Download Apache Sqoop Cookbook: Unlocking Hadoop for Your Relational by Kathleen Ting, Jarek Jarcec Cecho PDF

By Kathleen Ting, Jarek Jarcec Cecho

Integrating information from a number of resources is key within the age of huge facts, however it could be a not easy and time-consuming job. this convenient cookbook offers dozens of ready-to-use recipes for utilizing Apache Sqoop, the command-line interface software that optimizes facts transfers among relational databases and Hadoop. Sqoop is either strong and bewildering, yet with this cookbook's problem-solution-discussion layout, you are going to speedy install after which follow Sqoop on your surroundings. The authors supply MySQL, Oracle, and PostgreSQL database examples on GitHub so you might simply adapt for SQL Server, Netezza, Teradata, or different relational structures.

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Extra resources for Apache Sqoop Cookbook: Unlocking Hadoop for Your Relational Database

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2. Inserting Data in Batches Problem While Sqoop’s export feature fits your needs, it’s too slow. It seems that each row is inserted in a separate insert statement. Is there a way to batch multiple insert statements together? Solution Tailored for various databases and use cases, Sqoop offers multiple options for inserting more than one row at a time. com/sqoop \ --username sqoop \ --password sqoop \ --table cities \ --export-dir cities The default values can vary from connector to connector. transaction properties.

Info CHAPTER 5 Export The previous three chapters had one thing in common: they described various use cases of transferring data from a database server to the Hadoop ecosystem. What if you have the opposite scenario and need to transfer generated, processed, or backed-up data from Hadoop to your database? Sqoop also provides facilities for this use case, and the fol‐ lowing recipes in this chapter will help you understand how to take advantage of this feature. 1. Transferring Data from Hadoop Problem You have a workflow of various Hive and MapReduce jobs that are generating data on a Hadoop cluster.

The implementation may vary from database to database. Whereas some database drivers use the ability to send multiple rows to remote databases inside one request to achieve better performance, others might simply send each query separately. Some drivers cause even worse performance when running in batch mode due to the extra overhead in‐ troduced by serializing the row in internal caches before sending it row by row to the database server. The second method of batching multiple rows into the same query is by specifying multiple rows inside one single insert statement.

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