high availability failover replication load balancing clustering data partitioning 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. 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. Some solutions deal with synchronization by allowing only one server to modify the data. Servers that can modify data are called read/write, master or primary servers. Servers that track changes in the primary are called standby or secondary servers. A standby server that cannot be connected to until it is promoted to a primary server is called a warm standby server, and one that can accept connections and serves read-only queries is called a hot standby server. 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. 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. 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. The remainder of this section outlines various failover, replication, and load balancing solutions. Shared Disk Failover 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. 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 POSIX behavior (see ). 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. File System (Block Device) Replication 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 primary. DRBD is a popular file system replication solution for Linux. Write-Ahead Log Shipping Warm and hot standby servers can be kept current by reading a stream of write-ahead log (WAL) records. If the main server fails, the standby contains almost all of the data of the main server, and can be quickly made the new primary database server. This can be synchronous or asynchronous and can only be done for the entire database server. A standby server can be implemented using file-based log shipping () or streaming replication (see ), or a combination of both. For information on hot standby, see . Logical Replication Logical replication allows a database server to send a stream of data modifications to another server. PostgreSQL logical replication constructs a stream of logical data modifications from the WAL. Logical replication allows replication of data changes on a per-table basis. In addition, a server that is publishing its own changes can also subscribe to changes from another server, allowing data to flow in multiple directions. For more information on logical replication, see . Through the logical decoding interface (), third-party extensions can also provide similar functionality. Trigger-Based Primary-Standby Replication A trigger-based replication setup typically funnels data modification queries to a designated primary server. Operating on a per-table basis, the primary server sends data changes (typically) asynchronously to the standby servers. Standby servers can answer queries while the primary is running, and may allow some local data changes or write activity. This form of replication is often used for offloading large analytical or data warehouse queries. Slony-I is an example of this type of replication, with per-table granularity, and support for multiple standby servers. Because it updates the standby server asynchronously (in batches), there is possible data loss during fail over. SQL-Based Replication Middleware With SQL-based replication middleware, a program intercepts every SQL query and sends it to one or all servers. Each server operates independently. Read-write queries must be sent to all servers, so that every server receives any changes. But read-only queries can be sent to just one server, allowing the read workload to be distributed among them. If queries are simply broadcast unmodified, functions like random(), CURRENT_TIMESTAMP, and sequences can have different values on different servers. This is because each server operates independently, and because SQL queries are broadcast rather than actual data changes. If this is unacceptable, either the middleware or the application must determine such values from a single source and then use those values in write queries. Care must also be taken that all transactions either commit or abort on all servers, perhaps using two-phase commit ( and ). Pgpool-II and Continuent Tungsten are examples of this type of replication. Asynchronous Multimaster Replication For servers that are not regularly connected or have slow communication links, 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. Synchronous Multimaster Replication 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 and commit delays, leading to poor performance. 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 primary and standby servers, and because the data changes are sent from one server to another, there is no problem with non-deterministic functions like random(). PostgreSQL does not offer this type of replication, though PostgreSQL two-phase commit ( and ) can be used to implement this in application code or middleware. summarizes the capabilities of the various solutions listed above. Feature Shared Disk File System Repl. Write-Ahead Log Shipping Logical Repl. Trigger-&zwsp;Based Repl. SQL Repl. Middle-ware Async. MM Repl. Sync. MM Repl. Popular examples NAS DRBD built-in streaming repl. built-in logical repl., pglogical Londiste, Slony pgpool-II Bucardo Comm. method shared disk disk blocks WAL logical decoding table rows SQL table rows table rows and row locks No special hardware required • • • • • • • Allows multiple primary servers • • • • No overhead on primary • • • • No waiting for multiple servers • with sync off with sync off • • Primary failure will never lose data • • with sync on with sync on • • Replicas accept read-only queries with hot standby • • • • • Per-table granularity • • • • No conflict resolution necessary • • • • • • There are a few solutions that do not fit into the above categories: Data Partitioning 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 primary/standby replication can be used to keep a read-only copy of the other office's data on each server. Multiple-Server Parallel Query Execution 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. This can be implemented using the PL/Proxy tool set. It should also be noted that because PostgreSQL is open source and easily extended, a number of companies have taken PostgreSQL and created commercial closed-source solutions with unique failover, replication, and load balancing capabilities. These are not discussed here. Continuous archiving can be used to create a high availability (HA) cluster configuration with one or more standby servers ready to take over operations if the primary server fails. This capability is widely referred to as warm standby or log shipping. 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 solutions. This configuration also has relatively low performance impact on the primary server. Directly moving WAL records from one database server to another is typically described as log shipping. PostgreSQL implements file-based log shipping by transferring WAL records 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 more granular and streams WAL changes incrementally over a network connection (see ). It should be noted that 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 size of the data loss window in file-based log shipping can be limited by use of the archive_timeout parameter, which can be set as low as a few seconds. However such a low setting will substantially increase the bandwidth required for file shipping. Streaming replication (see ) allows a much smaller window of data loss. 