Book Image

Apache Hive Cookbook

Book Image

Apache Hive Cookbook

Overview of this book

Hive was developed by Facebook and later open sourced in Apache community. Hive provides SQL like interface to run queries on Big Data frameworks. Hive provides SQL like syntax also called as HiveQL that includes all SQL capabilities like analytical functions which are the need of the hour in today’s Big Data world. This book provides you easy installation steps with different types of metastores supported by Hive. This book has simple and easy to learn recipes for configuring Hive clients and services. You would also learn different Hive optimizations including Partitions and Bucketing. The book also covers the source code explanation of latest Hive version. Hive Query Language is being used by other frameworks including spark. Towards the end you will cover integration of Hive with these frameworks.
Table of Contents (19 chapters)
Apache Hive Cookbook
Credits
About the Authors
About the Reviewer
www.PacktPub.com
Preface
Index

Bucketing


Bucketing is a technique that allows you to decompose your data into more manageable parts, that is, fix the number of buckets. Usually, partitioning provides a way of segregating the data of a Hive table into multiple files or directories. Partitioning is used to increase the performance of queries, but the partitioning technique is efficient only if there is a limited number of partitions. Partitioning doesn't perform well if there is a large number of partitions; for example, we are doing partitioning on a column that has large number of unique values, then there will be a large number of partitions.

To overcome the problem of partitioning, Hive provides the concept of bucketing. In bucketing, we specify the fixed number of buckets in which entire data is to be decomposed. Bucketing concept is based on the hashing principle, where same type of keys are always sent to the same bucket.

In bucketing, records with the same bucketed columns will always go to the same bucket. When data...