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Learn PostgreSQL
Learn PostgreSQL

Learn PostgreSQL: Use, manage, and build secure and scalable databases with PostgreSQL 16 , Second Edition

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Profile Icon Luca Ferrari Profile Icon Enrico Pirozzi
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Arrow left icon
Profile Icon Luca Ferrari Profile Icon Enrico Pirozzi
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€26.99
Full star icon Full star icon Full star icon Full star icon Half star icon 4.4 (31 Ratings)
eBook Oct 2023 744 pages 2nd Edition
eBook
€26.99
Paperback
€33.99
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Free Trial
Renews at €18.99p/m
eBook
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Learn PostgreSQL

Getting to Know Your Cluster

To be a proficient user and administrator of a PostgreSQL cluster, you first must know and understand how PostgreSQL works. A database system is a very complex beast, and PostgreSQL, being an enterprise-level Database Management System (DBMS), is in no way a simple software system. However, thanks to very good design and implementation, once you understand the basic concepts and terminology of PostgreSQL, things will quickly become comprehensive and clear.

This chapter will continue from the foundation of the previous chapter and introduce you to some other PostgreSQL terminology and concepts, as well as teaching you how to interact with the cluster. You will also be introduced to the psql client, which ships with PostgreSQL and is the recommended way to connect to your database. You are free to use any SQL client that can connect to PostgreSQL, and all the code and examples shown in this chapter will run out of the box in any other client as well, but we recommend that you take some time to learn psql. Shipped with PostgreSQL, psql is guaranteed to work in any situation and is the default way to connect to a cluster. psql is a text-only client; if you are more comfortable using a graphical client, you can have a look at pgAdmin4, one of the most famous PostgreSQL graphical clients.

This chapter covers the following main topics:

  • Managing your cluster
  • Connecting to the cluster
  • Exploring the disk layout of PGDATA
  • Exploring configuration files and parameters

Technical requirements

The knowledge required in this chapter is as follows:

  • How to install binary packages on your Unix machine
  • PostgreSQL basic terminology (from the previous chapter)
  • Basic Unix command-line usage
  • Basic SQL statements covered in this chapter, like SELECT

The chapter examples can be run on the standalone Docker image, which you can find in the book’s GitHub repository: https://github.com/PacktPublishing/Learn-PostgreSQL-Second-Edition. For installation and usage of the Docker images available for this book, please refer to the instructions in Chapter 1, Introduction to PostgreSQL.

Managing your cluster

A PostgreSQL cluster is a collection of several databases that all run under the very same PostgreSQL service or instance.

Managing a cluster means being able to start, stop, take control, and get information about the status of a PostgreSQL instance.

From an operating system point of view, PostgreSQL is a service that can be started, stopped, and, of course, monitored. As you saw in the previous chapter, usually when you install PostgreSQL, you also get a set of operating system-specific tools and scripts to integrate PostgreSQL with your operating system service management. Usually, you will find system service files or other operating system-specific tools, like pg_ctl cluster, which is shipped with Debian GNU/Linux and its derivatives.

PostgreSQL ships with a specific tool called pg_ctl, which helps in managing the cluster and the related running processes. This section introduces you to the basic usage of pg_ctl and to the processes that you can encounter in a running cluster. It does not matter which service management system your operating system is using, pg_ctl will always be available to the PostgreSQL administrator in order to take control of a database instance.

pg_ctl

The pg_ctl command-line utility allows you to perform different actions on a cluster, mainly initialize, start, restart, stop, and so on. pg_ctl accepts the command to execute as the first argument, followed by other specific arguments—the main commands are as follows:

  • start, stop, and restart execute the corresponding actions on the cluster.
  • status reports the current status (running or not) of the cluster.
  • initdb (or init for short) executes the initialization of the cluster, possibly removing any previously existing data.
  • reload causes the PostgreSQL server to reload the configuration, which is useful when you want to apply configuration changes.
  • promote is used when the cluster is running as a replica server (namely a standby node) and, from now on, must be detached from the original primary becoming independent (replication will be explained in later chapters).

Generally speaking, pg_ctl interacts mainly with the postmaster (the first process launched within a cluster), which in turn “redirects” commands to other existing processes. For instance, when pg_ctl starts a server instance, it makes the postmaster process run, which in turn completes all the startup activities, including launching other utility processes (as briefly explained in the previous chapter). On the other hand, when pg_ctl stops a cluster, it issues a halt command to the postmaster, which in turn requires other active processes to exit, waiting for them to finish.

The postmaster process is just the very first PostgreSQL-related process launched within the instance; on some systems, there is a process named “postmaster,” while on other operating systems, there are only processes named “postgres.” The first process ever launched, despite its name, is referred to as the postmaster. The name postmaster is just that, a name used to identify a process among the others (in particular, the first process launched within the cluster).

pg_ctl needs to know where the PGDATA is located, and this can be specified by either setting an environment variable named PGDATA or by specifying it on the command line by means of the –D flag.

Interacting with a cluster status (for example, to stop it) is an action that not every user must be able to perform; usually, only an operating system administrator must be able to interact with services including PostgreSQL.

PostgreSQL, in order to mitigate the side effects of privilege escalation, does not allow a cluster to be run by privileged users, such as root. Therefore, PostgreSQL is run by a “normal” user, usually named postgres on all operating systems. This unprivileged user owns the PGDATA directory and runs the postmaster process, and, therefore, also all the processes launched by the postmaster itself. pg_ctl must be run by the same unprivileged operating system user that is going to run the cluster.

