0001-opt-parallelcost-refactoring-v8.patch

diff --git a/src/backend/optimizer/path/allpaths.c b/src/backend/optimizer/path/allpaths.c
index 46d7d06..3cf9417 100644
--- a/src/backend/optimizer/path/allpaths.c
+++ b/src/backend/optimizer/path/allpaths.c
@@ -126,6 +126,7 @@ static void subquery_push_qual(Query *subquery,
 static void recurse_push_qual(Node *setOp, Query *topquery,
 				  RangeTblEntry *rte, Index rti, Node *qual);
 static void remove_unused_subquery_outputs(Query *subquery, RelOptInfo *rel);
+static int	compute_parallel_worker(RelOptInfo *rel, BlockNumber pages);
 
 
 /*
@@ -678,49 +679,7 @@ create_plain_partial_paths(PlannerInfo *root, RelOptInfo *rel)
 {
 	int			parallel_workers;
 
-	/*
-	 * If the user has set the parallel_workers reloption, use that; otherwise
-	 * select a default number of workers.
-	 */
-	if (rel->rel_parallel_workers != -1)
-		parallel_workers = rel->rel_parallel_workers;
-	else
-	{
-		int			parallel_threshold;
-
-		/*
-		 * If this relation is too small to be worth a parallel scan, just
-		 * return without doing anything ... unless it's an inheritance child.
-		 * In that case, we want to generate a parallel path here anyway.  It
-		 * might not be worthwhile just for this relation, but when combined
-		 * with all of its inheritance siblings it may well pay off.
-		 */
-		if (rel->pages < (BlockNumber) min_parallel_relation_size &&
-			rel->reloptkind == RELOPT_BASEREL)
-			return;
-
-		/*
-		 * Select the number of workers based on the log of the size of the
-		 * relation.  This probably needs to be a good deal more
-		 * sophisticated, but we need something here for now.  Note that the
-		 * upper limit of the min_parallel_relation_size GUC is chosen to
-		 * prevent overflow here.
-		 */
-		parallel_workers = 1;
-		parallel_threshold = Max(min_parallel_relation_size, 1);
-		while (rel->pages >= (BlockNumber) (parallel_threshold * 3))
-		{
-			parallel_workers++;
-			parallel_threshold *= 3;
-			if (parallel_threshold > INT_MAX / 3)
-				break;			/* avoid overflow */
-		}
-	}
-
-	/*
-	 * In no case use more than max_parallel_workers_per_gather workers.
-	 */
-	parallel_workers = Min(parallel_workers, max_parallel_workers_per_gather);
+	parallel_workers = compute_parallel_worker(rel, rel->pages);
 
 	/* If any limit was set to zero, the user doesn't want a parallel scan. */
 	if (parallel_workers <= 0)
@@ -2866,6 +2825,59 @@ remove_unused_subquery_outputs(Query *subquery, RelOptInfo *rel)
 	}
 }
 
