postgresql replication

Label:Basic Environment Description: 9.3 PostgreSQL version:9.3. 6 Master:192.168. 56.101 Standby:192.168. 56.102 Installation process slightly, based on pkg package 1. Configure the Master side # psql-u pgsql-d postgres-c"CREATE USER Rep REPLICATION LOGIN ENCRYPTED PASSWORD ' PASSWORD ';" # cd/usr/local/pgsql # vim data/postgresql.conf listen_addresses='*'Wal_level='Hot_standby'max_wal_senders=1# Vim da

: There are various types of xlog records (for example, Heap,btree,clog,storage,gin, and Standby records, just to name a few).Xlog Records Backward links. This way, each entry points to the previous entry in the file. In this way, we can fully believe that we have found the end of the record as long as we want to point to the pointer to the previous entry.make XLOG with certaintyAs you can see, a change could trigger many xlog entries. This is true for all kinds of statements, such as a large DE

Label:4.4 Stream-based and file-based recoveryLife is not always black or white; sometimes there are some shades of gray. For some scenarios, stream replication may be just right. In other cases, file-based replication and PITR are what you need. However, there are also many cases where you need both stream replication and file-based

So far, we have processed file-based replication (or log shipping) and simple stream-based replication settings. In both cases, after the transaction is committed on master, the data is submitted and received by slave. It will still be lost at the time that master commits and slave actually receives the data completely.In this chapter, we will study the following topics:• Ensure that no transactions are los

recovery (pitr,point-in-time-recovery). ] In this scenario, stream replication will resolve your issue. With stream replication, the latency of replication will be minimal and you can enjoy some extra level of protection for your data. Let's talk about the overall architecture of the PostgreSQL streaming infrastructur

2.4 Adjusting checkpoints and xlogSo far, this chapter has provided insight into how PostgreSQL writes data, in general, what Xlog is used for. Given this knowledge, we can now continue and learn what we can do to make our databases work more efficiently in both replication and single-server operations.2.4.1 Understanding CheckpointsIn this chapter, we have seen that it has been written to Xlog before the d

Label:2.2 Xlog and ReplicationIn this chapter, you have learned that the transaction log for PostgreSQL has made all changes to the database. The transaction log itself is packaged as an easy-to-use 16MB segment.The idea of using this change set to replicate data is not farfetched. In fact, this is a logical step in the development of each relational (or even non-relational) database system. Other parts of the book, you will see in many ways how the

Label:PostgreSQL replication Series translated from PostgreSQL replication book In this chapter, you'll look at different replication concepts, and you'll see which types of replication are most appropriate for which practical scenarios. At the end of this chapter, you will

to • It is supported by many frameworks • It can be combined with a variety of other replication methods • It can support PostgreSQL very well (e.g. using pl/proxy) Light and shadow tend to go together, so fragmentation has its shortcomings, as follows: • Adding servers to a running cluster is cumbersome (depending on the type of partition function) • Your flexibility may be severely reduced. • Not all typ

4.7 Conflict ManagementIn PostgreSQL, stream replication data flows in only one direction. Xlog is provided by master to several slave that consume transaction logs and provide you with a better backup of your data. You may wonder how this can lead to a conflict, which can occur.Consider the situation: as you know, there is a small delay in data replication. Ther

replication and have shown how data is replicated synchronously. We also described how to change the durability requirements by modifying the operating parameters of PostgreSQL. PostgreSQL gives the user the choice of how to replicate the transaction, and the level of durability required for a particular transactional replication.In the next chapter, we'll drill

script will be executed at each restart point. So what is the beginning of the heavy? Each time PostgreSQL transitions from file-based replay to stream-based replay, you are facing a heavy starting point. In fact, starting a stream copy again is considered to be a boot point.Once the start point arrives, you can have PostgreSQL perform some cleanup (or anything else). It is easy to clean out old xlog or tr

Postgresql fatal error: Reserved connection locations are reserved for Super Users who execute non-replication requests, and postgresql Super Users Recently, database monitoring of the monitoring system is always delayed. An error is reported when you view the log: 10:20:19, 534 ERROR Traceback (most recent call last): File "oracle_mon.py", line 306, in Check t

will wait for a file/tmp/start_me_up.txt to make the condition set. The content of this file is completely irrelevant; PostgreSQL simply checks to see if the file exists and, if so, stops the recovery and converts itself to master.Creating an empty file is fairly straightforward work:imac:slavehs$ Touch/tmp/start_me_up.txtThe database system will respond to the new file Start_me_up.txtFatal:terminating Walreceiver proced Fire up:Log:trigger file foun

wal_keep_segments heavily. The idea of this postgresql.conf setup is to keep master in more Xlog files than is theoretically needed. If you set the variable to 1000, it means that master will keep the xlog above 16GB. In other words, your slave can disappear 16GB compared to normal (convert to master). This greatly increases the slave's advantage of joining a cluster without having to fully synchronize itself from the beginning. For a 500MB database this is not worth mentioning, but if your set

few milliseconds) or very long (minutes, hours, days). One important fact is that the data may be lost. A small lag is less likely to be a data loss, but any lag greater than 0 can easily lead to data loss.If you want to make sure that data is never lost, you must switch to synchronous replication. As you have seen in this section, a synchronous transaction is synchronous because it is valid if the thing is committed to two servers.Consider performan

Label:What is the latency between the PostgreSQL database stream replication master and standby and should be evaluated for both HA and load balancing. A simple HA architecture, for example, is how much time we allow for data loss in the event of a failure of the main library. No nonsense, go directly into this experiment test. Test environment:Main Library: Memory: 32g,cpu:8 Core, ip:192.168.122.101 Standb

Use pg_basebackup to build a PostgreSQL stream replication Environment This article introduces the high availability of PostgreSQL. Here we will first conduct a stream replication experiment. Environment:OS: [Ha @ node0 ~] $ Uname-Linux node0 2.6.32-358. el6.x86 _ 64 #1 SMP Fri Feb 22 00:31:26 UTC 2013 x86_64 x86_64 x8