If you are using the Docker image, PostgreSQL is already running as the main service. This means that issuing a stop or a restart command will force you to exit from the container due to its shutdown.

Moreover, in the Docker container, the PostgreSQL service will be already running without any need for manual intervention.

The status command just queries the cluster to get information, so it is pretty safe as a starting point to understand what is happening:

$ pg_ctl status
pg_ctl: server is running (PID: 1)
/usr/lib/postgresql/16/bin/postgres

The command reports back that the server is running, with a Process Identifier (PID) equal to one (this number will be different on your machine). Moreover, the command reports the executable file used to launch the server, in the above example, /usr/lib/postgresql/16/bin/postgres.

If the server is not running for any reason, the pg_ctl command will report an appropriate message to indicate that is unable to find an instance of PostgreSQL started:

$ pg_ctl status
pg_ctl: no server running

In order to report the status of the cluster, pg_ctl needs to know where the database is storing its own data—that is, where the PGDATA is on disk. There are two ways to make pg_ctl aware of where the PGDATA is:

  • Setting an environment variable named PGDATA, containing the path of the data directory
  • Using the –D command-line flag to specify the path to the data directory

Almost every PostgreSQL cluster-related command searches for the value of PGDATA as an environmental variable or as a -D command-line option.

In the previous examples, no PGDATA has been specified, and this is because it has been assumed the value of the PGDATA was specified by an environment variable.

It is quite easy to verify this—for example, in the Docker container:

$ echo $PGDATA
/postgres/16/data
$ pg_ctl status
pg_ctl: server is running (PID: 1)
/usr/lib/postgresql/16/bin/postgres

In the case that your setup does not include an PGDATA environment variable, you can always set it manually before launching pg_ctl or any other cluster-related command:

$ export PGDATA=/postgres/16/data
$ pg_ctl status
pg_ctl: server is running (PID: 1)

The command-line argument, specified with -D, always has precedence against any PGDATA environment variable, so if you don’t set or misconfigure the PGDATA variable but, instead, pass the right value on the command line, everything works fine:

$ export PGDATA=/postgres/data  # wrong PGDATA!
$ pg_ctl status -D /postgres/16/data
pg_ctl: server is running (PID: 1)
/usr/lib/postgresql/16/bin/postgres "-D" "/postgres/16/data"

The same concepts of PGDATA and the -D optional argument are true for pretty much any “low-level” commands that act against a cluster and make clear that, with the same set of executables, you can run multiple instances of PostgreSQL on the same machine, as long as you keep the PGDATA directory of each one separate.

Do not use the same PGDATA directory for multiple versions of PostgreSQL. While it could be tempting, on your own test machine, to have a single PGDATA directory that can be used in turn by a PostgreSQL 16 and a PostgreSQL 15 instance, this will not work as expected and you risk losing all your data. Luckily, PostgreSQL is smart enough to see that PGDATA has been created and used by a different version and refuses to operate, but please be careful not to share the same PGDATA directory with different instances.

pg_ctl can be used to start and stop a cluster by means of appropriate commands. For example, you can start an instance with the start command (assuming a PGDATA environment variable has been set):

$ pg_ctl start
waiting for server to start....
[27765] LOG:  starting PostgreSQL 16.0 on x
86_64-pc-linux-gnu, compiled by gcc (GCC) 12.1.0, 64-bit
[27765] LOG:  listening on IPv6 address "::1", port 5432
[27765] LOG:  listening on IPv4 address "127.0.0.1", port 5432 [27765] LOG:  listening on Unix socket "/tmp/.s.PGSQL.5432"
[27768] LOG:  database system was shut down at 2023-07-19 07:20:24 EST
[27765] LOG:  database system is ready to accept connections
done
server started

The start, stop, and restart commands do not work on the Docker images from this book’s repository because such containers are running PostgreSQL as the main process; therefore, stopping (or restarting) will cause the container to exit. Similarly, there is no need to start the service because it is automatically started once the container starts.

The pg_ctl command launches the postmaster process, which prints out a few log lines before redirecting the logs to the appropriate log file. The server started message at the end confirms that the server has started. During the startup, the PID of the postmaster is reported within square brackets; in the above example, the postmaster is the operating system process number 27765.

Now, if you run pg_ctl again to check the server, you will see that it has been started:

$ pg_ctl status
pg_ctl: server is running (PID: 27765)
/usr/pgsql-16/bin/postgres

As you can see, the server is now running and pg_ctl shows the PID of the running postmaster (27765), as well as the executable command line (in this case, /usr/pgsql-16/bin/postgres).

Remember: The postmaster process is the first process ever started in the cluster. Both the backend processes and the postmaster are run starting from the postgres executable, and the postmaster is just the root of all PostgreSQL processes, with the main aim of keeping all the other processes under control.

Now that the cluster is running, let’s stop it. As you can imagine, stop is the command used to instruct pg_ctl about which action to perform:

$ pg_ctl stop
waiting for server to shut down....
[27765] LOG:  received fast shutdown request
[27765] LOG:  aborting any active transactions
[27765] LOG:  background worker "logical replication launcher" (PID 27771) exited with exit code 1
[27766] LOG:  shutting down
[27766] LOG:  checkpoint starting: shutdown immediate
[27766] LOG:  checkpoint complete: wrote 0 buffers (0.0%); 0 WAL file(s) added, 0 removed, 0 recycled; write=0.001 s, sync=0.001 s, total=0.035 s; sync files=0, longest=0.000 s, average=0.000 s; distance=0 kB, estimate=237 kB; lsn=0/1529DC8, redo lsn=0/1529DC8
[27765] LOG:  database system is shut down
done
server stopped

During a shutdown, the system prints a few messages to inform the administrator about what is happening, and as soon as the server stops, the message server stopped confirms that the cluster is no longer running.

