PgConf.Russia 2016

Whenever multiple users, processes, or threads are concurrently modifying data which is shared among them, problems can occur if race conditions are not handled somehow. These problems are particularly acute in a database which provide ACID semantics. A set of changes grouped into a database transaction must appear atomically, both to concurrent transactions and in terms of crash recovery. Each transaction must move the database from one consistent state (with regard to business rules) to another. For programming efficiency, each transaction must be able to be coded independently of what other transactions may happen to be running at the same time. In the event of a crash, all modifications made by transactions for which the application was notified of successful completion, and all modifications which had become visible to other transactions, must still be completed upon crash recovery. Over the years, various strategies have been employed to provide these guarantees, and sometimes the guarantees have been compromised in one way or another. This talk will cover the approaches taken to provide these guarantees or compromised variations of them, with an emphasis on the Serializable Snapshot Isolation (SSI) technique available in PostgreSQL (and so far not in any other production product). While SSI already performs faster and with higher concurrency than any other technique for managing race conditions with most common workloads, there are many opportunities for further enhancing performance, some of which would require the assistance of people expert in the various index access methods; these issues will be discussed. The talk will also present some rough ideas about how SSI techniques might be used with XTM in a distributed system.

Time will be reserved at the end of the talk for group discussion of optimizations and possible application in distributed environments.

The talk is about PostgreSQL clusters using streaming replication and pgpool-II, which are quite popular in Japan. Plus, the next version of pgpool-II will be released this winter, so the talk will be about what's new in the version.

Postgresql's buffer manager has parts where it's showing its age. We'll discuss how it currently works, what problems there are, and what attempts are in progress to rectify its weaknesses.

• Lookups in the buffer cache are expensive
• The buffer mapping table is organized as a hash table, which makes efficient implementations of prefetching, write coalescing, dropping of cache contents hard
• Relation extension scales badly
• Cache replacement is inefficient
• Cache replacement replaces the wrong buffers

Alibaba has provided a relational database service (RDS) for postgres in our public cloud platform (aliyun.com, the currently biggest public cloud in China). We are also enabling internal applications to use postgres in our other internet business and we can share our experience