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, this is called a warm standby configuration which 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. A standby server can also be used for read-only queries, in which case it is called a hot standby server. See for more information. warm standby PITR standby standby server log shipping witness server STONITH 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 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. In general, log shipping between servers running different major 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. A server enters standby mode if a standby.signal standby.signal file exists in the data directory when the server is started. In standby mode, the server continuously applies WAL received from the primary server. The standby server can read WAL from a WAL archive (see ) or directly from the primary over a TCP connection (streaming replication). The standby server will also attempt to restore any WAL found in the standby cluster's pg_wal directory. That typically happens after a server restart, when the standby replays again WAL that was streamed from the primary before the restart, but you can also manually copy files to pg_wal at any time to have them replayed. At startup, the standby begins by restoring all WAL available in the archive location, calling restore_command. Once it reaches the end of WAL available there and restore_command fails, it tries to restore any WAL available in the pg_wal directory. If that fails, and streaming replication has been configured, the standby tries to connect to the primary server and start streaming WAL from the last valid record found in archive or pg_wal. If that fails or streaming replication is not configured, or if the connection is later disconnected, the standby goes back to step 1 and tries to restore the file from the archive again. This loop of retries from the archive, pg_wal, and via streaming replication goes on until the server is stopped or is promoted. Standby mode is exited and the server switches to normal operation when pg_ctl promote is run, or pg_promote() is called. Before failover, any WAL immediately available in the archive or in pg_wal will be restored, but no attempt is made to connect to the primary. Set up continuous archiving on the primary to an archive directory accessible from the standby, as described in . The archive location should be accessible from the standby even when the primary is down, i.e., it should reside on the standby server itself or another trusted server, not on the primary server. If you want to use streaming replication, set up authentication on the primary server to allow replication connections from the standby server(s); that is, create a role and provide a suitable entry or entries in pg_hba.conf with the database field set to replication. Also ensure max_wal_senders is set to a sufficiently large value in the configuration file of the primary server. If replication slots will be used, ensure that max_replication_slots is set sufficiently high as well. Take a base backup as described in to bootstrap the standby server. To set up the standby server, restore the base backup taken from primary server (see ). Create a file standby.signalstandby.signal in the standby's cluster data directory. Set to a simple command to copy files from the WAL archive. If you plan to have multiple standby servers for high availability purposes, make sure that recovery_target_timeline is set to latest (the default), to make the standby server follow the timeline change that occurs at failover to another standby. should return immediately if the file does not exist; the server will retry the command again if necessary. If you want to use streaming replication, fill in with a libpq connection string, including the host name (or IP address) and any additional details needed to connect to the primary server. If the primary needs a password for authentication, the password needs to be specified in as well. 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 using a WAL archive, its size can be minimized using the parameter to remove files that are no longer required by the standby server. The pg_archivecleanup utility is designed specifically to be used with archive_cleanup_command in typical single-standby configurations, see . Note however, that if you're using the archive for backup purposes, you need to retain files needed to recover from at least the latest base backup, even if they're no longer needed by the standby. A simple example of configuration is: primary_conninfo = 'host=192.168.1.50 port=5432 user=foo password=foopass options=''-c wal_sender_timeout=5000''' restore_command = 'cp /path/to/archive/%f %p' archive_cleanup_command = 'pg_archivecleanup /path/to/archive %r' You can have any number of standby servers, but if you use streaming replication, make sure you set max_wal_senders high enough in the primary to allow them to be connected simultaneously. Streaming Replication Streaming replication allows a standby server to stay more up-to-date than is possible with file-based log shipping. The standby connects to the primary, which streams WAL records to the standby as they're generated, without waiting for the WAL file to be filled. Streaming replication is asynchronous by default (see ), in which case there is a small delay between committing a transaction in the primary and the changes becoming visible in the standby. This delay is however much smaller than with file-based log shipping, typically under one second assuming the standby is powerful enough to keep up with the load. With streaming replication, archive_timeout is not required to reduce the data loss window. If you use streaming replication without file-based continuous archiving, the server might recycle old WAL segments before the standby has received them. If this occurs, the standby will need to be reinitialized from a new base backup. You can avoid this by setting wal_keep_size to a value large enough to ensure that WAL segments are not recycled too early, or by configuring a replication slot for the standby. If you set up a WAL archive that's accessible from the standby, these solutions are not required, since the standby can always use the archive to catch up provided it retains enough segments. To use streaming replication, set up a file-based log-shipping standby server as described in . The step that turns a file-based log-shipping standby into streaming replication standby is setting the primary_conninfo setting to point to the primary server. Set and authentication options (see pg_hba.conf) on the primary so that the standby server can connect to the replication pseudo-database on the primary server (see ). On systems that support the keepalive socket option, setting , and helps the primary promptly notice a broken connection. Set the maximum number of concurrent connections from the standby servers (see for details). When the standby is started and primary_conninfo is set correctly, the standby will connect to the primary after replaying all WAL files available in the archive. If the connection is established successfully, you will see