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<!-- $PostgreSQL: pgsql/doc/src/sgml/high-availability.sgml,v 1.44 2010/02/17 04:19:37 tgl Exp $ -->
<chapter id="high-availability">
<title>High Availability, Load Balancing, and Replication</title>
<indexterm><primary>high availability</></>
<indexterm><primary>failover</></>
<indexterm><primary>replication</></>
<indexterm><primary>load balancing</></>
<indexterm><primary>clustering</></>
<indexterm><primary>data partitioning</></>
<para>
Database servers can work together to allow a second server to
take over quickly if the primary server fails (high
availability), or to allow several computers to serve the same
data (load balancing). Ideally, database servers could work
together seamlessly. Web servers serving static web pages can
be combined quite easily by merely load-balancing web requests
to multiple machines. In fact, read-only database servers can
be combined relatively easily too. Unfortunately, most database
servers have a read/write mix of requests, and read/write servers
are much harder to combine. This is because though read-only
data needs to be placed on each server only once, a write to any
server has to be propagated to all servers so that future read
requests to those servers return consistent results.
</para>
<para>
This synchronization problem is the fundamental difficulty for
servers working together. Because there is no single solution
that eliminates the impact of the sync problem for all use cases,
there are multiple solutions. Each solution addresses this
problem in a different way, and minimizes its impact for a specific
workload.
</para>
<para>
Some solutions deal with synchronization by allowing only one
server to modify the data. Servers that can modify data are
called read/write or "master" servers. Servers that can reply
to read-only queries are called "slave" servers. Servers that
cannot be accessed until they are changed to master servers are
called "standby" servers.
</para>
<para>
Some solutions are synchronous,
meaning that a data-modifying transaction is not considered
committed until all servers have committed the transaction. This
guarantees that a failover will not lose any data and that all
load-balanced servers will return consistent results no matter
which server is queried. In contrast, asynchronous solutions allow some
delay between the time of a commit and its propagation to the other servers,
opening the possibility that some transactions might be lost in
the switch to a backup server, and that load balanced servers
might return slightly stale results. Asynchronous communication
is used when synchronous would be too slow.
</para>
<para>
Solutions can also be categorized by their granularity. Some solutions
can deal only with an entire database server, while others allow control
at the per-table or per-database level.
</para>
<para>
Performance must be considered in any choice. There is usually a
trade-off between functionality and
performance. For example, a fully synchronous solution over a slow
network might cut performance by more than half, while an asynchronous
one might have a minimal performance impact.
</para>
<para>
The remainder of this section outlines various failover, replication,
and load balancing solutions. A <ulink
url="http://www.postgres-r.org/documentation/terms">glossary</ulink> is
also available.
</para>
<sect1 id="different-replication-solutions">
<title>Comparison of different solutions</title>
<variablelist>
<varlistentry>
<term>Shared Disk Failover</term>
<listitem>
<para>
Shared disk failover avoids synchronization overhead by having only one
copy of the database. It uses a single disk array that is shared by
multiple servers. If the main database server fails, the standby server
is able to mount and start the database as though it were recovering from
a database crash. This allows rapid failover with no data loss.
</para>
<para>
Shared hardware functionality is common in network storage devices.
Using a network file system is also possible, though care must be
taken that the file system has full <acronym>POSIX</> behavior (see <xref
linkend="creating-cluster-nfs">). One significant limitation of this
method is that if the shared disk array fails or becomes corrupt, the
primary and standby servers are both nonfunctional. Another issue is
that the standby server should never access the shared storage while
the primary server is running.
</para>
</listitem>
</varlistentry>
<varlistentry>
<term>File System (Block-Device) Replication</term>
<listitem>
<para>
A modified version of shared hardware functionality is file system
replication, where all changes to a file system are mirrored to a file
system residing on another computer. The only restriction is that
the mirroring must be done in a way that ensures the standby server
has a consistent copy of the file system — specifically, writes
to the standby must be done in the same order as those on the master.
<productname>DRBD</> is a popular file system replication solution
for Linux.
</para>
<!--
https://forge.continuent.org/pipermail/sequoia/2006-November/004070.html
Oracle RAC is a shared disk approach and just send cache invalidations
to other nodes but not actual data. As the disk is shared, data is
only committed once to disk and there is a distributed locking
protocol to make nodes agree on a serializable transactional order.
-->
</listitem>
</varlistentry>
<varlistentry>
<term>Warm and Hot Standby Using Point-In-Time Recovery (<acronym>PITR</>)</term>
<listitem>
<para>
Warm and hot standby servers can be kept current by reading a
stream of write-ahead log (<acronym>WAL</>)
records. If the main server fails, the warm standby contains
almost all of the data of the main server, and can be quickly
made the new master database server. This is asynchronous and
can only be done for the entire database server.
</para>
<para>
A PITR standby server can be kept more up-to-date using streaming
replication.; see <xref linkend="streaming-replication">. For
warm standby information, see <xref linkend="warm-standby">, and
for hot standby, see <xref linkend="hot-standby">.
</para>
</listitem>
</varlistentry>
<varlistentry>
<term>Trigger-Based Master-Slave Replication</term>
<listitem>
<para>
A master-slave replication setup sends all data modification
queries to the master server. The master server asynchronously
sends data changes to the slave server. The slave can answer
read-only queries while the master server is running. The
slave server is ideal for data warehouse queries.
</para>
<para>
<productname>Slony-I</> is an example of this type of replication, with per-table
granularity, and support for multiple slaves. Because it
updates the slave server asynchronously (in batches), there is
possible data loss during fail over.
</para>
</listitem>
</varlistentry>
<varlistentry>
<term>Statement-Based Replication Middleware</term>
<listitem>
<para>
With statement-based replication middleware, a program intercepts
every SQL query and sends it to one or all servers. Each server
operates independently. Read-write queries are sent to all servers,
while read-only queries can be sent to just one server, allowing
the read workload to be distributed.
</para>
<para>
If queries are simply broadcast unmodified, functions like
<function>random()</>, <function>CURRENT_TIMESTAMP</>, and
sequences can have different values on different servers.
This is because each server operates independently, and because
SQL queries are broadcast (and not actual modified rows). If
this is unacceptable, either the middleware or the application
must query such values from a single server and then use those
values in write queries. Also, care must be taken that all
transactions either commit or abort on all servers, perhaps
using two-phase commit (<xref linkend="sql-prepare-transaction"
endterm="sql-prepare-transaction-title"> and <xref
linkend="sql-commit-prepared" endterm="sql-commit-prepared-title">.
<productname>Pgpool-II</> and <productname>Sequoia</> are examples of
this type of replication.
</para>
</listitem>
</varlistentry>
<varlistentry>
<term>Asynchronous Multimaster Replication</term>
<listitem>
<para>
For servers that are not regularly connected, like laptops or
remote servers, keeping data consistent among servers is a
challenge. Using asynchronous multimaster replication, each
server works independently, and periodically communicates with
the other servers to identify conflicting transactions. The
conflicts can be resolved by users or conflict resolution rules.
Bucardo is an example of this type of replication.
