PgConf.Russia 2019

In my talk I'll tell you about practices of working with Postgres in the Go-services. I’ll describe general advantages and disadvantages of the basic tools that are commonly used when working with Postgres using Go. Of course, we will touch on the nuances that need to be taken into account when your services are running inside the Kubernetes. I will also talk about Avito’s experience in providing a database of product’s developers. This presentation will be of interest to developers who want to avoid problems when working with Postgres, and will be useful to DBA who want to know what difficulties customers face in their database.

You just set up your first PostgreSQL cluster, created a database schema, loaded some data, did some fine tuning of configuration. Now you want to make your cluster highly available. Unfortunately, PostgreSQL doesn't offer built-in automatic failover, but luckily for us, there are plenty of external tools for that. As a next logical step you start choosing a tool, and... you already doing it wrong, because first you have to define SLA, RTO, and RPO. In this talk I am going to cover most of the common mistakes people do when setting up a highly available cluster.

One of the most soft after features of Postgres v10 is logical replication. In this presentation we will cover what Logical Replication is, how it compares to Binary (Streaming Replication), how Logical Replication works, configuring Logical Replication, Logical Replication limitations, gotchas, security and management. We will also discuss potential deployed architectures with Logical and Binary Replication and some neat features of the underlying technology.

At the end of this presentation an attendee with a reasonable understanding of how to manage Postgres will be able to configure Logical replication for use.

Many DBMS specialists do not like these three letters - ORM because they have repeatedly seen the enormous queries ORM-generated for simplest operations. However practice shows that the origin of the problem is not ORM itself but rather those developers who are not able to use ORM properly. In this report I will tell you the basic principles of how to write code for ORM which generates "good" queries and also show you "bad" code samples and what you get out of them. The main idea is we have to think in SQL-style when writing the code, and so to learn to foresee what kind of query will be generated. But even having mastered that you must always check the output SQL for complex queries. I will show an example when a slight change in ORM-logic increases the volume of output SQL by dozens of times(!). I will tell you about additional tools and tricks. Namely - disabling tracking, INCLUDE construction, alternative syntax for JOIN, how to get more data using a smaller number of queries, how to effectively write queries with grouping, and what do we need mappings for. I will not bypass the cases when it is not possible to effectively solve the problem by means of ORM (for example, queries with recursion). In addition to SELECT requests, there are some Batch-Update/Delete tools that allow you to update and delete data using ORM tools without downloading data to the client side. We'll also talk on how to force the ORM to insert large volumes of data quickly via Multi-Insert and COPY. I will also discuss how ORM supports PostgreSQL-specific data types i.g. arrays, hstore and jsonb. But does it make sense to use ORM at all, since there is so much to learn? Sure it does. There are advantages of using ORM, and we will discuss them as well. All examples are based on Entity Framework technology for .Net Core and .Net Framework in C#. There are some subtle differences in ORM usage in Hibernate/NHibernate, but the basic principles remain the same, so the report will be useful for developers using various technologies.