a walreceiver in the standby, and a corresponding walsender process in the primary. It is very important that the access privileges for replication be set up so that only trusted users can read the WAL stream, because it is easy to extract privileged information from it. Standby servers must authenticate to the primary as an account that has the REPLICATION privilege or a superuser. It is recommended to create a dedicated user account with REPLICATION and LOGIN privileges for replication. While REPLICATION privilege gives very high permissions, it does not allow the user to modify any data on the primary system, which the SUPERUSER privilege does. Client authentication for replication is controlled by a pg_hba.conf record specifying replication in the database field. For example, if the standby is running on host IP 192.168.1.100 and the account name for replication is foo, the administrator can add the following line to the pg_hba.conf file on the primary: # 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 ADDRESS METHOD host replication foo 192.168.1.100/32 md5 The host name and port number of the primary, connection user name, and password are specified in the . The password can also be set in the ~/.pgpass file on the standby (specify replication in the database field). For example, if the primary is running on host IP 192.168.1.50, port 5432, the account name for replication is foo, and the password is foopass, the administrator can add the following line to the postgresql.conf file on the standby: # 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' An important health indicator of streaming replication is the amount of WAL records generated in the primary, but not yet applied in the standby. You can calculate this lag by comparing the current WAL write location on the primary with the last WAL location received by the standby. These locations can be retrieved using pg_current_wal_lsn on the primary and pg_last_wal_receive_lsn on the standby, respectively (see and for details). The last WAL receive location in the standby is also displayed in the process status of the WAL receiver process, displayed using the ps command (see for details). You can retrieve a list of WAL sender processes via the pg_stat_replication view. Large differences between pg_current_wal_lsn and the view's sent_lsn field might indicate that the primary server is under heavy load, while differences between sent_lsn and pg_last_wal_receive_lsn on the standby might indicate network delay, or that the standby is under heavy load. On a hot standby, the status of the WAL receiver process can be retrieved via the pg_stat_wal_receiver view. A large difference between pg_last_wal_replay_lsn and the view's flushed_lsn indicates that WAL is being received faster than it can be replayed. replication slot streaming replication Replication slots provide an automated way to ensure that the primary does not remove WAL segments until they have been received by all standbys, and that the primary does not remove rows which could cause a recovery conflict even when the standby is disconnected. In lieu of using replication slots, it is possible to prevent the removal of old WAL segments using , or by storing the segments in an archive using or . However, these methods often result in retaining more WAL segments than required, whereas replication slots retain only the number of segments known to be needed. On the other hand, replication slots can retain so many WAL segments that they fill up the space allocated for pg_wal; limits the size of WAL files retained by replication slots. Similarly, on its own, without also using a replication slot, provides protection against relevant rows being removed by vacuum, but provides no protection during any time period when the standby is not connected. Replication slots overcome these disadvantages. Each replication slot has a name, which can contain lower-case letters, numbers, and the underscore character. Existing replication slots and their state can be seen in the pg_replication_slots view. Slots can be created and dropped either via the streaming replication protocol (see ) or via SQL functions (see ). You can create a replication slot like this: postgres=# SELECT * FROM pg_create_physical_replication_slot('node_a_slot'); slot_name | lsn -------------+----- node_a_slot | postgres=# SELECT slot_name, slot_type, active FROM pg_replication_slots; slot_name | slot_type | active -------------+-----------+-------- node_a_slot | physical | f (1 row) To configure the standby to use this slot, primary_slot_name should be configured on the standby. Here is a simple example: primary_conninfo = 'host=192.168.1.50 port=5432 user=foo password=foopass' primary_slot_name = 'node_a_slot' Cascading Replication The cascading replication feature allows a standby server to accept replication connections and stream WAL records to other standbys, acting as a relay. This can be used to reduce the number of direct connections to the primary and also to minimize inter-site bandwidth overheads. A standby acting as both a receiver and a sender is known as a cascading standby. Standbys that are more directly connected to the primary are known as upstream servers, while those standby servers further away are downstream servers. Cascading replication does not place limits on the number or arrangement of downstream servers, though each standby connects to only one upstream server which eventually links to a single primary server. A cascading standby sends not only WAL records received from the primary but also those restored from the archive. So even if the replication connection in some upstream connection is terminated, streaming replication continues downstream for as long as new WAL records are available. Cascading replication is currently asynchronous. Synchronous replication (see ) settings have no effect on cascading replication at present. Hot standby feedback propagates upstream, whatever the cascaded arrangement. If an upstream standby server is promoted to become the new primary, downstream servers will continue to stream from the new primary if recovery_target_timeline is set to 'latest' (the default). To use cascading replication, set up the cascading standby so that it can accept replication connections (that is, set and , and configure host-based authentication). You will also need to set primary_conninfo in the downstream standby to point to the cascading standby. Synchronous Replication PostgreSQL streaming replication is asynchronous by default. If the primary server crashes then some transactions that were committed may not have been replicated to the standby server, causing data loss. The amount of data loss is proportional to the replication delay at the time of failover. Synchronous replication offers the ability to confirm that all changes made by a transaction have been transferred to one or more synchronous standby servers. This extends that standard level of durability offered by a transaction commit. This level of protection is referred to as 2-safe replication in computer science theory, and group-1-safe (group-safe and 1-safe) when synchronous_commit is set to remote_write. When requesting synchronous replication, each commit of a write transaction will wait until confirmation is received that the commit has