Hi,

as this does not get any attention on the docs-list, once again here.
Any thoughts on this?

Regards
Daniel





From: Daniel Westermann (DWE)
Sent: Sunday, September 27, 2020 17:58
To: Pg Docs <pgsql-d...@lists.postgresql.org>
Subject: Wrong example in the bloom documentation 
 
Hi,

I've briefly discussed this with Bruce some time ago in [1].
Replaying the example referenced in the documentation does not give a Bitmap 
Heap Scan on tbloom but a parallel seq scan with the default configuration:

-- tested on head
postgres=# CREATE TABLE tbloom AS
postgres-#    SELECT
postgres-#      (random() * 1000000)::int as i1,
postgres-#      (random() * 1000000)::int as i2,
postgres-#      (random() * 1000000)::int as i3,
postgres-#      (random() * 1000000)::int as i4,
postgres-#      (random() * 1000000)::int as i5,
postgres-#      (random() * 1000000)::int as i6
postgres-#    FROM
postgres-#   generate_series(1,10000000);
SELECT 10000000
postgres=# CREATE INDEX bloomidx ON tbloom USING bloom (i1, i2, i3, i4, i5, i6);
CREATE INDEX
postgres=# CREATE index btreeidx ON tbloom (i1, i2, i3, i4, i5, i6);
CREATE INDEX
postgres=# EXPLAIN ANALYZE SELECT * FROM tbloom WHERE i2 = 898732 AND i5 = 
123451;
                                                         QUERY PLAN             
                                             
-----------------------------------------------------------------------------------------------------------------------------
 Gather  (cost=1000.00..127220.00 rows=250 width=24) (actual 
time=2134.851..2221.836 rows=0 loops=1)
   Workers Planned: 2
   Workers Launched: 2
   ->  Parallel Seq Scan on tbloom  (cost=0.00..126195.00 rows=104 width=24) 
(actual time=1770.691..1770.692 rows=0 loops=3)
         Filter: ((i2 = 898732) AND (i5 = 123451))
         Rows Removed by Filter: 3333333
 Planning Time: 0.895 ms
 JIT:
   Functions: 6
   Options: Inlining false, Optimization false, Expressions true, Deforming true
   Timing: Generation 65.512 ms, Inlining 0.000 ms, Optimization 46.328 ms, 
Emission 40.658 ms, Total 152.499 ms
 Execution Time: 2288.056 ms
(12 rows)


As bloom was introduced in 9.6 I quickly tried with 9.6.17 and indeed for this 
version the example is correct:
postgres=# select version();
                                                 version                        
                          
----------------------------------------------------------------------------------------------------------
 PostgreSQL 9.6.17 on x86_64-pc-linux-gnu, compiled by gcc (GCC) 8.3.1 20190507 
(Red Hat 8.3.1-4), 64-bit
(1 row)
postgres=# CREATE TABLE tbloom AS
postgres-#    SELECT
postgres-#      (random() * 1000000)::int as i1,
postgres-#      (random() * 1000000)::int as i2,
postgres-#      (random() * 1000000)::int as i3,
postgres-#      (random() * 1000000)::int as i4,
postgres-#      (random() * 1000000)::int as i5,
postgres-#      (random() * 1000000)::int as i6
postgres-#    FROM
postgres-#   generate_series(1,10000000);
SELECT 10000000
postgres=# CREATE INDEX bloomidx ON tbloom USING bloom (i1, i2, i3, i4, i5, i6);
CREATE INDEX
postgres=# CREATE index btreeidx ON tbloom (i1, i2, i3, i4, i5, i6);
CREATE INDEX
postgres=# EXPLAIN ANALYZE SELECT * FROM tbloom WHERE i2 = 898732 AND i5 = 
123451;
                                                          QUERY PLAN            
                                               
