Hadoop Ecosystem | Hadoop Ecosystem Tutorial | Hadoop Tutorial For Beginners | Simplilearn



This Hadoop tutorial will help you understand the different tools present in the Hadoop ecosystem. This Hadoop video will take you through an overview of the important tools of Hadoop ecosystem which include Hadoop HDFS, Hadoop Pig, Hadoop Yarn, Hadoop Hive, Apache Spark, Mahout, Apache Kafka, Storm, Sqoop, Apache Ranger, Oozie and also discuss the architecture of these tools. It will cover the different tasks of Hadoop such as data storage, data processing, cluster resource management, data ingestion, machine learning, streaming and more. Now, let us get started and understand each of these tools in detail.

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Below topics are explained in this Hadoop ecosystem tutorial:
1. What is Hadoop ecosystem? (00:13)
1. Pig (Scripting) (10:56)
2. Hive (SQL queries) (12:56)
3. Apache Spark (Real-time data analysis) (14:40)
4. Mahout (Machine learning) (17:07)
5. Apache Ambari (Management and monitoring) (18:17)
6. Kafka & Storm (Streaming) (19:17)
7. Apache Ranger & Apache Knox (Security) (20:47)
8. Oozie (Workflow system) (22:42)
9. Hadoop MapReduce (Data processing) (03:38)
10. Hadoop Yarn (Cluster resource management) (02:29)
11. Hadoop HDFS (Data storage) (00:40)
12. Sqoop & Flume (07:37)

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Simplilearn’s Big Data Hadoop training course lets you master the concepts of the Hadoop framework and prepares you for Cloudera’s CCA175 Big data certification. With our online Hadoop training, you’ll learn how the components of the Hadoop ecosystem, such as Hadoop 3.4, Yarn, MapReduce, HDFS, Pig, Impala, HBase, Flume, Apache Spark, etc. fit in with the Big Data processing lifecycle. Implement real life projects in banking, telecommunication, social media, insurance, and e-commerce on CloudLab.

What is this Big Data Hadoop training course about?
The Big Data Hadoop and Spark developer course have been designed to impart an in-depth knowledge of Big Data processing using Hadoop and Spark. The course is packed with real-life projects and case studies to be executed in the CloudLab.

What are the course objectives?
This course will enable you to:
1. Understand the different components of Hadoop ecosystem such as Hadoop 2.7, Yarn, MapReduce, Pig, Hive, Impala, HBase, Sqoop, Flume, and Apache Spark
2. Understand Hadoop Distributed File System (HDFS) and YARN as well as their architecture, and learn how to work with them for storage and resource management
3. Understand MapReduce and its characteristics, and assimilate some advanced MapReduce concepts
4. Get an overview of Sqoop and Flume and describe how to ingest data using them
5. Create database and tables in Hive and Impala, understand HBase, and use Hive and Impala for partitioning
6. Understand different types of file formats, Avro Schema, using Arvo with Hive, and Sqoop and Schema evolution
7. Understand Flume, Flume architecture, sources, flume sinks, channels, and flume configurations
8. Understand HBase, its architecture, data storage, and working with HBase. You will also understand the difference between HBase and RDBMS
9. Gain a working knowledge of Pig and its components
10. Do functional programming in Spark
11. Understand resilient distribution datasets (RDD) in detail
12. Implement and build Spark applications
13. Gain an in-depth understanding of parallel processing in Spark and Spark RDD optimization techniques

Who should take up this Big Data and Hadoop Certification Training Course?
1. Software Developers and Architects
2. Analytics Professionals
3. Senior IT professionals
4. Testing and Mainframe professionals
5. Data Management Professionals
6. Business Intelligence Professionals
7. Project Managers
8. Aspiring Data Scientists

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8 thoughts on “Hadoop Ecosystem | Hadoop Ecosystem Tutorial | Hadoop Tutorial For Beginners | Simplilearn”
  1. That's a quite informative video about Hadoop & I got a clear picture about Hadoop. Thanks for that. I'm also wondering that being a Linux server admin how's d career of hadoop admin & future. Specially in India?

  2. Do you have any questions on this topic? Please share your feedback in the comment section below and we'll have our experts answer it for you. Thanks for watching the video. Cheers!

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