Chapter 01, Relational Databases, introduces relational database system concepts, including relational database properties, relational algebra, and database modeling. Also, it describes different database management systems such as graph, document, key value, and columnar databases.
Chapter 02, PostgreSQL in Action, provides first-hand experience of installing the PostgreSQL server and client tools on different platforms. This chapter also introduces PostgreSQL capabilities, such as out-of-the-box replication support and its very rich data types.
Chapter 03, PostgreSQL Basic Building Blocks, provides some coding best practices, such as coding conventions of PostgreSQL and identifier names. This chapter describes the basic building blocks and the interaction between these blocks, mainly template databases, user databases, tablespaces, roles, and settings. Also, it describes basic data types and tables.
Chapter 04, PostgreSQL Advanced Building Blocks, introduces several building blocks, including views, indexes, functions, user-defined data types, triggers, and rules. This chapter provides use cases of these building blocks and compares building blocks that can be used for the same case, such as rules and triggers.
Chapter 05, SQL Language, introduces structured query language (SQL), which is used to interact with a database, create and maintain data structures, and enter data into databases as well as, change it, retrieve it, and delete it. SQL has commands related to data definition language (DDL), data manipulation language (DML), and data control language (DCL). Four SQL statements form the basis of DML and are described in this chapter. The SELECT statement is examined in detail to explain SQL concepts such as grouping and filtering to show what SQL expressions and conditions are and how to use subqueries. Some relational algebra topics are also covered in application to joining tables.
Chapter 06, Advanced Query Writing, describes advanced SQL concepts and features such as common table expressions and window functions. This helps you implement a logic that would not be possible without them, such as recursive queries. Other techniques explained here, such as the DISTINCT ON clause, the FILTER clause, and lateral subqueries, are not irreplaceable. However, they can help make a query smaller, easier, and faster.
Chapter 07, Server-Side Programming with PL/pgSQL, covers function parameters, such as the number of returned rows and function cost, which is mainly used by the query planner. Also, it presents control statements such as conditionals and iteration. Finally, it explains the concept of dynamic SQL and some recommended practices when using dynamic SQL.
Chapter 08, OLAP and Data Warehousing, introduces several concepts regarding the usage of recreational databases in the realm of analytical processing. It discusses the deference between OLTP load and OLAP loads; furthermore, it discusses the modeling aspect of OLAP applications. In addition to that, it discusses some technical methods to perform ETL (extract, transform, and load) operations such as the COPY command. Also, it discusses some features of PostgreSQL which increasing data retrieval performance such as index-only scans and table partitioning.
Chapter 09, Beyond Conventional Data types, discusses several rich data types, including arrays, hash stores, JSON documents, and full-text search. It presents operations and functions for each data type to initialize, insert, update, access, and delete these data types. Finally, it shows how PostgreSQL can be combined with Nginx to serve read-only restful requests.
Chapter 10, Transactions and Concurrency Control, discusses in detail the ACID properties and the relation between these properties and concurrency controls. This chapter also discusses concepts such as isolation levels and their side-effects and it shows these side-effects using SQL examples. Finally, the chapter discusses different locking methods, including pessimistic locking strategies such as row locking and advisory locks.
Chapter 11, PostgreSQL Security, covers concepts of authentication and authorization. It describes PostgreSQL authentication methods and explains the structure of a PostgreSQL host-based authentication configuration file. It also discusses the permissions that can be granted to database building objects such as schemas, tables, views, indexes, and columns. Finally, it shows how sensitive data, such as passwords, can be protected using different techniques, including one-way and two-way encryption.
Chapter 12, The PostgreSQL Catalog, provides several recipes to maintain a database cluster, including cleaning up data, maintaining user processes, cleaning up indexes and unused databases objects, discovering and adding indexes to foreign keys, and so on.
Chapter 13, Optimizing Database Performance, discusses several approaches to optimize performance. It presents PostgreSQL cluster configuration settings, which are used in tuning the whole cluster's performance. Also, it presents common mistakes in writing queries and discusses several approaches to increase performance, such as using indexes or table partitioning and constraint exclusion.
Chapter 14, Testing, covers some aspects of the software testing process and how it can be applied to databases. Unit tests for databases can be written as SQL scripts or stored functions in a database. There are several frameworks that help us write unit tests and process the results of testing.
Chapter 15, Using PostgreSQL in Python Applications, discusses several advanced concepts, such as connection pooling, asynchronous access, and object relational mappers (ORMs). The chapter shows by example how to connect to database, query it, and perform updates using Python. Finally, it introduces different technologies that interact with PostgreSQL, and this gives the developer a broad overview of the state-of-the-art technologies.
Chapter 16, Scalability, discusses the problem of scalability and the CAP theorem in detail. Also, it covers data replication in PostgreSQL, including physical replication and logical replication. Finally, it shows different scaling scenarios and their implementation in PostgreSQL.
