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Data Partitioning documentation section reduced and moved to the end.

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Bruce Momjian 2006-11-17 13:29:53 +00:00
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doc/src/sgml/failover.sgml
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<!-- $PostgreSQL: pgsql/doc/src/sgml/failover.sgml,v 1.12 2006/11/17 09:00:03 neilc Exp $ --> <!-- $PostgreSQL: pgsql/doc/src/sgml/failover.sgml,v 1.13 2006/11/17 13:29:53 momjian Exp $ -->
<chapter id="failover"> <chapter id="failover">
<title>Failover, Replication, Load Balancing, and Clustering Options</title> <title>Failover, Replication, Load Balancing, and Clustering Options</title>
@ -137,52 +137,14 @@
</varlistentry> </varlistentry>
<varlistentry> <varlistentry>
<term>Data Partitioning</term> <term>Query Broadcasting</term>
<listitem> <listitem>
<para> <para>
Data partitioning splits tables into data sets. Each set can In query broadcasting, a program intercepts every SQL query
be modified by only one server. For example, data can be and sends it to all servers. Each server operates independently.
partitioned by offices, e.g. London and Paris. While London Read-only queries can be sent to a single server because there
and Paris servers have all data records, only London can modify is no need for all servers to process it.
London records, and Paris can only modify Paris records. This
is similar to the "Master/Slave Replication" item above, except
that instead of having a read/write server and a read-only
server, each server has a read/write data set and a read-only
data set.
</para>
<para>
Such partitioning provides both failover and load balancing. Failover
is achieved because the data resides on both servers, and this is an
ideal way to enable failover if the servers share a slow communication
channel. Load balancing is possible because read requests can go to any
of the servers, and write requests are split among the servers. Of
course, the communication to keep all the servers up-to-date adds
overhead, so ideally the write load should be low, or localized as in
the London/Paris example above.
</para>
<para>
Data partitioning is usually handled by application code, though rules
and triggers can be used to keep the read-only data sets current. Slony-I
can also be used in such a setup. While Slony-I replicates only entire
tables, London and Paris can be placed in separate tables, and
inheritance can be used to access both tables using a single table name.
</para>
</listitem>
</varlistentry>
<varlistentry>
<term>Multi-Master Replication Using Query Broadcasting</term>
<listitem>
<para>
One way to do multi-master replication is by having a program
intercept every SQL query and send it to all servers. Each
server operates independently. Read-only queries can be sent
to a single server because there is no need for all servers to
process it.
</para> </para>
<para> <para>
@ -235,6 +197,22 @@
</listitem> </listitem>
</varlistentry> </varlistentry>
<varlistentry>
<term>Data Partitioning</term>
<listitem>
<para>
Data partitioning splits tables into data sets. Each set can
be modified by only one server. For example, data can be
partitioned by offices, e.g. London and Paris, with a server
in each office. If queries combining London and Paris data
are necessary, an application can query both servers, or
master/slave replication can be used to keep a read-only copy
of the other office's data on each server.
</para>
</listitem>
</varlistentry>
<varlistentry> <varlistentry>
<term>Clustering For Parallel Query Execution</term> <term>Clustering For Parallel Query Execution</term>
<listitem> <listitem>