Shutting down a cluster can be much more problematic than starting it, and for that reason, it is possible to pass extra arguments to the stop command in order to let pg_ctl act accordingly. There are three ways of stopping a cluster:

  • The smart mode means that the PostgreSQL cluster will gently wait for all the connected clients to disconnect and only then will it shut the cluster down.
  • The fast mode will immediately disconnect every client and will shut down the server without having to wait.
  • The immediate mode will abort every PostgreSQL process, including client connections, and shut down the cluster in a dirty way, meaning that the server will need some specific activity on the restart to clean up such dirty data (more on this in the next chapters).

In any case, once a stop command is issued, the server will not accept any new incoming connections from clients, and depending on the stop mode you have selected, existing connections will be terminated. The default stop mode, if none is specified, is fast, which forces an immediate disconnection of the clients but ensures data integrity.

If you want to change the stop mode, you can use the -m flag, specifying the mode name, as follows:

$ pg_ctl stop -m smart
waiting for server to shut down........................ done
server stopped

In the preceding example, the pg_ctl command will wait, printing a dot every second until all the clients disconnect from the server. In the meantime, if you try to connect to the same cluster from another client, you will receive an error, because the server has entered the stopping procedure:

$ psql
psql: error: could not connect to server: FATAL:  the database system is shutting down

It is possible to specify just the first letter of the stop mode instead of the whole word; so, for instance, s for smart, i for immediate, and f for fast.

PostgreSQL processes

You have already learned how the postmaster is the root of all PostgreSQL processes, but as explained in Chapter 1, Introduction to PostgreSQL, PostgreSQL will launch multiple different processes at startup. These processes are in charge of keeping the cluster operational and in good health. This section provides a glance at the main processes you can find in a running cluster, allowing you to recognize each of them and their respective purposes.

If you inspect a running cluster from the operating system point of view, you will see a bunch of processes tied to PostgreSQL:

$ pstree -p postgres
postgres(1)─┬─postgres(34)
           ├─postgres(35)
           ├─postgres(37)
           ├─postgres(38)
           └─postgres(39)
$ ps -C postgres -af
postgres       1       0  0 11:08 ?        00:00:00 postgres
postgres      34       1  0 11:08 ?        00:00:00 postgres: checkpointer
postgres      35       1  0 11:08 ?        00:00:00 postgres: background writer
postgres      37       1  0 11:08 ?        00:00:00 postgres: walwriter
postgres      38       1  0 11:08 ?        00:00:00 postgres: autovacuum launcher
postgres      39       1  0 11:08 ?        00:00:00 postgres: logical replication launcher

The PID numbers reported in these examples refer to the Docker container, where the first PostgreSQL process has a PID equal to 1. On other machines, you will get different PID numbers.

As you can see, the process with PID 1 is one that spawns several other child processes and hence is the first and main PostgreSQL process launched, and as such, is usually called postmaster. The other processes are as follows:

  • checkpointer is the process responsible for executing the checkpoints, which are points in time where the database ensures that all the data is actually stored persistently on the disk.
  • background writer is responsible for helping to push the data out of the memory to permanent storage.
  • walwriter is responsible for writing out the Write-Ahead Logs (WALs), the logs that are needed to ensure data reliability even in the case of a database crash.
  • logical replication launcher is the process responsible for handling logical replication.

Depending on the exact configuration of the cluster, there could be other processes active:

  • Background workers: These are processes that can be customized by the user to perform background tasks.
  • WAL receiver and/or WAL sender: These are processes involved in receiving data from or sending data to another cluster in replication scenarios.

Many of the concepts and aims of the preceding process list will become clearer as you progress through the book’s chapters, but for now, it is sufficient that you know that PostgreSQL has a few other processes that are always active without any regard to incoming client connections.

When a client connects to your cluster, a new process is spawned: this process, named the backend process, is responsible for serving the client requests (meaning executing the queries and returning the results). You can see and count connections by inspecting the process list:

$ ps -C postgres -af
UID          PID    PPID  C STIME TTY          TIME CMD
postgres       1       0  0 11:08 ?        00:00:00 postgres
postgres      34       1  0 11:08 ?        00:00:00 postgres: checkpointer
postgres      35       1  0 11:08 ?        00:00:00 postgres: background writer
postgres      37       1  0 11:08 ?        00:00:00 postgres: walwriter
postgres      38       1  0 11:08 ?        00:00:00 postgres: autovacuum launcher
postgres      39       1  0 11:08 ?        00:00:00 postgres: logical replication launcher
postgres    40    1  0 04:35 ?        00:00:00 postgres: postgres postgres [local] idle

If you compare the preceding list with the previous one, you will see that there is another process with PID 40: this process is a backend process. In particular, this process represents a client connection to the database named postgres.

PostgreSQL uses a process approach to concurrency instead of a multi-thread approach. There are different reasons for this: most notably, the isolation and portability that a multi-process approach offers. Moreover, on modern hardware and software, forking a process is no longer so much of an expensive operation.

Therefore, once PostgreSQL is running, there is a tree of processes that roots at postmaster. The aim of the latter is to spawn new processes when there is the need to handle new database connections, as well as to monitor all maintenance processes to ensure that the cluster is running fine.