</para>
</listitem>
</varlistentry>
<varlistentry>
<term>Synchronous Multimaster Replication</term>
<listitem>
<para>
In synchronous multimaster replication, each server can accept
write requests, and modified data is transmitted from the
original server to every other server before each transaction
commits. Heavy write activity can cause excessive locking,
leading to poor performance. In fact, write performance is
often worse than that of a single server. Read requests can
be sent to any server. Some implementations use shared disk
to reduce the communication overhead. Synchronous multimaster
replication is best for mostly read workloads, though its big
advantage is that any server can accept write requests —
there is no need to partition workloads between master and
slave servers, and because the data changes are sent from one
server to another, there is no problem with non-deterministic
functions like <function>random()</>.
</para>
<para>
<productname>PostgreSQL</> does not offer this type of replication,
though <productname>PostgreSQL</> two-phase commit (<xref
linkend="sql-prepare-transaction"
endterm="sql-prepare-transaction-title"> and <xref
linkend="sql-commit-prepared" endterm="sql-commit-prepared-title">)
can be used to implement this in application code or middleware.
</para>
</listitem>
</varlistentry>
<varlistentry>
<term>Commercial Solutions</term>
<listitem>
<para>
Because <productname>PostgreSQL</> is open source and easily
extended, a number of companies have taken <productname>PostgreSQL</>
and created commercial closed-source solutions with unique
failover, replication, and load balancing capabilities.
</para>
</listitem>
</varlistentry>
</variablelist>
<para>
<xref linkend="high-availability-matrix"> summarizes
the capabilities of the various solutions listed above.
</para>
<table id="high-availability-matrix">
<title>High Availability, Load Balancing, and Replication Feature Matrix</title>
<tgroup cols="8">
<thead>
<row>
<entry>Feature</entry>
<entry>Shared Disk Failover</entry>
<entry>File System Replication</entry>
<entry>Hot/Warm Standby Using PITR</entry>
<entry>Trigger-Based Master-Slave Replication</entry>
<entry>Statement-Based Replication Middleware</entry>
<entry>Asynchronous Multimaster Replication</entry>
<entry>Synchronous Multimaster Replication</entry>
</row>
</thead>
<tbody>
<row>
<entry>Most Common Implementation</entry>
<entry align="center">NAS</entry>
<entry align="center">DRBD</entry>
<entry align="center">PITR</entry>
<entry align="center">Slony</entry>
<entry align="center">pgpool-II</entry>
<entry align="center">Bucardo</entry>
<entry align="center"></entry>
</row>
<row>
<entry>Communication Method</entry>
<entry align="center">shared disk</entry>
<entry align="center">disk blocks</entry>
<entry align="center">WAL</entry>
<entry align="center">table rows</entry>
<entry align="center">SQL</entry>
<entry align="center">table rows</entry>
<entry align="center">table rows and row locks</entry>
</row>
<row>
<entry>No special hardware required</entry>
<entry align="center"></entry>
<entry align="center">•</entry>
<entry align="center">•</entry>
<entry align="center">•</entry>
<entry align="center">•</entry>
<entry align="center">•</entry>
<entry align="center">•</entry>
</row>
<row>
<entry>Allows multiple master servers</entry>
<entry align="center"></entry>
<entry align="center"></entry>
<entry align="center"></entry>
<entry align="center"></entry>
<entry align="center">•</entry>
<entry align="center">•</entry>
<entry align="center">•</entry>
</row>
<row>
<entry>No master server overhead</entry>
<entry align="center">•</entry>
<entry align="center"></entry>
<entry align="center">•</entry>
<entry align="center"></entry>
<entry align="center">•</entry>
<entry align="center"></entry>
<entry align="center"></entry>
</row>
<row>
<entry>No waiting for multiple servers</entry>
<entry align="center">•</entry>
<entry align="center"></entry>
<entry align="center">•</entry>
<entry align="center">•</entry>
<entry align="center"></entry>
<entry align="center">•</entry>
<entry align="center"></entry>
</row>
<row>
<entry>Master failure will never lose data</entry>
<entry align="center">•</entry>
<entry align="center">•</entry>
<entry align="center"></entry>
<entry align="center"></entry>
<entry align="center">•</entry>
<entry align="center"></entry>
<entry align="center">•</entry>
</row>
<row>
<entry>Slaves accept read-only queries</entry>
<entry align="center"></entry>
<entry align="center"></entry>
<entry align="center">Hot only</entry>
<entry align="center">•</entry>
<entry align="center">•</entry>
<entry align="center">•</entry>
<entry align="center">•</entry>
</row>
<row>
<entry>Per-table granularity</entry>
<entry align="center"></entry>
<entry align="center"></entry>
<entry align="center"></entry>
<entry align="center">•</entry>
<entry align="center"></entry>
<entry align="center">•</entry>
<entry align="center">•</entry>
</row>
<row>
<entry>No conflict resolution necessary</entry>
<entry align="center">•</entry>
<entry align="center">•</entry>
<entry align="center">•</entry>
<entry align="center">•</entry>
<entry align="center"></entry>
<entry align="center"></entry>
<entry align="center">•</entry>
</row>
</tbody>
</tgroup>
</table>
<para>
There are a few solutions that do not fit into the above categories:
</para>
<variablelist>
<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>
<term>Multiple-Server Parallel Query Execution</term>
<listitem>
<para>
Many of the above solutions allow multiple servers to handle multiple
queries, but none allow a single query to use multiple servers to
complete faster. This solution allows multiple servers to work
concurrently on a single query. It is usually accomplished by
splitting the data among servers and having each server execute its
part of the query and return results to a central server where they
are combined and returned to the user. <productname>Pgpool-II</>
has this capability. Also, this can be implemented using the
<productname>PL/Proxy</> toolset.
</para>
</listitem>
</varlistentry>
</variablelist>
</sect1>
<sect1 id="warm-standby">
<title>File-based Log Shipping</title>
<indexterm zone="high-availability">
<primary>warm standby</primary>
</indexterm>
<indexterm zone="high-availability">
<primary>PITR standby</primary>
</indexterm>
<indexterm zone="high-availability">
<primary>standby server</primary>
</indexterm>
<indexterm zone="high-availability">
<primary>log shipping</primary>
</indexterm>
<indexterm zone="high-availability">
<primary>witness server</primary>
</indexterm>
<indexterm zone="high-availability">
<primary>STONITH</primary>
</indexterm>
<para>
Continuous archiving can be used to create a <firstterm>high
availability</> (HA) cluster configuration with one or more
<firstterm>standby servers</> ready to take over operations if the
primary server fails. This capability is widely referred to as
<firstterm>warm standby</> or <firstterm>log shipping</>.
</para>
<para>
The primary and standby server work together to provide this capability,
though the servers are only loosely coupled. The primary server operates
in continuous archiving mode, while each standby server operates in
continuous recovery mode, reading the WAL files from the primary. No
changes to the database tables are required to enable this capability,
so it offers low administration overhead compared to some other
replication approaches. This configuration also has relatively low
performance impact on the primary server.
