Cloudera Hadoop Training

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Cloudera Hadoop Training


 (4.9) | 350 Ratings


Introduction


Cloudera Hadoop Training Details
Track Regular Track Weekend Track Fast Track
Course Duration 35 Hrs 8 Weekends 5 Days
Hours 1hr/day 2 Hours a day 6 Hours a day
Training Mode Online Classroom Online Classroom Online Classroom
Delivery Instructor Led-Live Instructor Led-Live Instructor Led-Live


Course Curriculum

Introduction to BigData, Hadoop:-

  • Big Data Introduction
  • Hadoop Introduction
  • What is Hadoop? Why Hadoop?
  • Hadoop History?
  • Different types of Components in Hadoop?
  • HDFS, MapReduce, PIG, Hive, SQOOP, HBASE, OOZIE, Flume, Zookeeper and so on…
  • What is the scope of Hadoop?

Deep Drive in HDFS (for Storing the Data):-

  • Introduction of HDFS
  • HDFS Design
  • HDFS role in Hadoop
  • Features of HDFS
  • Daemons of Hadoop and its functionality
  • Name Node
  • Secondary Name Node
  • Job Tracker
  • Data Node
  • Task Tracker
  • Anatomy of File Wright
  • Anatomy of File Read
  • Network Topology
  • Nodes
  • Racks
  • Data Center
  • Parallel Copying using DistCp
  • Basic Configuration for HDFS
  • Data Organization
  • Blocks and
  • Replication
  • Rack Awareness
  • Heartbeat Signal
  • How to Store the Data into HDFS
  • How to Read the Data from HDFS
  • Accessing HDFS (Introduction of Basic UNIX commands)
  • CLI commands

MapReduce using Java (Processing the Data):-

  • Introduction of the MapReduce.
  • MapReduce Architecture
  • Data flow in MapReduce
  • Splits
  • Mapper
  • Portioning
  • Sort and shuffle
  • Combiner
  • Reducer
  • Understand Difference Between Block and InputSplit
  • Role of RecordReader
  • Basic Configuration of MapReduce
  • MapReduce life cycle
  • Driver Code
  • Mapper
  • and Reducer
  • How MapReduce Works
  • Writing and Executing the Basic MapReduce Program using Java
  • Submission & Initialization of MapReduce Job.
  • File Input/output Formats in MapReduce Jobs
  • Text Input Format
  • Key Value Input Format
  • Sequence File Input Format
  • NLine Input Format
  • Joins
  • Map-side Joins
  • Reducer-side Joins
  • Word Count Example
  • Partition MapReduce Program
  • Side Data Distribution
  • Distributed Cache (with Program)
  • Counters (with Program)
  • Types of Counters
  • Task Counters
  • Job Counters
  • User Defined Counters
  • Propagation of Counters
  • Job Scheduling

PIG:-

  • Introduction to Apache PIG
  • Introduction to PIG Data Flow Engine
  • MapReduce vs PIG in detail
  • When should PIG used?
  • Data Types in PIG
  • Basic PIG programming
  • Modes of Execution in PIG
  • Local Mode and
  • MapReduce Mode
  • Execution Mechanisms
  • Grunt Shell
  • Script
  • Embedded
  • Operators/Transformations in PIG
  • PIG UDF’s with Program
  • Word Count Example in PIG
  • The difference between the MapReduce and PIG

SQOOP:-

  • Introduction to SQOOP
  • Use of SQOOP
  • Connect to mySql database
  • SQOOP commands
  • Import
  • Export
  • Eval
  • Codegen and etc…
  • Joins in SQOOP
  • Export to MySQL

HIVE:-

  • Introduction to HIVE
  • HIVE Meta Store
  • HIVE Architecture
  • Tables in HIVE
  • Managed Tables
  • External Tables
  • Hive Data Types
  • Primitive Types
  • Complex Types
  • Partition
  • Joins in HIVE
  • HIVE UDF’s and UADF’s with Programs
  • Word Count Example

HBASE:-

  • Introduction to HBASE
  • Basic Configurations of HBASE
  • Fundamentals of HBase
  • What is NoSQL?
  • HBase DataModel
  • Table and Row
  • Column Family and Column Qualifier
  • Cell and its Versioning
  • Categories of NoSQL Data Bases
  • Key-Value Database
  • Document Database
  • Column Family Database
  • SQL vs NOSQL
  • How HBASE is the differ from RDBMS
  • HDFS vs HBase
  • Client-side buffering or bulk uploads
  • HBase Designing Tables
  • HBase Operations
  • Get
  • Scan
  • Put
  • Delete

MongoDB:–

  • What is MongoDB?
  • Where to Use?
  • Configuration On Windows
  • Inserting the data into MongoDB?
  • Reading the MongoDB data.

Cluster Setup:–

  • Downloading and installing the Ubuntu12.x
  • Installing Java
  • Installing Hadoop
  • Creating Cluster
  • Increasing Decreasing the Cluster size
  • Monitoring the Cluster Health
  • Starting and Stopping the Nodes

OOZIE

  • Introduction to OOZIE
  • Use of OOZIE
  • Where to use?