been written to the write-ahead log on disk of both the primary and standby server. The only possibility that data can be lost is if both the primary and the standby suffer crashes at the same time. This can provide a much higher level of durability, though only if the sysadmin is cautious about the placement and management of the two servers. Waiting for confirmation increases the user's confidence that the changes will not be lost in the event of server crashes but it also necessarily increases the response time for the requesting transaction. The minimum wait time is the round-trip time between primary and standby. Read-only transactions and transaction rollbacks need not wait for replies from standby servers. Subtransaction commits do not wait for responses from standby servers, only top-level commits. Long running actions such as data loading or index building do not wait until the very final commit message. All two-phase commit actions require commit waits, including both prepare and commit. A synchronous standby can be a physical replication standby or a logical replication subscriber. It can also be any other physical or logical WAL replication stream consumer that knows how to send the appropriate feedback messages. Besides the built-in physical and logical replication systems, this includes special programs such as pg_receivewal and pg_recvlogical as well as some third-party replication systems and custom programs. Check the respective documentation for details on synchronous replication support. Once streaming replication has been configured, configuring synchronous replication requires only one additional configuration step: must be set to a non-empty value. synchronous_commit must also be set to on, but since this is the default value, typically no change is required. (See and .) This configuration will cause each commit to wait for confirmation that the standby has written the commit record to durable storage. synchronous_commit can be set by individual users, so it can be configured in the configuration file, for particular users or databases, or dynamically by applications, in order to control the durability guarantee on a per-transaction basis. After a commit record has been written to disk on the primary, the WAL record is then sent to the standby. The standby sends reply messages each time a new batch of WAL data is written to disk, unless wal_receiver_status_interval is set to zero on the standby. In the case that synchronous_commit is set to remote_apply, the standby sends reply messages when the commit record is replayed, making the transaction visible. If the standby is chosen as a synchronous standby, according to the setting of synchronous_standby_names on the primary, the reply messages from that standby will be considered along with those from other synchronous standbys to decide when to release transactions waiting for confirmation that the commit record has been received. These parameters allow the administrator to specify which standby servers should be synchronous standbys. Note that the configuration of synchronous replication is mainly on the primary. Named standbys must be directly connected to the primary; the primary knows nothing about downstream standby servers using cascaded replication. Setting synchronous_commit to remote_write will cause each commit to wait for confirmation that the standby has received the commit record and written it out to its own operating system, but not for the data to be flushed to disk on the standby. This setting provides a weaker guarantee of durability than on does: the standby could lose the data in the event of an operating system crash, though not a PostgreSQL crash. However, it's a useful setting in practice because it can decrease the response time for the transaction. Data loss could only occur if both the primary and the standby crash and the database of the primary gets corrupted at the same time. Setting synchronous_commit to remote_apply will cause each commit to wait until the current synchronous standbys report that they have replayed the transaction, making it visible to user queries. In simple cases, this allows for load balancing with causal consistency. Users will stop waiting if a fast shutdown is requested. However, as when using asynchronous replication, the server will not fully shutdown until all outstanding WAL records are transferred to the currently connected standby servers. Synchronous replication supports one or more synchronous standby servers; transactions will wait until all the standby servers which are considered as synchronous confirm receipt of their data. The number of synchronous standbys that transactions must wait for replies from is specified in synchronous_standby_names. This parameter also specifies a list of standby names and the method (FIRST and ANY) to choose synchronous standbys from the listed ones. The method FIRST specifies a priority-based synchronous replication and makes transaction commits wait until their WAL records are replicated to the requested number of synchronous standbys chosen based on their priorities. The standbys whose names appear earlier in the list are given higher priority and will be considered as synchronous. Other standby servers appearing later in this list represent potential synchronous standbys. If any of the current synchronous standbys disconnects for whatever reason, it will be replaced immediately with the next-highest-priority standby. An example of synchronous_standby_names for a priority-based multiple synchronous standbys is: synchronous_standby_names = 'FIRST 2 (s1, s2, s3)' In this example, if four standby servers s1, s2, s3 and s4 are running, the two standbys s1 and s2 will be chosen as synchronous standbys because their names appear early in the list of standby names. s3 is a potential synchronous standby and will take over the role of synchronous standby when either of s1 or s2 fails. s4 is an asynchronous standby since its name is not in the list. The method ANY specifies a quorum-based synchronous replication and makes transaction commits wait until their WAL records are replicated to at least the requested number of synchronous standbys in the list. An example of synchronous_standby_names for a quorum-based multiple synchronous standbys is: synchronous_standby_names = 'ANY 2 (s1, s2, s3)' In this example, if four standby servers s1, s2, s3 and s4 are running, transaction commits will wait for replies from at least any two standbys of s1, s2 and s3. s4 is an asynchronous standby since its name is not in the list. The synchronous states of standby servers can be viewed using the pg_stat_replication view. Synchronous replication usually requires carefully planned and placed standby servers to ensure applications perform acceptably. Waiting doesn't utilize system resources, but transaction locks continue to be held until the transfer is confirmed. As a result, incautious use of synchronous replication will reduce performance for database applications because of increased response times and higher contention. PostgreSQL allows the application developer to specify the durability level required via replication. This can be specified for the system overall, though it can also be specified for specific users or connections, or even individual transactions. For