</para>
<para>
Directly moving WAL records from one database server to another
is typically described as log shipping. <productname>PostgreSQL</>
implements file-based log shipping, which means that WAL records are
transferred one file (WAL segment) at a time. WAL files (16MB) can be
shipped easily and cheaply over any distance, whether it be to an
adjacent system, another system at the same site, or another system on
the far side of the globe. The bandwidth required for this technique
varies according to the transaction rate of the primary server.
Record-based log shipping is also possible with custom-developed
procedures, as discussed in <xref linkend="warm-standby-record">.
</para>
<para>
It should be noted that the log shipping is asynchronous, i.e., the WAL
records are shipped after transaction commit. As a result there is a
window for data loss should the primary server suffer a catastrophic
failure: transactions not yet shipped will be lost. The length of the
window of data loss can be limited by use of the
<varname>archive_timeout</varname> parameter, which can be set as low
as a few seconds if required. However such a low setting will
substantially increase the bandwidth required for file shipping.
If you need a window of less than a minute or so, it's probably better
to consider record-based log shipping.
</para>
<para>
The standby server is not available for access, since it is continually
performing recovery processing. Recovery performance is sufficiently
good that the standby will typically be only moments away from full
availability once it has been activated. As a result, we refer to this
capability as a warm standby configuration that offers high
availability. Restoring a server from an archived base backup and
rollforward will take considerably longer, so that technique only
offers a solution for disaster recovery, not high availability.
</para>
<sect2 id="warm-standby-planning">
<title>Planning</title>
<para>
It is usually wise to create the primary and standby servers
so that they are as similar as possible, at least from the
perspective of the database server. In particular, the path names
associated with tablespaces will be passed across unmodified, so both
primary and standby servers must have the same mount paths for
tablespaces if that feature is used. Keep in mind that if
<xref linkend="sql-createtablespace" endterm="sql-createtablespace-title">
is executed on the primary, any new mount point needed for it must
be created on the primary and all standby servers before the command
is executed. Hardware need not be exactly the same, but experience shows
that maintaining two identical systems is easier than maintaining two
dissimilar ones over the lifetime of the application and system.
In any case the hardware architecture must be the same — shipping
from, say, a 32-bit to a 64-bit system will not work.
</para>
<para>
In general, log shipping between servers running different major
<productname>PostgreSQL</> release
levels is not possible. It is the policy of the PostgreSQL Global
Development Group not to make changes to disk formats during minor release
upgrades, so it is likely that running different minor release levels
on primary and standby servers will work successfully. However, no
formal support for that is offered and you are advised to keep primary
and standby servers at the same release level as much as possible.
When updating to a new minor release, the safest policy is to update
the standby servers first — a new minor release is more likely
to be able to read WAL files from a previous minor release than vice
versa.
</para>
<para>
There is no special mode required to enable a standby server. The
operations that occur on both primary and standby servers are
normal continuous archiving and recovery tasks. The only point of
contact between the two database servers is the archive of WAL files
that both share: primary writing to the archive, standby reading from
the archive. Care must be taken to ensure that WAL archives from separate
primary servers do not become mixed together or confused. The archive
need not be large if it is only required for standby operation.
</para>
<para>
The magic that makes the two loosely coupled servers work together is
simply a <varname>restore_command</> used on the standby that,
when asked for the next WAL file, waits for it to become available from
the primary. The <varname>restore_command</> is specified in the
<filename>recovery.conf</> file on the standby server. Normal recovery
processing would request a file from the WAL archive, reporting failure
if the file was unavailable. For standby processing it is normal for
the next WAL file to be unavailable, so we must be patient and wait for
it to appear. For files ending in <literal>.backup</> or
<literal>.history</> there is no need to wait, and a non-zero return
code must be returned. A waiting <varname>restore_command</> can be
written as a custom script that loops after polling for the existence of
the next WAL file. There must also be some way to trigger failover, which
should interrupt the <varname>restore_command</>, break the loop and
return a file-not-found error to the standby server. This ends recovery
and the standby will then come up as a normal server.
</para>
<para>
Pseudocode for a suitable <varname>restore_command</> is:
<programlisting>
triggered = false;
while (!NextWALFileReady() && !triggered)
{
sleep(100000L); /* wait for ~0.1 sec */
if (CheckForExternalTrigger())
triggered = true;
}
if (!triggered)
CopyWALFileForRecovery();
</programlisting>
</para>
<para>
A working example of a waiting <varname>restore_command</> is provided
as a <filename>contrib</> module named <application>pg_standby</>. It
should be used as a reference on how to correctly implement the logic
described above. It can also be extended as needed to support specific
configurations and environments.
</para>
<para>
<productname>PostgreSQL</productname> does not provide the system
software required to identify a failure on the primary and notify
the standby database server. Many such tools exist and are well
integrated with the operating system facilities required for
successful failover, such as IP address migration.
</para>
<para>
The method for triggering failover is an important part of planning
and design. One potential option is the <varname>restore_command</>
command. It is executed once for each WAL file, but the process
running the <varname>restore_command</> is created and dies for
each file, so there is no daemon or server process, and we cannot
use signals or a signal handler. Therefore, the
<varname>restore_command</> is not suitable to trigger failover.
It is possible to use a simple timeout facility, especially if
used in conjunction with a known <varname>archive_timeout</>
setting on the primary. However, this is somewhat error prone
since a network problem or busy primary server might be sufficient
to initiate failover. A notification mechanism such as the explicit
creation of a trigger file is ideal, if this can be arranged.
</para>
<para>
The size of the WAL archive can be minimized by using the <literal>%r</>
option of the <varname>restore_command</>. This option specifies the
last archive file name that needs to be kept to allow the recovery to
restart correctly. This can be used to truncate the archive once
files are no longer required, assuming the archive is writable from the
standby server.
</para>
</sect2>
<sect2 id="warm-standby-config">
<title>Implementation</title>
<para>
The short procedure for configuring a standby server is as follows. For
full details of each step, refer to previous sections as noted.
<orderedlist>
<listitem>
<para>
Set up primary and standby systems as nearly identical as
possible, including two identical copies of
<productname>PostgreSQL</> at the same release level.
</para>
</listitem>
<listitem>
<para>
Set up continuous archiving from the primary to a WAL archive
directory on the standby server. Ensure that
<xref linkend="guc-archive-mode">,
<xref linkend="guc-archive-command"> and
<xref linkend="guc-archive-timeout">
are set appropriately on the primary
(see <xref linkend="backup-archiving-wal">).
</para>
</listitem>
<listitem>
<para>
Make a base backup of the primary server (see <xref
linkend="backup-base-backup">), and load this data onto the standby.
</para>
</listitem>
<listitem>
<para>
Begin recovery on the standby server from the local WAL
archive, using a <filename>recovery.conf</> that specifies a
<varname>restore_command</> that waits as described
previously (see <xref linkend="backup-pitr-recovery">).
</para>
</listitem>
</orderedlist>
</para>
<para>
Recovery treats the WAL archive as read-only, so once a WAL file has
been copied to the standby system it can be copied to tape at the same
time as it is being read by the standby database server.
Thus, running a standby server for high availability can be performed at
the same time as files are stored for longer term disaster recovery
purposes.
