Download Apache Sqoop Cookbook: Unlocking Hadoop for Your Relational by Kathleen Ting, Jarek Jarcec Cecho PDF
By Kathleen Ting, Jarek Jarcec Cecho
Integrating facts from a number of resources is vital within the age of huge facts, however it could be a not easy and time-consuming activity. this convenient cookbook offers dozens of ready-to-use recipes for utilizing Apache Sqoop, the command-line interface software that optimizes information transfers among relational databases and Hadoop. Sqoop is either robust and bewildering, yet with this cookbook's problem-solution-discussion layout, you are going to speedy the way to installation after which observe Sqoop on your atmosphere. The authors supply MySQL, Oracle, and PostgreSQL database examples on GitHub that you should simply adapt for SQL Server, Netezza, Teradata, or different relational structures.
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Additional info for Apache Sqoop Cookbook: Unlocking Hadoop for Your Relational Database
This feature is not available on all database systems nor supported by all Sqoop connectors. Currently it’s available only for Oracle and nondirect MySQL exports. Each database implements the upsert feature a bit differently. With Oracle, Sqoop uses a MERGE statement that specifies an entire condition for distinguishing whether an insert or update operation should be performed. With MySQL, Sqoop uses an ON DUPLICATE KEY UPDATE clause that does not accept any user-specified conditions; it decides whether to update or insert based on the table’s unique key.
Therefore, new rows are not exported in update mode at all. 5. Updating or Inserting at the Same Time Problem You have data in your database from a previous export, but now you need to propagate updates from Hadoop. Unfortunately, you can’t use the update mode, as you have a considerable number of new rows and you need to export them as well. Solution If you need both updates and inserts in the same job, you can activate the so-called upsert mode with the --update-mode allowinsert parameter. com/sqoop \ --username sqoop \ --password sqoop \ --table cities \ --update-key id \ --update-mode allowinsert Discussion The ability to conditionally insert a new row or update an existing one is an advanced database feature known as upsert.
Some codecs do not support seeking to the middle of the compressed file without reading all previous content, effectively preventing Hadoop from processing the input files in a parallel manner. You should use a splittable codec for data that you’re planning to use in subsequent processing. Table 2-2 contains a list of splittable and nonsplittable compression codecs that will help you choose the proper codec for your use case. Table 2-2. 7. Speeding Up Transfers Problem Sqoop is a great tool, and it’s processing bulk transfers very well.