Apache Hive Tutorial For Beginners | Apache Hive | Big Data Training | Edureka | Big Data Rewind

Описание: 🔥Edureka Big Data Hadoop Certification Training - https://www.edureka.co/big-data-hadoo...
This Edureka video on "Apache Hive Tutorial For Beginners" will provide you with detailed knowledge about Hive and the functionalities it can perform.

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About the Course:

Edureka's Big Data Hadoop Training Course is curated by Hadoop industry experts, and it covers in-depth knowledge on Big Data and Hadoop Ecosystem tools such as HDFS, YARN, MapReduce, Hive, Pig, HBase, Spark, Oozie, Flume and Sqoop. Throughout this online instructor-led Hadoop Training, you will be working on real-life industry use cases in Retail, Social Media, Aviation, Tourism and Finance domain using Edureka's Cloud Lab.

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What are the skills that you will be learning with our Big Data Hadoop Certification Training?

Big Data Hadoop Certification Training will help you to become a Big Data expert. It will hone your skills by offering you comprehensive knowledge on Hadoop framework, and the required hands-on experience for solving real-time industry-based Big Data projects. During Big Data & Hadoop course you will be trained by our expert instructors to:
Master the concepts of HDFS (Hadoop Distributed File System), YARN (Yet Another Resource Negotiator), & understand how to work with Hadoop storage & resource management.
Understand MapReduce Framework
Implement complex business solution using MapReduce
Learn data ingestion techniques using Sqoop and Flume
Perform ETL operations & data analytics using Pig and Hive
Implementing Partitioning, Bucketing and Indexing in Hive
Understand HBase, i.e a NoSQL Database in Hadoop, HBase Architecture & Mechanisms
Integrate HBase with Hive
Schedule jobs using Oozie
Implement best practices for Hadoop development
Understand Apache Spark and its Ecosystem
Learn how to work with RDD in Apache Spark
Work on real-world Big Data Analytics Project
Work on a real-time Hadoop cluster

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For more information, please write back to us at [email protected] or call us at:
IND: 9606058406 / US: 18338555775 (toll free).