example, an application workload might consist of: 10% of changes are important customer details, while 90% of changes are less important data that the business can more easily survive if it is lost, such as chat messages between users. With synchronous replication options specified at the application level (on the primary) we can offer synchronous replication for the most important changes, without slowing down the bulk of the total workload. Application level options are an important and practical tool for allowing the benefits of synchronous replication for high performance applications. You should consider that the network bandwidth must be higher than the rate of generation of WAL data. synchronous_standby_names specifies the number and names of synchronous standbys that transaction commits made when synchronous_commit is set to on, remote_apply or remote_write will wait for responses from. Such transaction commits may never be completed if any one of the synchronous standbys should crash. The best solution for high availability is to ensure you keep as many synchronous standbys as requested. This can be achieved by naming multiple potential synchronous standbys using synchronous_standby_names. In a priority-based synchronous replication, the standbys whose names appear earlier in the list will be used as synchronous standbys. Standbys listed after these will take over the role of synchronous standby if one of current ones should fail. In a quorum-based synchronous replication, all the standbys appearing in the list will be used as candidates for synchronous standbys. Even if one of them should fail, the other standbys will keep performing the role of candidates of synchronous standby. When a standby first attaches to the primary, it will not yet be properly synchronized. This is described as catchup mode. Once the lag between standby and primary reaches zero for the first time we move to real-time streaming state. The catch-up duration may be long immediately after the standby has been created. If the standby is shut down, then the catch-up period will increase according to the length of time the standby has been down. The standby is only able to become a synchronous standby once it has reached streaming state. This state can be viewed using the pg_stat_replication view. If primary restarts while commits are waiting for acknowledgment, those waiting transactions will be marked fully committed once the primary database recovers. There is no way to be certain that all standbys have received all outstanding WAL data at time of the crash of the primary. Some transactions may not show as committed on the standby, even though they show as committed on the primary. The guarantee we offer is that the application will not receive explicit acknowledgment of the successful commit of a transaction until the WAL data is known to be safely received by all the synchronous standbys. If you really cannot keep as many synchronous standbys as requested then you should decrease the number of synchronous standbys that transaction commits must wait for responses from in synchronous_standby_names (or disable it) and reload the configuration file on the primary server. If the primary is isolated from remaining standby servers you should fail over to the best candidate of those other remaining standby servers. If you need to re-create a standby server while transactions are waiting, make sure that the commands pg_backup_start() and pg_backup_stop() are run in a session with synchronous_commit = off, otherwise those requests will wait forever for the standby to appear. continuous archiving in standby When continuous WAL archiving is used in a standby, there are two different scenarios: the WAL archive can be shared between the primary and the standby, or the standby can have its own WAL archive. When the standby has its own WAL archive, set archive_mode to always, and the standby will call the archive command for every WAL segment it receives, whether it's by restoring from the archive or by streaming replication. The shared archive can be handled similarly, but the archive_command or archive_library must test if the file being archived exists already, and if the existing file has identical contents. This requires more care in the archive_command or archive_library, as it must be careful to not overwrite an existing file with different contents, but return success if the exactly same file is archived twice. And all that must be done free of race conditions, if two servers attempt to archive the same file at the same time. If archive_mode is set to on, the archiver is not enabled during recovery or standby mode. If the standby server is promoted, it will start archiving after the promotion, but will not archive any WAL or timeline history files that it did not generate itself. To get a complete series of WAL files in the archive, you must ensure that all WAL is archived, before it reaches the standby. This is inherently true with file-based log shipping, as the standby can only restore files that are found in the archive, but not if streaming replication is enabled. When a server is not in recovery mode, there is no difference between on and always modes. If the primary server fails then the standby server should begin failover procedures. 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 restarted immediately, taking advantage of restartable recovery. If the standby server cannot be restarted, then a full new standby server instance should be created. 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 the 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. 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. PostgreSQL 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. Once failover to the standby occurs, there is 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, a standby server must be recreated, either on the former primary system when it comes up, or on a third, possibly new, system. The utility can be used to speed up this process on large clusters. 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. 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. To trigger failover of a log-shipping standby server, run pg_ctl promote or call pg_promote(). If you're setting up reporting servers that are only used to offload read-only queries from the primary, not for high availability purposes, you don't need to promote. hot standby Hot standby is the term used to describe the ability to connect to the server and run read-only queries while the server is in archive recovery or standby mode. This is useful both for replication purposes and for restoring a backup to a desired state with great precision. The term hot standby also refers to the ability of the server to move from recovery through to normal operation while users continue running queries and/or keep their connections open. Running queries in hot standby mode is similar to normal query operation, though there are several usage and administrative differences explained below. When the parameter is set to true on a standby server, it will begin accepting connections once the recovery has brought the system to a consistent state. All such connections are strictly read-only; not even temporary tables may be written. 