Book Image

PostgreSQL High Performance Cookbook

By : Chitij Chauhan, Dinesh Kumar
Book Image

PostgreSQL High Performance Cookbook

By: Chitij Chauhan, Dinesh Kumar

Overview of this book

PostgreSQL is one of the most powerful and easy to use database management systems. It has strong support from the community and is being actively developed with a new release every year. PostgreSQL supports the most advanced features included in SQL standards. It also provides NoSQL capabilities and very rich data types and extensions. All of this makes PostgreSQL a very attractive solution in software systems. If you run a database, you want it to perform well and you want to be able to secure it. As the world’s most advanced open source database, PostgreSQL has unique built-in ways to achieve these goals. This book will show you a multitude of ways to enhance your database’s performance and give you insights into measuring and optimizing a PostgreSQL database to achieve better performance. This book is your one-stop guide to elevate your PostgreSQL knowledge to the next level. First, you’ll get familiarized with essential developer/administrator concepts such as load balancing, connection pooling, and distributing connections to multiple nodes. Next, you will explore memory optimization techniques before exploring the security controls offered by PostgreSQL. Then, you will move on to the essential database/server monitoring and replication strategies with PostgreSQL. Finally, you will learn about query processing algorithms.
Table of Contents (19 chapters)
PostgreSQL High Performance Cookbook
Credits
About the Authors
About the Reviewers
www.PacktPub.com
Customer Feedback
Preface

Aggregate and hash aggregate


In this recipe, we will be discussing aggregate and hash aggregate mechanisms in PostgreSQL.

Getting ready

Aggregate is a node type that only evaluates the aggregate operators. Some of the aggregate operators are SUM, MIN, MAX, and so on.

Hash aggregate is a node type that requires an aggregate operator, and a group key column. In general, we see this node type being utilized during the GROUP BY, DISTINCT, or set operations.

How to do it…

Aggregate

  1. To demonstrate the aggregates behavior, let's query the benchmarsql as follows:

    benchmarksql=# EXPLAIN SELECT max(i_price) FROM bmsql_item;
                                   QUERY PLAN                               
    ------------------------------------------------------------------------
    
    Aggregate
      (cost=2549.00..2549.01 rows=1 width=6)
       ->  Seq Scan on bmsql_item  (cost=0.00..2299.00 rows=100000
              width=6)
    (2 rows)
    
  2. From the preceding plan, as expected we got the aggregate node type, which is followed by...