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PostgreSQL Administration Essentials
PostgreSQL Administration Essentials

PostgreSQL Administration Essentials: Discover efficient ways to administer, monitor, replicate, and handle your PostgreSQL databases

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Profile Icon Hans-Jürgen Schönig
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Full star icon Full star icon Full star icon Half star icon Empty star icon 3.1 (8 Ratings)
Paperback Oct 2014 142 pages 1st Edition
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Arrow left icon
Profile Icon Hans-Jürgen Schönig
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Full star icon Full star icon Full star icon Half star icon Empty star icon 3.1 (8 Ratings)
Paperback Oct 2014 142 pages 1st Edition
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PostgreSQL Administration Essentials

Chapter 2. Indexing and Performance Tuning

You might wonder why a book about PostgreSQL administration actually contains a chapter on indexing and performance tuning. The answer is quite simple actually; extensive experience in database engineering and support shows that a poor indexing strategy will, on a regular basis, totally cripple user experience as well as performance. It happens on a regular basis that a bad overall indexing strategy totally destroys user experience as well as performance.

Therefore, it is one of my primary goals to provide as much information as possible about hunting down wrong or missing indexes so that you, the reader, can easily optimize your system to enjoy the full power of PostgreSQL.

In this chapter, you will be guided through PostgreSQL indexing, and you will learn how to fix performance issues and find performance bottlenecks. Understanding indexing will be vital to your success as a DBA—you cannot count on software engineers to get this...

Using simple binary trees

In this section, you will learn about simple binary trees and how the PostgreSQL optimizer treats the trees. Once you understand the basic decisions taken by the optimizer, you can move on to more complex index types.

Preparing the data

Indexing does not change user experience too much, unless you have a reasonable amount of data in your database—the more data you have, the more indexing can help to boost things. Therefore, we have to create some simple sets of data to get us started. Here is a simple way to populate a table:

test=# CREATE TABLE t_test (id serial, name text);
CREATE TABLE
test=# INSERT INTO t_test (name) SELECT 'hans' FROM generate_series(1, 2000000);
INSERT 0 2000000
test=# INSERT INTO t_test (name) SELECT 'paul' FROM generate_series(1, 2000000);
INSERT 0 2000000

In our example, we created a table consisting of two columns. The first column is simply an automatically created integer value. The second column contains the...

Understanding the concept of execution plans

It is impossible to understand the use of indexes without understanding the concept of execution plans. Whenever you execute a query in PostgreSQL, it generally goes through four central steps, described as follows:

  • Parser: PostgreSQL will check the syntax of the statement.
  • Rewrite system: PostgreSQL will rewrite the query (for example, rules and views are handled by the rewrite system).
  • Optimizer or planner: PostgreSQL will come up with a smart plan to execute the query as efficiently as possible. At this step, the system will decide whether or not to use indexes.
  • Executor: Finally, the execution plan is taken by the executor and the result is generated.

Being able to understand and read execution plans is an essential task of every DBA. To extract the plan from the system, all you need to do is use the explain command, shown as follows:

test=# explain SELECT count(*) FROM t_test;
                              QUERY PLAN                         ...

Dealing with different types of indexes

Let's move on to an important issue: not everything can be sorted easily and in a useful way. Have you ever tried to sort circles? If the question seems odd, just try to do it. It will not be easy and will be highly controversial, so how do we do it best? Would we sort by size or coordinates? Under any circumstances, using a B-tree to store circles, points, or polygons might not be a good idea at all. A B-tree does not do what you want it to do because a B-tree depends on some kind of sorting order.

To provide end users with maximum flexibility and power, PostgreSQL provides more than just one index type. Each index type supports certain algorithms used for different purposes. The following list of index types is available in PostgreSQL (as of Version 9.4.1):

  • btree: These are the high-concurrency B-trees
  • gist: This is an index type for geometric searches (GIS data) and for KNN-search
  • gin: This is an index type optimized for Full-Text Search (FTS...

Detecting missing indexes

Now that we have covered the basics and some selected advanced topics of indexing, we want to shift our attention to a major and highly important administrative task: hunting down missing indexes.

When talking about missing indexes, there is one essential query I have found to be highly valuable. The query is given as follows:

test=# \x
Expanded display (expanded) is on.
test=# SELECT   relname, seq_scan, seq_tup_read, 
      idx_scan, idx_tup_fetch, 
      seq_tup_read / seq_scan 
  FROM   pg_stat_user_tables 
  WHERE   seq_scan > 0 
  ORDER BY seq_tup_read DESC;
-[ RECORD 1 ]-+---------
 relname       | t_user   
 seq_scan      | 824350        
 seq_tup_read  | 2970269443530 
 idx_scan      | 0        
 idx_tup_fetch | 0        
 ?column?      | 3603165  

The pg_stat_user_tables option contains statistical information about tables and their access patterns. In this example, we found a classic problem. The t_user table has been scanned close to 1 million times...

Detecting slow queries

Now that we have seen how to hunt down tables that might need an index, we can move on to the next example and try to figure out the queries that cause most of the load on your system. Sometimes, the slowest query is not the one causing a problem; it is a bunch of small queries, which are executed over and over again. In this section, you will learn how to track down such queries.