-------------------------------------------------------------------------------------------------------------------------------
 Bitmap Heap Scan on tbloom  (cost=178436.06..179392.83 rows=250 width=24) 
(actual time=2279.363..2279.363 rows=0 loops=1)
   Recheck Cond: ((i2 = 898732) AND (i5 = 123451))
   Rows Removed by Index Recheck: 2329
   Heap Blocks: exact=2288
   ->  Bitmap Index Scan on bloomidx  (cost=0.00..178436.00 rows=250 width=0) 
(actual time=994.406..994.406 rows=2329 loops=1)
         Index Cond: ((i2 = 898732) AND (i5 = 123451))
 Planning time: 282.059 ms
 Execution time: 2286.138 ms
(8 rows)

The reason is that parallel execution is disabled by default in 9.6, and if 
that is turned on the plan changes there as well:

postgres=# set max_parallel_workers_per_gather = 2;
SET
postgres=# EXPLAIN ANALYZE SELECT * FROM tbloom WHERE i2 = 898732 AND i5 = 
123451;
                                                        QUERY PLAN              
                                           
---------------------------------------------------------------------------------------------------------------------------
 Gather  (cost=1000.00..127194.29 rows=1 width=24) (actual 
time=1148.047..1148.206 rows=0 loops=1)
   Workers Planned: 2
   Workers Launched: 2
   ->  Parallel Seq Scan on tbloom  (cost=0.00..126194.19 rows=1 width=24) 
(actual time=1039.501..1039.501 rows=0 loops=3)
         Filter: ((i2 = 898732) AND (i5 = 123451))
         Rows Removed by Filter: 3333333
 Planning time: 0.580 ms
 Execution time: 1148.247 ms
(8 rows)

Starting with PostgreSQL 10 the example in the documentation is therefore 
wrong. Attached a proposal to fix this. The new example starts with 100x 
reduced rows (as suggested by Bruce in [1] and adds a note that the behavior 
changes as soon as parallel execution is cheaper than the index access.

Thoughts?

Regards
Daniel

[1] 
https://www.postgresql.org/message-id/flat/20191105231854.GA26542%40momjian.us#7859b106ce614dd9530941196dad5bbc
diff --git a/doc/src/sgml/bloom.sgml b/doc/src/sgml/bloom.sgml
index 285b67b3f1..1af9b8fbab 100644
--- a/doc/src/sgml/bloom.sgml
+++ b/doc/src/sgml/bloom.sgml
@@ -108,77 +108,81 @@ CREATE INDEX bloomidx ON tbloom USING bloom (i1,i2,i3)
      (random() * 1000000)::int as i5,
      (random() * 1000000)::int as i6
    FROM
-  generate_series(1,10000000);
-SELECT 10000000
+  generate_series(1,10000);
+SELECT 10000
 =# CREATE INDEX bloomidx ON tbloom USING bloom (i1, i2, i3, i4, i5, i6);
 CREATE INDEX
 =# SELECT pg_size_pretty(pg_relation_size('bloomidx'));
- pg_size_pretty
+ pg_size_pretty 
 ----------------
- 153 MB
+ 168 kB
 (1 row)
 =# CREATE index btreeidx ON tbloom (i1, i2, i3, i4, i5, i6);
 CREATE INDEX
 =# SELECT pg_size_pretty(pg_relation_size('btreeidx'));
- pg_size_pretty
+ pg_size_pretty 
 ----------------
- 387 MB
+ 416 kB
 (1 row)
 </programlisting>
 
   <para>
-   A sequential scan over this large table takes a long time:
+   Wihtout the two indexes being created, a parallel sequential scan will happen for the query below: 
 <programlisting>
 =# EXPLAIN ANALYZE SELECT * FROM tbloom WHERE i2 = 898732 AND i5 = 123451;
-                                                 QUERY PLAN
--------------------------------------------------------------------&zwsp;-----------------------------------------
- Seq Scan on tbloom  (cost=0.00..213694.08 rows=1 width=24) (actual time=1445.438..1445.438 rows=0 loops=1)
+                                            QUERY PLAN                                             
+---------------------------------------------------------------------------------------------------
+ Seq Scan on tbloom  (cost=0.00..214.00 rows=1 width=24) (actual time=2.729..2.731 rows=0 loops=1)
    Filter: ((i2 = 898732) AND (i5 = 123451))
-   Rows Removed by Filter: 10000000
- Planning time: 0.177 ms
- Execution time: 1445.473 ms
+   Rows Removed by Filter: 10000
+ Planning Time: 0.257 ms
+ Execution Time: 2.764 ms
 (5 rows)
 </programlisting>
   </para>
 
