Tuesday 20 March 2018

HADOOP BIG DATA SUMMER TRAINING CLASSES

ASCENT SOFTWARE TRAINING INSTITUTE IN BANGALORE PROVIDES YOU HADOOP BIG DATA TRAINING CLASSES IN THIS SUMMER 

Check The Following Details Abot Ascent - Hadoop Big Data Summer Classes In Bangalore

Best Hadoop Training Institute In Bangalore With Placements

Big Data & Hadoop Training Institute :

Hadoop-Training-Institute

Big Data & Hadoop Training Institute :

Overview of Big Data & Hadoop

1.What is Big Data & Hadoop
2.Sources of Big Data
3.Challenges with Big Data
4.Problems with traditional RDBMS
5.What is Hadoop
6.History of Hadoop
7.Benefits of Hadoop
8.How Hadoop solves problems with RDBMS?
9.Why Hadoop?

Software Installation

1.Pre requisites
2.Understanding decencies software and installing
3.Understanding hadoop configuration files
4.Setup single node hadoop cluster
5.Configuring Hadoop
6.The Command-Line Interface
7.Understanding hadoop Shell and shell commands
8.Hands on hadoop shell commands


HDFS (Hadoop Distributed File System)
1.Architecture of HDFS
2.HDFS Features
3.Name Node & Data Node
4.Secondary Name Node
5.Data Loading into HDFS
6.Anatomy of File Read & Write
7.Rack Awareness
8.Check Pointing
9.HDFS Integrity
10.Safe Mode
Federation & High Availability

Map Reduce-1(Classic)

1.Map Reduce Architecture
2.JobTraker & TaskTracer
3.Job Execution Flow
4.Monitoring Progress
5.Debugging MapReduce Jobs
6.Input Splits , Shuffling & Sorting
7.Practitioner & Record Readers
8.Combiners
9.Distributed cache
10.Using Joins in MapReduce
11.Input & Output Formats
12.Data Compression Techniques
13.Job Schedulers
14.Failovers in Map Reduce
15.Hadoop Pipes and Hadoop Streaming
16.Hands on Examples: Writing a MapReduce Program and Running a MapReduce Job

Map Reduce-2(YARN)

1.Limitations of Mardeuce-1
2.YARN Architecture
3.Resource Manager
4.Node Manager
5.Application Master
6.Task Manager
7.Job Flow
8.Handing Failovers

Spark

1.Introduction to Spark
2.Spark RDD’s
3.Architecture of Spark
4.Spark execution engine
5.MapReduce v/s Spark
6.Spark Transformers
7.Spark Actions
8.Introduction to Flume,Kafka,Scala

Impala

1.Introduction to Impala
2.Impala v/s Hive,Pig,RDBMS
3.Features & benefits of Impala
4.Analyzing data with Impala

Pig

1.Introductions to Pig
2.Architecture of Pig
3.Pig Latin
4.Pig Data Types, Commands & Operators
5.Data Loading
6.Data processing
7.Pig Builtin Functions & UDFs
8.Pig Workflows
9.Hands on Exercises &Real Time Examples
Hive
1.Introduction & Architecture
2.Hive Configuration and Settings
3.Hive Query Language
4.Hive Data Types, DDL & DML
5.Loading Data into hive tables
6.Partitions & Bucketing
7.SERDEs in hive
8.Hive Built-in Functions& User Defined Functions(UDFs)
9.Writing & Executing Hive scripts
10.Hands on Examples& Real time Examples
Scoop
1.Installing & Configuring Sqoop
2.Sqoop Tools
3.Import RDBMS data to Hive using Sqoop
4.Export from to Hive to RDBMS using Sqoop
5.Hands-On Exercise: Import data from RDBMS to HDFS and Hive
6.Hands-On Exercise: Export data from HDFS/Hive to RDBMS
HCatalog
1.Introduction to HCatalog
2.Advantages and Uses of HCatalog
3.HCatalog Load and Store Interfaces
4.Using HCatalog in PIG
Beeline
1.Introduction to Beeline
2.Advantages of Beeline
3.Beeline v/s Hive
HBase
1.Introduction to NoSQL Databases
2.HBase Architecture
3.Internals of HBase
4.Hbase-Hive Integration
5.Real time use case of HBase
2.YARN Architecture
3.Resource Manager
4.Node Manager
5.Application Master
6.Task Manager
7.Job Flow
8.Handing Failovers
Ascent Softrware Training Institute, Bangalore
call: 9035752162, hr@asti.co.in
www.asti.co.in

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