Hadoop Training and Certification in Mumbai | Sulekha

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    Hadoop Training in Mumbai as on Feb 24, 2018

    1. Sun Infosystems, Thane West

      9 Reviews 6.8 Sulekha Score
      +91 22 33854557
      Hadoop Training, Big data & Hadoop training

      No. 303, Sameer Arcad, Station Road, Jamli Naka, Thane West, Mumbai - 400601 Get Directions

    2. Net Tech India, Thane

      47 Reviews 7.5 Sulekha Score
      +91 22 33486971
      Hadoop Training, Informatica training

      Ratnamani Building ,No. 203, Dada Patil Wadi, Thane, Mumbai - 400601 Get Directions

    3. RV Technology, Vashi

      3 Reviews 6.3 Sulekha Score
      +91 22 49433884
      Hadoop Training, Big data & Hadoop training

      Aditi Apartment ,F-1/ C-3 ,Sector 9, Sector 9, Vashi, Mumbai - 400703 Get Directions

    4. Sun Infosystems, Chembur

      4 Reviews 6.9 Sulekha Score
      +91 22 33292892
      Hadoop Training, Business intelligence & analytics training

      No. 201, 2nd Floor, Bhairav Krupa Building, Chembur Station Road, Chembur East, Chembur, Mumbai - 400071

    5. IIHT Vashi Navi Mumbai, Vashi

      43 Reviews 7.6 Sulekha Score
      +91 22 33486003
      Hadoop Training, Big data & Hadoop training

      Havare Fantasia Business Park ,F-190, 1st Floor, Sector 30A, Vashi, Mumbai - 400703 Get Directions

    6. SIT Computer Institute, Airoli

      24 Reviews 6.7 Sulekha Score
      +91 22 33488277
      Hadoop Training, SAS training

      No. H-133, Sector 3, Airoli, Mumbai - 400708 Get Directions

    7. +91 22 33486847
      Hadoop Training, Informatica training

      Sai Arcade, B-Wing, 2nd Floor, No. 213/216, Plot No.184, Panvel Bus Depot, Panvel, Mumbai - 410206

    8. +91 22 49468487
      Hadoop Training, SAS training

      House No C 534,Sector No 2, Airoli, Mumbai - 400708 Get Directions

    9. Techdata Solution, Kurla West

      49 Reviews 7.9 Sulekha Score
      +91 97020 66624
      Hadoop Training, SAS training

      G11, kohinoor mall, kamani, Kurla West, Mumbai - 400070 Get Directions

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    • Hadoop Training FAQ

      • What you will learn In This Course?

        The objective of this course are as follows:

        • Learning how to install a Hadoop cluster from scratch
        • Understanding all the key concepts for Big Data and Hadoop
        • A broad understanding of all MapReduce concepts
        • Understanding how to write programs in MapReduce
        • Understanding how Hadoop Works
        • Being able to work around the complex architecture of Hadoop
        • Being able to use Hive and Pig
        • Being able to design a data pipeline with the help of Pig and Hive
      • What are the pre-requisites?

        There aren't any specific pre-requisites for learning Hadoop but a candidate with basic knowledge in Java, UNIX and SQL will have a head start. Students should also be familiar with loops, variable and objects.

      • What is the course duration of Hadoop training?

        The course duration for this training course will vary depending upon the requirements of the candidate. Most institutes create courses which are tailor made to suit the needs of everyone.

        • Weekday Training4 Weeks (1.5 hours/class)
        • Weekend Training6 Weekends (2.5 hours/class)
        • Fast track training 1 week (5 hours/class)

      Hadoop Course Contents

      Introduction to Big Data

      • Big Data Overview
      • Hadoop vs traditional systems
      • Types of Data
      • Attributes used in Big Data
      • Limitations of existing data analytics

      Hadoop Ecosystem

      • Hadoop Ecosystem overview
      • Hadoop features
      • Hadoop storage
      • HDFS
      • MapReduce Framework
      • Hadoop processing
      • Existing data analytics architecture

      Configuration and installation of Hadoop

      • Installing Hadoop
      • Commands used in Hadoop
      • Configuration Files
      • Hadoop Jars
      • Cloudera
      • VM version installation

       Hadoop Architecture

      • Production of Hadoop clusters
      • Hadoop cluster modes
      • Hadoop shell commands
      • Flume
      • SQOOP
      • Data Loading Techniques
      • Hadoop 2.x configuration files
      • SSH
      • MapReduce Job Execution

      MapReduce Framework

      • Use Cases
      • Traditional vs MapReduce methods
      • MapReduce Architecture
      • Anatomy of MapReduce
      • MapReduce Components
      • YARN workflow
      • Application Execution flow
      • Mappers in Java
      • Reducers in Java
      • Input Splits
      • HDFS blocks
      • Job Submission flow
      • Eclipse
      • Combiner and partitioner

      Advanced MapReduce

      • Counters
      • MRunit
      • Distributed Cache
      • Sequence Input format
      • Custom Input format

      Hive

      • Hive use case
      • About Hive
      • Hive vs Pig
      • Metastore in Hive
      • Hive Limitations
      • Hive and RDBMS differences
      • Hive DDL
      • Hive Data Type
      • Data Models
      • Partitions
      • Buckets
      • Hive Tables
      • Importing and Querying Data
      • Hive UDF
      • Hive Script

      Pig

      • Introduction to Pig
      • MapReduce Vs Pig
      • Pig Architecture
      • Use Cases
      • Programming structure in Pig
      • Shell components
      • Running Models
      • Execution
      • Latin Program
      • Data Models in Pig
      • Jars Import
      • Limitations of PIG
      • Pig UDF
      • Relational operators
      • File Loaders
      • Group Operator
      • Diagnostic Operators

      Advanced Hive and HBase

      • HBase
      • HBase Architecture
      • Components
      • Storage Model
      • HBase
      • Mongo DB
      • CRUD
      • HiveQL
      • HBase
      • Thrift Server
      • Dynamic Partitioning
      • HBase vs RDBMS
      • NoSQL Database
      • HBase Cluster Deployment