13 декабря 2021
5 недель
Стоимость курса
499 USD

Big data hadoop

Навыки, которые вы получите:
Hadoop Apache Spark BigData Apache hive Apache pig Apache HBase

Edureka’s extensive Big Data Hadoop training is curated by Hadoop experts, and it covers in-depth knowledge on Big Data and Hadoop Ecosystem tools such as HDFS, YARN, MapReduce, Hive, and Pig. Throughout this online instructor-led Big Data Hadoop certification training, you will be working on real-life industry use cases in Retail, Social Media, Aviation, Tourism, and Finance domains using Edureka’s Cloud Lab. Enroll now in this Big Data Certification to learn Big Data from instructors with over 10+ years of experience, with hands-on demonstrations.

Who is this course for

  • Software Developers, Project Managers.
  • Software Architects.
  • ETL and Data Warehousing Professionals.
  • Data Engineers.
  • Data Analysts & Business Intelligence Professionals.
  • DBAs and DB professionals.
  • Senior IT Professionals.
  • Testing professionals.
  • Mainframe professionals.
  • Graduates looking to build a career in Big Data Field.

Necessary preparation

There are no such prerequisites for Big Data and Hadoop Course. However, prior knowledge of Core Java and SQL will be helpful but is not mandatory. Further, to brush up your skills, Edureka offers a complimentary self-paced course on «Java essentials for Hadoop» when you enroll for the Big Data and Hadoop Course.

The Program

  1. Understanding Big Data and Hadoop.
  2. Hadoop Architecture and HDFS.
  3. Hadoop MapReduce Framework.
  4. Advanced Hadoop MapReduce.
  5. Apache Pig.
  6. Apache Hive.
  7. Advanced Apache HBase.
  8. Processing Distributed Data with Apache Spark.
  9. Oozie and Hadoop Project.
  10. Certification Project.

What will you learn

  • 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.