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Design, build, and execute effective big data strategies with advanced Hadoop concepts

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Big-Data-Processing-with-Hadoop---A-Complete-Reference-Guide

Design, build, and execute effective big data strategies with advanced Hadoop concepts Apache Hadoop is one of the most popular big data solutions for distributed storage and data processing. This Learning Path will empower you to easily build solutions with Hadoop, along with a host of other big data tools.

This Hadoop book begins by helping you gain complete understanding of data life cycle management. You’ll learn how to design real-time streaming pipelines by using Apache Spark and build efficient enterprise search solutions using Elasticsearch. You’ll also understand how you can visualize your data using tools such as Apache Superset. Through this Learning Path, you’ll get well versed with techniques for deploying your big data solutions on the cloud using Apache Ambari to manage and administer your Hadoop cluster. As you advance, you’ll even discover how to address common challenges like using Kafka efficiently, designing low latency, and handling high data volumes.

By the end of this Learning Path, you’ll have a complete understanding of how components in the Hadoop ecosystem are effectively integrated to implement a fast and reliable data pipeline

What You Will Learn

Develop enterprise-grade applications using Apache Spark and Flink Create Hadoop data pipelines with security, monitoring, and data governance Explore Hadoop security, including authorization and authentication Design streaming data pipelines and build your own search solutions Plan, set up, and administer your own Hadoop cluster Build analytics solutions and visualize them with Apache Superset

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