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Contributors
About the author
Hans-Jürgen Schönig has 20 years’ experience with PostgreSQL. He is the CEO of a PostgreSQL consulting and support company called CYBERTEC PostgreSQL International GmbH. It has successfully served countless customers around the globe. Before founding CYBERTEC PostgreSQL International GmbH in 2000, he worked as a database developer at a private research company that focused on the Austrian labor market, where he primarily worked on data mining and forecast models. He has also written several books about PostgreSQL.
About the reviewers
Burhan Akbulut is the co-founder of PostgresTech. It is a company that provides PostgreSQL consultancy and support to start-ups and enterprise companies. Burhan Akbulut started his career as a PostgreSQL consultant at CookSoft, a well-known PostgreSQL consulting firm founded by Şahap Aşçı, where he provided consultancy and support to many international customers. Before founding PostgresTech, he worked at Vodafone as an open source database senior specialist responsible for all PostgreSQL databases. He has especially focused on database management with IaC, management of cloud databases, and migration from other databases to PostgreSQL during his career.
I would like to thank my colleague Şeyma Mintaş who helped me review the book.
Marcelo Diaz is a software engineer with more than 15 years of experience, with a special focus on PostgreSQL. He is passionate about open source software and has promoted its application in critical and high-demand environments, working as a software developer and consultant for both private and public companies. He currently works very happily at Cybertec and as a technical reviewer for Packt Publishing. He enjoys spending his leisure time with his daughter, Malvina, and his wife, Romina. He also likes playing football.
Dinesh Kumar Chemuduru works as a principal architect (OSS) at Tessell Inc. He has been working with PostgreSQL since 2011, and he also worked as a consultant at AWS. He is also an author and contributor to a few popular open source solutions. He co-authored PostgreSQL High Performance Cookbook 9.6, which was released in 2016. He loves to code in Dart, Go, Angular, and C++ and loves to deploy them in Kubernetes.
Thanks and love to my wife, Manoja Reddy, and my kids, Yashvi and Isha.
Sense of Backups and Replication
Deciding on Useful Extensions
Troubleshooting PostgreSQL
Preface
Mastering the art of handling data is an ever more important skill that is important to have. In a digital world, “data” is more or less the “new oil” – an important asset that drives the world. Every sector of IT is data-driven. It does not matter whether you are at the forefront of machine learning or whether you are working on bookkeeping software – at the end of the day, IT is all about data.
PostgreSQL has become a hot technology in the area of open source, and it is an excellent technology to store and process data in the most efficient way possible. This book will teach you how to use PostgreSQL in the most professional way and explain how to operate, optimize, and monitor this core technology, which has become so popular over the years.
By the end of the book, you will be able to use PostgreSQL to its utmost capacity by applying advanced technology and cutting-edge features.
Who this book is for
This book is ideal for PostgreSQL developers and administrators alike who want to familiarize themselves with the technology. It will provide you with deep insights and explain advanced technologies such as clustering, modern analytics, and a lot more.
Prior exposure to PostgreSQL and basic SQL knowledge is required to follow along.
What this book covers
Chapter 1, PostgreSQL 15 Overview, guides you through the most important features that have made it into the new release of PostgreSQL and explains how those features can be used.
Chapter 2, Understanding Transactions and Locking, explains the fundamental concepts of transactions and locking. Both topics are key requirements to understand storage management in PostgreSQL.
Chapter 3, Making Use of Indexes, introduces the concept of indexes, which are the key ingredient when dealing with performance in general. You will learn about simple indexes as well as more sophisticated concepts.
Chapter 4, Handling Advanced SQL, unleashes the full power of SQL and outlines the most advanced functionality a query language has to offer. You will learn about windowing functions, ordered sets, hypothetical aggregates, and a lot more. All those techniques will open a totally new world of functionality.
Chapter 5, Log Files and System Statistics, explains how you can use runtime statistics collected by PostgreSQL to make operations easier and to debug the database. You will be guided through the internal information-gathering infrastructure.
Chapter 6, Optimizing Queries for Good Performance, is all about good query performance and outlines optimization techniques that are essential to bringing your database up to speed to handle even bigger workloads.
Chapter 7, Writing Stored Procedures, introduces you to the concept of server-side code such as functions, stored procedures, and a lot more. You will learn how to write triggers and dive into server-side logic.
