English | March 5, 2018 | ASIN: B07B8FCYTX | 114 Pages | PDF | 2 MB
Hive allows you to take data in Hadoop, apply a fixed external schema, and query the data with an SQL-like language. With Hive, complex queries can yield simpler, more effectively visualized results. Author Elton Stoneman uses Hive Succinctly to introduce the core principles of Hive and guides readers through mapping Hadoop and HBase data in Hive, writing complex queries in HiveQL, and running custom code inside Hive queries using a variety of languages. With this e-book, getting the most out of big data and Hadoop has never been easier.
Hive is a data warehouse for Big Data. It allows you to take unstructured, variable data in Hadoop, apply a fixed external schema, and query the data with an SQL-like language. Hive abstracts the complexity of writing and running map/reduce jobs in Hadoop, presenting a familiar and accessible interface for Big Data.
Hadoop is the most popular framework for storing and processing very large quantities of data. It runs on a cluster of machines-at the top end of the scale are Hadoop deployments running across thousands of servers, storing petabytes of data. With Hadoop, you query data using jobs that can be broken up into tasks and distributed around the cluster. These map/reduce tasks are powerful, but they are complex, even for simple queries.