Connecting to the cluster

Once PostgreSQL is running, it awaits incoming database connections to serve; as soon as a connection comes in, PostgreSQL serves it by connecting the client to the right database. This means that to interact with the cluster, you need to connect to it. However, you don’t connect to the whole cluster; rather, you ask PostgreSQL to interact with one of the databases the cluster is serving. Therefore, when you connect to the cluster, you need to connect to a specific database. This also means that the cluster must have at least one database from the very beginning of its life.

When you initialize the cluster with the initdb command, PostgreSQL builds the filesystem layout of the PGDATA directory and builds two template databases, named template0 and template1. The template databases are used as a starting point to clone other new databases, which can then be used by normal users to connect to. In a freshly installed PostgreSQL cluster, you usually end up with a postgres database, used to allow the database administrator user postgres to connect to and interact with the cluster.

To connect to one of the databases, either a template or a user-defined one, you need a client to connect with. PostgreSQL ships with psql, a command-line client that allows you to connect, interact with, and administer databases and the cluster itself.

Other clients do exist, but they will not be discussed in this book. You are free to choose the client you like the most, since every command, query, and example shown in the book will run with no exception under every compatible client.

While connecting interactively to the cluster is an important task for a database administrator, often, developers need their own applications to connect to the cluster. To achieve this, the applications need a so-called connection string, a URI indicating all the required parameters to connect to the database.

This section will explain all the preceding concepts, starting from the template databases and then showing the basic usage of psql and the connection string.

The template databases

The template1 database is the first database created when the system is initialized, and then it is cloned into template0. This means that the two databases are, at least initially, identical, and the aim of template0 is to act as a safe copy for rebuilding in case it is accidentally damaged or removed.

You can inspect available databases using the psql -l command. On a freshly installed installation, you will get the following three databases:

$ psql -l                             List of databases
  Name    |  Owner   | Encoding |   Collate   |    Ctype    | ICU Locale | Locale Provider |   Access privileges
-----------+----------+----------+-------------+-------------+------------+-----------------+-----------------------
postgres  | postgres | UTF8     | it_IT.UTF-8 | it_IT.UTF-8 |            | libc            |
 template0 | postgres | UTF8     | it_IT.UTF-8 | it_IT.UTF-8 |            | libc            | =c/postgres          +
          |          |          |             |             |            |                 | postgres=CTc/postgres
template1 | postgres | UTF8     | it_IT.UTF-8 | it_IT.UTF-8 |            | libc            | =c/postgres          +
          |          |          |             |             |            |                 | postgres=CTc/postgres
(3 rows)
          +

In the Docker image, you will also see the forumdb database, which has been automatically created for you to let you interact with other examples.

It is interesting to note that, alongside the two template databases, there’s a third database that is created during the installation process: the postgres database. That database belongs to the postgres user, which is, by default, the only database administrator created during the initialization process. This database is a common space to be used for connections instead of the template databases.

The name template indicates the real aim of these two databases: when you create a new database, PostgreSQL clones a template database as a common base. This is somewhat like creating a user home directory on Unix systems: the system clones a skeleton directory and assigns the new copy to the user. PostgreSQL does the same—it clones template1 and assigns the newly created database to the user that requested it.

What this also means is that whatever object you put into template1, you will find the very same object in freshly created databases. This can be really useful for providing a common base database and having all other databases brought to life with the same set of attributes and objects.

Nevertheless, you are not forced to use template1 as the base template; in fact, you can create your own databases and use them as templates for other databases. However, please keep in mind that, by default, (and most notably on a newly initialized system), the template1 database is the one that is cloned for the first databases you will create.

Another difference between template1 and template0, apart from the former being the default for new databases, is that you cannot connect to the latter. This is in order to prevent accidental damage to template0 (the safety copy).

It is important to note that the cluster (and all user-defined databases) can work even without the template databases—the template1 and template0 databases are not fundamental for the other databases to run. However, if you lose the templates, you will be required to use another database as a template every time you perform an action that requires it, such as creating a new database.

Template databases are not meant for interactive connections, and you should not connect to the template databases unless you need to customize them. PostgreSQL will present as a skeleton for another database if there are active connections to it.

The psql command-line client

The psql command is the command-line interface that ships with every installation of PostgreSQL. While you can certainly use a graphical user interface to connect and interact with the databases, a basic knowledge of psql is mandatory in order to administer a PostgreSQL cluster. In fact, a specific psql version is shipped with every release of PostgreSQL; therefore, it is the most up-to-date client speaking the same language (i.e., protocol) of the cluster. Moreover, the client is lightweight and useful even in emergency situations when a GUI is not available.

psql accepts several options to connect to a database, mainly the following:

  • -d: The database name
  • -U: The username
  • -h: The host (either an IPv4 or IPv6 address or a hostname)

If no option is specified, psql assumes your operating system user is trying to connect to a database with the same name, and a database user with a name that matches the operating system on a local connection. Take the following connection:

$ id
uid=999(postgres) gid=999(postgres) groups=999(postgres),101(ssl-cert)
$ psql
psql (16.0)
Type "help" for help.
postgres=#

This means that the current operating system user (postgres) has required psql to connect to a database named postgres via the PostgreSQL user named postgres on the local machine. Explicitly, the connection could have been requested as follows:

$ psql -U postgres -d postgres
psql (16.0)
Type "help" for help.
postgres=#

The first thing to note is that once a connection has been established, the command prompt changes: psql reports the database to which the user has been connected (postgres) and a sign to indicate they are a superuser (#). In the case that the user is not a database administrator, a > sign is placed at the end of the prompt.

