Part 2. Data logistics
If you’ve been thinking about how to work with Hadoop in production settings, this part of the book covers the first two hurdles you’ll need to jump. These chapters detail the often-overlooked yet crucial topics that deal with data management in Hadoop.
Chapter 2 looks at ways to manage moving large quantities of data into and out of Hadoop. Examples include working with relational data in RDBMSs, structured files, and HBase.
The focus of chapter 3 is on ways to work with data stored in different formats, such as XML and JSON, which paves the way to a broader examination of data formats such as Thrift and Avro that work best with big data and Hadoop.
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