To track down slow operations, we can rely on a module called pg_stat_statements. This module is available as part of the PostgreSQL contrib section. Installing a module from this section is really easy. Connect to PostgreSQL as a superuser, and execute the following instruction (if contrib packages have been installed):

test=# CREATE EXTENSION pg_stat_statements;
CREATE EXTENSION

This module will install a system view that will contain all the relevant information we need to find expensive operations:

test=# \d pg_stat_statements
          View "public.pg_stat_statements"
      ...

Adjusting memory parameters

After we find the slow queries, we can do something about them. The first step is always to fix indexing and make sure that sane requests are sent to the database. If you are requesting stupid things from PostgreSQL, you can expect trouble. Once the basic steps have been performed, we can move on to the PostgreSQL memory parameters, which need some tuning.

Optimizing shared buffers

One of the most essential memory parameters is shared_buffers. What are shared buffers? Let's assume we are about to read a table consisting of 8,000 blocks. PostgreSQL will check if the buffer is already in cache (shared_buffers), and if it is not, it will ask the underlying operating system to provide the database with the missing 8,000 blocks. If we are lucky, the operating system has a cached copy of the block. If we are not so lucky, the operating system has to go to the disk system and fetch the data (worst case). So, the more data we have in cache, the more efficient we will...

Using simple binary trees


In this section, you will learn about simple binary trees and how the PostgreSQL optimizer treats the trees. Once you understand the basic decisions taken by the optimizer, you can move on to more complex index types.

Preparing the data

Indexing does not change user experience too much, unless you have a reasonable amount of data in your database—the more data you have, the more indexing can help to boost things. Therefore, we have to create some simple sets of data to get us started. Here is a simple way to populate a table:

test=# CREATE TABLE t_test (id serial, name text);
CREATE TABLE
test=# INSERT INTO t_test (name) SELECT 'hans' FROM generate_series(1, 2000000);
INSERT 0 2000000
test=# INSERT INTO t_test (name) SELECT 'paul' FROM generate_series(1, 2000000);
INSERT 0 2000000

In our example, we created a table consisting of two columns. The first column is simply an automatically created integer value. The second column contains the name.

Once the table is created...

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Description

If you are a database administrator who needs to get to grips with PostgreSQL quickly and efficiently, then this book is for you. This book will also be highly beneficial if you are a project leader or a developer who is interested in knowing more about database systems or bottleneck detection, as it will enable you to work more closely and cooperatively with your administrators.

What you will learn

  • Perform routine backups and restore your databases safely
  • Set up replication quickly and easily
  • Handle logfiles and extract information from PostgreSQL
  • Monitor PostgreSQL and integrate it into the existing infrastructure
  • Build desktop applications using C#
  • Optimize PostgreSQL for high speed and tune your database parameters
  • Adjust your user permissions and lock out intruders
  • Detect bottlenecks and find missing indexes with ease

Product Details

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Publication date, Length, Edition, Language, ISBN-13
Publication date : Oct 10, 2014
Length: 142 pages
Edition : 1st
Language : English
ISBN-13 : 9781783988983
Vendor :
PostgreSQL Global Development Group
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Publication date : Oct 10, 2014
Length: 142 pages
Edition : 1st
Language : English
ISBN-13 : 9781783988983
Vendor :
PostgreSQL Global Development Group
Category :
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Tools :

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Table of Contents

8 Chapters
1. Installing PostgreSQL Chevron down icon Chevron up icon
2. Indexing and Performance Tuning Chevron down icon Chevron up icon
3. Users and Permissions Chevron down icon Chevron up icon
4. Managing Logfiles Chevron down icon Chevron up icon
5. Backup and Recovery Chevron down icon Chevron up icon
6. Handling Replication and Improving Performance Chevron down icon Chevron up icon
7. Monitoring PostgreSQL Chevron down icon Chevron up icon
Index Chevron down icon Chevron up icon

Customer reviews

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Full star icon Full star icon Full star icon Half star icon Empty star icon 3.1
(8 Ratings)
5 star 37.5%
4 star 12.5%
3 star 0%
2 star 25%
1 star 25%
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Sally Jan 29, 2016
Full star icon Full star icon Full star icon Full star icon Full star icon 5
easy read, good introduction for someone already familiar with rdbms products.
Amazon Verified review Amazon
Amazon Customer Jul 27, 2020
Full star icon Full star icon Full star icon Full star icon Full star icon 5
very good
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Amazon Customer Nov 03, 2016
Full star icon Full star icon Full star icon Full star icon Full star icon 5
Tiene excelentes tips para troubleshooting, te lleva de la mano para que puedas mejorar el performance de tu server sin impactar o perjudicar lo que existe actualmente
Amazon Verified review Amazon
Sebastian Broekhoven Mar 05, 2015
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Good written.
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Anthony Garratt Jan 17, 2017
Full star icon Full star icon Empty star icon Empty star icon Empty star icon 2
This book is pretty awful. By 'essential' it appears to mean scant of detail or explanation, rather than a description of important highlights. The author wastes space by asking pointless questions and then failing to explain adequately why the answer is as it is. For example, "How are xlog files organised? If you look into one of these files, you will see that they are basically unreadable. It is impossible to modify the xlog files." The question in, and of itself, is of little value. This is a common theme in the book.The best bit is the section on logging; that's really the only bit I can recommend.It's quite short at around 120 pages. The Packt books are usually pretty good, so get a different one.
Amazon Verified review Amazon
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