Book Image

Modern Big Data Processing with Hadoop

By : V Naresh Kumar, Manoj R Patil, Prashant Shindgikar
Book Image

Modern Big Data Processing with Hadoop

By: V Naresh Kumar, Manoj R Patil, Prashant Shindgikar

Overview of this book

The complex structure of data these days requires sophisticated solutions for data transformation, to make the information more accessible to the users.This book empowers you to build such solutions with relative ease with the help of Apache Hadoop, along with a host of other Big Data tools. This book will give you a complete understanding of the data lifecycle management with Hadoop, followed by modeling of structured and unstructured data in Hadoop. It will also show you how to design real-time streaming pipelines by leveraging tools such as Apache Spark, and build efficient enterprise search solutions using Elasticsearch. You will learn to build enterprise-grade analytics solutions on Hadoop, and how to visualize your data using tools such as Apache Superset. This book also covers techniques for deploying your Big Data solutions on the cloud Apache Ambari, as well as expert techniques for managing and administering your Hadoop cluster. By the end of this book, you will have all the knowledge you need to build expert Big Data systems.
Table of Contents (12 chapters)

Supported datatypes

The following datatypes are supported by Hive version 0.14:

Datatype group Datatype Format
String STRING column_name STRING
VARCHAR column_name VARCHAR(max_length)
CHAR column_name CHAR(length)
Numeric TINYINT column_name TINYINT
INT column_name INT
BIGINT column_name BIGINT
FLOAT column_name FLOAT
DOUBLE column_name DOUBLE
DECIMAL column_name DECIMAL[(precision[,scale])]
Date/time type TIMESTAMP column_name TIMESTAMP
DATE column_name DATE
INTERVAL column_name INTERVAL year to month
Miscellaneous type BOOLEAN column_name BOOLEAN
BINARY column_name BINARY
Complex type ARRAY column_name ARRAY < type >
MAPS column_name MAP < primitive_type, type >
STRUCT column_name STRUCT < name : type [COMMENT 'comment_string'] >
UNION column_name UNIONTYPE <int, double, array...