By Hans-Jurgen Schonig
Leverage the ability of PostgreSQL replication to make your databases extra powerful, safe, scalable, and fast
About This Book
- Efficiently reflect PostgreSQL utilizing high-end options to guard your information and run your server with no interruptions
- Improve reliability, fault-tolerance, and accessibility by means of keeping consistency among redundant resources
- Get grips with the newest model of PostgreSQL with this example-based guide
Who This ebook Is For
This publication is perfect for PostgreSQL directors who are looking to manage and comprehend replication. through the top of the e-book, it is possible for you to to make your databases extra powerful and safe by means of attending to grips with PostgreSQL replication.
What you'll Learn
- Use Point-in-time restoration to accomplish facts restoration in addition to replication
- Set up synchronous in addition to asynchronous streaming replication
- Get familiarized with the transaction log, the center part of so much replication setups and its purpose
- Improve velocity and reliability with an figuring out of pgpool and PgBouncer
- Increase your info defense and geographically distribute data
- Make your platforms extra on hand and safe with Linux excessive Availability
- Scale out with PL/Proxy and Postgres-XC
- Detect, examine, and resolve replication-related problems
In Detail
PostgreSQL bargains a accomplished set of replication comparable positive aspects. Unleashing the facility of PostgreSQL will give you numerous possibilities and a aggressive virtue over different database systems.
This publication will advisor you thru crucial options of PostgreSQL replication. It comprises the entire details you must layout and function replicated setups.
Beginning via providing you with an realizing of replication strategies, the PostgreSQL transaction log, and Point-in-time restoration, we progressively circulate directly to developing asynchronous and synchronous replication. subsequent up, you are going to discover ways to display screen a PostgreSQL cluster setup, take care of tracking instruments, after which circulate directly to figuring out Linux excessive Availability. additional, we discover widely-used instruments reminiscent of Slony, SkyTools, Postgres-XC, and walbouncer, and arrange PL/Proxy.
Finally, you will get conversant in the hot expertise of BDR, which permits bidirectional replication in PostgreSQL.
Read or Download PostgreSQL Replication PDF
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Extra resources for PostgreSQL Replication
Sample text
The first distinction we can make is whether to replicate synchronously or asynchronously. What does this mean? Let's assume we have two servers and we want to replicate data from one server (the master) to the second server (the slave). The following diagram illustrates the concept of synchronous and asynchronous replication: We can use a simple transaction like the one shown in the following: BEGIN; INSERT INTO foo VALUES ('bar'); COMMIT; In the case of asynchronous replication, the data can be replicated after the transaction has been committed on the master.
How PostgreSQL writes data PostgreSQL replication is all about writing data. Therefore, the way PostgreSQL writes a chunk of data internally is highly relevant and directly connected to replication and replication concepts. In this section, we will dig into writes. [ 21 ] Understanding the PostgreSQL Transaction Log The PostgreSQL disk layout One of the first things we want to take a look at in this chapter is the PostgreSQL disk layout. Knowing about the disk layout can be very helpful when inspecting an existing setup, and it can be helpful when designing an efficient, high-performance installation.
This leaves us with the second option, which is storing data redundantly. Storing a set of data twice, or even more often, is not too uncommon, and it's actually a good way to approach the problem. The following diagram shows how this can be done: As you can see, we have two clusters in this scenario. When a query comes in, the system has to decide which data can be found on which node. For cases where the name is queried, we have (for the sake of simplicity) simply split the data into half alphabetically.