path.pathtarget->cost.per_tuple * path->path.rows;
+	cpu_run_cost += path->path.pathtarget->cost.per_tuple * path->path.rows;
+
+	/* Adjust costing for parallelism, if used. */
+	if (path->path.parallel_workers > 0)
+	{
+		double		parallel_divisor = get_parallel_divisor(&path->path);
+
+		path->path.rows = clamp_row_est(path->path.rows / parallel_divisor);
+
+		/* The CPU cost is divided among all the workers. */
+		cpu_run_cost /= parallel_divisor;
+	}
+
+	run_cost += cpu_run_cost;
 
 	path->path.startup_cost = startup_cost;
 	path->path.total_cost = startup_cost + run_cost;