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Home > Data > Database Administration > PostgreSQL for Data Architects
PostgreSQL for Data Architects
PostgreSQL for Data Architects

PostgreSQL for Data Architects: Discover how to design, develop, and maintain your database application effectively with PostgreSQL

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PostgreSQL for Data Architects

Chapter 2. Server Architecture

In the previous chapter, we saw that starting a PostgreSQL cluster kicks off a few processes. The processes manage quite a bit of file I/O, manage other processes, and deal with memory allocation and a lot of other work. In this chapter, we will focus on the processes and their roles, memory management, and how they work together.

We will start by listing the processes once again. No client is connected to any of the databases yet:

[root@MyCentOS ~]# ps f -U postgres
  PID TTY      STAT   TIME COMMAND
 1918 tty1     S      0:00 /usr/local/pgsql/bin/postgres
 1920 ?        Ss     0:00  \_ postgres: checkpointer process   
 1921 ?        Ss     0:00  \_ postgres: writer process     
 1922 ?        Ss     0:00  \_ postgres: wal writer process   
 1923 ?        Ss     0:00  \_ postgres: autovacuum launcher process 
 1924 ?        Ss     0:00  \_ postgres: stats collector process

Starting with the daemon process

The first process that is started when we start PostgreSQL is /usr/local/pgsql/bin/postgres. This process has quite a few responsibilities such as performing recovery, initializing shared data structures/memory space, and kicking off the mandatory and optional processes. These processes are also referred to as utility processes and include bgwriter, checkpointer, autovacuum launcher, log writer, stats collector process, and so on. The daemon process also listens for connection requests, receives requests for connections from clients, and spawns server processes for the client. It's obvious that the daemon itself is a mandatory process that should be running for a user to connect to the database.

Let's focus on the user connecting-issuing-commands scenario and other pieces should fall in place. The following diagram walks you through the process of how the daemon process receives a connection request and starts (forks) a backend process. The backend...

Understanding the shared buffer

When there are thousands of users trying to read/write data to many different tables, reading from the directories/files (which we saw getting created when we installed PostgreSQL and created a database with a couple of tables) will result in a miserably non-scalable system. The reads and writes will result in searching for many files, opening these files, using fseek() for specific data records, locking, editing, and unlocking. To make this a lot more scalable and faster, the concept of shared buffers (memory area) is introduced. Now, the backend processes are no longer reading from the files and writing to the files, but dealing with buffers or RAM, with significant improvement in performance. The amount of memory to be allocated is decided by the shared_buffers parameter in postgresql.conf. This fixed-size block of shared memory is allocated when the server is started.

It's not this memory chunk alone that is responsible for improving the response...

Checkpoint

Checkpoint is a mandatory process. To understand this, let's discuss blocks. PostgreSQL always reads and writes data in blocks. Consider the emp table. It has just one record. The data in this record should add up to a few bytes; we have the value 1 in the column id, and the value Newname in the column first_name. However, this table will consume 8K in the disk because PostgreSQL works with 8K blocks. A block is also referred to as a page. It is easy to verify that PostgreSQL uses blocks. Ensure that our table has just one record as follows:

SELECT * FROM emp;
 id | first_name 
----+------------
  1 | Newname
(1 row)

Then, we find the filename:

SELECT pg_relation_filepath('emp');
 pg_relation_filepath 
----------------------
 base/24741/24742
(1 row)

Now, we check the size of the file:

\! ls -l /pgdata/9.3/base/24741/24742
-rw-------. 1 postgres postgres 8192 Nov 15 11:33 /pgdata/9.3/base/24741/24742

8192 bytes = 8K. So, a table with just one record takes up 8K.

Let&apos...

WAL and the WAL writer process

When we make changes to the data, the changes are not written to the data files immediately, as mentioned before (probably many times). Changes are made to the blocks in the buffer and records of these changes are written to the WAL buffer (as soon as changes to data are made). The changes are flushed to the WAL segments when the changes are committed.