If you need to connect to a database that is named differently by your operating system username, you need to specify it:

$ psql -d template1
psql (16.0)
Type "help" for help.
template1=#

Similarly, if you need to connect to a database that does not correspond to your operating username with a PostgreSQL user that is different from your operating system username, you have to explicitly pass both parameters to psql:

$ id
uid=999(postgres) gid=999(postgres) groups=999(postgres),101(ssl-cert)
$ psql -d template1 -U luca
psql (16.0)
Type "help" for help.
template1=>

As you can see from the preceding example, the operating system user postgres has connected to the template1 database with the PostgreSQL user luca. Since the latter is not a system administrator, the command prompt ends with the > sign.

To quit from psql and close the connection to the database, you have to type \q or quit and press Enter (you can also press CTRL + D to exit on any Unix and Linux machines):

$ psql -d template1 -U luca
psql (16.0)
Type "help" for help.
template1=> \q
$

Entering SQL statements via psql

Once you are connected to a database via psql, you can issue any statement you like. Statements must be terminated by a semicolon, indicating that the next Enter key will execute the statement. The following is an example where the Enter key has been emphasized:

$ psql -d template1 -U luca
psql (16.0)
Type "help" for help.
template1=> SELECT current_time; <ENTER>
  current_time
--------------------
06:04:57.435155-05
(1 row)

SQL is a case-insensitive language, so you can enter statements in either uppercase, lowercase, or a mix. The same rule applies to column names, which are case-insensitive. If you need to have identifiers with specific cases, you need to quote them in double quotes.

Another way to execute the statement is to issue a \g command, again followed by <ENTER>. This is useful when connecting via a terminal emulator that has keys remapped:

template1=> SELECT current_time \g <ENTER>
 current_time
--------------------
06:07:03.328744-05
(1 row)

Until you end a statement with a semicolon or \g, psql will keep the content you are typing in the query buffer, so you can also edit multiple lines of text as follows:

template1=> SELECT
template1-> current_time
template1-> ;
 current_time
--------------------
06:07:28.908215-05
(1 row)

Note how the psql command prompt has changed on the lines following the first one: the difference is there to remind you that you are editing a multi-line statement and psql has not (yet) found a statement terminator (either a semicolon or the \g).

One useful feature of the psql query buffer is the capability to edit the content of the query buffer in an external editor. If you issue the \e command, your favorite editor will pop up with the content of the last-edited query. You can then edit and refine your SQL statement as much as you want, and once you exit the editor, psql will read what you have produced and execute it. The editor to use is chosen with the EDITOR operating system environment variable.

It is also possible to execute all the statements included in a file or edit a file before executing it. As an example, assume the test.sql file has the following content:

$ cat test.sql
SELECT current_database();
SELECT current_time;
SELECT current_role;

The file has three very simple SQL statements. In order to execute the whole file at once, you can use the \i special command followed by the name of the file:

template1=> \i test.sql
current_database
------------------
template1
(1 row)
   current_time
--------------------
06:08:43.077305-05
(1 row)
 current_role
--------------
 luca
(1 row)

As you can see, the client has executed, one after the other, every statement within the file. If you need to edit the file without leaving psql, you can issue \e test.sql to open your favorite editor, make changes, and come back to the psql connection.

SQL is case-insensitive and space-insensitive: you can write it in all uppercase or all lowercase, with however many horizontal and vertical spaces you want. In this book, SQL keywords will be written in uppercase and the statements will be formatted to read cleanly.

A glance at the psql commands

Every command specific to psql starts with a backslash character (\). It is possible to get some help with SQL statements and PostgreSQL commands via the special \h command, after which you can specify the specific statement you want help for:

template1=> \h SELECT
Command:     SELECT
Description: retrieve rows from a table or view
Syntax:
[ WITH [ RECURSIVE ] with_query [, ...] ]
SELECT [ ALL | DISTINCT [ ON ( expression [, ...] ) ] ]
    [ * | expression [ [ AS ] output_name ] [, ...] ]
...
URL: https://www.postgresql.org/docs/16/sql-select.html

The displayed help is, for space reasons, concise. You can find a much more verbose description and usage examples in the online documentation. For this reason, at the end of the help screen, there is a link reference to the online documentation.

If you need help with the psql commands, you can issue a \? command:

template1=> \?
General
  \copyright             show PostgreSQL usage and distribution terms
  \crosstabview [COLUMNS] execute query and display results in crosstab
  \errverbose            show most recent error message at maximum verbosity
  \g [FILE] or ;         execute query (and send results to file or |pipe)
  \gdesc                 describe result of query, without executing it
...

There are also a lot of introspection commands, such as, for example, \d to list all user-defined tables. These special commands are, under the hood, a way to execute queries against the PostgreSQL system catalogs, which are, in turn, registries about all objects that live in a database. The introspection commands will be shown later in the book and are useful as shortcuts to get an idea of which objects are defined in the current database.

Many psql features will be detailed as you move on through the book, but it is worth spending some time trying to get used to this very efficient and rich command-line client.

Introducing the connection string

In the previous section, you learned how to specify basic connection options, such as -d and -U for a database and user, respectively. psql also accepts a LibPQ connection string.

LibPQ is the underlying library that every application can use to connect to a PostgreSQL cluster and is, for example, used in C and C++ clients, as well as non-native connectors.

