Data Analytics with Hadoop (eBook, ePUB) - Bengfort, Benjamin
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  • Format: ePub

Ready to use statistical and machine-learning techniques across large data sets? This practical guide shows you why the Hadoop ecosystem is perfect for the job. Instead of deployment, operations, or software development usually associated with distributed computing, youll focus on particular analyses you can build, the data warehousing techniques that Hadoop provides, and higher order data workflows this framework can produce.Data scientists and analysts will learn how to perform a wide range of techniques, from writing MapReduce and Spark applications with Python to using advanced modeling…mehr

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Produktbeschreibung
Ready to use statistical and machine-learning techniques across large data sets? This practical guide shows you why the Hadoop ecosystem is perfect for the job. Instead of deployment, operations, or software development usually associated with distributed computing, youll focus on particular analyses you can build, the data warehousing techniques that Hadoop provides, and higher order data workflows this framework can produce.Data scientists and analysts will learn how to perform a wide range of techniques, from writing MapReduce and Spark applications with Python to using advanced modeling and data management with Spark MLlib, Hive, and HBase. Youll also learn about the analytical processes and data systems available to build and empower data products that can handleand actually requirehuge amounts of data.Understand core concepts behind Hadoop and cluster computingUse design patterns and parallel analytical algorithms to create distributed data analysis jobsLearn about data management, mining, and warehousing in a distributed context using Apache Hive and HBaseUse Sqoop and Apache Flume to ingest data from relational databasesProgram complex Hadoop and Spark applications with Apache Pig and Spark DataFramesPerform machine learning techniques such as classification, clustering, and collaborative filtering with Sparks MLlib

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Autorenporträt
Jenny Kim is an experienced big data engineer who works in both commercial software efforts as well as in academia. She has significant experience in working with large scale data, machine learning, and Hadoop implementations in production and research environments. Jenny (with Benjamin Bengfort) previously built a large scale recommender system that used a web crawler to gather ontological information about apparel products and produce recommendations from transactions. Currently, she is working with the Hue team at Cloudera, to help build intuitive interfaces for analyzing big data with Hadoop.