Postrelease
Talks
Talks archive
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Marco Slot Citus DataCitusDB 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.
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Heikki Linnakangas Pivotal LtdPostgreSQL includes several index types: GiST, SP-GiST, GIN, and of course, the regular B-tree. DBAs are familiar with using each of these for specific use cases, GIN for full-text search, GiST for geometrical data, and so on, but how do they work internally? What makes them suitable for the cases they're typically used for?
In this presentation, I will walk through the internal structure of each of these index types, explaining what strengths and weaknesses each one of them have.
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Alexander Krizhanovsky NatSys LabWe'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.
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Alex Chistyakov Git in SkyWe love to stress test software, since we are a performance engineering company. Our friends from a hosting company servers.com provided us with a modern dedicated server so we immediately started to test PostgreSQL in different environments, including SmartOS, DragonFly and Windows. We would like to present our results (and all the gory details) to community.
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