Tuning PostgreSQL for High Write Workloads
David Wein is a Principal Software Engineer at Amazon Web Services where he works on RDS - Amazon’s Relational Database Service. David’s primary focus at AWS has been the development of Amazon Aurora PostgreSQL-compatible Edition. Prior to AWS, David was a Development Architect at SAP where he implemented persistence and recovery in the HANA in-memory database engine. David came to SAP from Sybase where he was a lead engineer on the Adaptive Server Enterprise database kernel and the in-memory store of Sybase IQ. He earned an M.S. in Interdisciplinary Telecommunications from the College of Engineering and Applied Science at the University of Colorado at Boulder.
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In this session we will cover a number of the way that you can tune PostgreSQL to better handle high write workloads. We will cover both application and database tuning methods as each type can have substantial benefits but can also interact in unexpected ways when you are operating at scale. On the application side we will look at write batching, use of GUID's, general index structure, the cost of additional indexes and impact of working set size. For the database we will see how wal compression, auto vacuum and checkpoint settings as well as a number of other configuration parameters can greatly affect the write performance of your database and application.
- 2017 November 14 16:40 UTC
- 50 min
- PGConf Local: Seattle [PgConf.US]