1. Hadoop Training Institutes in Pune Introduction:Grab the
Excellent & Huge Job opportunities in the Big-Data Hadoop
Market today with the help of Mindscripts Technologies. Mindscripts
Technologies is the Best Big-Data Hadoop Training Institutes in
Pune. Providing you a Complete Hadoop Course with Cloud Era
Certification. As Hadoop Course is developed & work under
Apache License. Big-data Hadoop is the Latest Technology in IT
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complete knowledge to the candidates or to the Cocorporate employee
who are interested to make their career in Big-Data Hadoop course.
Target & final Career objective is to complete the Hadoop
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& get the Job in Multinational companies for starting your
career.For More Details you may Contact us on:-
2. Hotline no - 9595957557 Mobile no 8805674210 Website:-
www.mindscripts.com Office Branch Address:MindScripts Technologies,
2nd Floor, Siddharth Hall, Near Ranka Jewellers, Behind HP Petrol
Pump, Karve Rd, Pune 411004 MindScripts Technologies, C8, 2nd
Floor, Sant Tukaram Complex , Pradhikaran, Above Savali Hotel, Opp
Nigdi Bus Stand, Nigdi, Pune 411044 Objective:Get Complete
Knowledge Of Big-Data with Live Projects at the end of the
Course.Complete Big-Data Hadoop Course with CloudEra Certification
from Technical Experts.Eligibility:Candidate should a Graduate
before applying for this course.He should have the knowledge of
Java. And Java skills are mandatory or he should posses a past
Experience in Software Development field.Course Overview:The Course
consists of following modules which include both theoretical &
Practical knowledge.Hadoop Hadoop EcosystemIntroduction Hadoop:
Basic Concepts What is Hadoop? The Hadoop Distributed File System
Hadoop Map Reduce WorksHBase HBase concepts HBase architecture
Region server architecture File storage architecture HBase
basics
3. Anatomy of a Hadoop ClusterColumn access Scans Hadoop demons
HBase use cases Master Daemons Install and configure HBase on a
multi node Name node cluster Job Tracker Create database, Develop
and run sample Secondary name node applications Slave Daemons
Access data stored in HBase using clients like Job tracker Java,
Python and Pearl Task tracker HBase and Hive Integration HBase
admin tasks HDFS ( Hadoop Distributed File System ) Defining Schema
and basic operation Blocks and Splits Hive Input Splits Hive
concepts HDFS Splits Hive architecture Data Replication Install and
configure hive on cluster Hadoop Rack Aware Create database, access
it from java client Data high availability Buckets Data Integrity
Partitions Cluster architecture and block placement Joins in hive
Accessing HDFS Inner joins JAVA Approach Outer Joins CLI Approach
Hive UDF Programming Practices Hive UDAF Developing MapReduce
Programs in Hive UDTF Local Mode Develop and run sample
applications in Running without HDFS and Mapreduce Java/Python to
access hive Pseudo-distributed Mode Running all daemons in a single
node PIG Fully distributed mode Pig basics Running daemons on
dedicated nodes Install and configure PIG on a cluster PIG Vs
MapReduce and SQL Setup Hadoop cluster Pig Vs Hive Make a fully
distributed Hadoop cluster Write sample Pig Latin scripts Cluster
Specification Modes of running PIG Network Topology Running in
Grunt shell Cluster Specification and installation Programming in
Eclipse Hadoop configuration Running as Java program PIG UDFs
Writing a MapReduce Program Pig Macros Examining a Sample MapReduce
Program With several examples Flume Basic API Concepts Flume
concepts The Driver Code Install and configure flume on cluster The
Mapper Create a sample application to capture logs The Reducer from
Apache using flume
4. Hadoop's Streaming API Performing several hadoop jobs The
configure and close Methods Sequence Files Record Reader Record
Writer Role of Reporter Output Collector Processing XML files
Counters Directly Accessing HDFS ToolRunner Using The Distributed
Cache Common MapReduce Algorithms Sorting and Searching Indexing
Classification/Machine Learning Term Frequency - Inverse Document
Frequency Word Co-Occurrence Hands-On Exercise: Creating an
Inverted Index Identity Mapper Identity Reducer Exploring well
known problems using MapReduce applications Debugging MapReduce
Programs Testing with MRUnit Logging Other Debugging Strategies.
Advanced MapReduce Programming A Recap of the MapReduce Flow The
Secondary Sort Customized Input Formats and Output FormatsSqoop
Getting Sqoop A Sample Import Database Imports Controlling the
import Imports and consistency Direct-mode imports Performing an
Export CDH4 Enhancements Name Node High Availability Name Node
federation Fencing YARN