PostgreSQL Advanced Building Blocks | Learning PostgreSQL 10

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Learning PostgreSQL 10 - Second Edition

By : Salahaldin Juba, Andrey Volkov, Sheldon Strauch, Isabel Maria Duarte Rosa

2.3 (6)

Learning PostgreSQL 10

2.3 (6)

By: Salahaldin Juba, Andrey Volkov, Sheldon Strauch, Isabel Maria Duarte Rosa

Overview of this book

PostgreSQL is one of the most popular open source databases in the world, supporting the most advanced features included in SQL standards. This book will familiarize you with the latest features released in PostgreSQL 10. We’ll start with a thorough introduction to PostgreSQL and the new features introduced in PostgreSQL 10. We’ll cover the Data Definition Language (DDL) with an emphasis on PostgreSQL, and the common DDL commands supported by ANSI SQL. You’ll learn to create tables, define integrity constraints, build indexes, and set up views and other schema objects. Moving on, we’ll cover the concepts of Data Manipulation Language (DML) and PostgreSQL server-side programming capabilities using PL/pgSQL. We’ll also explore the NoSQL capabilities of PostgreSQL and connect to your PostgreSQL database to manipulate data objects. By the end of this book, you’ll have a thorough understanding of the basics of PostgreSQL 10 and will have the necessary skills to build efficient database solutions.

Preface

Preface

What this book covers

What you need for this book

Who this book is for

Conventions

Reader feedback

Customer support

Free Chapter

Relational Databases

Relational Databases

Database management systems

Relational and object relational databases

Relational algebra

Data modeling

Summary

PostgreSQL in Action

PostgreSQL in Action

An overview of PostgreSQL

PostgreSQL capabilities

Installing PostgreSQL

Summary

PostgreSQL Basic Building Blocks

PostgreSQL Basic Building Blocks

Database coding

PostgreSQL objects hierarchy

PostgreSQL database components

The car web portal database

Summary

PostgreSQL Advanced Building Blocks

PostgreSQL Advanced Building Blocks

Views

View synopsis

View categories

Updatable views

Indexes

Functions

User-defined data types

Triggers and rule systems

Summary

SQL Language

SQL Language

SQL fundamentals

Querying data with SELECT statements

Changing the data in the database

Summary

Advanced Query Writing

Advanced Query Writing

Common table expressions

Window functions

Advanced SQL techniques

Summary

Server-Side Programming with PL/pgSQL

Server-Side Programming with PL/pgSQL

SQL language and PL/pgSQL – a comparison

PostgreSQL function parameters

The PostgreSQL PL/pgSQL control statements

Function predefined variables

Exception handling

Dynamic SQL

Summary

OLAP and Data Warehousing

OLAP and Data Warehousing

Online analytical processing

Partitioning

Parallel query

Index-only scans

Summary

Beyond Conventional Data Types

Beyond Conventional Data Types

Arrays

The hash store data structure

The JSON data structure

A PostgreSQL full text search

Summary

Transactions and Concurrency Control

Transactions and Concurrency Control

Transactions

Explicit locking

Summary

PostgreSQL Security

PostgreSQL Security

Authentication in PostgreSQL

Authentication best practices

PostgreSQL default access privileges

Role system and proxy authentication

PostgreSQL security levels

Encrypting data

Summary

The PostgreSQL Catalog

The PostgreSQL Catalog

The system catalog

System catalog for administrators

Cleaning up the database

Tuning for performance

Selective dump

Summary

Optimizing Database Performance

Optimizing Database Performance

PostgreSQL configuration tuning

Tuning performance for write

Tuning performance for read

Detecting problems in query plans

Common mistakes in writing queries

Table partitioning

Query rewriting

Summary

Testing

Testing

Unit testing

Database abstraction interfaces

Summary

Using PostgreSQL in Python Applications

Using PostgreSQL in Python Applications

Python DB API 2.0

Low-level database access with psycopg2

Alternative drivers for PostgreSQL

Object relational mapping with SQLAlchemy

Summary

Scalability

Scalability

The problem of scalability and the CAP theorem

Data replication in PostgreSQL

Using replication to scale PostgreSQL

Summary

Indexes

An index is a physical database object that is defined on a table column or a list of columns. In PostgreSQL, there are many types of indexes and several ways to use them. Indexes can be used, in general, to do the following:

Optimize performance: an index allows the efficient retrieval of a small number of rows from the table. Whether or not a number of rows is considered small is determined by the total number of rows in the table and execution planner settings.
Validate constraints: An index can be used to validate the constraints on several rows. For example, the UNIQUE check constraint creates a unique index on the column behind the scenes.

The following example shows how to use GIST to forbid overlapping between date ranges. For more information, have a look at https://www.postgresql.org/docs/current/static/rangetypes.html

CREATE TABLE no_date_overlap (
    date_range daterange,
    EXCLUDE USING GIST (date_range WITH &&)
);

To test date range overlapping:

car_portal=# INSERT...

CONTINUE READING

83

Tech Concepts

36

Programming languages

73

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