PostgreSQL Cluster Guide 101: Easy Set-Up and How to Deploy for High Availability
A PostgreSQL cluster can be thought of as a collection of databases with their configurations. For example, you have a cluster with two databases that utilize Postgres v9, and all databases use the same cluster settings, such as buffer size, number of connections allowed, connection pool size, and so on. Similarly, you can create a cluster that runs on Postgres 12 and can contain many databases. Multiple clusters with the same version but different configurations are also possible.
Table of Contents
This article dives into topics like PostgreSQL, High Availability, and Clusters. You will learn the steps to set up a PostgreSQL cluster and the multiple options available to create a high availability environment in PostgreSQL.
Table of Contents
- What is PostgreSQL?
- What is High Availability?
- What is Clustering?
- What are PostgreSQL Clusters?
- Steps for Setting Up a Basic PostgreSQL Cluster
- Clustering Options to Create High Availability Environment in PostgreSQL
- Monitoring PostgreSQL Database Cluster Performance
What is PostgreSQL?
PostgreSQL is an Open-source Relational Database System. Relational (SQL) and Non-relational (JSON) querying are both supported by PostgreSQL. Many web applications and mobile applications, use PostgreSQL as their primary database.
Here are some of the common use cases of PostgreSQL:
- A robust database in the LAPP (Linux, Apache, PostgreSQL, and PHP) stack. PostgreSQL is generally utilized as a powerful back-end database that underpins a wide range of dynamic websites and web applications.
- Geospatial database.
- General-purpose transaction database.
Key Features of PostgreSQL
- User-Defined Datatypes: PostgreSQL can be used to create user-defined data types. It must have an input and output function.
- Sophisticated Locking Mechanism: It has three mechanisms of locking i.e. row-level, table-level, and advisory locks.
- Table Inheritance: PostgreSQL lets you create child tables based on another table.
- Foreign Key Referential Integrity: It specifies that the foreign key values correspond to actual primary key values in another table.
- Nested Transactions (Savepoints): It means that the result of a subquery isn’t rolled back when its parent query is rolled back. But with savepoints, if the top-level transaction is rolled back, all the savepoints are also rolled back.
What is High Availability?
This article presents several designs for PostgreSQL deployments on Google Cloud that enable high availability (HA). The measure of system durability in the face of underlying infrastructure failure is known as HA.
The Data Persistence layer (the data tier) must be accessible to correctly handle requests for data queries or modifications whenever a system or application requires a permanent state to process requests or transactions. The data tier is unavailable, preventing the system or application from completing its functions.
What is Clustering?
Clustering is the process of splitting a set of data into many groups so that data points in the same group are more similar than data points in other groups. The motive is to separate the groups with similar characteristics and assign them to clusters.
For example, you are the owner of a rental store and want to learn more about your customers’ preferences to expand your business. Is it possible for you to examine each customer’s details and design a unique business plan for each? Certainly not. However, you can group all of your customers into, say, ten groups depending on their purchase behavior, and employ a different method for each of these ten groups. This is referred to as Clustering.
Clustering can be categorized into two categories in general:
- Hard Clustering: In hard clustering, each data point is either totally or partially associated with a cluster.
- Soft Clustering: Instead of assigning each data point to a separate cluster, soft clustering assigns a chance or likelihood of that data point being in those clusters.
What are PostgreSQL Clusters?
The term “cluster” in PostgreSQL refers to a “cluster” of databases, as opposed to the more common notion of a collection of servers or virtual machines operating together. The term “cluster” in PostgreSQL is a historical quirk, and it has nothing to do with the common definition of “compute cluster,” which often refers to groups of machines that collaborate to improve speed and/or availability. It also has nothing to do with the PostgreSQL CLUSTER command, which is used to organize tables. A cluster is made up of two elements:
- The Data Directory: contains a collection of files created and maintained by Postgres tools and processes. Databases, Tables, and all other logical entities with which you interact are stored in these files.