Hadoop Ecosystem Overview

  • Oozie
  • HBase
  • Pig
  • Sqoop
  • Casandra
  • Chukwa
  • Mahout
  • Zoo Keeper
  • Flume

 

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Course Curriculum

Introduction to BigData, Hadoop:-

  • Big Data Introduction
  • Hadoop Introduction
  • What is Hadoop? Why Hadoop?
  • Hadoop History?
  • Different types of Components in Hadoop?
  • HDFS, MapReduce, PIG, Hive, SQOOP, HBASE, OOZIE, Flume, Zookeeper and so on…
  • What is the scope of Hadoop?

Deep Drive in HDFS (for Storing the Data):-

  • Introduction of HDFS
  • HDFS Design
  • HDFS role in Hadoop
  • Features of HDFS
  • Daemons of Hadoop and its functionality
  • Name Node
  • Secondary Name Node
  • Job Tracker
  • Data Node
  • Task Tracker
  • Anatomy of File Wright
  • Anatomy of File Read
  • Network Topology
  • Nodes
  • Racks
  • Data Center
  • Parallel Copying using DistCp
  • Basic Configuration for HDFS
  • Data Organization
  • Blocks and
  • Replication
  • Rack Awareness
  • Heartbeat Signal
  • How to Store the Data into HDFS
  • How to Read the Data from HDFS
  • Accessing HDFS (Introduction of Basic UNIX commands)
  • CLI commands

MapReduce using Java (Processing the Data):-

  • Introduction of the MapReduce.
  • MapReduce Architecture
  • Data flow in MapReduce
  • Splits
  • Mapper
  • Portioning
  • Sort and shuffle
  • Combiner
  • Reducer
  • Understand Difference Between Block and InputSplit
  • Role of RecordReader
  • Basic Configuration of MapReduce
  • MapReduce life cycle
  • Driver Code
  • Mapper
  • and Reducer
  • How MapReduce Works
  • Writing and Executing the Basic MapReduce Program using Java
  • Submission & Initialization of MapReduce Job.
  • File Input/output Formats in MapReduce Jobs
  • Text Input Format
  • Key Value Input Format
  • Sequence File Input Format
  • NLine Input Format
  • Joins
  • Map-side Joins
  • Reducer-side Joins
  • Word Count Example
  • Partition MapReduce Program
  • Side Data Distribution
  • Distributed Cache (with Program)
  • Counters (with Program)
  • Types of Counters
  • Task Counters
  • Job Counters
  • User Defined Counters
  • Propagation of Counters
  • Job Scheduling

PIG:-

  • Introduction to Apache PIG
  • Introduction to PIG Data Flow Engine
  • MapReduce vs PIG in detail
  • When should PIG used?
  • Data Types in PIG
  • Basic PIG programming
  • Modes of Execution in PIG
  • Local Mode and
  • MapReduce Mode
  • Execution Mechanisms
  • Grunt Shell
  • Script
  • Embedded
  • Operators/Transformations in PIG
  • PIG UDF’s with Program
  • Word Count Example in PIG
  • The difference between the MapReduce and PIG

SQOOP:-

  • Introduction to SQOOP
  • Use of SQOOP
  • Connect to mySql database
  • SQOOP commands
  • Import
  • Export
  • Eval
  • Codegen and etc…
  • Joins in SQOOP
  • Export to MySQL

HIVE:-

  • Introduction to HIVE
  • HIVE Meta Store
  • HIVE Architecture
  • Tables in HIVE
  • Managed Tables
  • External Tables
  • Hive Data Types
  • Primitive Types
  • Complex Types
  • Partition
  • Joins in HIVE
  • HIVE UDF’s and UADF’s with Programs
  • Word Count Example

HBASE:-

  • Introduction to HBASE
  • Basic Configurations of HBASE
  • Fundamentals of HBase
  • What is NoSQL?
  • HBase DataModel
  • Table and Row
  • Column Family and Column Qualifier
  • Cell and its Versioning
  • Categories of NoSQL Data Bases
  • Key-Value Database
  • Document Database
  • Column Family Database
  • SQL vs NOSQL
  • How HBASE is the differ from RDBMS
  • HDFS vs HBase
  • Client-side buffering or bulk uploads
  • HBase Designing Tables
  • HBase Operations
  • Get
  • Scan
  • Put
  • Delete

MongoDB:–

  • What is MongoDB?
  • Where to Use?
  • Configuration On Windows
  • Inserting the data into MongoDB?
  • Reading the MongoDB data.

Cluster Setup:–

  • Downloading and installing the Ubuntu12.x
  • Installing Java
  • Installing Hadoop
  • Creating Cluster
  • Increasing Decreasing the Cluster size
  • Monitoring the Cluster Health
  • Starting and Stopping the Nodes

OOZIE

  • Introduction to OOZIE
  • Use of OOZIE
  • Where to use?

Hadoop Ecosystem Overview

  • Oozie
  • HBase
  • Pig
  • Sqoop
  • Casandra
  • Chukwa
  • Mahout
  • Zoo Keeper
  • Flume

 

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