PGConf.Russia 2018

Last year we announced Skala-SR / Postgres Pro database machine with a hardware and software support for remote direct memory access (RDMA) as a key feature. The first appliances have been already installed at customer sites, and even with the first version customers got some constructions, that were impossible without RDMA and CPU offload (got with Mellanox networking). However, capabilities of this equipment are much wider, and this talk is dedicated to current works and prospective developments for this topic.

Lately, the PostgreSQL is more widely being used for Enterprise. Our company, Ingram Micro Cloud, is one of the first companies that did it. We have been using PostgreSQL for many years as the main DBMS for our products. In our report, we want to tell about the evolution of our High Availability (HA) PostgreSQL cluster. We will tell about how quickly we implemented the solution using pgpool-II, wrote failover scripts, tested Postgres-XL, and came up with unusual configurations of Stolon. We will also cover the problems of load balancing, pooling connections, and backups.

PostGIS is a spatial extension to PostgreSQL that enables spatial datatypes, access methods and a set of functions to perform geometric operations on them.

Typically PostGIS is used to select a small subset of a big static dataset. In this talk I'll cover issues that arise when working with big dynamic data flows, and ways to resolve them, on examples that we've met developing Juno ride sharing service backend.

Avito is the biggest classified site of Russia, and the third largest classified site in the world (after Craigslist of USA and 58.com of China). In Avito, ads are stored in PostgreSQL databases. At the same time, for many years already the logical replication is actively used. With its help, the following issues are successfully solved: the growth of data volume and growth of number of requests to it, the scaling and distribution of the load, the delivery of data to the DWH and the search subsystems, inter-base and internetwork data synchronization etc. But nothing happens "for free" - at the output we have a complex distributed system. Hardware failures can happen - it is natural - you need to be always ready for it. There is plenty of samples of logical replication configuration and lots of success stories about using it. But with all this documentation there is nothing about samples of the recovery after crashes and data corruptions, moreover there are no ready-made tools for it. Over the years of constantly using PgQ replication, we have gained extensive experience, rethought a lot, implemented our own add-ins and extensions to restore and synchronize data after crashes in distributed data processing systems. In this report, we would like to show how our experience can be shifted to a new logical replication subsystem in 10th version of PostgreSQL. In the current implementation, these are only non-trivial solutions - there is a number of issues for the community, that come down to implementing simple recovery mechanisms - as simple as configuring the replication in 10th version.