- Postgres: which is the master process. It controls the files in this directory and provides interfaces for manipulating their contents.
Using PostgreSQL clusters turns out to be extremely handy in some cases, such as establishing test fixtures for automated tests, bringing up a temporary database without disrupting any existing Postgres configuration, running multiple versions of Postgres at the same time, and so on.
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Steps for Setting Up a Basic PostgreSQL Cluster
All of a cluster’s data, including its configuration, can be kept entirely within the data directory. When you use Postgres tools to build a data directory, it is initially self-contained. Stopping the Postgres process and copying this directory creates a complete backup of the cluster’s data. The entire directory can be moved and will continue to function normally.
The steps for setting up a PostgreSQL cluster are given below. These work only in Ubuntu.
PostgreSQL Cluster Set-Up: Creating a New PostgreSQL Cluster
- To create a new PostgreSQL cluster, use the following command:
initdb -D /usr/local/pgsql/data
- This builds a new database and a data directory in the specified location. This directory must be created by a user who has the authority to do so. Also, default configurations would be created, which are normally stored in /var/lib/postgresql/version/clusterName.
- To connect to a PostgreSQL cluster, you can use the following command:
psql -U Postgres -p 5436 -h localhost
- Each PostgreSQL cluster has its unique port number, so you have to use the correct port number while typing in the command.
- To create a new database, use the above command and then use the one below:
CREATE DATABASE mynewdb;
PostgreSQL Cluster Set-Up: Start a Server for a Cluster
- To start a server, use the following command:
pg_ctlcluster 12 main start
- In the above code main is the name of the PostgreSQL cluster used and 12 is the Postgres version being used.
PostgreSQL Cluster Set-Up: Stop the Server for a Cluster
- To stop the PostgreSQL cluster, use the following command:
pg_ctlcluster 12 main stop
- Similarly, to check the status of the PostgreSQL Cluster, you can use this:
pg_ctlcluster 12 main status
PostgreSQL Cluster Set-Up: Reload or Restart the Server for the Cluster
- To reload or restart the server for the PostgreSQL Cluster, use the following command:
pg_ctlcluster 12 main restart/reload
- Restarting it stops the server if it is running and starts it and Reloading it Causes the configuration files to be re-read without a full shutdown of the server.
Clustering Options to Create High Availability Environment in PostgreSQL
A Cluster is a collection of hosts that work together and are viewed as a single entity. By adding servers, you can obtain horizontal scalability and the ability to process more work. It can withstand a node failure and continue to operate transparently.
Depending on what is exchanged, there are two models:
Here are some of the clustering options offered in PostgreSQL:
Atsushi Mitani and the PGCluster developer’s team created PGCluster, a PostgreSQL multi-master and synchronous replication solution based on shared-nothing architecture. The main benefit of PgCluster is that it prevents data loss and the system from shutting down. Because all nodes are synchronous, any machine in a 6-server arrangement can go down without losing data. It’s supposed to provide some read scaling as well, but it doesn’t for most people looking for a PostgreSQL Cluster.
- High Availability: During failover, auto-recovery, dynamic add and upgrade server, and so on, the service is not interrupted. Also, there isn’t a single point of failure. Data transfer speed is automatically adjusted depending on network bandwidth. Servers for load balancing and monitoring are included.
- Synchronous multi‐master configuration: Any change to one master is immediately apparent to all other masters. There has been no change in the way transactions are handled. On top of this, the now() and random() values are duplicated.
- Based on PostgreSQL: PgCluster is one of the crucial clustering options that is based on PostgreSQL.
- Apps have the same API as PostgreSQL: PgCluster’s apps have the same API as PostgreSQL which makes it so compatible with it to begin with.