</para>
<para>
For testing purposes, it is possible to run both primary and standby
servers on the same system. This does not provide any worthwhile
improvement in server robustness, nor would it be described as HA.
</para>
</sect2>
<sect2 id="warm-standby-record">
<title>Record-based Log Shipping</title>
<para>
<productname>PostgreSQL</productname> directly supports file-based
log shipping as described above. It is also possible to implement
record-based log shipping, though this requires custom development.
</para>
<para>
An external program can call the <function>pg_xlogfile_name_offset()</>
function (see <xref linkend="functions-admin">)
to find out the file name and the exact byte offset within it of
the current end of WAL. It can then access the WAL file directly
and copy the data from the last known end of WAL through the current end
over to the standby servers. With this approach, the window for data
loss is the polling cycle time of the copying program, which can be very
small, and there is no wasted bandwidth from forcing partially-used
segment files to be archived. Note that the standby servers'
<varname>restore_command</> scripts can only deal with whole WAL files,
so the incrementally copied data is not ordinarily made available to
the standby servers. It is of use only when the primary dies —
then the last partial WAL file is fed to the standby before allowing
it to come up. The correct implementation of this process requires
cooperation of the <varname>restore_command</> script with the data
copying program.
</para>
<para>
Starting with <productname>PostgreSQL</> version 9.0, you can use
streaming replication (see <xref linkend="streaming-replication">) to
achieve the same with less effort.
</para>
</sect2>
</sect1>
<sect1 id="streaming-replication">
<title>Streaming Replication</title>
<indexterm zone="high-availability">
<primary>Streaming Replication</primary>
</indexterm>
<para>
<productname>PostgreSQL</> includes a simple streaming replication
mechanism, which lets the standby server to stay more up-to-date than
file-based log shipping allows. The standby connects to the primary
and the primary starts streaming WAL records from where the standby
left off, and continues streaming them as they are generated, without
waiting for the WAL file to be filled. So with streaming replication,
<varname>archive_timeout</> does not need to be configured.
</para>
<para>
Streaming replication relies on file-based continuous archiving for
making the base backup and for allowing a standby to catch up if it's
disconnected from the primary for long enough for the primary to
delete old WAL files still required by the standby.
</para>
<sect2 id="streaming-replication-setup">
<title>Setup</title>
<para>
The short procedure for configuring streaming replication is as follows.
For full details of each step, refer to other sections as noted.
<orderedlist>
<listitem>
<para>
Set up primary and standby systems as near identically as possible,
including two identical copies of <productname>PostgreSQL</> at the
same release level.
</para>
</listitem>
<listitem>
<para>
Set up continuous archiving from the primary to a WAL archive located
in a directory on the standby server. Ensure that
<xref linkend="guc-archive-mode">,
<xref linkend="guc-archive-command"> and
<xref linkend="guc-archive-timeout">
are set appropriately on the primary
(see <xref linkend="backup-archiving-wal">).
</para>
</listitem>
<listitem>
<para>
Set <xref linkend="guc-listen-addresses"> and authentication options
(see <filename>pg_hba.conf</>) so that the standby server can connect to
the pseudo <literal>replication</> database of the primary server (see
<xref linkend="streaming-replication-authentication">).
</para>
<para>
On systems that support the keepalive socket option, setting
<xref linkend="guc-tcp-keepalives-idle">,
<xref linkend="guc-tcp-keepalives-interval"> and
<xref linkend="guc-tcp-keepalives-count"> helps the master to notice
a broken connection promptly.
</para>
</listitem>
<listitem>
<para>
Set the maximum number of concurrent connections from the standby servers
(see <xref linkend="guc-max-wal-senders"> for details).
</para>
</listitem>
<listitem>
<para>
Start the <productname>PostgreSQL</> server on the primary.
</para>
</listitem>
<listitem>
<para>
Make a base backup of the primary server (see
<xref linkend="backup-base-backup">), and load this data onto the
standby. Note that all files present in <filename>pg_xlog</>
and <filename>pg_xlog/archive_status</> on the <emphasis>standby</>
server should be removed because they might be obsolete.
</para>
</listitem>
<listitem>
<para>
If you're setting up the standby server for high availability purposes,
set up WAL archiving, connections and authentication like the primary
server, because the standby server will work as a primary server after
failover. If you're setting up the standby server for e.g reporting
purposes, with no plans to fail over to it, configure the standby
accordingly.
</para>
</listitem>
<listitem>
<para>
Create a recovery command file <filename>recovery.conf</> in the data
directory on the standby server.
</para>
<variablelist id="replication-config-settings" xreflabel="Replication Settings">
<varlistentry id="standby-mode" xreflabel="standby_mode">
<term><varname>standby_mode</varname> (<type>boolean</type>)</term>
<listitem>
<para>
Specifies whether to start the <productname>PostgreSQL</> server as
a standby. If this parameter is <literal>on</>, the server will
not end recovery when the end of archived WAL is reached, but
will keep trying to continue recovery using <varname>restore_command</>
and by connecting to the primary server as specified by
<varname>primary_conninfo</> setting.
</para>
</listitem>
</varlistentry>
<varlistentry>
<term><varname>restore_command</varname> (<type>string</type>)</term>
<term><varname>restore_end_command</varname> (<type>string</type>)</term>
<listitem>
<para>
In standby-mode, <varname>restore_command</> (and <varname>restore_end_command</>) is set to a
simple command or script like in PITR. pg_standby or similar tools
that wait for the next WAL file to arrive, cannot be used with
streaming replication, as the server handles retries and waiting
itself. Set <varname>restore_command</> as you would if you were
recovering using a Continuous archiving backup (see <xref linkend="backup-pitr-recovery">).
</para>
</listitem>
</varlistentry>
<varlistentry id="primary-conninfo" xreflabel="primary_conninfo">
<term><varname>primary_conninfo</varname> (<type>string</type>)</term>
<listitem>
<para>
Specifies a connection string which is used for the standby server
to connect with the primary. This string is in the same format as
described in <xref linkend="libpq-connect">. If any option is
unspecified in this string, then the corresponding environment
variable (see <xref linkend="libpq-envars">) is checked. If the
environment variable is not set either, then the indicated built-in
defaults are used.
</para>
<para>
The built-in replication requires that a host name (or host address)
or port number which the primary server listens on should be
specified in this string, respectively. Also ensure that a role with
the <literal>SUPERUSER</> and <literal>LOGIN</> privileges on the
primary is set (see
<xref linkend="streaming-replication-authentication">). Note that
the password needs to be set if the primary demands password
authentication.
</para>
<para>
This setting has no effect if <varname>standby_mode</> is <literal>off</>.
</para>
</listitem>
</varlistentry>
<varlistentry id="trigger-file" xreflabel="trigger_file">
<term><varname>trigger_file</varname> (<type>string</type>)</term>
<listitem>
<para>
Specifies a trigger file whose presence ends recovery in the
standby. If no trigger file is specified, the standby never exits
recovery.
</para>
<para>
This setting has no effect if <varname>standby_mode</> is <literal>off</>.