In the pg_xlog directory, the WAL segments are each 16 MB in size:

[postgres@MyCentOS pg_xlog]$ pwd
/pgdata/9.3/pg_xlog
[postgres@MyCentOS pg_xlog]$ ls -alrt
total 16396
drwx------.  2 postgres postgres     4096 Oct 13 13:23 archive_status
drwx------.  3 postgres postgres     4096 Oct 13 13:23 .
drwx------. 15 postgres postgres     4096 Nov 15 20:17 ..
-rw-------.  1 postgres postgres 16777216 Nov 15 20:17 000000010000000000000001

We can find out the segment PostgreSQL is writing to now using the pg_current_xlog_location function:

[postgres@MyCentOS pg_xlog]$ psql
psql (9.3.0)
Type "help" for help.

postgres...

The background writer

The background writer is responsible for writing to disk specific dirty buffers based on an algorithm, whereas checkpointer writes all dirty buffers. The process takes into consideration shared memory usage data as well as information about which blocks have been used/accessed recently (least recently used). The primary objective of this process is to ensure that free buffers are available for use. The relevant parameters are as follows:

#bgwriter_delay = 200ms                 # 10-10000ms between rounds
#bgwriter_lru_maxpages = 100            # 0-1000 max buffers written/round
#bgwriter_lru_multiplier = 2.0          # 0-10.0 multiplier on buffers scanned/round

As we can see, the default value for delay is 200 milliseconds. This parameter specifies how long the process should wait between successive executions. The bgwriter_lru_maxpages parameter specifies the maximum number of buffers that will be written by the process in each iteration. The third parameter is also...

Starting with the daemon process

The first process that is started when we start PostgreSQL is /usr/local/pgsql/bin/postgres. This process has quite a few responsibilities such as performing recovery, initializing shared data structures/memory space, and kicking off the mandatory and optional processes. These processes are also referred to as utility processes and include bgwriter, checkpointer, autovacuum launcher, log writer, stats collector process, and so on. The daemon process also listens for connection requests, receives requests for connections from clients, and spawns server processes for the client. It's obvious that the daemon itself is a mandatory process that should be running for a user to connect to the database.

Let's focus on the user connecting-issuing-commands scenario and other pieces should fall in place. The following diagram walks you through the process of how the daemon process receives a connection request and starts (forks) a backend process. The backend process...

Understanding the shared buffer

When there are thousands of users trying to read/write data to many different tables, reading from the directories/files (which we saw getting created when we installed PostgreSQL and created a database with a couple of tables) will result in a miserably non-scalable system. The reads and writes will result in searching for many files, opening these files, using fseek() for specific data records, locking, editing, and unlocking. To make this a lot more scalable and faster, the concept of shared buffers (memory area) is introduced. Now, the backend processes are no longer reading from the files and writing to the files, but dealing with buffers or RAM, with significant improvement in performance. The amount of memory to be allocated is decided by the shared_buffers parameter in postgresql.conf. This fixed-size block of shared memory is allocated when the server is started.

It's not this memory chunk alone that is responsible for improving the response times...

Checkpoint

Checkpoint is a mandatory process. To understand this, let's discuss blocks. PostgreSQL always reads and writes data in blocks. Consider the emp table. It has just one record. The data in this record should add up to a few bytes; we have the value 1 in the column id, and the value Newname in the column first_name. However, this table will consume 8K in the disk because PostgreSQL works with 8K blocks. A block is also referred to as a page. It is easy to verify that PostgreSQL uses blocks. Ensure that our table has just one record as follows:

SELECT * FROM emp;
 id | first_name 
----+------------
  1 | Newname
(1 row)

Then, we find the filename:

SELECT pg_relation_filepath('emp');
 pg_relation_filepath 
----------------------
 base/24741/24742
(1 row)

Now, we check the size of the file:

\! ls -l /pgdata/9.3/base/24741/24742
-rw-------. 1 postgres postgres 8192 Nov 15 11:33 /pgdata/9.3/base/24741/24742

8192 bytes = 8K. So, a table with just one record takes up 8K.

Let's try inserting some...

WAL and the WAL writer process

When we make changes to the data, the changes are not written to the data files immediately, as mentioned before (probably many times). Changes are made to the blocks in the buffer and records of these changes are written to the WAL buffer (as soon as changes to data are made). The changes are flushed to the WAL segments when the changes are committed.

