Category: Partitioning

Umair Shahid continues a series on migrating from Oracle to PostgreSQL:

Table partitioning is a database design technique that divides a large table into smaller, more manageable sub-tables called partitions. Each partition holds a subset of the data based on specific criteria, such as date ranges, categories, or hash values. While partitioning makes it seem like you’re working with a single large table, behind the scenes, queries and operations are distributed across multiple partitions.

Read on to understand the differences between the two platforms. In this case, there are some pretty significant differences.

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Lee Asher talks partitions:

Partitioning in PostgreSQL was for many years a feature almost entirely ignored, and even today is often thought of only as a means to increase performance on large tables. While it’s certainly useful for this, it’s also an invaluable tool for solving common data maintenance problems. In this article, we’ll examine the feature from this perspective.

Let’s consider a common situation: a table continually ingesting time series data ordered chronologically: purchase orders, forum posts, time-series data, whatever. Most systems contain more than one table like this. And because we live in a world of Big Data, these tables can contain hundreds of millions, even billions of rows. Business rules require the data to remain active for some fixed period of time, then be deleted, (or archived first, then deleted). Commonly this is a monthly process: every month copy data that has “aged out” to another location, then delete the rows from the live table.

It’s interesting that people consider partitioning a performance-improving technique in the PostgreSQL world, but in the SQL Server world, partitioning is primarily for ease of maintenance and we warn against thinking about it as a performance-improving technique.

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Semab Tariq shows how to perform three types of partitioning in PostgreSQL:

PostgreSQL is renowned for its exceptional performance in managing data. One of its standout features is partitioning, a technique that divides large datasets into smaller, more manageable segments. Partitioning provides several benefits, including improved query performance, streamlined data management, and enhanced scalability. By organizing data into partitions, PostgreSQL can execute searches more efficiently and handle tasks with greater ease. 

In this blog, we will delve into the details of partitioning in PostgreSQL, exploring its various types, advantages, and drawbacks. We’ll uncover how partitioning can revolutionize data management and decision-making processes in database environments.

Click through for demonstrations of range, list, and hash partitioning.

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Andrea Allred has a script for us:

I recently needed to know which tables in my database were partitioned. I tried a bunch of queries and some got incredibly complex. I finally found one that I like:

Click through for the script and for the assumption Andrea makes (which is a reasonable one).

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