</para>
</listitem>
</varlistentry>
</variablelist>
</listitem>
<listitem>
<para>
Start the <productname>PostgreSQL</> server on the standby. The standby
server will go into recovery mode and proceeds to receive WAL records
from the primary and apply them continuously.
</para>
</listitem>
</orderedlist>
</para>
</sect2>
<sect2 id="streaming-replication-authentication">
<title>Authentication</title>
<para>
It's very important that the access privilege for replication are set
properly so that only trusted users can read the WAL stream, because it's
easy to extract serious information from it.
</para>
<para>
Only superuser is allowed to connect to the primary as the replication
standby. So a role with the <literal>SUPERUSER</> and <literal>LOGIN</>
privileges needs to be created in the primary.
</para>
<para>
Client authentication for replication is controlled by the
<filename>pg_hba.conf</> record specifying <literal>replication</> in the
<replaceable>database</> field. For example, if the standby is running on
host IP <literal>192.168.1.100</> and the superuser's name for replication
is <literal>foo</>, the administrator can add the following line to the
<filename>pg_hba.conf</> file on the primary.
<programlisting>
# Allow the user "foo" from host 192.168.1.100 to connect to the primary
# as a replication standby if the user's password is correctly supplied.
#
# TYPE DATABASE USER CIDR-ADDRESS METHOD
host replication foo 192.168.1.100/32 md5
</programlisting>
</para>
<para>
The host name and port number of the primary, user name to connect as,
and password are specified in the <filename>recovery.conf</> file or
the corresponding environment variable on the standby.
For example, if the primary is running on host IP <literal>192.168.1.50</>,
port <literal>5432</literal>, the superuser's name for replication is
<literal>foo</>, and the password is <literal>foopass</>, the administrator
can add the following line to the <filename>recovery.conf</> file on the
standby.
<programlisting>
# The standby connects to the primary that is running on host 192.168.1.50
# and port 5432 as the user "foo" whose password is "foopass".
primary_conninfo = 'host=192.168.1.50 port=5432 user=foo password=foopass'
</programlisting>
</para>
</sect2>
</sect1>
<sect1 id="warm-standby-failover">
<title>Failover</title>
<para>
If the primary server fails then the standby server should begin
failover procedures.
</para>
<para>
If the standby server fails then no failover need take place. If the
standby server can be restarted, even some time later, then the recovery
process can also be immediately restarted, taking advantage of
restartable recovery. If the standby server cannot be restarted, then a
full new standby server instance should be created.
</para>
<para>
If the primary server fails and the standby server becomes the
new primary, and then the old primary restarts, you must have
a mechanism for informing old primary that it is no longer the primary. This is
sometimes known as STONITH (Shoot The Other Node In The Head), which is
necessary to avoid situations where both systems think they are the
primary, which will lead to confusion and ultimately data loss.
</para>
<para>
Many failover systems use just two systems, the primary and the standby,
connected by some kind of heartbeat mechanism to continually verify the
connectivity between the two and the viability of the primary. It is
also possible to use a third system (called a witness server) to prevent
some cases of inappropriate failover, but the additional complexity
might not be worthwhile unless it is set up with sufficient care and
rigorous testing.
</para>
<para>
Once failover to the standby occurs, we have only a
single server in operation. This is known as a degenerate state.
The former standby is now the primary, but the former primary is down
and might stay down. To return to normal operation we must
fully recreate a standby server,
either on the former primary system when it comes up, or on a third,
possibly new, system. Once complete the primary and standby can be
considered to have switched roles. Some people choose to use a third
server to provide backup for the new primary until the new standby
server is recreated,
though clearly this complicates the system configuration and
operational processes.
</para>
<para>
So, switching from primary to standby server can be fast but requires
some time to re-prepare the failover cluster. Regular switching from
primary to standby is useful, since it allows regular downtime on
each system for maintenance. This also serves as a test of the
failover mechanism to ensure that it will really work when you need it.
Written administration procedures are advised.
</para>
</sect1>
<sect1 id="hot-standby">
<title>Hot Standby</title>
<indexterm zone="high-availability">
<primary>Hot Standby</primary>
</indexterm>
<para>
Hot Standby is the term used to describe the ability to connect to
the server and run queries while the server is in archive recovery. This
is useful for both log shipping replication and for restoring a backup
to an exact state with great precision.
The term Hot Standby also refers to the ability of the server to move
from recovery through to normal running while users continue running
queries and/or continue their connections.
</para>
<para>
Running queries in recovery is in many ways the same as normal running
though there are a large number of usage and administrative points
to note.
</para>
<sect2 id="hot-standby-users">
<title>User's Overview</title>
<para>
Users can connect to the database while the server is in recovery
and perform read-only queries. Read-only access to catalogs and views
will also occur as normal.
</para>
<para>
The data on the standby takes some time to arrive from the primary server
so there will be a measurable delay between primary and standby. Running the
same query nearly simultaneously on both primary and standby might therefore
return differing results. We say that data on the standby is eventually
consistent with the primary.
Queries executed on the standby will be correct with regard to the transactions
that had been recovered at the start of the query, or start of first statement,
in the case of serializable transactions. In comparison with the primary,
the standby returns query results that could have been obtained on the primary
at some exact moment in the past.
</para>
<para>
When a transaction is started in recovery, the parameter
<varname>transaction_read_only</> will be forced to be true, regardless of the
<varname>default_transaction_read_only</> setting in <filename>postgresql.conf</>.
It can't be manually set to false either. As a result, all transactions
started during recovery will be limited to read-only actions only. In all
other ways, connected sessions will appear identical to sessions
initiated during normal processing mode. There are no special commands
required to initiate a connection at this time, so all interfaces
work normally without change. After recovery finishes, the session
will allow normal read-write transactions at the start of the next
transaction, if these are requested.
</para>
<para>
Read-only here means "no writes to the permanent database tables".
There are no problems with queries that make use of transient sort and
work files.
</para>
<para>
The following actions are allowed
<itemizedlist>
<listitem>
<para>
Query access - SELECT, COPY TO including views and SELECT RULEs
</para>
</listitem>
<listitem>
<para>
Cursor commands - DECLARE, FETCH, CLOSE,
</para>
</listitem>
<listitem>
<para>
Parameters - SHOW, SET, RESET
</para>
</listitem>
<listitem>
<para>
Transaction management commands
<itemizedlist>
<listitem>
<para>
BEGIN, END, ABORT, START TRANSACTION
</para>
</listitem>
<listitem>
<para>
SAVEPOINT, RELEASE, ROLLBACK TO SAVEPOINT
</para>
</listitem>
<listitem>
<para>
EXCEPTION blocks and other internal subtransactions
</para>
</listitem>
</itemizedlist>
</para>
</listitem>
<listitem>
<para>
LOCK TABLE, though only when explicitly in one of these modes:
ACCESS SHARE, ROW SHARE or ROW EXCLUSIVE.
</para>
</listitem>
<listitem>
<para>
Plans and resources - PREPARE, EXECUTE, DEALLOCATE, DISCARD
</para>
</listitem>
<listitem>
<para>
Plugins and extensions - LOAD
</para>
</listitem>
</itemizedlist>
</para>
<para>
These actions produce error messages
<itemizedlist>
<listitem>
<para>
Data Manipulation Language (DML) - INSERT, UPDATE, DELETE, COPY FROM, TRUNCATE.
