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Hbase Essentials

Hbase Essentials

By : Garg
3.5 (2)
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Hbase Essentials

Hbase Essentials

3.5 (2)
By: Garg

Overview of this book

This book is intended for developers and Big Data engineers who want to know all about HBase at a hands-on level. For in-depth understanding, it would be helpful to have a bit of familiarity with HDFS and MapReduce programming concepts with no prior experience with HBase or similar technologies. This book is also for Big Data enthusiasts and database developers who have worked with other NoSQL databases and now want to explore HBase as another futuristic, scalable database solution in the Big Data space.
Table of Contents (9 chapters)
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The Hadoop ecosystem client


So far, we discussed that HBase clients which work in the interactive mode are synchronous in nature. For batch processing that runs background work such as building search indexes, building statistical data for reporting needs, and so on, a Hadoop ecosystem client such as Hive is used.

Note

The Hadoop MapReduce framework is used to process a large scale of data. For these MapReduce jobs, Hbase can be used in variety of ways such as data source or target or both. This section does not talk about MapReduce usage as it is already covered in the previous chapter.

Hive

Hive is a data warehouse infrastructure built on top of Hadoop. Hive provides a SQL-like query language called HiveQL that allows querying the semi-structured data stored in Hadoop. This query is converted into a MapReduce job and is executed as a MapReduce cluster. These jobs, like any other MR (MapReduce) job, can read and process data other than the Hive table stored on HDFS. In Hive, tables can be defined...

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