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.

A modern database should be capable of storing big values. Storing itself is not a big deal, however, operations with big values or fields are a non-trivial task. PostgreSQL has several options for storing big values, but none of them is perfect. How do we respond to this challenge? Our presentation answers this question, let's see how to store big and complex values in Postgres properly, and how operate with them.

The more tables are involved with the query, the more difficult it is for the scheduler to choose a suitable execution plan (both time and memory usage increase). How can we "tell" the planner that it is better to connect this pair of tables first, and the rest can be connected later? What if we see that a part of our query can be improved, but the optimizer does not do this. In my presentation, I will talk about managing the order of connections. I will explain how we can influence the formation of a query plan using the standard "vanilla" PostgreSQL methods.

The plv8 extension is very underestimated, though it can help simplify development for a variety of tasks. It's been a year since we started using this extension in our projects. The main reason for its low popularity is the complexity of building. Moreover, building plv8 requires a lot of traffic and disc space for temporary files. That's why we decided to build plv8 and provide ready-made binaries freely to anyone interested, not just as an offering for our customers. First, we made the binaries available on GitHub. Then we created a Docker image for Postgres with pre-installed plv8 based on Debian. It looked too heavy to us, and we decided to check Alpine, however, building it for Alpine appeared to be more complicated than we expected. I'll explain what difficulties we faced and how we managed to overcome them. I will also list the tasks that can be solved with plv8 and provide advice on how to make the development process more convenient. I will also share the links to our Docker images for the latest Postgres 13 and Postgres 14 releases, that are compact and can be used for any types of tasks.