Data Stage Training in Bangalore


Understanding Big Data and Hadoop

Topics – Big Data, Limitations and Solutions of existing Data Analytics Architecture, Hadoop, Hadoop Features, Hadoop Ecosystem, Hadoop 2.x core components, Hadoop Storage: HDFS, Hadoop Processing: MapReduce Framework, Hadoop Different Distributions. 

Hadoop Architecture and HDFS

Topics – Hadoop 2.x Cluster Architecture – Federation and High Availability, A Typical Production Hadoop Cluster, Hadoop Cluster Modes, Common Hadoop Shell Commands, Hadoop 2.x Configuration Files, Single node cluster and Multi node cluster set up Hadoop Administration. 

Hadoop MapReduce Framework

Topics – MapReduce Use Cases, Traditional way vs. MapReduce way, Why MapReduce, Hadoop 2.x MapReduce Architecture, Hadoop 2.x MapReduce Components, YARN MR Application Execution Flow, YARN Workflow, Anatomy of MapReduce Program, Demo on MapReduce. Input Splits, Relation between Input Splits and HDFS Blocks, MapReduce: Combiner & Partitioner, Demo on de-identifying Health Care Data set, Demo on Weather Data set. 

Advanced MapReduce

Topics – Counters, Distributed Cache, MRunit, Reduce Join, Custom Input Format, Sequence Input Format, Xml file Parsing using MapReduce.


Topics – About Pig, MapReduce Vs Pig, Pig Use Cases, Programming Structure in Pig, Pig Running Modes, Pig components, Pig Execution, Pig Latin Program, Data Models in Pig, Pig Data Types, Shell and Utility Commands, Pig Latin : Relational Operators, File Loaders, Group Operator, COGROUP Operator, Joins and COGROUP, Union, Diagnostic Operators, Specialized joins in Pig, Built In Functions ( Eval Function, Load and Store Functions, Math function, String Function, Date Function, Pig UDF, Piggybank, Parameter Substitution ( PIG macros and Pig Parameter substitution ), Pig Streaming, Testing Pig scripts with Punit, Aviation use case in PIG, Pig Demo on Healthcare Data set.


Topics – Hive Background, Hive Use Case, About Hive, Hive Vs. Pig, Hive Architecture and Components, Metastore in Hive, Limitations of Hive, Comparison with Traditional Database, Hive Data Types and Data Models, Partitions and Buckets, Hive Tables (Managed Tables and External Tables), Importing Data, Querying Data, Managing Outputs, Hive Script, Hive UDF, Retail use case in Hive, Hive Demo on Healthcare Data set. 

Advanced Hive and HBase

Topics – Hive QL: Joining Tables, Dynamic Partitioning, Custom Map/Reduce Scripts, Hive Indexes and views Hive query optimizers, Hive : Thrift Server, User Defined Functions, HBase: Introduction to NoSQL Databases and HBase, HBase v/s RDBMS, HBase Components, HBase Architecture, Run Modes & Configuration, HBase Cluster Deployment. 

Advanced HBase

Topics – HBase Data Model, HBase Shell, HBase Client API, Data Loading Techniques, ZooKeeper Data Model, Zookeeper Service, Zookeeper, Demos on Bulk Loading, Getting and Inserting Data, Filters in HBase. 

Processing Distributed Data with Apache Spark 

Topics – What is Apache Spark, Spark Ecosystem, Spark Components, History of Spark and Spark Versions/Releases, Spark a Polyglot, What is Scala?, Why Scala?, SparkContext, RDD.  

Oozie and Hadoop Project

Topics – Flume and Sqoop Demo, Oozie, Oozie Components, Oozie Workflow, Scheduling with Oozie, Demo on Oozie Workflow, Oozie Co-coordinator, Oozie Commands, Oozie Web Console, Oozie for MapReduce, PIG, Hive, and Sqoop, Combine flow of MR, PIG, Hive in Oozie, Hadoop Project Demo, Hadoop Integration with Talend. 

Core Java Topics 

Topics – Core Java Basic Concepts, Different Objects, Classes, Operators, Data Types and Arrays, Constructors, Constructor overloading Package, Inheritance, Method Overloading, Method Overriding Abstract Class, Interface and Concept of Input and Output Method.’Enums’, Different LoopConstructs, ArrayList, HashMap, HashTable, Exception Handling, and Try and Catch Block. 


Topics- Introduction to SQL,DDL Statements(Create,Alter,Drop etc.), DML Statements(Insert update Delete), Aggregate functions, GROUP BY, HAVING clauses, Simple and complex joins, Sub queries, Where and order by clauses,sequences and views. 


Topics- Unix Architecture, Login, Change password, Listing directories, Listing files, Creating files, Editing files, Displaying contents of file, Copying files, Renaming files, Deleting files, Unix directories, Listing directories, Creating directories,Removing directories, Changing directories, Unix file permissions, Using chmod to change permissions, File access modes, Background processes



Best dataStage Training institutes with Certification Providing in Akshaya Learning. Spark & Scala  courses in Bangalore with live project  development course in Bangalore. Akshaya Learning is the best Bigdata & Hadoop with spark and scala training  institute in Bangalore with 100% placement Support Provided for Students. We will provide the Courses for beginners from Scratch to advanced Concepts in Real-time. Learn Hadoop with all Advanced topics training and placement as well.The best training institute for Hadoop , Big data ,spark & Scala courses. Best Training institutes in Bangalore with Placements is Akshaya Learning.

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