+static int
+compute_parallel_worker(RelOptInfo *rel, BlockNumber pages)
+{
+	int			parallel_workers;
+
+	/*
+	 * If the user has set the parallel_workers reloption, use that; otherwise
+	 * select a default number of workers.
+	 */
+	if (rel->rel_parallel_workers != -1)
+		parallel_workers = rel->rel_parallel_workers;
+	else
+	{
+		int			parallel_threshold;
+
+		/*
+		 * If this relation is too small to be worth a parallel scan, just
+		 * return without doing anything ... unless it's an inheritance child.
+		 * In that case, we want to generate a parallel path here anyway.  It
+		 * might not be worthwhile just for this relation, but when combined
+		 * with all of its inheritance siblings it may well pay off.
+		 */
+		if (pages < (BlockNumber) min_parallel_relation_size &&
+			rel->reloptkind == RELOPT_BASEREL)
+			return 0;
+
+		/*
+		 * Select the number of workers based on the log of the size of the
+		 * relation.  This probably needs to be a good deal more
+		 * sophisticated, but we need something here for now.  Note that the
+		 * upper limit of the min_parallel_relation_size GUC is chosen to
+		 * prevent overflow here.
+		 */
+		parallel_workers = 1;
+		parallel_threshold = Max(min_parallel_relation_size, 1);
+		while (pages >= (BlockNumber) (parallel_threshold * 3))
+		{
+			parallel_workers++;
+			parallel_threshold *= 3;
+			if (parallel_threshold > INT_MAX / 3)
+				break;			/* avoid overflow */
+		}
+	}
+
+	/*
+	 * In no case use more than max_parallel_workers_per_gather workers.
+	 */
+	parallel_workers = Min(parallel_workers, max_parallel_workers_per_gather);
+
+	return parallel_workers;
+}
+
+
 /*****************************************************************************
  *			DEBUG SUPPORT
  *****************************************************************************/
diff --git a/src/backend/optimizer/path/costsize.c b/src/backend/optimizer/path/costsize.c
index a52eb7e..deb973b 100644
--- a/src/backend/optimizer/path/costsize.c
+++ b/src/backend/optimizer/path/costsize.c
@@ -161,6 +161,7 @@ static Selectivity get_foreign_key_join_selectivity(PlannerInfo *root,
 static void set_rel_width(PlannerInfo *root, RelOptInfo *rel);
 static double relation_byte_size(double tuples, int width);
 static double page_size(double tuples, int width);
+static Cost update_cost_for_parallelism(Path *path, Cost cpu_run_cost);
 
 
 /*
@@ -237,44 +238,7 @@ cost_seqscan(Path *path, PlannerInfo *root,
 
 	/* Adjust costing for parallelism, if used. */
 	if (path->parallel_workers > 0)
-	{
-		double		parallel_divisor = path->parallel_workers;
-		double		leader_contribution;
-
-		/*
-		 * Early experience with parallel query suggests that when there is
-		 * only one worker, the leader often makes a very substantial
-		 * contribution to executing the parallel portion of the plan, but as
-		 * more workers are added, it does less and less, because it's busy
-		 * reading tuples from the workers and doing whatever non-parallel
-		 * post-processing is needed.  By the time we reach 4 workers, the
-		 * leader no longer makes a meaningful contribution.  Thus, for now,
-		 * estimate that the leader spends 30% of its time servicing each
-		 * worker, and the remainder executing the parallel plan.
-		 */
-		leader_contribution = 1.0 - (0.3 * path->parallel_workers);
-		if (leader_contribution > 0)
-			parallel_divisor += leader_contribution;
-
-		/*
-		 * In the case of a parallel plan, the row count needs to represent
-		 * the number of tuples processed per worker.  Otherwise, higher-level
-		 * plan nodes that appear below the gather will be costed incorrectly,
-		 * because they'll anticipate receiving more rows than any given copy
-		 * will actually get.
-		 */
-		path->rows = clamp_row_est(path->rows / parallel_divisor);
-
-		/* The CPU cost is divided among all the workers. */
-		cpu_run_cost /= parallel_divisor;
-
-		/*
-		 * It may be possible to amortize some of the I/O cost, but probably
-		 * not very much, because most operating systems already do aggressive
-		 * prefetching.  For now, we assume that the disk run cost can't be
-		 * amortized at all.
-		 */
-	}
+		cpu_run_cost = update_cost_for_parallelism(path, cpu_run_cost);
 
 	path->startup_cost = startup_cost;
 	path->total_cost = startup_cost + cpu_run_cost + disk_run_cost;
@@ -831,7 +795,6 @@ cost_bitmap_heap_scan(Path *path, PlannerInfo *root, RelOptInfo *baserel,
 	Cost		startup_cost = 0;
 	Cost		run_cost = 0;
 	Cost		indexTotalCost;
-	Selectivity indexSelectivity;
 	QualCost	qpqual_cost;
 	Cost		cpu_per_tuple;
 	Cost		cost_per_page;
@@ -855,13 +818,12 @@ cost_bitmap_heap_scan(Path *path, PlannerInfo *root, RelOptInfo *baserel,
 	if (!enable_bitmapscan)
 		startup_cost += disable_cost;
 
