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PostgreSQL 10 High Performance

PostgreSQL 10 High Performance

By : Enrico Pirozzi
2.5 (2)
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PostgreSQL 10 High Performance

PostgreSQL 10 High Performance

2.5 (2)
By: Enrico Pirozzi

Overview of this book

PostgreSQL database servers have a common set of problems that they encounter as their usage gets heavier and requirements get more demanding. Peek into the future of your PostgreSQL 10 database's problems today. Know the warning signs to look for and how to avoid the most common issues before they even happen. Surprisingly, most PostgreSQL database applications evolve in the same way—choose the right hardware, tune the operating system and server memory use, optimize queries against the database and CPUs with the right indexes, and monitor every layer, from hardware to queries, using tools from inside and outside PostgreSQL. Also, using monitoring insight, PostgreSQL database applications continuously rework the design and configuration. On reaching the limits of a single server, they break things up; connection pooling, caching, partitioning, replication, and parallel queries can all help handle increasing database workloads. By the end of this book, you will have all the knowledge you need to design, run, and manage your PostgreSQL solution while ensuring high performance and high availability
Table of Contents (18 chapters)
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Processing nodes

Once you have a set of rows, the next type of node you'll encounter when using a single table are ones that process that set in various ways. These nodes typically take in a row set and output a different row set, of either the same size or smaller (perhaps only a single value).

Sort

Sort nodes can appear when you insert ORDER BY statements into your queries:

EXPLAIN ANALYZE SELECT customerid FROM customers ORDER BY zip;
QUERY PLAN
----------
Sort (cost=2104.77..2154.77 rows=20000 width=8) (actual time=162.796..199.971 rows=20000 loops=1)
    Sort Key: zip
    Sort Method:  external sort  Disk: 352kB
    ->  Seq Scan on customers  (cost=0.00..676.00 rows=20000 width=8) (actual time=0.013..46.748 rows...

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