Chapter 8, Managing PostgreSQL Security, helps you to make your database more secure, and explains what can be done to ensure safety and data protection at all levels.
Chapter 9, Handling Backup and Recovery, helps you to make copies of your database to protect yourself against crashes and database failure.
Chapter 10, Making Sense of Backups and Replication, follows up on backups and recovery and explains additional techniques, such as streaming replication, clustering, and a lot more. It covers the most advanced topics.
Chapter 11, Deciding on Useful Extensions, explores extensions and additional useful features that can be added to PostgreSQL.
Chapter 12, Troubleshooting PostgreSQL, completes the circle of topics and explains what can be done if things don’t work as expected. You will learn how to find the most common issues and understand how problems can be fixed.
Chapter 13, Migrating to PostgreSQL, teaches you how to move your databases to PostgreSQL efficiently and quickly. It covers the most common database systems people will migrate from.
To get the most out of this book
This book has been written for a broad audience. However, some basic knowledge of SQL is necessary to follow along and make full use of the examples presented. In general, it is also a good idea to familiarize yourself with basic Unix commands as most of the book has been produced on Linux and macOS.
Software/hardware covered in the book
Pgadmin4
PostgreSQL 15
SQL Shell (psql)
Operating system requirements
Windows, macOS, or Linux
Note:
Some parts of chapters i.e., 8, 9, 10, 11,12 and 13 are mostly dedicated to unix / linux and mac users and rest runs fine on windows.
Download the example code files
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Conventions used
There are a number of text conventions used throughout this book.
Code in text: Indicates code words in text, database table names, folder names, filenames, file extensions, pathnames, dummy URLs, user input, and Twitter handles. Here is an example: “. You cannot run it inside a SELECT statement. Instead, you have to invoke CALL. The following listing shows the syntax of the CALL command.”
Any command-line input or output is written as follows:
# - Connection Settings –
# listen_addresses = 'localhost'
# what IP address(es) to listen on;
# comma-separated list of addresses;
# defaults to 'localhost'; use '*' for all
# (change requires restart)
Bold: Indicates a new term, an important word, or words that you see onscreen. For instance, words in menus or dialog boxes appear in bold. Here is an example: “Select System info from the Administration panel.”
Tips or important notes
Appear like this.
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PostgreSQL 15 Overview
A full year has passed and the PostgreSQL community has released version 15 of the database, which includes various powerful new features that will benefit a large user base. The PostgreSQL project has also come a long way and improvements are being added constantly at a rapid pace that make the database more useful, more efficient, and more widely accepted. The times when PostgreSQL was some unknown obscure thing are long gone. PostgreSQL has reached the data center and has been widely adopted in many large companies as well as by governments around the world.
In this chapter, you will learn about new features that made it into PostgreSQL 15. Those features add additional capabilities, more performance, as well as security and enhanced usability.
The following topics are covered in this chapter:
• DBA-related features
• Developer-related features
• Performance-related features
• Additional replication features
Of course, there is always more stuff. However, let us focus on the most important changes affecting most users.
Making use of DBA-related features
In PostgreSQL 15, a couple of developer-related features were added. Some features were also finally deprecated and have been removed from the server. In this section, we will go through the most important major changes.
Removing support for old pg_dump
One of the first things that is worth noting is that support for really old databases has been removed from pg_dump. PostgreSQL databases that are older than PostgreSQL 9.2 are not supported anymore.
Considering that PostgreSQL 9.2.0 was released to the PostgreSQL community FTP server on September 10, 2012, most people should have gotten rid of their PostgreSQL 9.1 (and older) systems by now.
If you have not been able to upgrade since then, we highly recommend doing that. It is still possible to upgrade from such an old version to PostgreSQL 15. However, you will need an intermediate step and to use pg_dump twice.
Deprecating Python 2
PostgreSQL allows developers to write stored procedures in various languages. This includes Python but is not limited to it. The trouble is that Python 2.x has been deprecated for a long time already. Starting with version 15, the PostgreSQL community has also dropped support for PL/Python2U and only supports version 3 from now on.
This means that all code that is still in Python 2 should be moved to Python 3 in order to function properly.
Fixing the public schema
Up to PostgreSQL 14, the public schema that exists in every database has been available to every user. This has caused various security concerns among the user base. Basically it is easy to just use the following:
REVOKE ALL ON SCHEMA public FROM public;
This was rarely done but caused security leaks people were generally not aware of. With the introduction of PostgreSQL, the situation has changed. The public schema is, from now on, not available to the general public and you have to be granted permission to use it like before. The new behavior will make applications a lot safer and ensure that permissions are not there accidentally.
