A comprehensive practical guide that walks you through the multiple stages of data management in enterprise and gives you numerous design patterns with appropriate code examples to solve frequent problems in each of these stages. The chapters are organized to mimick the sequential data flow evidenced in Analytics platforms, but they can also be read independently to solve a particular group of problems in the Big Data life cycle. If you are an experienced developer who is already familiar with Pig and is looking for a use case standpoint where they can relate to the problems of data ingestion, profiling, cleansing, transforming, and egressing data encountered in the enterprises. Knowledge of Hadoop and Pig is necessary for readers to grasp the intricacies of Pig design patterns better.Unlike the sequence files, which are accessible onlythroughJava API, Avro files can beaccessedfromother languages suchasC, C++, C#, Ruby, andPython. Usingits uniqueformat for interoperability, the Avro files can be transferred from beingcodewrittenin one language to a different code ... Code. snippets. The following code exampleusesan XML dataset that has MedlinePlus health discussions.
|Title||:||Pig Design Patterns|
|Publisher||:||Packt Publishing Ltd - 2014-04-17|