Book Image

Apache Hive Essentials. - Second Edition

By : Dayong Du
Book Image

Apache Hive Essentials. - Second Edition

By: Dayong Du

Overview of this book

In this book, we prepare you for your journey into big data by frstly introducing you to backgrounds in the big data domain, alongwith the process of setting up and getting familiar with your Hive working environment. Next, the book guides you through discovering and transforming the values of big data with the help of examples. It also hones your skills in using the Hive language in an effcient manner. Toward the end, the book focuses on advanced topics, such as performance, security, and extensions in Hive, which will guide you on exciting adventures on this worthwhile big data journey. By the end of the book, you will be familiar with Hive and able to work effeciently to find solutions to big data problems
Table of Contents (12 chapters)

Buckets

Besides partition, the bucket is another technique to cluster datasets into more manageable parts to optimize query performance. Different from a partition, a bucket corresponds to segments of files in HDFS. For example, the employee_partitioned table from the previous section uses year and month as the top-level partition. If there is a further request to use employee_id as the third level of partition, it creates many partition directories. For instance, we can bucket the employee_partitioned table using employee_id as a bucket column. The value of this column will be hashed by a user-defined number of buckets. The records with the same employee_id will always be stored in the same bucket (segment of files). The bucket columns are defined by CLUSTERED BY keywords. It is quite different from partition columns since partition columns refer to the directory, while bucket...