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Coles Apache Sqoop Cookbook: Unlocking Hadoop For Your Relational Database at Bayshore Shopping Centre in Ottawa, ON
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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
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
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