PgConf.Russia 2016

CitusDB is an extension for PostgreSQL that can distribute tables across a cluster of PostgreSQL servers. Data is stored in shards that can use append-partitioning for bulk-loading of time series data or hash-partitioning for real-time data ingestion. SELECT queries on distributed tables are transparently parallelised across the cluster, using all available cores. Distributed tables can also be joined in parallel, even if they are not partitioned along the same column. CitusDB is especially suitable for real-time analytics use-cases such as dashboards which require fast analytical queries over live data, and can simultaneously act as a scalable operational database. This talk will describe the internals of CitusDB and give a live demo of a large-scale CitusDB cluster.

More than 300.000 developers use technology platform "1C:Enterprise" as a main development tool. I'll tell you about architecture and features that made "1C:Enterprise" one of the most popular development environment in Russia and CIS and about growing popularity of PostgreSQL amongst 1C users.

We'll discuss how does Linux work with virtual memory. The following topics will be covered: * x86-64 page table, context switch and page fault; * internals of virtual memory management (VMM) in Linux; * page eviction methods in Linux, page cache and anonymous pages; * huge and gigantic pages, transparent huge pages; * how mmap(2) works and what madvise(2), msync(2) etc. provide; * why large databases don't use mmap(2), but rather implement buffer pool on their own; * ans surely how to tune Linux VMM using sysctl.

The talk describes performance benchmarking results of PostgreSQL on modern Hi-End servers. The main attention was paid to the locks for shared data access and associated bottlenecks. The testing propose was to test the linear read scalability limits with an increase of cores number allocated for PostgreSQL. Testing was performed for different postgres versions (9.4, 9.5, 9.6) to check new features designed to increase performance on multiprocessing architectures.