Note that there are no allowed actions that result in a trigger
being executed during recovery.
</para>
</listitem>
<listitem>
<para>
Data Definition Language (DDL) - CREATE, DROP, ALTER, COMMENT.
This also applies to temporary tables currently because currently their
definition causes writes to catalog tables.
</para>
</listitem>
<listitem>
<para>
SELECT ... FOR SHARE | UPDATE which cause row locks to be written
</para>
</listitem>
<listitem>
<para>
RULEs on SELECT statements that generate DML commands.
</para>
</listitem>
<listitem>
<para>
LOCK TABLE, in short default form, since it requests ACCESS EXCLUSIVE MODE.
LOCK TABLE that explicitly requests a mode higher than ROW EXCLUSIVE MODE.
</para>
</listitem>
<listitem>
<para>
Transaction management commands that explicitly set non-read only state
<itemizedlist>
<listitem>
<para>
BEGIN READ WRITE,
START TRANSACTION READ WRITE
</para>
</listitem>
<listitem>
<para>
SET TRANSACTION READ WRITE,
SET SESSION CHARACTERISTICS AS TRANSACTION READ WRITE
</para>
</listitem>
<listitem>
<para>
SET transaction_read_only = off
</para>
</listitem>
</itemizedlist>
</para>
</listitem>
<listitem>
<para>
Two-phase commit commands - PREPARE TRANSACTION, COMMIT PREPARED,
ROLLBACK PREPARED because even read-only transactions need to write
WAL in the prepare phase (the first phase of two phase commit).
</para>
</listitem>
<listitem>
<para>
sequence update - nextval()
</para>
</listitem>
<listitem>
<para>
LISTEN, UNLISTEN, NOTIFY since they currently write to system tables
</para>
</listitem>
</itemizedlist>
</para>
<para>
Note that current behaviour of read only transactions when not in
recovery is to allow the last two actions, so there are small and
subtle differences in behaviour between read-only transactions
run on standby and during normal running.
It is possible that the restrictions on LISTEN, UNLISTEN, NOTIFY and
temporary tables may be lifted in a future release, if their internal
implementation is altered to make this possible.
</para>
<para>
If failover or switchover occurs the database will switch to normal
processing mode. Sessions will remain connected while the server
changes mode. Current transactions will continue, though will remain
read-only. After recovery is complete, it will be possible to initiate
read-write transactions.
</para>
<para>
Users will be able to tell whether their session is read-only by
issuing SHOW transaction_read_only. In addition a set of
functions <xref linkend="functions-recovery-info-table"> allow users to
access information about Hot Standby. These allow you to write
functions that are aware of the current state of the database. These
can be used to monitor the progress of recovery, or to allow you to
write complex programs that restore the database to particular states.
</para>
<para>
In recovery, transactions will not be permitted to take any table lock
higher than RowExclusiveLock. In addition, transactions may never assign
a TransactionId and may never write WAL.
Any <command>LOCK TABLE</> command that runs on the standby and requests
a specific lock mode higher than ROW EXCLUSIVE MODE will be rejected.
</para>
<para>
In general queries will not experience lock conflicts with the database
changes made by recovery. This is becase recovery follows normal
concurrency control mechanisms, known as <acronym>MVCC</>. There are
some types of change that will cause conflicts, covered in the following
section.
</para>
</sect2>
<sect2 id="hot-standby-conflict">
<title>Handling query conflicts</title>
<para>
The primary and standby nodes are in many ways loosely connected. Actions
on the primary will have an effect on the standby. As a result, there is
potential for negative interactions or conflicts between them. The easiest
conflict to understand is performance: if a huge data load is taking place
on the primary then this will generate a similar stream of WAL records on the
standby, so standby queries may contend for system resources, such as I/O.
</para>
<para>
There are also additional types of conflict that can occur with Hot Standby.
These conflicts are <emphasis>hard conflicts</> in the sense that we may
need to cancel queries and in some cases disconnect sessions to resolve them.
The user is provided with a number of optional ways to handle these
conflicts, though we must first understand the possible reasons behind a conflict.
<itemizedlist>
<listitem>
<para>
Access Exclusive Locks from primary node, including both explicit
LOCK commands and various kinds of DDL action
</para>
</listitem>
<listitem>
<para>
Dropping tablespaces on the primary while standby queries are using
those tablespaces for temporary work files (work_mem overflow)
</para>
</listitem>
<listitem>
<para>
Dropping databases on the primary while users are connected to that
database on the standby.
</para>
</listitem>
<listitem>
<para>
Waiting to acquire buffer cleanup locks
</para>
</listitem>
<listitem>
<para>
Early cleanup of data still visible to the current query's snapshot
</para>
</listitem>
</itemizedlist>
</para>
<para>
Some WAL redo actions will be for DDL actions. These DDL actions are
repeating actions that have already committed on the primary node, so
they must not fail on the standby node. These DDL locks take priority
and will automatically *cancel* any read-only transactions that get in
their way, after a grace period. This is similar to the possibility of
being canceled by the deadlock detector, but in this case the standby
process always wins, since the replayed actions must not fail. This
also ensures that replication doesn't fall behind while we wait for a
query to complete. Again, we assume that the standby is there for high
availability purposes primarily.
</para>
<para>
An example of the above would be an Administrator on Primary server
runs a <command>DROP TABLE</> on a table that's currently being queried
in the standby server.
Clearly the query cannot continue if we let the <command>DROP TABLE</>
proceed. If this situation occurred on the primary, the <command>DROP TABLE</>
would wait until the query has finished. When the query is on the standby
and the <command>DROP TABLE</> is on the primary, the primary doesn't have
information about which queries are running on the standby and so the query
does not wait on the primary. The WAL change records come through to the
standby while the standby query is still running, causing a conflict.
</para>
<para>
The most common reason for conflict between standby queries and WAL redo is
"early cleanup". Normally, <productname>PostgreSQL</> allows cleanup of old
row versions when there are no users who may need to see them to ensure correct
visibility of data (the heart of MVCC). If there is a standby query that has
been running for longer than any query on the primary then it is possible
for old row versions to be removed by either a vacuum or HOT. This will
then generate WAL records that, if applied, would remove data on the
standby that might *potentially* be required by the standby query.
In more technical language, the primary's xmin horizon is later than
the standby's xmin horizon, allowing dead rows to be removed.
</para>
<para>
Experienced users should note that both row version cleanup and row version
freezing will potentially conflict with recovery queries. Running a
manual <command>VACUUM FREEZE</> is likely to cause conflicts even on tables
with no updated or deleted rows.
</para>
<para>
We have a number of choices for resolving query conflicts. The default
is that we wait and hope the query completes. The server will wait
automatically until the lag between primary and standby is at most
<varname>max_standby_delay</> seconds. Once that grace period expires,
we take one of the following actions:
<itemizedlist>
<listitem>
<para>
If the conflict is caused by a lock, we cancel the conflicting standby
transaction immediately. If the transaction is idle-in-transaction
then currently we abort the session instead, though this may change
in the future.