A connection string in LibPQ is a URI made up of several parts:

postgresql://username@host:port/database

Here, we have the following:

  • postgresql is a fixed string that specifies the protocol the URI refers to.
  • username is the PostgreSQL username to use when connecting to the database.
  • host is the hostname (or IP address) to connect to.
  • port is the TCP/IP port the server is listening on (by default, 5432).
  • database is the name of the database to which you want to connect.

The username, port, and database parts can be omitted if they are set to their default (the username is the same as the operating system username).

The following connections are all equivalent:

$ psql -d template1 -U luca -h localhost
$ psql postgresql://luca@localhost/template1
$ psql postgresql://luca@localhost:5432/template1

Solving common connection problems

There are a few common problems when dealing with database connections, and this section explains them in order to ease your task of getting connected to your cluster.

Please note that the solutions provided here are just for testing purposes and not for production usage. All of the security settings will be explained in later chapters, so the aim of the following subsection is just to help you get your test environment usable.

Database “foo” does not exist

This means either you misspelled the name of the database in the connection string or you are trying to connect without specifying the database name.

For instance, the following connection fails when executed by an operating system user named luca because, by default, it is assuming that the user luca is trying to connect to a database with the same name (meaning luca) since none has been explicitly set:

$ psql
psql: error: could not connect to server: FATAL:  database "luca" does not exist

The solution is to provide an existing database name via the -d option or to create a database with the same name as the user.

Connection refused

This usually means there is a network connection problem, so either the host you are trying to connect to is not reachable or the cluster is not listening on the network.

As an example, imagine PostgreSQL is running on a machine named venkman and we are trying to connect from another host on the same network:

$ psql -h venkman -U luca template1
psql: error: could not connect to server: could not connect to server: Connection refused
        Is the server running on host "venkman" (192.168.222.123) and accepting
        TCP/IP connections on port 5432?

In this case, the database cluster is running on the remote host but is not accepting connections from the outside. Usually, you have to fix the server configuration or connect to the remote machine (via SSH, for instance) and open a local connection from there.

In order to quickly solve the problem, you have to edit the postgresql.conf file (usually located under the PGDATA directory) and ensure the listen_address option has an asterisk (or the name of your external network card) so that the server will listen on any available network address:

listen_addresses = '*'

After a restart of the service, by means of the restart command issued to pg_ctl, the client will be able to connect. Please note that enabling the server to listen on any available network address might not be the optimal solution and can expose the server to risks in a production environment. Later in the book, you will learn how to specifically configure the connection properties for your server.

No pg_hba.conf entry

This error means the server is up and running and able to accept your request, but the PostgreSQL built-in Host-Based Access (HBA) control does not permit you to enter.

This error should never happen in the Docker container used for this chapter, because its configuration is already allowing trusted connections. However, other PostgreSQL installations will be stricter; therefore, knowing about this type of error message can help you to quickly figure out where the configuration problem is.

As an example, the following connection is refused:

$  psql -h localhost -U luca template1
psql: error: could not connect to server: FATAL:  no pg_hba.conf entry for host "127.0.0.1", user "luca", database "template1", SSL off

The reason for this is that, inspecting the pg_hba.conf file, there is no rule to let the user luca in on the localhost interface. So, for instance, adding a single line such as the following to the pg_hba.conf file can fix the problem:

host all luca 127.0.0.1/32 trust

You need to reload the configuration in order to apply changes. The format of every line in the pg_hba.conf file will be discussed later, but for now, please assume that the preceding line instruments the cluster to accept any connection incoming from localhost by means of the user luca.

Exploring the disk layout of PGDATA

In the previous sections, you have seen how to install PostgreSQL and connect to it, but we have not looked at the storage part of a cluster. Since the aim of PostgreSQL, as well as the aim of any relational database, is to permanently store data, the cluster needs some sort of permanent storage. In particular, PostgreSQL exploits the underlying filesystem to store its own data. All of the PostgreSQL-related stuff is contained in a directory known as PGDATA.

The PGDATA directory acts as the disk container that stores all the data of the cluster, including the users’ data and cluster configuration.

The following is an example of the content of PGDATA for a running PostgreSQL 16 cluster:

$  ls -1 /postgres/16/data
base
global
pg_commit_ts
pg_dynshmem
pg_hba.conf
pg_ident.conf
pg_logical
pg_multixact
pg_notify
pg_replslot
pg_serial
pg_snapshots
pg_stat
pg_stat_tmp
pg_subtrans
pg_tblspc
pg_twophase
PG_VERSION
pg_wal
pg_xact
postgresql.auto.conf
postgresql.conf
postmaster.opts
postmaster.pid

The PGDATA directory is structured in several files and subdirectories. The main files are as follows:

  • postgresql.conf is the main configuration file, used by default when the service is started.
  • postgresql.auto.conf is the automatically included configuration file used to store dynamically changed settings via SQL instructions.
  • pg_hba.conf is the HBA file that provides the configuration regarding available database connections.
  • PG_VERSION is a text file that contains the major version number (useful when inspecting the directory to understand which version of the cluster has managed the PGDATA directory).
  • postmaster.pid is the PID of the postmaster process, the first launched process in the cluster.

The main directories available in PGDATA are as follows:

  • base is a directory that contains all the users’ data, including databases, tables, and other objects.
  • global is a directory containing cluster-wide objects.
  • pg_wal is the directory containing the WAL files.
  • pg_stat and pg_stat_tmp are, respectively, the storage of permanent and temporary statistical information about the status and health of the cluster.