In the pg_xlog directory, the WAL segments are each 16 MB in size:

[postgres@MyCentOS pg_xlog]$ pwd
/pgdata/9.3/pg_xlog
[postgres@MyCentOS pg_xlog]$ ls -alrt
total 16396
drwx------.  2 postgres postgres     4096 Oct 13 13:23 archive_status
drwx------.  3 postgres postgres     4096 Oct 13 13:23 .
drwx------. 15 postgres postgres     4096 Nov 15 20:17 ..
-rw-------.  1 postgres postgres 16777216 Nov 15 20:17 000000010000000000000001

We can find out the segment PostgreSQL is writing to now using the pg_current_xlog_location function:

[postgres@MyCentOS pg_xlog]$ psql
psql (9.3.0)
Type "help" for help.

postgres=# SELECT...

The background writer

The background writer is responsible for writing to disk specific dirty buffers based on an algorithm, whereas checkpointer writes all dirty buffers. The process takes into consideration shared memory usage data as well as information about which blocks have been used/accessed recently (least recently used). The primary objective of this process is to ensure that free buffers are available for use. The relevant parameters are as follows:

#bgwriter_delay = 200ms                 # 10-10000ms between rounds
#bgwriter_lru_maxpages = 100            # 0-1000 max buffers written/round
#bgwriter_lru_multiplier = 2.0          # 0-10.0 multiplier on buffers scanned/round

As we can see, the default value for delay is 200 milliseconds. This parameter specifies how long the process should wait between successive executions. The bgwriter_lru_maxpages parameter specifies the maximum number of buffers that will be written by the process in each iteration. The third parameter is also...

The autovacuum launcher process

This is an optional process. There is a parameter called autovacuum in postgresql.conf, with ON as default value. This process automates the execution of vacuum and analyzes commands based on a few parameters. To understand autovacuum, first, we have to understand vacuum.

Assume that we delete a few records from a table. PostgreSQL does not immediately remove the deleted tuples from the data files. These are marked as deleted. Similarly, when a record is updated, it's roughly equivalent to one delete and one insert. The previous version of the record continues to be in the data file. Each update of a database row generates a new version of the row. The reason is simple: there can be active transactions, which want to see the data as it was before. As a result of this activity, there will be a lot of unusable space in the data files. After some time, these dead records become irrelevant as there are no transactions still around to see the old data. However,...

The logging process

This is an optional process and the default setting is off. We have to set the logging_collector parameter to on to start this process:

cd $PGDATA

Edit the postgresql.conf file and make a few changes:

log_destination = 'stderr'
logging_collector = on
log_directory = 'pg_log'
log_min_duration_statement = 0

[postgres@MyCentOS 9.3]$ pg_ctl restart
waiting for server to shut down.... done
server stopped
server starting
[postgres@MyCentOS 9.3]$ ps f -U postgres
  PID TTY      STAT   TIME COMMAND
 2581 pts/2    S      0:00 -bash
 3201 pts/2    R+     0:00  \_ ps f -U postgres
 2218 pts/1    S+     0:00 -bash
 3186 pts/2    S      0:00 /usr/local/pgsql/bin/postgres
 3187 ?        Ss     0:00  \_ postgres: logger process     
 3189 ?        Ss     0:00  \_ postgres: checkpointer process   
 3190 ?        Ss     0:00  \_ postgres: writer process     
 3191 ?        Ss     0:00  \_ postgres: wal writer process   
 3192 ?        Ss     0:00  \_ postgres: autovacuum launcher process...
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Description

This book is for developers and data architects who have some exposure to databases. It is assumed that you understand the basic concepts of tables and common database objects, including privileges and security.

Who is this book for?

This book is for developers and data architects who have some exposure to databases. It is assumed that you understand the basic concepts of tables and common database objects, including privileges and security.

What you will learn

  • Compile PostgreSQL from source and understand the PostgreSQL architecture
  • Configure parameters and change default settings for a PostgreSQL server
  • Leverage the logging mechanism to identify errors and suboptimal queries
  • Use replication to scale horizontally
  • Set up backup and recovery processes
  • Tweak parameters to optimize queries and processes
  • Troubleshoot connection errors
  • Use indexes and rewrite queries to improve performance
  • Install and use PostgreSQL extensions
  • Learn how to leverage the commandline client (psql)
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Publication date, Length, Edition, Language, ISBN-13
Publication date : Mar 30, 2015
Length: 272 pages
Edition : 1st
Language : English
ISBN-13 : 9781783288601
Category :
Data
Concepts :
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Tools :
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Length: 272 pages
Edition : 1st
Language : English
ISBN-13 : 9781783288601
Category :
Data
Concepts :
Database Administration
Tools :
PostgreSQL