</para>
</listitem>
<listitem>
<para>
If the conflict is caused by cleanup records we tell the standby query
that a conflict has occurred and that it must cancel itself to avoid the
risk that it silently fails to read relevant data because
that data has been removed. (This is regrettably very similar to the
much feared and iconic error message "snapshot too old"). Some cleanup
records only cause conflict with older queries, though some types of
cleanup record affect all queries.
</para>
<para>
If cancellation does occur, the query and/or transaction can always
be re-executed. The error is dynamic and will not necessarily occur
the same way if the query is executed again.
</para>
</listitem>
</itemizedlist>
</para>
<para>
<varname>max_standby_delay</> is set in <filename>postgresql.conf</>.
The parameter applies to the server as a whole so if the delay is all used
up by a single query then there may be little or no waiting for queries that
follow immediately, though they will have benefited equally from the initial
waiting period. The server may take time to catch up again before the grace
period is available again, though if there is a heavy and constant stream
of conflicts it may seldom catch up fully.
</para>
<para>
Users should be clear that tables that are regularly and heavily updated on
primary server will quickly cause cancellation of longer running queries on
the standby. In those cases <varname>max_standby_delay</> can be
considered somewhat but not exactly the same as setting
<varname>statement_timeout</>.
</para>
<para>
Other remedial actions exist if the number of cancellations is unacceptable.
The first option is to connect to primary server and keep a query active
for as long as we need to run queries on the standby. This guarantees that
a WAL cleanup record is never generated and we don't ever get query
conflicts as described above. This could be done using contrib/dblink
and pg_sleep(), or via other mechanisms. If you do this, you should note
that this will delay cleanup of dead rows by vacuum or HOT and many
people may find this undesirable. However, we should remember that
primary and standby nodes are linked via the WAL, so this situation is no
different to the case where we ran the query on the primary node itself
except we have the benefit of off-loading the execution onto the standby.
</para>
<para>
It is also possible to set <varname>vacuum_defer_cleanup_age</> on the primary
to defer the cleanup of records by autovacuum, vacuum and HOT. This may allow
more time for queries to execute before they are cancelled on the standby,
without the need for setting a high <varname>max_standby_delay</>.
</para>
<para>
Three-way deadlocks are possible between AccessExclusiveLocks arriving from
the primary, cleanup WAL records that require buffer cleanup locks and
user requests that are waiting behind replayed AccessExclusiveLocks. Deadlocks
are resolved by time-out when we exceed <varname>max_standby_delay</>.
</para>
<para>
Dropping tablespaces or databases is discussed in the administrator's
section since they are not typical user situations.
</para>
</sect2>
<sect2 id="hot-standby-admin">
<title>Administrator's Overview</title>
<para>
If there is a <filename>recovery.conf</> file present the server will start
in Hot Standby mode by default, though <varname>recovery_connections</> can
be disabled via <filename>postgresql.conf</>, if required. The server may take
some time to enable recovery connections since the server must first complete
sufficient recovery to provide a consistent state against which queries
can run before enabling read only connections. Look for these messages
in the server logs
<programlisting>
LOG: entering standby mode
... then some time later ...
LOG: consistent recovery state reached
LOG: database system is ready to accept read only connections
</programlisting>
Consistency information is recorded once per checkpoint on the primary, as long
as <varname>recovery_connections</> is enabled (on the primary). If this parameter
is disabled, it will not be possible to enable recovery connections on the standby.
The consistent state can also be delayed in the presence of both of these conditions
<itemizedlist>
<listitem>
<para>
a write transaction has more than 64 subtransactions
</para>
</listitem>
<listitem>
<para>
very long-lived write transactions
</para>
</listitem>
</itemizedlist>
If you are running file-based log shipping ("warm standby"), you may need
to wait until the next WAL file arrives, which could be as long as the
<varname>archive_timeout</> setting on the primary.
</para>
<para>
The setting of some parameters on the standby will need reconfiguration
if they have been changed on the primary. The value on the standby must
be equal to or greater than the value on the primary. If these parameters
are not set high enough then the standby will not be able to track work
correctly from recovering transactions. If these values are set too low the
the server will halt. Higher values can then be supplied and the server
restarted to begin recovery again.
<itemizedlist>
<listitem>
<para>
<varname>max_connections</>
</para>
</listitem>
<listitem>
<para>
<varname>max_prepared_transactions</>
</para>
</listitem>
<listitem>
<para>
<varname>max_locks_per_transaction</>
</para>
</listitem>
</itemizedlist>
</para>
<para>
It is important that the administrator consider the appropriate setting
of <varname>max_standby_delay</>, set in <filename>postgresql.conf</>.
There is no optimal setting and should be set according to business
priorities. For example if the server is primarily tasked as a High
Availability server, then you may wish to lower
<varname>max_standby_delay</> or even set it to zero, though that is a
very aggressive setting. If the standby server is tasked as an additional
server for decision support queries then it may be acceptable to set this
to a value of many hours (in seconds).
</para>
<para>
Transaction status "hint bits" written on primary are not WAL-logged,
so data on standby will likely re-write the hints again on the standby.
Thus the main database blocks will produce write I/Os even though
all users are read-only; no changes have occurred to the data values
themselves. Users will be able to write large sort temp files and
re-generate relcache info files, so there is no part of the database
that is truly read-only during hot standby mode. There is no restriction
on the use of set returning functions, or other users of tuplestore/tuplesort
code. Note also that writes to remote databases will still be possible,
even though the transaction is read-only locally.
</para>
<para>
The following types of administrator command are not accepted
during recovery mode
<itemizedlist>
<listitem>
<para>
Data Definition Language (DDL) - e.g. CREATE INDEX
</para>
</listitem>
<listitem>
<para>
Privilege and Ownership - GRANT, REVOKE, REASSIGN
</para>
</listitem>
<listitem>
<para>
Maintenance commands - ANALYZE, VACUUM, CLUSTER, REINDEX
</para>
</listitem>
</itemizedlist>
</para>
<para>
Note again that some of these commands are actually allowed during
"read only" mode transactions on the primary.
</para>
<para>
As a result, you cannot create additional indexes that exist solely
on the standby, nor can statistics that exist solely on the standby.
If these administrator commands are needed they should be executed
on the primary so that the changes will propagate through to the
standby.
</para>
<para>
<function>pg_cancel_backend()</> will work on user backends, but not the
Startup process, which performs recovery. pg_stat_activity does not
show an entry for the Startup process, nor do recovering transactions
show as active. As a result, pg_prepared_xacts is always empty during
recovery. If you wish to resolve in-doubt prepared transactions
then look at pg_prepared_xacts on the primary and issue commands to
resolve those transactions there.
</para>
<para>
pg_locks will show locks held by backends as normal. pg_locks also shows
a virtual transaction managed by the Startup process that owns all
AccessExclusiveLocks held by transactions being replayed by recovery.
Note that Startup process does not acquire locks to
make database changes and thus locks other than AccessExclusiveLocks
do not show in pg_locks for the Startup process, they are just presumed
to exist.
