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PostgreSQL Development Essentials

You're reading from   PostgreSQL Development Essentials Advanced querying, data modeling and performance tuning

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Product type Paperback
Published in Sep 2016
Publisher Packt
ISBN-13 9781783989003
Length 210 pages
Edition 1st Edition
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Author (1):
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Baji Shaik Baji Shaik
Author Profile Icon Baji Shaik
Baji Shaik
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Toc

Table of Contents (12) Chapters Close

Preface 1. Advanced SQL FREE CHAPTER 2. Data Manipulation 3. Triggers 4. Understanding Database Design Concepts 5. Transactions and Locking 6. Indexes and Constraints 7. Table Partitioning 8. Query Tuning and Optimization 9. PostgreSQL Extensions and Large Object Support 10. Using PHP in PostgreSQL 11. Using Java in PostgreSQL

Bad query performance with stale statistics


Query performance always depends on the plan chosen by the Optimizer. Optimizer again depends on the statistics of corresponding relations to generate a plan for the query. If Postgres has stale statistics, the query might get bad plans irrespective of the existing datasets.

For example, consider we have the following two test tables on which we perform basic operations like the following:

CREATE TABLE out(t INTEGER);
CREATE TABLE inn(t INTEGER);
postgres=# SELECT COUNT(*) FROM out;
count 
-------
1000
(1 row)
postgres=# SELECT COUNT(*) FROM inn;
count 
-------
1000
(1 row)
postgres=# EXPLAIN ANALYZE SELECT * FROM out WHERE t IN(SELECT t  FROM inn);
                       QUERY PLAN
----------------------------------------------------------------               
Hash Semi Join  (cost=27.50..56.25 rows=1000 width=4) (actual  time=1.201..3.646 rows=1000 loops=1)
Hash Cond: ("out".t = inn.t)
-> Seq Scan on "out"  (cost=0.00..15.00 rows=1000...
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