Of course, all files and directories in PGDATA are important for the cluster to work properly, but so far, the preceding is the “core” list of objects that are fundamental in PGDATA itself. Other files and directories will be discussed in later chapters.

Objects in the PGDATA directory

PostgreSQL does not name objects on disk, such as tables, in a mnemonic or human-readable way; instead, every file is named after a numeric identifier. You can see this by having a look, for instance, at the base subdirectory:

$  ls -1 /postgres/16/data/base
1
16386
4
5

As you can see from the preceding code, the base directory contains four objects, named 1,4, 5, and 16386. Please note that these numbers could be different on your machine. In particular, each of the preceding is a directory that contains other files, as shown here:

$ ls -1 /postgres/16/data/base/16386 | head
112
113
1247
1247_fsm
1247_vm
1249
1249_fsm
1249_vm
1255
1255_fsm

As you can see, each file is named with a numeric identifier. Internally, PostgreSQL holds a specific catalog that allows the database to match a mnemonic name to a numeric identifier, and vice versa. The integer identifier is named OID (or, Object Identifier); this name is a historical term that today corresponds to the so-called filenode. The two terms will be used interchangeably in this section.

There is a specific utility that allows you to inspect a PGDATA directory and extract mnemonic names: oid2name. For example, if you executed the oid2name utility, you’d get a list of all available databases similar to the following one:

$ oid2name
All databases:
   Oid  Database Name  Tablespace
----------------------------------
 16390        forumdb  pg_default
     5       postgres  pg_default
     4      template0  pg_default
     1      template1  pg_default

As you can see, the Oid numbers in the oid2name output reflect the same directory names listed in the base directory; every subdirectory has a name corresponding to the database.

You can even go further and inspect a single file going into the database directory, specifying the database where you are going to search for an object name with the -d flag:

$ cd /postgres/16/data/base/1
$ oid2name -d template1 -f 3395
From database "template1":
  Filenode                 Table Name
-------------------------------------
      3395  pg_init_privs_o_c_o_index

As you can see from the preceding example, the 3395 file in the /postgres/16/data/base/1 directory corresponds to the table named pg_init_privs_o_c_o_index. Therefore, when PostgreSQL needs to interact with a table like this, it will seek the disk to the /postgres/16/data/base/1/3395 file.

From the preceding example, it should be clear that every SQL table is stored as a file with a numeric name. However, PostgreSQL does not allow a single file to be greater than 1 GB in size, so what happens if a table grows beyond that limit? PostgreSQL “attaches” another file with a numeric extension that indicates the next chunk of 1 GB of data. In other words, if your table is stored in the 123 file, the second gigabyte will be stored in the 123.1 file, and if another gigabyte of storage is needed, another file, 123.2, will be created. Therefore, the filenode refers to the very first file related to a specific table, but more than one file can be stored on disk.

Tablespaces

PostgreSQL pretends to find all its data within the PGDATA directory, but that does not mean that your cluster is “jailed” in this directory. In fact, PostgreSQL allows “escaping” the PGDATA directory by means of tablespaces. A tablespace is a directory that can be outside the PGDATA directory and can also belong to different storage. Tablespaces are mapped into the PGDATA directory by means of symbolic links stored in the pg_tblspc subdirectory. In this way, the PostgreSQL processes do not have to look outside PGDATA, but are still able to access “external” storage. A tablespace can be used to achieve different aims, such as enlarging the storage data or providing different storage performances for specific objects. For instance, you can create a tablespace on a slow disk to contain infrequently accessed objects and tables, keeping fast storage within another tablespace for frequently accessed objects.

You don’t have to make links by yourself: PostgreSQL provides the TABLESPACE feature to manage this and the cluster will create and manage the appropriate links under the pg_tblspc subdirectory.

For instance, the following is a PGDATA directory that has three different tablespaces:

$ ls -l /postgres/16/data/pg_tblspc/
lrwxrwxrwx 1 postgres postgres 22 Jan 19 13:08 16384 -> /data/tablespaces/ts_a
lrwxrwxrwx 1 postgres postgres 22 Jan 19 13:08 16385 -> /data/tablespaces/ts_b
lrwxrwxrwx 1 postgres postgres 22 Jan 19 13:08 16386 -> /data/tablespaces/ts_c

As you can see from the preceding example, there are three tablespaces that are attached to the /data storage. You can inspect them with oid2name and the -s flag:

$ oid2name -s
All tablespaces:
    Oid  Tablespace Name
------------------------
   1663       pg_default
   1664        pg_global
  16384             ts_a
  16385             ts_b
  16386             ts_c

As you can see, the numeric identifiers of the symbolic links are mapped to the mnemonic names of the tablespaces. From the preceding example, you can observe that there are also two particular tablespaces:

  • pg_default is the default tablespace corresponding to “none,” the default storage to be used for every object when nothing is explicitly specified. In other words, every object stored directly under the PGDATA directory is attached to the pg_default tablespace.
  • pg_global is the tablespace used for system-wide objects.

By default, both of the preceding tablespaces refer directly to the PGDATA directory, meaning any cluster without a custom tablespace is totally contained within the PGDATA directory.