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Table of Contents

13 Chapters
1. Installing PostgreSQL Chevron down icon Chevron up icon
1. Installing PostgreSQL
Installation options
Dependencies to compile the source
Configuring and creating the makefile
Building and creating the executables
Installing and moving the files to where they belong
Initializing a cluster
Working with extensions
Summary
2. Server Architecture Chevron down icon Chevron up icon
2. Server Architecture
Starting with the daemon process
Understanding the shared buffer
Checkpoint
WAL and the WAL writer process
The background writer
The autovacuum launcher process
The logging process
The stats collector process
The WAL sender and WAL receiver
Sorting in memory with work_mem
Maintenance with maintenance_work_mem
Summary
3. PostgreSQL – Object Hierarchy and Roles Chevron down icon Chevron up icon
3. PostgreSQL – Object Hierarchy and Roles
The PostgreSQL cluster
Understanding tablespaces
Databases, schemas, and search_path
Roles and privileges
Summary
4. Working with Transactions Chevron down icon Chevron up icon
4. Working with Transactions
Understanding transactions
PostgreSQL and MVCC
Summary
5. Data Modeling with SQL Power Architect Chevron down icon Chevron up icon
5. Data Modeling with SQL Power Architect
Tools for databases and their uses
Database design tools
Generating SQL
Summary
6. Client Tools Chevron down icon Chevron up icon
6. Client Tools
GUI tools and command-line tools
pgAdmin – downloading and installation
psql – working from the command line
Summary
7. SQL Tuning Chevron down icon Chevron up icon
7. SQL Tuning
Understanding basic facts about databases
Query execution components
Finding the execution plan
Optimization guidelines and catches
Summary
8. Server Tuning Chevron down icon Chevron up icon
8. Server Tuning
Server-wide memory settings
Managing writes, connections, and maintenance
Seek/scan cost and statistics parameters
Materialized views
Partitioned tables
Summary
9. Tools to Move Data in and out of PostgreSQL Chevron down icon Chevron up icon
9. Tools to Move Data in and out of PostgreSQL
Setting up the production database – considerations
COPY
Fast loading with pg_bulkload
pg_dump
Filtering options
Summary
10. Scaling, Replication, and Backup and Recovery Chevron down icon Chevron up icon
10. Scaling, Replication, and Backup and Recovery
Scalability
Point-in-time recovery
Summary
11. PostgreSQL – Troubleshooting Chevron down icon Chevron up icon
11. PostgreSQL – Troubleshooting
Connection issues
Authentication and permission issues
Parameter changes not effective
Query not responding
Summary
12. PostgreSQL – Extras Chevron down icon Chevron up icon
12. PostgreSQL – Extras
Interesting data types
Features over time
Summary
Index Chevron down icon Chevron up icon
Index

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Customer reviews

Rating distribution
Full star icon Full star icon Full star icon Full star icon Full star icon 5
(2 Ratings)
5 star 100%
4 star 0%
3 star 0%
2 star 0%
1 star 0%
Geordee Naliyath Jul 07, 2015
Full star icon Full star icon Full star icon Full star icon Full star icon 5
This book gives a good overview of PostgreSQL database. It is an easy read, especially so if you have some background in any other databases. The book is logically organized from the installation steps to advanced topics. Even the process of installation is explained pretty nicely, explaining the internals of the database systems - which is pretty rare in similar books.In the past I have built quite a number of products with PostgreSQL as the backend. I could work with PostgreSQL easily with the general overview and DBMS concepts from other databases. The chapters on server architecture and object hierarchies really helped me to understand PostgreSQL in depth, especially in relation to other databases. As I mentioned earlier, and as the title implies, if you have been a database programmer, administrator or an architect, the details are presented concisely, in a logical order. I should also mention the handy queries and commands in every section, that prompts me to leave the eBook on the desktop.Next two chapters focus on the transactions, data modeling, and client tools which are more beginner-friendly. However, it helps to understand how PostgreSQL implements or supports those features. The book then takes a steep climb to more serious topics such as tuning, administration and scaling.SQL Tuning is quite enjoyable, starting with a few thought-provoking facts and strategies. Each of the tuning tips is well-demonstrated. A better (and consistent) layout would have made it a little more easier to read. The chapter on server tuning is also quite easy to read, especially if you have some similar background from any of the databases.Scaling, Replication, and Backup and Recovery is one of the longest, and toughest chapters. Overlapping concepts from all four topics are distilled here, and it would take some effort from the reader to keep everything in mind, together. A lot of details present here would require additional reading to get a fair understanding and grip on the subject. The book serves the purpose of keeping the concepts together as an overview.PostgreSQL is one database that competes well against the NoSQL data stores. The last chapter gives a glimpse of PostgreSQL’s not-so-conventional capabilities. The books covers PostgreSQL 9.3. Hope that it would be revised with 9.4 or even 9.5 in future, with more details on the newer features available to data architects.Overall a good read, and a book worth keeping.
Amazon Verified review Amazon
Denver Water - Dawson Mar 04, 2016
Full star icon Full star icon Full star icon Full star icon Full star icon 5
Wonderful published book. Great vendor!!
Amazon Verified review Amazon

