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Apache Hive Cookbook

Apache Hive Cookbook

By : Hanish Bansal, Saurabh Chauhan, Shrey Mehrotra
3 (4)
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Apache Hive Cookbook

Apache Hive Cookbook

3 (4)
By: Hanish Bansal, Saurabh Chauhan, Shrey Mehrotra

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 (14 chapters)
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13
Index

Serialization and deserialization formats and data types


Serialization and deserialization formats are popularly known as SerDes. Hive allows the framework to read or write data in a particular format. These formats parse the structured or unstructured data bytes stored in HDFS in accordance with the schema definition of Hive tables. Hive provides a set of in-built SerDes and also allows the user to create custom SerDes based on their data definition. These are as follows:

  • LazySimpleSerDe

  • RegexSerDe

  • AvroSerDe

  • OrcSerde

  • ParquetHiveSerDe

  • JSONSerDe

  • CSVSerDe

How to do it…

You can use different types of SerDes for reading or writing the data in a particular format.

LazySimpleSerDe

This is the default SerDes format of Hive. When a user creates a table in Hive without any explicit SerDes definition, LazySimpleSerDe gets associated with the table. LazySimpleSerDe takes line feed (\n) as the record separator and tab ('\t') as the attribute (column) delimiter. It parse the data bytes it receives from HDFS and...

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