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. Once the commit record for a transaction is replayed on the standby, the changes made by that transaction will be visible to any new snapshots taken on the standby. Snapshots may be taken at the start of each query or at the start of each transaction, depending on the current transaction isolation level. For more details, see . Transactions started during hot standby may issue the following commands: Query access: SELECT, COPY TO Cursor commands: DECLARE, FETCH, CLOSE Settings: SHOW, SET, RESET Transaction management commands: BEGIN, END, ABORT, START TRANSACTION SAVEPOINT, RELEASE, ROLLBACK TO SAVEPOINT EXCEPTION blocks and other internal subtransactions LOCK TABLE, though only when explicitly in one of these modes: ACCESS SHARE, ROW SHARE or ROW EXCLUSIVE. Plans and resources: PREPARE, EXECUTE, DEALLOCATE, DISCARD Plugins and extensions: LOAD UNLISTEN Transactions started during hot standby will never be assigned a transaction ID and cannot write to the system write-ahead log. Therefore, the following actions will produce error messages: Data Manipulation Language (DML): INSERT, UPDATE, DELETE, MERGE, COPY FROM, TRUNCATE. Note that there are no allowed actions that result in a trigger being executed during recovery. This restriction applies even to temporary tables, because table rows cannot be read or written without assigning a transaction ID, which is currently not possible in a hot standby environment. Data Definition Language (DDL): CREATE, DROP, ALTER, COMMENT. This restriction applies even to temporary tables, because carrying out these operations would require updating the system catalog tables. SELECT ... FOR SHARE | UPDATE, because row locks cannot be taken without updating the underlying data files. Rules on SELECT statements that generate DML commands. LOCK that explicitly requests a mode higher than ROW EXCLUSIVE MODE. LOCK in short default form, since it requests ACCESS EXCLUSIVE MODE. Transaction management commands that explicitly set non-read-only state: BEGIN READ WRITE, START TRANSACTION READ WRITE SET TRANSACTION READ WRITE, SET SESSION CHARACTERISTICS AS TRANSACTION READ WRITE SET transaction_read_only = off 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). Sequence updates: nextval(), setval() LISTEN, NOTIFY In normal operation, read-only transactions are allowed to use LISTEN and NOTIFY, so hot standby sessions operate under slightly tighter restrictions than ordinary read-only sessions. It is possible that some of these restrictions might be loosened in a future release. During hot standby, the parameter transaction_read_only is always true and may not be changed. But as long as no attempt is made to modify the database, connections during hot standby will act much like any other database connection. If failover or switchover occurs, the database will switch to normal processing mode. Sessions will remain connected while the server changes mode. Once hot standby finishes, it will be possible to initiate read-write transactions (even from a session begun during hot standby). Users can determine whether hot standby is currently active for their session by issuing SHOW in_hot_standby. (In server versions before 14, the in_hot_standby parameter did not exist; a workable substitute method for older servers is SHOW transaction_read_only.) In addition, a set of functions () allow users to access information about the standby server. These allow you to write programs 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. The primary and standby servers 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. There are also additional types of conflict that can occur with hot standby. These conflicts are hard conflicts in the sense that queries might need to be canceled and, in some cases, sessions disconnected to resolve them. The user is provided with several ways to handle these conflicts. Conflict cases include: Access Exclusive locks taken on the primary server, including both explicit LOCK commands and various DDL actions, conflict with table accesses in standby queries. Dropping a tablespace on the primary conflicts with standby queries using that tablespace for temporary work files. Dropping a database on the primary conflicts with sessions connected to that database on the standby. Application of a vacuum cleanup record from WAL conflicts with standby transactions whose snapshots can still see any of the rows to be removed. Application of a vacuum cleanup record from WAL conflicts with queries accessing the target page on the standby, whether or not the data to be removed is visible. On the primary server, these cases simply result in waiting; and the user might choose to cancel either of the conflicting actions. However, on the standby there is no choice: the WAL-logged action already occurred on the primary so the standby must not fail to apply it. Furthermore, allowing WAL application to wait indefinitely may be very undesirable, because the standby's state will become increasingly far behind the primary's. Therefore, a mechanism is provided to forcibly cancel standby queries that conflict with to-be-applied WAL records. An example of the problem situation is an administrator on the primary server running DROP TABLE on a table that is currently being queried on the standby server. Clearly the standby query cannot continue if the DROP TABLE is applied on the standby. If this situation occurred on the primary, the DROP TABLE would wait until the other query had finished. But when DROP TABLE is run on the primary, the primary doesn't have information about what queries are running on the standby, so it will not wait for any such standby queries. The WAL change records come through to the standby while the standby query is still running, causing a conflict. The standby server must either delay application of the WAL records (and everything after them, too) or else cancel the conflicting query so that the DROP TABLE can be applied. When a conflicting query is short, it's typically desirable to allow it to complete by delaying WAL application for a little bit; but a long delay in WAL application is usually not desirable. So the cancel mechanism has parameters, and , that define the maximum allowed delay in WAL application. Conflicting queries will be canceled once it has taken longer than the relevant delay setting to apply any newly-received WAL data. There are two parameters so that different delay values can be specified for the case of reading WAL data from an archive (i.e., initial recovery from a base backup or catching up a standby server that has fallen far behind) versus reading WAL data via streaming replication. In a standby server that exists primarily for high availability, it's best to set the delay parameters relatively short, so that the server cannot fall far behind the primary due to delays caused by standby queries. However, if the standby server is meant for executing long-running queries, then a high or even infinite delay value may be preferable. Keep in mind however that a long-running query could cause other sessions on the standby server to not see recent changes on the primary, if it delays application of WAL records. Once the delay specified by max_standby_archive_delay or max_standby_streaming_delay has been exceeded, conflicting queries will be canceled. This