![Alex Chistyakov Alex Chistyakov](/media//2016/01/18/AleksandrChistyakov.jpg.180x180.jpg)
Stainless steel elephant: PostgreSQL performance testing continued
We 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.
Слайды
Видео
Другие доклады
-
DDmitry Melnik ИСП РАН
Speeding up query execution in PostgreSQL using LLVM JIT compiler
Currently, PostgreSQL uses the interpreter to execute SQL-queries. This yields an overhead caused by indirect calls to handler functions and runtime checks, which could be avoided if the query were compiled into the native code "on-the-fly" (i.e. JIT-compiled): at a run time the specific table structure is known as well as data types used in the query. This is especially important for complex queries, which performance is CPU-bound. At the moment there are two major projects that implement JIT-compilation in PostgreSQL: a commercial database Vitesse DB and an open-source project PGStorm. The former uses LLVM JIT to achieve up to 8x speedup on selected TPC-H benchmarks, while the latter JIT-compiles the query using CUDA and executes it on GPU, which allows to speed up execution of specific query types by an order.
Our work is dedicated to adding support for SQL query JIT-compilation to PostgreSQL using LLVM compiler infrastructure. In the presentation we'll discuss how JIT-compilation can be used to speed up various stages of query execution in PostgreSQL, and the specifics of translating an SQL query into LLVM bitcode to achieve good performing native code. Also we'll present preliminary results for our JIT-compiler on TPC-H benchmark.
-
Oleg Ivanov Postgres Professional
Machine learning for better query planning
In the speech we consider the current PostgreSQL planner model, then the possibilities of applying machine learning methods for planner improvement and the obtained results.
-
Jean-Paul Argudo Dalibo
Migration to PostgreSQL : reasons... and consequences
The talk will be articulated around all the traditional arguments to "how chose PostgreSQL over other choices in the database domain"... But also, and that's quite new in the comunity, what are the consequences of this choice. Because the PostgreSQL adoption brings adoption of other things like Linux, but also, Open Source thinking, the fast pace of PostgreSQL will command new methods of validation the company must adapt to... etc.
-
Mikhail Tyurin Avito
My Five Slides About Postgres
My experience of working with PostgreSQL has provided clear understanding of its main advantages, making us choose and recommend choosing it.
1. Beginning
2. Documentation
3. Community
4.1 Transactional DDL
4.2 WAL and True Physical Replication
4.3 Transactional Snapshot and True Logical Replication and PGQ
4.4 Exciting extensibility
5. Success