   <para>
    So the planner will usually select an index scan if possible.
-   With a btree index, we get results like this:
+   But even with the btree index defined the result will still be a sequential scan:
 <programlisting>
 =# EXPLAIN ANALYZE SELECT * FROM tbloom WHERE i2 = 898732 AND i5 = 123451;
-                                                           QUERY PLAN
--------------------------------------------------------------------&zwsp;-------------------------------------------------------------
- Index Only Scan using btreeidx on tbloom  (cost=0.56..298311.96 rows=1 width=24) (actual time=445.709..445.709 rows=0 loops=1)
-   Index Cond: ((i2 = 898732) AND (i5 = 123451))
-   Heap Fetches: 0
- Planning time: 0.193 ms
- Execution time: 445.770 ms
-(5 rows)
+                                                         QUERY PLAN                                                          
+-----------------------------------------------------------------------------------------------------------------------------
+ Gather  (cost=1000.00..127220.00 rows=250 width=24) (actual time=2191.907..2271.154 rows=0 loops=1)
+   Workers Planned: 2
+   Workers Launched: 2
+   ->  Parallel Seq Scan on tbloom  (cost=0.00..126195.00 rows=104 width=24) (actual time=1591.546..1591.547 rows=0 loops=3)
+         Filter: ((i2 = 898732) AND (i5 = 123451))
+         Rows Removed by Filter: 3333333
+ Planning Time: 31.985 ms
+ JIT:
+   Functions: 6
+   Options: Inlining false, Optimization false, Expressions true, Deforming true
+   Timing: Generation 468.814 ms, Inlining 0.000 ms, Optimization 67.622 ms, Emission 97.406 ms, Total 633.842 ms
+ Execution Time: 2745.745 ms
+(12 rows)
 </programlisting>
   </para>
 
   <para>
-   Bloom is better than btree in handling this type of search:
+   Having the bloom index defined on the table is better than btree in handling this type of search:
 <programlisting>
 =# EXPLAIN ANALYZE SELECT * FROM tbloom WHERE i2 = 898732 AND i5 = 123451;
-                                                        QUERY PLAN
--------------------------------------------------------------------&zwsp;--------------------------------------------------------
- Bitmap Heap Scan on tbloom  (cost=178435.39..178439.41 rows=1 width=24) (actual time=76.698..76.698 rows=0 loops=1)
+                                                    QUERY PLAN                                                     
+-------------------------------------------------------------------------------------------------------------------
+ Bitmap Heap Scan on tbloom  (cost=184.00..188.02 rows=1 width=24) (actual time=0.212..0.215 rows=0 loops=1)
    Recheck Cond: ((i2 = 898732) AND (i5 = 123451))
-   Rows Removed by Index Recheck: 2439
-   Heap Blocks: exact=2408
-   -&gt;  Bitmap Index Scan on bloomidx  (cost=0.00..178435.39 rows=1 width=0) (actual time=72.455..72.455 rows=2439 loops=1)
+   Rows Removed by Index Recheck: 3
+   Heap Blocks: exact=3
+   ->  Bitmap Index Scan on bloomidx  (cost=0.00..184.00 rows=1 width=0) (actual time=0.135..0.136 rows=3 loops=1)
          Index Cond: ((i2 = 898732) AND (i5 = 123451))
- Planning time: 0.475 ms
- Execution time: 76.778 ms
+ Planning Time: 0.466 ms
+ Execution Time: 0.272 ms
 (8 rows)
 </programlisting>
-   Note the relatively large number of false positives: 2439 rows were
+   Note the number of false positives: 3 rows were
    selected to be visited in the heap, but none actually matched the
    query.  We could reduce that by specifying a larger signature length.
-   In this example, creating the index with <literal>length=200</literal>
-   reduced the number of false positives to 55; but it doubled the index size
-   (to 306 MB) and ended up being slower for this query (125 ms overall).
   </para>
 
