PgConf.Russia 2016

Challenges and solutions found in documents dematerialization and bank cheque processing system used in the Bank of Brazil.

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.

Heroku Postgres is a cloud database service and the largest provider of PostgreSQL as a service anywhere. We operate more than 1,000,000 PostgreSQL databases with a team of about 10 people. We may be the most efficient DBAs in history, with approximately 100,000 databases per person on our team! This talk will introduce the opportunity and challenges of building and operating a cloud database service, as well as discussing the strategies we use to build, operate, and scale this product and team for the last six years now. We will include details about * a brief introduction to the service to provide context * strategies to design and build such a data service * operational war stories like how to recover from losing thousands of servers at once, * common challenges users have with Postgres * and a basic overview of the technical architecture

This is a complementary talk to Will Leinweber's talk, which will go into much more depth on the architecture of the software we have written.

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