postgresql/doc/src/sgml/bloom.sgml

<!-- doc/src/sgml/bloom.sgml -->

<sect1 id="bloom" xreflabel="bloom">
 <title>bloom</title>

 <indexterm zone="bloom">
  <primary>bloom</primary>
 </indexterm>

 <para>
  <literal>bloom</> is a contrib which implements index access method.  It comes
  as example of custom access methods and generic WAL records usage.  But it
  is also useful itself.
 </para>

 <sect2>
  <title>Introduction</title>

  <para>
   Implementation of
   <ulink url="http://en.wikipedia.org/wiki/Bloom_filter">Bloom filter</ulink>
   allows fast exclusion of non-candidate tuples.
   Since signature is a lossy representation of all indexed attributes, 
   search results should be rechecked using heap information. 
   User can specify signature length (in uint16, default is 5) and the number of 
   bits, which can be setted, per attribute (1 < colN < 2048).
  </para>

  <para>
   This index is useful if table has many attributes and queries can include
   their arbitary combinations.  Traditional <literal>btree</> index is faster
   than bloom index, but it'd require too many indexes to support all possible 
   queries, while one need only one bloom index.  Bloom index supports only 
   equality comparison.  Since it's a signature file, not a tree, it always
   should be readed fully, but sequentially, so index search performance is 
   constant and doesn't depend on a query. 
  </para>
 </sect2>

 <sect2>
  <title>Parameters</title>

  <para>
   <literal>bloom</> indexes accept following parameters in <literal>WITH</>
   clause.
  </para>

   <variablelist>
   <varlistentry>
    <term><literal>length</></term>
    <listitem>
     <para>
      Length of signature in uint16 type values
     </para>
    </listitem>
   </varlistentry>
   </variablelist>
   <variablelist>
   <varlistentry>
    <term><literal>col1 &mdash; col16</></term>
    <listitem>
     <para>
      Number of bits for corresponding column
     </para>
    </listitem>
   </varlistentry>
   </variablelist>
 </sect2>

 <sect2>
  <title>Examples</title>

  <para>
   Example of index definition is given below.
  </para>

<programlisting>
CREATE INDEX bloomidx ON tbloom(i1,i2,i3) 
       WITH (length=5, col1=2, col2=2, col3=4);
</programlisting>

  <para>
   Here, we create bloom index with signature length 80 bits and attributes
   i1, i2  mapped to 2 bits, attribute i3 - to 4 bits.
  </para>

  <para>
   Example of index definition and usage is given below.
  </para>

<programlisting>
CREATE TABLE tbloom AS
SELECT
    random()::int as i1,
    random()::int as i2,
    random()::int as i3,
    random()::int as i4,
    random()::int as i5,
    random()::int as i6,
    random()::int as i7,
    random()::int as i8,
    random()::int as i9,
    random()::int as i10,
    random()::int as i11,
    random()::int as i12,
    random()::int as i13
FROM
    generate_series(1,1000);
CREATE INDEX bloomidx ON tbloom USING
             bloom (i1, i2, i3, i4, i5, i6, i7, i8, i9, i10, i11, i12);
SELECT pg_relation_size('bloomidx');
CREATE index btree_idx ON tbloom(i1,i2,i3,i4,i5,i6,i7,i8,i9,i10,i11,i12);
SELECT pg_relation_size('btree_idx');
</programlisting>

<programlisting>
=# EXPLAIN ANALYZE SELECT * FROM tbloom WHERE i2 = 20 AND i10 = 15;
                                                   QUERY PLAN
-----------------------------------------------------------------------------------------------------------------
 Bitmap Heap Scan on tbloom  (cost=1.50..5.52 rows=1 width=52) (actual time=0.057..0.057 rows=0 loops=1)
   Recheck Cond: ((i2 = 20) AND (i10 = 15))
   ->  Bitmap Index Scan on bloomidx  (cost=0.00..1.50 rows=1 width=0) (actual time=0.041..0.041 rows=9 loops=1)
         Index Cond: ((i2 = 20) AND (i10 = 15))
 Total runtime: 0.081 ms
(5 rows)
</programlisting>

  <para>
   Seqscan is slow.
  </para>

<programlisting>
=# SET enable_bitmapscan = off;
=# SET enable_indexscan = off;
=# EXPLAIN ANALYZE SELECT * FROM tbloom WHERE i2 = 20 AND i10 = 15;
                                            QUERY PLAN
--------------------------------------------------------------------------------------------------
 Seq Scan on tbloom  (cost=0.00..25.00 rows=1 width=52) (actual time=0.162..0.162 rows=0 loops=1)
   Filter: ((i2 = 20) AND (i10 = 15))
 Total runtime: 0.181 ms
(3 rows)
</programlisting>

 <para>
  Btree index will be not used for this query.
 </para>

<programlisting>
=# DROP INDEX bloomidx;
=# CREATE INDEX btree_idx ON tbloom(i1, i2, i3, i4, i5, i6, i7, i8, i9, i10, i11, i12);
=# EXPLAIN ANALYZE SELECT * FROM tbloom WHERE i2 = 20 AND i10 = 15;
                                            QUERY PLAN
--------------------------------------------------------------------------------------------------
 Seq Scan on tbloom (cost=0.00..25.00 rows=1 width=52) (actual time=0.210..0.210 rows=0 loops=1)
   Filter: ((i2 = 20) AND (i10 = 15))
 Total runtime: 0.250 ms
(3 rows)
</programlisting>
 </sect2>

 <sect2>
  <title>Opclass interface</title>

  <para>
   Bloom opclass interface is simple.  It requires 1 supporting function:
   hash function for indexing datatype.  And it provides 1 search operator:
   equality operator.  The example below shows <literal>opclass</> definition
   for <literal>text</> datatype.
  </para>

<programlisting>
CREATE OPERATOR CLASS text_ops
DEFAULT FOR TYPE text USING bloom AS
    OPERATOR    1   =(text, text),
    FUNCTION    1   hashtext(text);
</programlisting>
 </sect2>

 <sect2>
  <title>Limitation</title>
  <para>

   <itemizedlist>
    <listitem>
     <para>
      For now, only opclasses for <literal>int4</>, <literal>text</> comes
      with contrib.  However, users may define more of them.
     </para>
    </listitem>

    <listitem>
     <para>
      Only <literal>=</literal> operator is supported for search now.  But it's
      possible to add support of arrays with contains and intersection
      operations in future.
     </para>
    </listitem>
   </itemizedlist>
  </para>
 </sect2>

 <sect2>
  <title>Authors</title>

  <para>
   Teodor Sigaev <email>teodor@postgrespro.ru</email>, Postgres Professional, Moscow, Russia
  </para>

  <para>
   Alexander Korotkov <email>a.korotkov@postgrespro.ru</email>, Postgres Professional, Moscow, Russia
  </para>

  <para>
   Oleg Bartunov <email>obartunov@postgrespro.ru</email>, Postgres Professional, Moscow, Russia
  </para>
 </sect2>

</sect1>