Here is my first draft of a new replication section for our documentation. I am looking for any comments.
--------------------------------------------------------------------------- Replication =========== Database replication allows multiple computers to work together, making them appear as a single computer to user applications. This might involve allowing a backup server to take over if the primary server fails, or it might involve allowing several computers to work together at the same time. It would be ideal if database servers could be combined seamlessly. Web servers serving static web pages can be combined quite easily by merely load-balancing web requests to multiple machines. In fact, most read-only servers can be combined relatively easily. 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 has to be placed on each each server only once, a write to any server has to be seen by all other servers so that future read requests to those servers return consistent results. This "sync problem" is the fundamental difficulty of doing database replication. Because there is no single solution that limits the impact of the sync problem for all workloads, there are multiple replication solutions. Each solution addresses the sync problem in a different way, and minimizes its impact for a specific workload. This section first outlines two important replication capabilities, and then outlines various replication solutions. Sychronous vs. Asynchronous Replication --------------------------------------- The term sychronous replication means that a query is not considered committed unless all servers have access to the committed records. In that case, a failover to a backup server will lose no data records. Asynchronous replication has a small delay between the time of commit and its propogation to backup servers, opening the possibility that some transactions might be lost in a switch to a backup server. Asynchronous is used when sychronous replication would be too slow. Full vs. Partial Replication ---------------------------- The term full replication means only a full database cluster can be replicated, while partial replication means more fine-grained control over replicated objects is possible. Shared Disk Failover -------------------- This replication solution avoids the sync problem by having only one copy of the database. This is possible because a single disk array is shared by multiple servers. If the main database server fails, the backup server is able to mount and start the database as though it was restarting after a database crash. This shared hardware functionality is common in network storage devices. This allows sychronous, full replication. Warm Standby Using Point-In-Time Recovery ----------------------------------------- A warm standby server (add doc xref) can be kept current by reading a stream of WAL records. If the main server fails, the warm standby contains almost all of the data as the main server, and can be used as the new database server. This allows asychronous, full replication. Point-In-Time Recovery [Asychronous, Full] ---------------------- A Point-In-Time Recovery is the same as a Warm Standby server except that the standby server must go though a full restore and archive recovery operation, delaying how quickly it can be used as the main database server. This allows asychronous, full replication. Continuously Running Failover Server ------------------------------------ A continuously running failover server allows the backup server to answer read-only queries while the master server is running. It receives a continuous stream of write activity from the master server. Because the failover server can be used for read-only database requests, it is ideal for data warehouse queries. Slony offers this as asychronous, partial replication. Data Partitioning ----------------- Data partitioning partitions the database into data sets. To achieve replication, each data set can only be modified by one server. For example, data can be partitioned by main office, e.g. London and Paris. While London and Paris servers have all data records, only London can modify London records, and Paris can only modify Paris records. Such partitioning is usually accomplished in application code, though rules and triggers can help enforce such partitioning and keep the read-only data sets current. Slony can also be used in such a setup. While Slony replicates only entire tables, London and Paris can be placed in separate tables, and inheritance can be used to pull from both tables at the same time. Query Broadcast Replication --------------------------- This involves sending write queries to multiple servers. Read-only queries can be sent to a single server because there is no need for all servers to process it. This can be complex to setup because functions like random() and CURRENT_TIMESTAMP will have different values on different servers, and sequences should be consistent across servers. Pgpool implements this type of replication. Multi-Master Replication ------------------------ In multi-master replication, each server can accept write requests, and these write requests are broadcast to all other servers before the transaction commits. Under heavy load, this type of replication can cause excessive locking and performance degradation. It is implemented by Oracle in their RAC product. PostgreSQL does not offer this type of replication, though PostgreSQL two-phase commit can be used to implement this in application code. Performance ----------- Performance must be considered in any repliacation choice. There is usually a tradeoff between functionality and performance. For example, full sychronousreplication over a slow network might cut performance by more than half, while asynchronous replication might have a minimal performance imact. -- Bruce Momjian [EMAIL PROTECTED] EnterpriseDB http://www.enterprisedb.com + If your life is a hard drive, Christ can be your backup. + ---------------------------(end of broadcast)--------------------------- TIP 9: In versions below 8.0, the planner will ignore your desire to choose an index scan if your joining column's datatypes do not match