usually results just in a cancellation error, although in the case of replaying a DROP DATABASE the entire conflicting session will be terminated. Also, if the conflict is over a lock held by an idle transaction, the conflicting session is terminated (this behavior might change in the future). Canceled queries may be retried immediately (after beginning a new transaction, of course). Since query cancellation depends on the nature of the WAL records being replayed, a query that was canceled may well succeed if it is executed again. Keep in mind that the delay parameters are compared to the elapsed time since the WAL data was received by the standby server. Thus, the grace period allowed to any one query on the standby is never more than the delay parameter, and could be considerably less if the standby has already fallen behind as a result of waiting for previous queries to complete, or as a result of being unable to keep up with a heavy update load. The most common reason for conflict between standby queries and WAL replay is early cleanup. Normally, PostgreSQL allows cleanup of old row versions when there are no transactions that need to see them to ensure correct visibility of data according to MVCC rules. However, this rule can only be applied for transactions executing on the primary. So it is possible that cleanup on the primary will remove row versions that are still visible to a transaction on the standby. Row version cleanup isn't the only potential cause of conflicts with standby queries. All index-only scans (including those that run on standbys) must use an MVCC snapshot that agrees with the visibility map. Conflicts are therefore required whenever VACUUM sets a page as all-visible in the visibility map containing one or more rows not visible to all standby queries. So even running VACUUM against a table with no updated or deleted rows requiring cleanup might lead to conflicts. Users should be clear that tables that are regularly and heavily updated on the primary server will quickly cause cancellation of longer running queries on the standby. In such cases the setting of a finite value for max_standby_archive_delay or max_standby_streaming_delay can be considered similar to setting statement_timeout. Remedial possibilities exist if the number of standby-query cancellations is found to be unacceptable. The first option is to set the parameter hot_standby_feedback, which prevents VACUUM from removing recently-dead rows and so cleanup conflicts do not occur. If you do this, you should note that this will delay cleanup of dead rows on the primary, which may result in undesirable table bloat. However, the cleanup situation will be no worse than if the standby queries were running directly on the primary server, and you are still getting the benefit of off-loading execution onto the standby. If standby servers connect and disconnect frequently, you might want to make adjustments to handle the period when hot_standby_feedback feedback is not being provided. For example, consider increasing max_standby_archive_delay so that queries are not rapidly canceled by conflicts in WAL archive files during disconnected periods. You should also consider increasing max_standby_streaming_delay to avoid rapid cancellations by newly-arrived streaming WAL entries after reconnection. The number of query cancels and the reason for them can be viewed using the pg_stat_database_conflicts system view on the standby server. The pg_stat_database system view also contains summary information. Users can control whether a log message is produced when WAL replay is waiting longer than deadlock_timeout for conflicts. This is controlled by the parameter. If hot_standby is on in postgresql.conf (the default value) and there is a standby.signalstandby.signalfor hot standby file present, the server will run in hot standby mode. However, it may take some time for hot standby connections to be allowed, because the server will not accept connections until it has completed sufficient recovery to provide a consistent state against which queries can run. During this period, clients that attempt to connect will be refused with an error message. To confirm the server has come up, either loop trying to connect from the application, or look for these messages in the server logs: LOG: entering standby mode ... then some time later ... LOG: consistent recovery state reached LOG: database system is ready to accept read-only connections Consistency information is recorded once per checkpoint on the primary. It is not possible to enable hot standby when reading WAL written during a period when wal_level was not set to replica or logical on the primary. Reaching a consistent state can also be delayed in the presence of both of these conditions: A write transaction has more than 64 subtransactions Very long-lived write transactions If you are running file-based log shipping ("warm standby"), you might need to wait until the next WAL file arrives, which could be as long as the archive_timeout setting on the primary. The settings of some parameters determine the size of shared memory for tracking transaction IDs, locks, and prepared transactions. These shared memory structures must be no smaller on a standby than on the primary in order to ensure that the standby does not run out of shared memory during recovery. For example, if the primary had used a prepared transaction but the standby had not allocated any shared memory for tracking prepared transactions, then recovery could not continue until the standby's configuration is changed. The parameters affected are: max_connections max_prepared_transactions max_locks_per_transaction max_wal_senders max_worker_processes The easiest way to ensure this does not become a problem is to have these parameters set on the standbys to values equal to or greater than on the primary. Therefore, if you want to increase these values, you should do so on all standby servers first, before applying the changes to the primary server. Conversely, if you want to decrease these values, you should do so on the primary server first, before applying the changes to all standby servers. Keep in mind that when a standby is promoted, it becomes the new reference for the required parameter settings for the standbys that follow it. Therefore, to avoid this becoming a problem during a switchover or failover, it is recommended to keep these settings the same on all standby servers. The WAL tracks changes to these parameters on the primary. If a hot standby processes WAL that indicates that the current value on the primary is higher than its own value, it will log a warning and pause recovery, for example: WARNING: hot standby is not possible because of insufficient parameter settings DETAIL: max_connections = 80 is a lower setting than on the primary server, where its value was 100. LOG: recovery has paused DETAIL: If recovery is unpaused, the server will shut down. HINT: You can then restart the server after making the necessary configuration changes. At that point, the settings on the standby need to be updated and the instance restarted before recovery can continue. If the standby is not a hot standby, then when it encounters the incompatible parameter change, it will shut down immediately without pausing, since there is then no value in