Adding pre-defined roles
In recent versions of PostgreSQL, more and more pre-defined users have been added. The core idea is to ensure that people do not have to use their superuser accounts so often. For security reasons, it is not recommended to use superusers unless explicitly needed. However, with the introduction of pre-defined roles, it is a lot easier to run things without superusers:
test=# SELECT rolname FROM pg_authid WHERE oid < 16384 AND rolname <> CURRENT_USER; rolname
pg_database_owner
pg_read_all_data
pg_write_all_data
pg_monitor
pg_read_all_settings
pg_read_all_stats
pg_stat_scan_tables
pg_read_server_files
pg_write_server_files
pg_execute_server_program
pg_signal_backend
pg_checkpointer (12 rows)
With the introduction of PostgreSQL, a new role has been added, pg_checkpointer, which allows users to manually run checkpoints if needed.
Adding permissions to variables
However, there is more. It is now possible to define permissions on variables. This was not possible before version 15. Here is an example:
GRANT SET ON PARAMETER track_functions TO hans;
This new feature allows administrators to disable bad behavior and prohibit bad parameter settings that can compromise the availability of the entire server.
Improving pg_stat_statements
Every version will also provide us with some improvements related to pg_stat_statements , which in my judgment is the key to good performance. Consider the following code snippet: test=# \d pg_stat_statements
View "public.pg_stat_statements"
Column | Type | ...
jit_functions | bigint | ...
jit_generation_time | double precision | ...
jit_inlining_count | bigint | ...
jit_inlining_time | double precision | ...
jit_optimization_count | bigint | ...
jit_optimization_time | double precision | ...
jit_emission_count | bigint | ...
jit_emission_time | double precision | ...
The module is now able to display information about the JIT compilation process and helps to detect JIT-related performance problems. Those problems are not too frequent – however, it can happen that once in a while, a JIT compilation process takes too long. This is especially true if you are running a query containing hundreds of columns.
New wait events
What is also new in PostgreSQL is a couple of wait events that give you some insights into where time is the list. The following events have been added to the system:
• ArchiveCommand
• ArchiveCleanupCommand
• RestoreCommand
• RecoveryEndCommand
Those events complement the existing wait event infrastructure and give some insights into replication-related issues.
Adding logging functionality
PostgreSQL 15 comes with a spectacular new feature: JSON logging. While JSON is comparatively large compared to the standard log format, it still comes with a couple of advantages, such as easy parsing.
Let us configure JSON logging in postgresql.conf:
log_destination = 'jsonlog' # Valid values are combinations of
# stderr, csvlog, jsonlog, syslog, and
# eventlog, depending on platform.
# csvlog and jsonlog require
# logging_collector to be on.
# This is used when logging to stderr: logging_collector = on
CET","txid":0,"error_severity":"LOG","message":"ending log output to stderr","hint":"Future log output will go to log destination \"jsonlog\".","backend_ type":"postmaster","query_id":0}
CET","txid":0,"error_severity":"LOG","message":"starting PostgreSQL 15.0 on x86_64-appledarwin21.6.0, compiled by Apple clang version 13.1.6 (clang-1316.0.21.2.5), 64bit","backend_type":"postmaster","query_id":0}
Reading a tightly packed file containing millions of JSON documents is not really user-friendly, so I recommend using a tool such as jq to make this stream more readable and user-friendly to process:
In general, it is recommended to not use JSON logs excessively as they occupy a fair amount of space.
Understanding developer-related features
Administration-related features are not everything. PostgreSQL 15 also provides some developerrelated features that are useful to build even more powerful applications. In this section, you will learn which ones are available.
Security invoker views
In PostgreSQL, a view is a separate security context. It might happen that somebody is allowed to access a view but not the underlying table. Why does this matter? Consider the following scenario:
• Joe is allowed to see all sales
• Jane is only allowed to see total turnover by country
Jane will be granted rights on a view that sums up the data. She will be able to read that view without having the right to read the sales table directly.