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Key benefits

  • Learn the fundamentals of PostgreSQL 16, including SQL statements, replication, and security
  • Enhance your learning journey with the provided Docker images for practical hands-on exercises and tests at the end of each chapter
  • Get new and improved examples, use-cases, and scenarios specifically for concepts like partitioning, replication, back-up and restore, cluster configuration, monitoring and others

Description

The latest edition of this PostgreSQL book will help you to start using PostgreSQL from absolute scratch, helping you to quickly understand the internal workings of the database. With a structured approach and practical examples, go on a journey that covers the basics, from SQL statements and how to run server-side programs, to configuring, managing, securing, and optimizing database performance. This new edition will not only help you get to grips with all the recent changes within the PostgreSQL ecosystem but will also dig deeper into concepts like partitioning and replication with a fresh set of examples. The book is also equipped with Docker images for each chapter which makes the learning experience faster and easier. Starting with the absolute basics of databases, the book sails through to advanced concepts like window functions, logging, auditing, extending the database, configuration, partitioning, and replication. It will also help you seamlessly migrate your existing database system to PostgreSQL and contains a dedicated chapter on disaster recovery. Each chapter ends with practice questions to test your learning at regular intervals. By the end of this book, you will be able to install, configure, manage, and develop applications against a PostgreSQL database.

Who is this book for?

Learning PostgresSQL 16 book is for anyone interested in learning about the PostgreSQL database from scratch. Anyone looking to build robust data warehousing applications and scale the database for high-availability and performance using the latest features of PostgreSQL will also find this book useful. Although prior knowledge of PostgreSQL is not required, familiarity with databases is expected.

What you will learn

  • Gain a deeper understanding of PostgreSQL internals like transactions, MVCC, security and replication
  • Enhance data management with PostgreSQL's latest partitioning features
  • Choose the right replication strategy for your database
  • See concrete examples of how to migrate data from another database, perform backups and restores, monitor your PostgreSQL installation and more
  • Ensure security and compliance with schemas and user privileges
  • Create customized database functions and extensions
  • Get to grips with server-side programming, window functions, and triggers

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Table of Contents

21 Chapters
Introduction to PostgreSQL Chevron down icon Chevron up icon
Getting to Know Your Cluster Chevron down icon Chevron up icon
Managing Users and Connections Chevron down icon Chevron up icon
Basic Statements Chevron down icon Chevron up icon
Advanced Statements Chevron down icon Chevron up icon
Window Functions Chevron down icon Chevron up icon
Server-Side Programming Chevron down icon Chevron up icon
Triggers and Rules Chevron down icon Chevron up icon
Partitioning Chevron down icon Chevron up icon
Users, Roles, and Database Security Chevron down icon Chevron up icon
Transactions, MVCC, WALs, and Checkpoints Chevron down icon Chevron up icon
Extending the Database – the Extension Ecosystem Chevron down icon Chevron up icon
Query Tuning, Indexes, and Performance Optimization Chevron down icon Chevron up icon
Logging and Auditing Chevron down icon Chevron up icon
Backup and Restore Chevron down icon Chevron up icon
Configuration and Monitoring Chevron down icon Chevron up icon
Physical Replication Chevron down icon Chevron up icon
Logical Replication Chevron down icon Chevron up icon
Useful Tools and Extensions Chevron down icon Chevron up icon
Other Books You May Enjoy Chevron down icon Chevron up icon
Index Chevron down icon Chevron up icon

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Arden Feb 01, 2024
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Recently I came across this book after watching Doug Ortiz interview I can vouch this book is no less than a dream out there there has been so much concept clarification and amazing experiences that its been an amazing resource to consider if you are new into this field
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Daniela O Feb 20, 2024
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This book provides detailed review on setting up postgresql. It also provides screenshots of expected outcome that guides the learner on setting up and output of the commands in the book. Highly recommend for anyone looking to learn Postgres sql and how to install the application.
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H2N Nov 12, 2023
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"Learn PostgreSQL" is an in-depth and informative 19-chapter guide covering the entire spectrum of PostgreSQL database management. It traces PostgreSQL's evolution from its Ingres roots in 1986 to the advanced features of PostgreSQL 16. This book, ideal for both novices and experienced administrators, thoroughly explains PostgreSQL's architecture, including Clusters, Postmasters, Backend Processes, and more, with a focus on its native command-line client, PSQL. Its clear, example-laden content is best appreciated with some Linux, Unix, and SQL knowledge. This guide not only makes you proficient in PostgreSQL but also enriches your understanding of RDBMS principles relevant to other databases. A must-read for anyone keen on mastering PostgreSQL and applying it effectively.
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Vivek Verma May 01, 2024
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"Learn PostgreSQL" is a must-have for anyone looking to dive into PostgreSQL.The authors provide a practical guide that walks you through the basics of installation and configuration and advanced topics such as performance tuning and replication. With easy-to-understand explanations and real-world examples, this book is perfect for beginners and experienced users.Key Takeaways :Provides a hands-on approach to learning PostgreSQL.Covers advanced topics such as performance tuning, high availability, and security.Covers both SQL and procedural programming in PostgreSQL.Provides practical tips and best practices for PostgreSQL developers and administrators
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Brady Nov 10, 2023
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I have the digital copy of this book and it is great to quickly search and find an area you want to refresh or dive deeper into. Being able to copy and paste code as a starting point quickly too is great. As mainly a user of T-SQL, this book was easy to follow and get understand the benefits of PostgreSQL and the different syntax.Its comprehensive coverage, practical examples, and strong focus on security make it an indispensable resource for both beginners and experienced professionals. In addition to security, the book covers scalability, performance optimization, and best practices for managing PostgreSQL databases in production environments. Overall great book to have on hand.
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