</para>
<para>
<productname>check_pgsql</> will work, but it is very simple.
<productname>check_postgres</> will also work, though many some actions
could give different or confusing results.
e.g. last vacuum time will not be maintained for example, since no
vacuum occurs on the standby (though vacuums running on the primary do
send their changes to the standby).
</para>
<para>
WAL file control commands will not work during recovery
e.g. <function>pg_start_backup</>, <function>pg_switch_xlog</> etc..
</para>
<para>
Dynamically loadable modules work, including pg_stat_statements.
</para>
<para>
Advisory locks work normally in recovery, including deadlock detection.
Note that advisory locks are never WAL logged, so it is not possible for
an advisory lock on either the primary or the standby to conflict with WAL
replay. Nor is it possible to acquire an advisory lock on the primary
and have it initiate a similar advisory lock on the standby. Advisory
locks relate only to a single server on which they are acquired.
</para>
<para>
Trigger-based replication systems such as <productname>Slony</>,
<productname>Londiste</> and <productname>Bucardo</> won't run on the
standby at all, though they will run happily on the primary server as
long as the changes are not sent to standby servers to be applied.
WAL replay is not trigger-based so you cannot relay from the
standby to any system that requires additional database writes or
relies on the use of triggers.
</para>
<para>
New oids cannot be assigned, though some <acronym>UUID</> generators may still
work as long as they do not rely on writing new status to the database.
</para>
<para>
Currently, temp table creation is not allowed during read only
transactions, so in some cases existing scripts will not run correctly.
It is possible we may relax that restriction in a later release. This is
both a SQL Standard compliance issue and a technical issue.
</para>
<para>
<command>DROP TABLESPACE</> can only succeed if the tablespace is empty.
Some standby users may be actively using the tablespace via their
<varname>temp_tablespaces</> parameter. If there are temp files in the
tablespace we currently cancel all active queries to ensure that temp
files are removed, so that we can remove the tablespace and continue with
WAL replay.
</para>
<para>
Running <command>DROP DATABASE</>, <command>ALTER DATABASE ... SET TABLESPACE</>,
or <command>ALTER DATABASE ... RENAME</> on primary will generate a log message
that will cause all users connected to that database on the standby to be
forcibly disconnected. This action occurs immediately, whatever the setting of
<varname>max_standby_delay</>.
</para>
<para>
In normal running, if you issue <command>DROP USER</> or <command>DROP ROLE</>
for a role with login capability while that user is still connected then
nothing happens to the connected user - they remain connected. The user cannot
reconnect however. This behaviour applies in recovery also, so a
<command>DROP USER</> on the primary does not disconnect that user on the standby.
</para>
<para>
Stats collector is active during recovery. All scans, reads, blocks,
index usage etc will all be recorded normally on the standby. Replayed
actions will not duplicate their effects on primary, so replaying an
insert will not increment the Inserts column of pg_stat_user_tables.
The stats file is deleted at start of recovery, so stats from primary
and standby will differ; this is considered a feature not a bug.
</para>
<para>
Autovacuum is not active during recovery, though will start normally
at the end of recovery.
</para>
<para>
Background writer is active during recovery and will perform
restartpoints (similar to checkpoints on primary) and normal block
cleaning activities. The <command>CHECKPOINT</> command is accepted during recovery,
though performs a restartpoint rather than a new checkpoint.
</para>
</sect2>
<sect2 id="hot-standby-parameters">
<title>Hot Standby Parameter Reference</title>
<para>
Various parameters have been mentioned above in the <xref linkend="hot-standby-admin">
and <xref linkend="hot-standby-conflict"> sections.
</para>
<para>
On the primary, parameters <varname>recovery_connections</> and
<varname>vacuum_defer_cleanup_age</> can be used to enable and control the
primary server to assist the successful configuration of Hot Standby servers.
<varname>max_standby_delay</> has no effect if set on the primary.
</para>
<para>
On the standby, parameters <varname>recovery_connections</> and
<varname>max_standby_delay</> can be used to enable and control Hot Standby.
standby server to assist the successful configuration of Hot Standby servers.
<varname>vacuum_defer_cleanup_age</> has no effect during recovery.
</para>
</sect2>
<sect2 id="hot-standby-caveats">
<title>Caveats</title>
<para>
At this writing, there are several limitations of Hot Standby.
These can and probably will be fixed in future releases:
<itemizedlist>
<listitem>
<para>
Operations on hash indexes are not presently WAL-logged, so
replay will not update these indexes. Hash indexes will not be
used for query plans during recovery.
</para>
</listitem>
<listitem>
<para>
Full knowledge of running transactions is required before snapshots
may be taken. Transactions that take use large numbers of subtransactions
(currently greater than 64) will delay the start of read only
connections until the completion of the longest running write transaction.
If this situation occurs explanatory messages will be sent to server log.
</para>
</listitem>
<listitem>
<para>
Valid starting points for recovery connections are generated at each
checkpoint on the master. If the standby is shutdown while the master
is in a shutdown state it may not be possible to re-enter Hot Standby
until the primary is started up so that it generates further starting
points in the WAL logs. This is not considered a serious issue
because the standby is usually switched into the primary role while
the first node is taken down.
</para>
</listitem>
<listitem>
<para>
At the end of recovery, AccessExclusiveLocks held by prepared transactions
will require twice the normal number of lock table entries. If you plan
on running either a large number of concurrent prepared transactions
that normally take AccessExclusiveLocks, or you plan on having one
large transaction that takes many AccessExclusiveLocks then you are
advised to select a larger value of <varname>max_locks_per_transaction</>,
up to, but never more than twice the value of the parameter setting on
the primary server in rare extremes. You need not consider this at all if
your setting of <varname>max_prepared_transactions</> is <literal>0</>.
</para>
</listitem>
</itemizedlist>
</para>
</sect2>
</sect1>
<sect1 id="backup-incremental-updated">
<title>Incrementally Updated Backups</title>
<indexterm zone="high-availability">
<primary>incrementally updated backups</primary>
</indexterm>
<indexterm zone="high-availability">
<primary>change accumulation</primary>
</indexterm>
<para>
In a warm standby configuration, it is possible to offload the expense of
taking periodic base backups from the primary server; instead base backups
can be made by backing
up a standby server's files. This concept is generally known as
incrementally updated backups, log change accumulation, or more simply,
change accumulation.
</para>
<para>
If we take a file system backup of the standby server's data
directory while it is processing
logs shipped from the primary, we will be able to reload that backup and
restart the standby's recovery process from the last restart point.
We no longer need to keep WAL files from before the standby's restart point.
If we need to recover, it will be faster to recover from the incrementally
updated backup than from the original base backup.
</para>
<para>
Since the standby server is not <quote>live</>, it is not possible to
use <function>pg_start_backup()</> and <function>pg_stop_backup()</>
to manage the backup process; it will be up to you to determine how
far back you need to keep WAL segment files to have a recoverable
backup. You can do this by running <application>pg_controldata</>
on the standby server to inspect the control file and determine the
current checkpoint WAL location, or by using the
<varname>log_checkpoints</> option to print values to the standby's
server log.
</para>
</sect1>
</chapter>
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