keeping it up. It is important that the administrator select appropriate settings for and . The best choices vary depending on business priorities. For example if the server is primarily tasked as a High Availability server, then you will want low delay settings, perhaps even zero, though that is a very aggressive setting. If the standby server is tasked as an additional server for decision support queries then it might be acceptable to set the maximum delay values to many hours, or even -1 which means wait forever for queries to complete. Transaction status "hint bits" written on the primary are not WAL-logged, so data on the standby will likely re-write the hints again on the standby. Thus, the standby server will still perform disk writes even though all users are read-only; no changes occur to the data values themselves. Users will still write large sort temporary files and re-generate relcache info files, so no part of the database is truly read-only during hot standby mode. Note also that writes to remote databases using dblink module, and other operations outside the database using PL functions will still be possible, even though the transaction is read-only locally. The following types of administration commands are not accepted during recovery mode: Data Definition Language (DDL): e.g., CREATE INDEX Privilege and Ownership: GRANT, REVOKE, REASSIGN Maintenance commands: ANALYZE, VACUUM, CLUSTER, REINDEX Again, note that some of these commands are actually allowed during "read only" mode transactions on the primary. As a result, you cannot create additional indexes that exist solely on the standby, nor statistics that exist solely on the standby. If these administration commands are needed, they should be executed on the primary, and eventually those changes will propagate to the standby. pg_cancel_backend() and pg_terminate_backend() will work on user backends, but not the startup process, which performs recovery. pg_stat_activity does not show recovering transactions as active. As a result, pg_prepared_xacts is always empty during recovery. If you wish to resolve in-doubt prepared transactions, view pg_prepared_xacts on the primary and issue commands to resolve transactions there or resolve them after the end of recovery. 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 the 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. The Nagios plugin check_pgsql will work, because the simple information it checks for exists. The check_postgres monitoring script will also work, though some reported values could give different or confusing results. For example, last vacuum time will not be maintained, since no vacuum occurs on the standby. Vacuums running on the primary do still send their changes to the standby. WAL file control commands will not work during recovery, e.g., pg_backup_start, pg_switch_wal etc. Dynamically loadable modules work, including pg_stat_statements. Advisory locks work normally in recovery, including deadlock detection. Note that advisory locks are never WAL logged, so it is impossible 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 the server on which they are acquired. Trigger-based replication systems such as Slony, Londiste and 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. New OIDs cannot be assigned, though some UUID generators may still work as long as they do not rely on writing new status to the database. Currently, temporary table creation is not allowed during read-only transactions, so in some cases existing scripts will not run correctly. This restriction might be relaxed in a later release. This is both an SQL standard compliance issue and a technical issue. DROP TABLESPACE can only succeed if the tablespace is empty. Some standby users may be actively using the tablespace via their temp_tablespaces parameter. If there are temporary files in the tablespace, all active queries are canceled to ensure that temporary files are removed, so the tablespace can be removed and WAL replay can continue. Running DROP DATABASE or ALTER DATABASE ... SET TABLESPACE on the primary will generate a WAL entry that will cause all users connected to that database on the standby to be forcibly disconnected. This action occurs immediately, whatever the setting of max_standby_streaming_delay. Note that ALTER DATABASE ... RENAME does not disconnect users, which in most cases will go unnoticed, though might in some cases cause a program confusion if it depends in some way upon database name. In normal (non-recovery) mode, if you issue DROP USER or 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 behavior applies in recovery also, so a DROP USER on the primary does not disconnect that user on the standby. The cumulative statistics system is active during recovery. All scans, reads, blocks, index usage, etc., will be recorded normally on the standby. However, WAL replay will not increment relation and database specific counters. I.e. replay will not increment pg_stat_all_tables columns (like n_tup_ins), nor will reads or writes performed by the startup process be tracked in the pg_statio views, nor will associated pg_stat_database columns be incremented. Autovacuum is not active during recovery. It will start normally at the end of recovery. The checkpointer process and the background writer process are active during recovery. The checkpointer process will perform restartpoints (similar to checkpoints on the primary) and the background writer process will perform normal block cleaning activities. This can include updates of the hint bit information stored on the standby server. The CHECKPOINT command is accepted during recovery, though it performs a restartpoint rather than a new checkpoint. Various parameters have been mentioned above in and . On the primary, the parameter can be used. and have no effect if set on the primary. On the standby, parameters , and can be used. There are several limitations of hot standby. These can and probably will be fixed in future releases: Full knowledge of running transactions is required before snapshots can be taken. Transactions that 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 the server log. Valid starting points for standby queries are generated at each checkpoint on the primary. If the standby is shut down while the primary is in a shutdown state, it might 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 situation isn't a problem in the most common situations where it might happen. Generally, if the primary is shut down and not available anymore, that's likely due to a serious failure that requires the standby being converted to operate as the new primary anyway. And in situations where the primary is being intentionally taken down, coordinating to make sure the standby becomes the new primary smoothly is also standard procedure. 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, you are advised to select a larger value of max_locks_per_transaction, perhaps as much as twice the value of the parameter on the primary server. You need not consider this at all if your setting of max_prepared_transactions is 0. The Serializable transaction isolation level is not yet available in hot standby. (See and for details.) An attempt to set a transaction to the serializable isolation level in hot standby mode will generate an error.