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Implement "fastupdate" support for GIN indexes, in which we try to accumulate
multiple index entries in a holding area before adding them to the main index structure. This helps because bulk insert is (usually) significantly faster than retail insert for GIN. This patch also removes GIN support for amgettuple-style index scans. The API defined for amgettuple is difficult to support with fastupdate, and the previously committed partial-match feature didn't really work with it either. We might eventually figure a way to put back amgettuple support, but it won't happen for 8.4. catversion bumped because of change in GIN's pg_am entry, and because the format of GIN indexes changed on-disk (there's a metapage now, and possibly a pending list). Teodor Sigaev
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@@ -1,4 +1,4 @@
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<!-- $PostgreSQL: pgsql/doc/src/sgml/gin.sgml,v 2.16 2008/07/22 22:05:24 tgl Exp $ -->
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<!-- $PostgreSQL: pgsql/doc/src/sgml/gin.sgml,v 2.17 2009/03/24 20:17:07 tgl Exp $ -->
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<chapter id="GIN">
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<title>GIN Indexes</title>
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@@ -100,11 +100,11 @@
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to consult <literal>n</> to determine the data type of
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<literal>query</> and the key values that need to be extracted.
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The number of returned keys must be stored into <literal>*nkeys</>.
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If the query contains no keys then <function>extractQuery</>
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If the query contains no keys then <function>extractQuery</>
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should store 0 or -1 into <literal>*nkeys</>, depending on the
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semantics of the operator. 0 means that every
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value matches the <literal>query</> and a sequential scan should be
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produced. -1 means nothing can match the <literal>query</>.
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value matches the <literal>query</> and a sequential scan should be
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produced. -1 means nothing can match the <literal>query</>.
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<literal>pmatch</> is an output argument for use when partial match
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is supported. To use it, <function>extractQuery</> must allocate
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an array of <literal>*nkeys</> booleans and store its address at
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@@ -188,9 +188,47 @@
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list of heap pointers (PL, posting list) if the list is small enough.
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</para>
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<sect2 id="gin-fast-update">
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<title>GIN fast update technique</title>
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<para>
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Updating a <acronym>GIN</acronym> index tends to be slow because of the
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intrinsic nature of inverted indexes: inserting or updating one heap row
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can cause many inserts into the index (one for each key extracted
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from the indexed value). As of <productname>PostgreSQL</productname> 8.4,
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<acronym>GIN</> is capable of postponing much of this work by inserting
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new tuples into a temporary, unsorted list of pending entries.
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When the table is vacuumed, or if the pending list becomes too large
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(larger than <xref linkend="guc-work-mem">), the entries are moved to the
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main <acronym>GIN</acronym> data structure using the same bulk insert
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techniques used during initial index creation. This greatly improves
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<acronym>GIN</acronym> index update speed, even counting the additional
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vacuum overhead. Moreover the overhead can be done by a background
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process instead of in foreground query processing.
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</para>
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<para>
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The main disadvantage of this approach is that searches must scan the list
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of pending entries in addition to searching the regular index, and so
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a large list of pending entries will slow searches significantly.
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Another disadvantage is that, while most updates are fast, an update
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that causes the pending list to become <quote>too large</> will incur an
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immediate cleanup cycle and thus be much slower than other updates.
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Proper use of autovacuum can minimize both of these problems.
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</para>
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<para>
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If consistent response time is more important than update speed,
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use of pending entries can be disabled by turning off the
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<literal>FASTUPDATE</literal> storage parameter for a
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<acronym>GIN</acronym> index. See <xref linkend="sql-createindex"
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endterm="sql-createindex-title"> for details.
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</para>
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</sect2>
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<sect2 id="gin-partial-match">
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<title>Partial match algorithm</title>
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<para>
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GIN can support <quote>partial match</> queries, in which the query
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does not determine an exact match for one or more keys, but the possible
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@@ -205,14 +243,6 @@
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to be searched, or greater than zero if the index key is past the range
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that could match.
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</para>
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<para>
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During a partial-match scan, all <literal>itemPointer</>s for matching keys
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are OR'ed into a <literal>TIDBitmap</>.
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The scan fails if the <literal>TIDBitmap</> becomes lossy.
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In this case an error message will be reported with advice
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to increase <literal>work_mem</>.
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</para>
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</sect2>
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</sect1>
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@@ -225,11 +255,18 @@
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<term>Create vs insert</term>
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<listitem>
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<para>
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In most cases, insertion into a <acronym>GIN</acronym> index is slow
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Insertion into a <acronym>GIN</acronym> index can be slow
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due to the likelihood of many keys being inserted for each value.
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So, for bulk insertions into a table it is advisable to drop the GIN
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index and recreate it after finishing bulk insertion.
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</para>
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<para>
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As of <productname>PostgreSQL</productname> 8.4, this advice is less
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necessary since delayed indexing is used (see <xref
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linkend="gin-fast-update"> for details). But for very large updates
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it may still be best to drop and recreate the index.
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</para>
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</listitem>
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</varlistentry>
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@@ -244,6 +281,23 @@
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</listitem>
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</varlistentry>
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<varlistentry>
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<term><xref linkend="guc-work-mem"></term>
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<listitem>
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<para>
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During a series of insertions into an existing <acronym>GIN</acronym>
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index that has <literal>FASTUPDATE</> enabled, the system will clean up
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the pending-entry list whenever it grows larger than
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<varname>work_mem</>. To avoid fluctuations in observed response time,
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it's desirable to have pending-list cleanup occur in the background
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(i.e., via autovacuum). Foreground cleanup operations can be avoided by
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increasing <varname>work_mem</> or making autovacuum more aggressive.
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However, enlarging <varname>work_mem</> means that if a foreground
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cleanup does occur, it will take even longer.
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</para>
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</listitem>
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</varlistentry>
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<varlistentry>
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<term><xref linkend="guc-gin-fuzzy-search-limit"></term>
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<listitem>
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@@ -311,8 +365,7 @@
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<function>extractQuery</function> must convert an unrestricted search into
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a partial-match query that will scan the whole index. This is inefficient
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but might be necessary to avoid corner-case failures with operators such
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as LIKE. Note however that failure could still occur if the intermediate
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<literal>TIDBitmap</> becomes lossy.
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as <literal>LIKE</>.
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</para>
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</sect1>
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