PGConf.Russia 2022

Every DBMS stores its data on a hard disc, so you may face a situation when your data on disc gets corrupted. This can happen due to a controller failure, logical or physical data corruption; there are also other reasons. If it is just the index file that gets corrupted, the index recreation command will enable you to restore data consistency in your DBMS. If a table file or a file of a system section gets corrupted, data restore is impossible. In this case, you need to invent workarounds. You can try to restore this data from backup files, copy it from the corrupted table, or find another way to solve this problem. In this talk, we'll tackle several cases of data corruption on disc and describe the options for restoring the data from the corrupted tables.

I am going to explain a sorting method added in Postgres 14 that allows to create GiST index much faster. We'll also talk about the disadvantages of this sorting method discovered during implementation of its support in PostGIS and how it will be improved in the future. Also, new features and improvements included in PostGIS 3.2 will be reviewed.

As opposed to in-memory DBMSs, traditional disc database management systems have an inherent physical limitation. It's their storage system which is by several orders of magnitude slower than CPU operation memory, even in the case of All-Flash NVM. It becomes especially critical for the development of business analytics apps and OLAP scenarios on disc DBMS. We will consider a number how-tos for improving the performance of traditional DBMSs, and then offer a new storage-centric approach to hardware-based speed-up for disc DBMSs.

Logical decoding and replication slots introduced in PostgreSQL 9.4 (released in 2014) created a solid foundation for implementing built-in core logical replication in version 10 (released in 2017). Unfortunately, there are a few limitations that make logical replication not very useful in real-world scenarios. Logical decoding currently isn’t supported on the standby server, and PostgreSQL allows creating logical replication slots only on the primary server. Or in other words, logical slots are lost on failover/switchover.

Postgres hackers made many attempts to address the problem, and most of them resulted in not too much success. Although, there is one little function introduced in PostgreSQL 11 that made it possible to implement failover of logical replication slots externally.

In my talk I will tell a story of how Patroni solves the problem of logical replication slots failover without using invasive third-party extensions, dig down into some of the Postgres internals in order to prove why this approach is safe, and finally, we will discuss limitations and potential downsides of this solution.