-	/*
-	 * Fetch total cost of obtaining the bitmap, as well as its total
-	 * selectivity.
-	 */
-	cost_bitmap_tree_node(bitmapqual, &indexTotalCost, &indexSelectivity);
+	pages_fetched = compute_bitmap_pages(root, baserel, bitmapqual,
+										 loop_count, &indexTotalCost,
+										 &tuples_fetched);
 
 	startup_cost += indexTotalCost;
+	T = (baserel->pages > 1) ? (double) baserel->pages : 1.0;
 
 	/* Fetch estimated page costs for tablespace containing table. */
 	get_tablespace_page_costs(baserel->reltablespace,
@@ -869,41 +831,6 @@ cost_bitmap_heap_scan(Path *path, PlannerInfo *root, RelOptInfo *baserel,
 							  &spc_seq_page_cost);
 
 	/*
-	 * Estimate number of main-table pages fetched.
-	 */
-	tuples_fetched = clamp_row_est(indexSelectivity * baserel->tuples);
-
-	T = (baserel->pages > 1) ? (double) baserel->pages : 1.0;
-
-	if (loop_count > 1)
-	{
-		/*
-		 * For repeated bitmap scans, scale up the number of tuples fetched in
-		 * the Mackert and Lohman formula by the number of scans, so that we
-		 * estimate the number of pages fetched by all the scans. Then
-		 * pro-rate for one scan.
-		 */
-		pages_fetched = index_pages_fetched(tuples_fetched * loop_count,
-											baserel->pages,
-											get_indexpath_pages(bitmapqual),
-											root);
-		pages_fetched /= loop_count;
-	}
-	else
-	{
-		/*
-		 * For a single scan, the number of heap pages that need to be fetched
-		 * is the same as the Mackert and Lohman formula for the case T <= b
-		 * (ie, no re-reads needed).
-		 */
-		pages_fetched = (2.0 * T * tuples_fetched) / (2.0 * T + tuples_fetched);
-	}
-	if (pages_fetched >= T)
-		pages_fetched = T;
-	else
-		pages_fetched = ceil(pages_fetched);
-
-	/*
 	 * For small numbers of pages we should charge spc_random_page_cost
 	 * apiece, while if nearly all the table's pages are being read, it's more
 	 * appropriate to charge spc_seq_page_cost apiece.  The effect is
@@ -944,6 +871,56 @@ cost_bitmap_heap_scan(Path *path, PlannerInfo *root, RelOptInfo *baserel,
 }
 