It’s a piece of software that connects PostgreSQL servers to PostgreSQL database clients. Pgpool-II communicates with both the backend and frontend of PostgreSQL and relays a connection between them. As a result, a database application (frontend) considers Pgpool-II to be the PostgreSQL server, while the server (backend) considers Pgpool-II to be one of its clients. Because Pgpool-II is transparent to both the server and the client, an existing database application can be utilized with it nearly without modifying its sources.
- Replication of the connection pool.
- Load balancing.
- Failover occurs automatically.
- Queries that run in parallel.
- It can be used in conjunction with streaming replication.
A multi-DBMS, asynchronous, multi-master, multiplatform replication solution. It does not support DDL, users, or grants because of triggers. Its primary goal is to make use and management as simple as possible.
- Configuration is simple.
- Installation is simple.
- Platform and table design are not dependent on each other.
Asynchronous row-based cascading master-slave replication with triggers and database queueing, as well as asynchronous master-master replication with triggers and configurable conflict resolution.
Bucardo requires a dedicated database and runs as a Perl daemon that communicates with it as well as any other databases in the replication process. It has two modes of operation: Multimaster and multi slave.
- Load balancing.
- Slaves are not bound by any rules.
- Replication in parts.
- On-demand replication.
- Slaves can be “pre-warmed” to save time during setup.
Postgres-XC is an open-source project that aims to provide a PostgreSQL cluster solution that is write-scalable, synchronous, symmetric, and transparent. It’s a set of tightly coupled database components that can be installed on several machines (physical or virtual).
The term “write-scalable” refers to the ability to scale up When opposed to a single database server, Postgres-XC can be configured with as many database servers as you wish and handle considerably more writes (updating SQL statements).
- Postgres-XC can be set up to run on several servers.
- Your data is kept in a distributed manner, i.e., partitioned or replicated, depending on the option you select for each table.
- When you run queries, Postgres-XC determines where the desired data is stored and sends queries to the servers that contain the data.
Citus is a PostgreSQL substitute that includes high-availability features like auto-sharding and replication. Citus partitions your database and replicate multiple copies of each shard among commodity machines in a cluster. It seamlessly sends any writes or queries to one of the other nodes, which houses a replica of the impacted shard, if any node in the cluster becomes unavailable.
- Sharding logic is done automatically.
- Replication is built-in.
- Replication that is aware of the data center for disaster recovery.
- Fault tolerance in the middle of a query with advanced load balancing.
You can improve the uptime of your PostgreSQL-powered real-time applications and reduce the impact of hardware failures on performance. This can be accomplished using built-in high availability tools, which reduce the need for costly and error-prone manual intervention.
It is a shared-nothing, Multimaster clustering system that can transparently distribute a table across a collection of nodes and execute queries on those nodes in parallel. It also contains a Global Transaction Manager (GTM) component that provides a globally consistent view of the cluster. The project is based on the PostgreSQL 9.5 version. Commercial support is provided by some companies, such as 2nd Quadrant.
They can handle a wide range of databases like:
- OLTP workloads that need a lot of writing.
- Business Intelligence that requires MPP parallelism.
- An operational data store is available.
- A key-value store is also available.
- Mixed-workload scenarios.
- Multi-tenant environments.
Monitoring PostgreSQL Database Cluster Performance
In PostgreSQL, there are two forms of monitoring:
- System Resource Monitoring: Examines the infrastructure on which PostgreSQL is installed, revealing information such as CPU and memory use.
- Database Monitoring: Ensures that your database is in good shape and performing at its best.
Here are a few tools you can use to monitor PostgreSQL Database Cluster Performance:
- Prometheus and Grafana
- Datadog APM
There are many more products to create a high availability environment for PostgreSQL. But you need to consider your infrastructure. If you only have one application server, no matter how well the databases are configured for high availability, you will be inaccessible if the application server dies. You must thoroughly investigate the infrastructure’s single points of failure and attempt to resolve them.
You have learned how to set up clusters in PostgreSQL and how to optimize them for high availability. You also read how to manage these and monitor the cluster performance.
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