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
具体描述
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用户评价
一问一答得方式解决问题，十分简短，个人觉得相当不错。
评分很简短的概述性的入门级书籍，很小巧和实用的SQl to hadOOP工具，方便将关系型数据库和企业级数据仓库中的数据与存放在Hadoop中的数据进行交换，感觉Cloudera将逐步从大数据工具领域中脱颖而出！
评分小巧实用，简明易读
评分很简短的概述性的入门级书籍，很小巧和实用的SQl to hadOOP工具，方便将关系型数据库和企业级数据仓库中的数据与存放在Hadoop中的数据进行交换，感觉Cloudera将逐步从大数据工具领域中脱颖而出！
评分要是能有API编程的相关内容就更好了
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