 /*
+ * update_cost_for_parallelism
+ *
+ * Adjust the cpu cost based on number of parallel workers, also update
+ * the number of rows processed at each worker.
+ */
+static Cost
+update_cost_for_parallelism(Path *path, Cost cpu_run_cost)
+{
+	double		parallel_divisor = path->parallel_workers;
+	double		leader_contribution;
+	Cost		cpu_cost = cpu_run_cost;
+
+	/*
+	 * Early experience with parallel query suggests that when there is only
+	 * one worker, the leader often makes a very substantial contribution to
+	 * executing the parallel portion of the plan, but as more workers are
+	 * added, it does less and less, because it's busy reading tuples from the
+	 * workers and doing whatever non-parallel post-processing is needed.  By
+	 * the time we reach 4 workers, the leader no longer makes a meaningful
+	 * contribution.  Thus, for now, estimate that the leader spends 30% of
+	 * its time servicing each worker, and the remainder executing the
+	 * parallel plan.
+	 */
+	leader_contribution = 1.0 - (0.3 * path->parallel_workers);
+	if (leader_contribution > 0)
+		parallel_divisor += leader_contribution;
+
+	/*
+	 * In the case of a parallel plan, the row count needs to represent the
+	 * number of tuples processed per worker.  Otherwise, higher-level plan
+	 * nodes that appear below the gather will be costed incorrectly, because
+	 * they'll anticipate receiving more rows than any given copy will
+	 * actually get.
+	 */
+	path->rows = clamp_row_est(path->rows / parallel_divisor);
+
+	/* The CPU cost is divided among all the workers. */
+	cpu_cost /= parallel_divisor;
+
+	/*
+	 * It may be possible to amortize some of the I/O cost, but probably not
+	 * very much, because most operating systems already do aggressive
+	 * prefetching.  For now, we assume that the disk run cost can't be
+	 * amortized at all.
+	 */
+
+	return cpu_cost;
+}
+
+/*
  * cost_bitmap_tree_node
  *		Extract cost and selectivity from a bitmap tree node (index/and/or)
  */
@@ -4798,3 +4775,69 @@ page_size(double tuples, int width)
 {
 	return ceil(relation_byte_size(tuples, width) / BLCKSZ);
 }
+
+/*
+ * compute_bitmap_pages
+ *
+ * compute number of pages fetched from heap in bitmap heap scan.
+ */
+double
+compute_bitmap_pages(PlannerInfo *root, RelOptInfo *baserel, Path *bitmapqual,
+					 int loop_count, Cost *cost, double *tuple)
+{
+	Cost		indexTotalCost;
+	Selectivity indexSelectivity;
+	double		T;
+	double		pages_fetched;
+	double		tuples_fetched;
+
+	/*
+	 * Fetch total cost of obtaining the bitmap, as well as its total
+	 * selectivity.
+	 */
+	cost_bitmap_tree_node(bitmapqual, &indexTotalCost, &indexSelectivity);
+
+	/*
+	 * Estimate number of main-table pages fetched.
+	 */
+	tuples_fetched = clamp_row_est(indexSelectivity * baserel->tuples);
+
+	T = (baserel->pages > 1) ? (double) baserel->pages : 1.0;
+
+	if (loop_count > 1)
+	{
+		/*
+		 * For repeated bitmap scans, scale up the number of tuples fetched in
+		 * the Mackert and Lohman formula by the number of scans, so that we
+		 * estimate the number of pages fetched by all the scans. Then
+		 * pro-rate for one scan.
+		 */
+		pages_fetched = index_pages_fetched(tuples_fetched * loop_count,
+											baserel->pages,
+											get_indexpath_pages(bitmapqual),
+											root);
+		pages_fetched /= loop_count;
+	}
+	else
+	{
+		/*
+		 * For a single scan, the number of heap pages that need to be fetched
+		 * is the same as the Mackert and Lohman formula for the case T <= b
+		 * (ie, no re-reads needed).
+		 */
+		pages_fetched =
+			(2.0 * T * tuples_fetched) / (2.0 * T + tuples_fetched);
+	}
+
+	if (pages_fetched >= T)
+		pages_fetched = T;
+	else
+		pages_fetched = ceil(pages_fetched);
+
+	if (cost)
+		*cost = indexTotalCost;
+	if (tuple)
+		*tuple = tuples_fetched;
+
+	return pages_fetched;
+}
diff --git a/src/include/optimizer/cost.h b/src/include/optimizer/cost.h
index 39376ec..0e68264 100644
--- a/src/include/optimizer/cost.h
+++ b/src/include/optimizer/cost.h
@@ -183,6 +183,8 @@ extern void set_cte_size_estimates(PlannerInfo *root, RelOptInfo *rel,
 					   double cte_rows);
 extern void set_foreign_size_estimates(PlannerInfo *root, RelOptInfo *rel);
 extern PathTarget *set_pathtarget_cost_width(PlannerInfo *root, PathTarget *target);
+extern double compute_bitmap_pages(PlannerInfo *root, RelOptInfo *baserel,
+				  Path *bitmapqual, int loop_count, Cost *cost, double *tuple);
 
 /*
  * prototypes for clausesel.c