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Deep Learning with TensorFlow and Keras – 3rd edition
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Oct 2022 698 pages
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Modern Generative AI with ChatGPT and OpenAI Models
Modern Generative AI with ChatGPT and OpenAI Models
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May 2023 286 pages
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Generative AI with LangChain
Generative AI with LangChain
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Dec 2023 368 pages
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Causal Inference and Discovery in Python
Causal Inference and Discovery in Python
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May 2023 456 pages
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About the author

Profile icon Jayadevan M
Jayadevan M
Jayadevan Maymala is a database developer, designer, and architect. He started working with the Oracle database in 1999. Over the years, he has worked with DB2, Sybase, and SQL Server. Of late, he has been working with open source technologies. His database of choice is PostgreSQL. In his career, he has worked in different domains spanning supply chain management, finance, and travel. He has spent an equal amount of time working with databases supporting critical transaction processing systems as well as data warehouses supporting analytical systems. When he is not working on open source technologies, he spends time reading and updating himself on economic and political issues.
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Shipping Details

USA:

'

Economy: Delivery to most addresses in the US within 10-15 business days

Premium: Trackable Delivery to most addresses in the US within 3-8 business days

UK:

Economy: Delivery to most addresses in the U.K. within 7-9 business days.
Shipments are not trackable

Premium: Trackable delivery to most addresses in the U.K. within 3-4 business days!
Add one extra business day for deliveries to Northern Ireland and Scottish Highlands and islands

EU:

Premium: Trackable delivery to most EU destinations within 4-9 business days.

Australia:

Economy: Can deliver to P. O. Boxes and private residences.
Trackable service with delivery to addresses in Australia only.
Delivery time ranges from 7-9 business days for VIC and 8-10 business days for Interstate metro
Delivery time is up to 15 business days for remote areas of WA, NT & QLD.

Premium: Delivery to addresses in Australia only
Trackable delivery to most P. O. Boxes and private residences in Australia within 4-5 days based on the distance to a destination following dispatch.

India:

Premium: Delivery to most Indian addresses within 5-6 business days

Rest of the World:

Premium: Countries in the American continent: Trackable delivery to most countries within 4-7 business days

Asia:

Premium: Delivery to most Asian addresses within 5-9 business days

Disclaimer:
All orders received before 5 PM U.K time would start printing from the next business day. So the estimated delivery times start from the next day as well. Orders received after 5 PM U.K time (in our internal systems) on a business day or anytime on the weekend will begin printing the second to next business day. For example, an order placed at 11 AM today will begin printing tomorrow, whereas an order placed at 9 PM tonight will begin printing the day after tomorrow.


Unfortunately, due to several restrictions, we are unable to ship to the following countries:

  1. Afghanistan
  2. American Samoa
  3. Belarus
  4. Brunei Darussalam
  5. Central African Republic
  6. The Democratic Republic of Congo
  7. Eritrea
  8. Guinea-bissau
  9. Iran
  10. Lebanon
  11. Libiya Arab Jamahriya
  12. Somalia
  13. Sudan
  14. Russian Federation
  15. Syrian Arab Republic
  16. Ukraine
  17. Venezuela