Apache Sqoop Cookbook

Kathleen Ting

ISBN 10: 1449364624 / ISBN 13: 9781449364625

Verlag: O Reilly Media, 2013

Beschreibung

2013. 1st Edition. Paperback. Integrating data from multiple sources is essential in the age of big data, but it can be a challenging and time-consuming task. This handy cookbook provides dozens of ready-to-use recipes for using Apache Sqoop, the command-line interface application that optimizes data transfers between relational databases and Hadoop Num Pages: 94 pages, black & white illustrations, black & white tables. BIC Classification: UN. Category: (XV) Technical / Manuals. Dimension: 234 x 177 x 6. Weight in Grams: 184. . . . . . Books ship from the US and Ireland.

Bestandsnummer des Verkäufers V9781449364625

Bibliografische Details

• Titel: Apache Sqoop Cookbook
• Verlag: O Reilly Media
• Erscheinungsjahr: 2013
• Sprache: Englisch
• ISBN-10: 1449364624
• ISBN-13: 9781449364625
• Einband: Softcover
• Zustand: New

Über diesen Titel

Inhaltsangabe

Integrating data from multiple sources is essential in the age of big data, but it can be a challenging and time-consuming task. This handy cookbook provides dozens of ready-to-use recipes for using Apache Sqoop, the command-line interface application that optimizes data transfers between relational databases and Hadoop.

Sqoop is both powerful and bewildering, but with this cookbook's problem-solution-discussion format, you'll quickly learn how to deploy and then apply Sqoop in your environment. The authors provide MySQL, Oracle, and PostgreSQL database examples on GitHub that you can easily adapt for SQL Server, Netezza, Teradata, or other relational systems.

• Transfer data from a single database table into your Hadoop ecosystem
• Keep table data and Hadoop in sync by importing data incrementally
• Import data from more than one database table
• Customize transferred data by calling various database functions
• Export generated, processed, or backed-up data from Hadoop to your database
• Run Sqoop within Oozie, Hadoop's specialized workflow scheduler
• Load data into Hadoop's data warehouse (Hive) or database (HBase)
• Handle installation, connection, and syntax issues common to specific database vendors

Über die Autorin bzw. den Autor

Kathleen Ting is currently a Customer Operations Engineering Manager at Cloudera where she helps customers deploy and use the Hadoop ecosystem in production. She has spoken on Hadoop, ZooKeeper, and Sqoop at many Big Data conferences including Hadoop World, ApacheCon, and OSCON. She's contributed to several projects in the open source community and is a Committer and PMC Member on Sqoop. Jarek Jarcec Cecho is currently a Software Engineer at Cloudera where he develops software to help customers better access and integrate with the Hadoop ecosystem. He has led the Sqoop community in the architecture of the next generation of Sqoop, known as Sqoop 2. He's contributed to several projects in the open source community and is a Committer and PMC Member on Sqoop, Flume, and MRUnit.