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Learn Hadoop for best career opportunities in business analytics
Hadoop is an Apache project (i.e. an open source software) to store & process Big Data. Hadoop stores Big Data in a distributed & fault tolerant manner over commodity hardware. Afterwards, Hadoop tools are used to perform parallel data processing over HDFS (Hadoop Distributed File System).
As organisations have realized the benefits of Big Data Analytics, so there is a huge demand for Big Data & Hadoop professionals. Companies are looking for Big data & Hadoop experts with the knowledge of Hadoop Ecosystem and best practices about HDFS, MapReduce, Spark, HBase, Hive, Pig, Oozie, Sqoop & Flume.
Need for Big Data
Distributed Cache
Distributed Cache (contd.)
Joins in MapReduce
Introduction to Pig
Components of Pig
Data Model
Pig vs. SQL
Prerequisites to Set the Environment for Pig Latin
Summary
Lesson 2 - Hive HBase and Hadoop Ecosystem Components
Introduction to Mahout
Usage of Mahout
Apache Cassandra
Apache Spark
Apache Ambari
Key Features of Apache Ambari
Hadoop Security—Kerberos
Summary
ICIT Course Completion Certificate will be awarded upon the completion of the project work (after the expert review) and upon scoring at least 50% marks in the quiz. ICIT certification is well recognized in top MNCs .
The market for Big Data analytics is growing across the world and this strong growth pattern translates into a great opportunity for all the IT Professionals. Hiring managers are looking for certified Big Data Hadoop professionals. Our Big Data & Hadoop Certification Training helps you to grab this opportunity and accelerate your career. Our Big Data Hadoop Course can be pursued by professional as well as freshers. It is best suited for:
For pursuing a career in Data Science, knowledge of Big Data, Apache Hadoop & Hadoop tools are necessary.
1. Explain “Big Data” and what are five V’s of Big Data?
“Big data” is the term for a collection of large and complex data sets, that makes it difficult to process using relational database management tools or traditional data processing applications. It is difficult to capture, curate, store, search, share, transfer, analyze, and visualize Big data. Big Data has emerged as an opportunity for companies. Now they can successfully derive value from their data and will have a distinct advantage over their competitors with enhanced business decisions making capabilities.
♣ Tip: It will be a good idea to talk about the 5Vs in such questions, whether it is asked specifically or not!
2. What is Hadoop and its components.
When “Big Data” emerged as a problem, Apache Hadoop evolved as a solution to it. Apache Hadoop is a framework which provides us various services or tools to store and process Big Data. It helps in analyzing Big Data and making business decisions out of it, which can’t be done efficiently and effectively using traditional systems.
♣ Tip: Now, while explaining Hadoop, you should also explain the main components of Hadoop, i.e.:
3. What are HDFS and YARN?
HDFS (Hadoop Distributed File System) is the storage unit of Hadoop. It is responsible for storing different kinds of data as blocks in a distributed environment. It follows master and slave topology.
♣ Tip: It is recommended to explain the HDFS components too i.e.
YARN (Yet Another Resource Negotiator) is the processing framework in Hadoop, which manages resources and provides an execution environment to the processes.
♣ Tip: Similarly, as we did in HDFS, we should also explain the two components of YARN:
4. Tell me about the various Hadoop daemons and their roles in a Hadoop cluster.
Generally approach this question by first explaining the HDFS daemons i.e. NameNode, DataNode and Secondary NameNode, and then moving on to the YARN daemons i.e. ResorceManager and NodeManager, and lastly explaining the JobHistoryServer.
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