However, in PostgreSQL, it is now possible to make PostgreSQL treat the view more like a preprocessor directive. By setting security_invoker, it will also check the underlying tables and not treat the view as a separate security context anymore:
CREATE VIEW sample_view WITH (security_invoker=true) AS SELECT * FROM some_table WHERE id < 100;
This feature is a classic example of open source sponsoring. It has been paid for by donations to a private company.
ICU locales
ICU locales are a truly important feature of PostgreSQL. Why is this relevant? The locale determines the sort order of characters. We all take our own sort order for granted (a, b, c, … ). However, not all languages sort equally. In some languages, some characters simply show up in different sequences. For the better part of the last 35 years, the sort order used by PostgreSQL has been provided by the underlying C library (the standard OS library). The problem is that the sort order of characters can change over time. Why does this matter? Because it breaks indexing.
Remember
Indexes are basically sorted lists. The trouble is when the sort order changes, your sorted list will be wrong, which of course matters if we are talking about tables in the TB range. This is a real issue as a changing locale can result in silently corrupted indexes.
The ICU library has been designed to fix those issues and provide a stable platform for such localerelated issues. Since PostgreSQL, it is now possible to use ICU locales on the instance as well as on the database library. The following code snippet shows an example:
initdb --locale-provider=icu --icu-locale=en_US
CREATE DATABASE foo TEMPLATE template0
LOCALE_PROVIDER 'icu'
ICU_LOCALE 'fi'
It is highly recommended to make use of the ICU library to handle locales in general. It makes longterm deployments more future-proof.
Better numeric
Locales are not the only thing that has been improved. The numeric data type has also gotten a boost and some new features have been added. Consider the following code snippet:
All those features come in handy and make the data type more useful in general.
Handling ON DELETE
The ON DELETE SET NULL mechanism has been around for many decades. However, from version 15 onward, it is now possible to set only some of the NULL columns:
CREATE TABLE n_side_of_the_model (
FOREIGN KEY (col1, col2, col3)
REFERENCES one_side_of_the_er_model
ON DELETE SET NULL (col2, col3) );
This feature will greatly improve the functionality of foreign keys and make them even more useful.
Working around NULL and UNIQUE
There is also news around NULL handling. Normally, a UNIQUE constraint handles NULL values as different values. Remember: NULL means undefined and therefore we don’t know whether undefined 1 is the same as undefined 2. This constraint is not violated. Here is an example:
test=# CREATE TABLE t_null (id int UNIQUE);
CREATE TABLE
test=# INSERT INTO t_null VALUES (1);
INSERT 0 1
test=# INSERT INTO t_null VALUES (NULL); INSERT 0 1
test=# INSERT INTO t_null VALUES (NULL); INSERT 0 1
As you can see, two NULL values are perfectly fine. However, this might not be desirable. Let us drop the table and start all over:
test=# DROP TABLE t_null; DROP TABLE
New syntax has been added to handle the NULL-related behavior:
test=# CREATE TABLE t_null (id int UNIQUE NULLS NOT DISTINCT);
CREATE TABLE
test=# INSERT INTO t_null VALUES (1); INSERT 0 1
test=# INSERT INTO t_null VALUES (NULL); INSERT 0 1
test=# INSERT INTO t_null VALUES (NULL);
ERROR: duplicate key value violates unique constraint "t_null_ id_key"
DETAIL: Key (id)=(null) already exists.
As we can see, the third INSERT will error out and throw a message.
Adding the MERGE command to PostgreSQL
The MERGE command is surely one of the most important new features provided by PostgreSQL 15. It has been in the making for many years and has finally been committed to the PostgreSQL core as part of the new release.
What is the idea of MERGE? Well, INSERT … ON CONFLICT is basically “upsert” while MERGE solves a totally different problem.
How does MERGE work? Let us take a look at the syntax first:
test=# \h MERGE
Command: MERGE
Description: conditionally insert, update, or delete rows of a table
Syntax:
[ WITH with_query [, ...] ]
MERGE INTO target_table_name [ [ AS ] target_alias ] USING data_source ON join_condition when_clause [...] where data_source is: { source_table_name | ( source_query ) } [ [ AS ] source_alias ] and when_clause is: { WHEN MATCHED [ AND condition ] THEN { merge_update | merge_delete | DO NOTHING } | WHEN NOT MATCHED [ AND condition ] THEN { merge_insert | DO NOTHING } } and merge_insert is:
INSERT [( column_name [, ...] )] [ OVERRIDING { SYSTEM | USER } VALUE ]
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