   <para>
@@ -188,24 +192,44 @@ CREATE INDEX
    Then the planner will choose something like this:
 <programlisting>
 =# EXPLAIN ANALYZE SELECT * FROM tbloom WHERE i2 = 898732 AND i5 = 123451;
-                                                          QUERY PLAN
--------------------------------------------------------------------&zwsp;-----------------------------------------------------------
- Bitmap Heap Scan on tbloom  (cost=9.29..13.30 rows=1 width=24) (actual time=0.148..0.148 rows=0 loops=1)
-   Recheck Cond: ((i5 = 123451) AND (i2 = 898732))
-   -&gt;  BitmapAnd  (cost=9.29..9.29 rows=1 width=0) (actual time=0.145..0.145 rows=0 loops=1)
-         -&gt;  Bitmap Index Scan on tbloom_i5_idx  (cost=0.00..4.52 rows=11 width=0) (actual time=0.089..0.089 rows=10 loops=1)
-               Index Cond: (i5 = 123451)
-         -&gt;  Bitmap Index Scan on tbloom_i2_idx  (cost=0.00..4.52 rows=11 width=0) (actual time=0.048..0.048 rows=8 loops=1)
-               Index Cond: (i2 = 898732)
- Planning time: 2.049 ms
- Execution time: 0.280 ms
-(9 rows)
+                                                      QUERY PLAN                                                       
+-----------------------------------------------------------------------------------------------------------------------
+ Index Scan using tbloom_i2_idx on tbloom  (cost=0.29..8.30 rows=1 width=24) (actual time=0.051..0.052 rows=0 loops=1)
+   Index Cond: (i2 = 898732)
+   Filter: (i5 = 123451)
+ Planning Time: 0.749 ms
+ Execution Time: 0.152 ms
+(5 rows)
 </programlisting>
    Although this query runs much faster than with either of the single
    indexes, we pay a large penalty in index size.  Each of the single-column
-   btree indexes occupies 214 MB, so the total space needed is over 1.2GB,
+   btree indexes occupies 240 kB, so the total space needed is over 1.2MB,
    more than 8 times the space used by the bloom index.
   </para>
+  <para>
+   The more rows the base tables contains, the more likely it is that parallel
+   execution will kick in. Replaying the example with 10000000 instead
+   of 100000 rows will show the effect:
+<programlisting>
+# EXPLAIN ANALYZE SELECT * FROM tbloom WHERE i2 = 898732 AND i5 = 123451;
+                                                         QUERY PLAN                                                          
+-----------------------------------------------------------------------------------------------------------------------------
+ Gather  (cost=1000.00..127220.00 rows=250 width=24) (actual time=2396.384..2494.623 rows=0 loops=1)
+   Workers Planned: 2
+   Workers Launched: 2
+   ->  Parallel Seq Scan on tbloom  (cost=0.00..126195.00 rows=104 width=24) (actual time=2116.296..2116.297 rows=0 loops=3)
+         Filter: ((i2 = 898732) AND (i5 = 123451))
+         Rows Removed by Filter: 3333333
+ Planning Time: 0.852 ms
+ JIT:
+   Functions: 6
+   Options: Inlining false, Optimization false, Expressions true, Deforming true
+   Timing: Generation 62.110 ms, Inlining 0.000 ms, Optimization 116.191 ms, Emission 104.750 ms, Total 283.051 ms
+ Execution Time: 2558.945 ms
+(12 rows)
+</programlisting>
+  In this case the bloom index as well as the btree index do not help for this query.
+  </para>
  </sect2>
 
  <sect2>

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