By Benjamin Bengfort,Jenny Kim
Ready to exploit statistical and machine-learning ideas throughout huge facts units? This functional consultant indicates you why the Hadoop surroundings is ideal for the activity. rather than deployment, operations, or software program improvement frequently linked to allotted computing, you’ll concentrate on specific analyses you could construct, the information warehousing innovations that Hadoop offers, and better order information workflows this framework can produce.
Data scientists and analysts will practice quite a lot of thoughts, from writing MapReduce and Spark functions with Python to utilizing complicated modeling and information administration with Spark MLlib, Hive, and HBase. You’ll additionally find out about the analytical approaches and knowledge structures on hand to construct and empower info items which may handle—and truly require—huge quantities of data.
- Understand middle strategies in the back of Hadoop and cluster computing
- Use layout styles and parallel analytical algorithms to create dispensed facts research jobs
- Learn approximately info administration, mining, and warehousing in a disbursed context utilizing Apache Hive and HBase
- Use Sqoop and Apache Flume to ingest info from relational databases
- Program complicated Hadoop and Spark functions with Apache Pig and Spark DataFrames
- Perform laptop studying innovations corresponding to type, clustering, and collaborative filtering with Spark’s MLlib
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Additional resources for Data Analytics with Hadoop: An Introduction for Data Scientists
Data Analytics with Hadoop: An Introduction for Data Scientists by Benjamin Bengfort,Jenny Kim