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 What is Big Data?
 What is Hadoop?
 Need of Hadoop
 Challenges with Big Data
 i.Storage
 ii.Processing
 Comparison with Other Technologies
 Hadoop Echo System components
 HDFS (Hadoop Distributed File System)
• Features of HDFS
• Configuring Block size,
• HDFS Architecture( 5 Daemons)
Name Node
Data Node
Job Tracker
Task Tracker
Secondary Name node
• Replication in Hadoop
• Configuring Custom Replication
• Fault Tolerance in Hadoop
• HDFS Commands
 MAP REDUCE
• Map Reduce Architecture
• Processing Daemons of Hadoop
• Job Tracker (Roles and Responsibilities)
• Task Tracker(Roles and Responsibilities)
• Input split
• Input split vs Block size
• Data Types in Map Reduce
• Map Reduce Programming Model
• Driver Code
• Mapper Code
• Reducer Code
• Combiner in Map Reduce
• Partitioner in Map Reduce
• File input formats
• File output formats
• Compression Techniques in Map Reduce
• Joins in Map Reduce
 PIG
• Introduction to pig
• Pig Latin Script
• Pig Console / Grunt Shell
• Execting Pig Latin Script
• Pig Relations, Bags, Tuples, Fields
• Data Types
• Nulls
• Constants
• Expressions
• Schemas
• Parameter Substitution
• Arithmetic Operators
• Comparison Operators
• Null Operators
• Boolean Operators
• Sign Operators
• Flatten Operators
 Relational Operators in Pig
• COGROUP
• CROSS
• DISTINCT
• FILTER
• FOREACH
• GROUP
• JOIN (INNER)
• JOIN (OUTER)
• LIMIT
• LOAD
• ORDER
• SAMPLE
• SPILT
• STORE
• UNION
 Diagnostic Operators in Pig
• Describe
• Dump
• Explain
• Illustrate
 Eval Functions in Pig
• AVG
• CONCAT
• COUNT
• DIFF
• IS EMPTY
• MAX
• MIN
• SIZE
• SUM
• TOKENIZE
• writing Custom UDFS in Pig
 HIVE
• Introduction
• Hive Architecture
• Hive Metastore
• Hive Query Launguage
• Difference between HQL and SQL
• Hive Built in Functions
• Hive UDF (user defined functions)
• Hive UDAF (user defined Aggregated functions)
• Hive UDTF (user defined table Generated functions)
• Hive Serde?
• Hive & Hbase Integration
• Hive Working with unstructured data
• Hive Working With Xml Data
• Hive Working With Json Data
• Hive Working With Urls And Weblog Data
• Hive – Json – Serde
• Loading Data From Local Files To Hive Tables
• Loading Data From Hdfs Files To Hive Tables
• Tables Types
• Inner Tables
• External Tables
• Partitioned Tables
• Non – Partitioned Tables
• Dynamic Partitions In Hive
• Bucketing in hive
• Hive Unions
• Hive Joins
• Multi Table / File Inserts
• Inserting Into Local Files
• Inserting Into Hdfs Files
• Array Operations In Hive
 SQOOP (SQL + HADOOP)
• Introduction to Sqoop
• SQOOP Import
• SQOOP Export
• Importing Data From RDBMS to HDFS
• Importing Data From RDBMS to HIVE
• Importing Data From RDBMS to HBASE
• Exporting From HASE to RDBMS
• Exporting From HBASE to RDBMS
• Exporting From HIVE to RDBMS
• Exporting From HDFS to RDBMS
• Transformations While Importing / Exporting
• Defining SQOOP Jobs
 NOSQL
• What is “Not only SQL”
• NOSQL Advantages
• What is problem with RDBMS for Large
• Data Scaling Systems
• Types of NOSQL & Purposes
• Key Value Store
• Columer Store
• Document Store
• Graph Store
• Introduction to cassandra – NOSQL Database
• Introduction to MangoDB and CouchDB Database
• Introduction to Neo4j – NOSQL Database
• Intergration of NOSQL Databases with Hadoop
 HBASE
• Introduction to big table
• What is NOSQL and colummer store Database
• HBASE Introduction
• Hbase use cases
• Hbase basics
• Column families
• Scans
• Hbase Architecture
• Thrift
• Map Reduce Integration
• Map Reduce Over Hbase
• Hbase data Modeling
• Hbase Schema design
• Hbase CRUD operators
• Hive & Hbase interagation
• Hbase storage handles
 FLUME
• Introduction to FLUME
• What is the streaming File
• FLUME Architecture
• FLUME Nodes & FLUME Manager
• FLUME Local & Physical Node
• FLUME Agents & FLUME Collector
 KAFKA
• Introduction to KAFKA
• KAFKA Architecture
• Kafka components
• BROKER
• Topics
• Producers
• Consumers
• Configurations
 OOZIE
• Introduction to OOZIE
• OOZIE as a seheduler
• OOZIE as a Workflow designer
• Seheduling jobs (OOZIE CODE)
• Defining Dependences between jobs
• (OOZIE Code Examples)
• Conditionally controlling jobs
• (OOZIE Code Examples)
• Defining parallel jobs (OOZIE Code Examples)
 YARN
• YARN Architecture
• Resource Manager
• Application Master
• Node Manager
• MR vs. YARN
 IMPALA
• What is Impala?
• Impala for query processing
• HIVE vs Impala
• Usecases with impala
 MONGODB
• Introduction to MongoDB
• Features of MongoDB
• MongoDB Basic operations
 Additional benefits from NBITS
• Course Material
• Sample resumes and Fine tuning of Resume
• Interview Questions
• Mock Interviews by Real time Consultants
• Certification Questions
• Job Assistance

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Hadoop Training in Hyderabad

  • 1.
  • 2.  What is Big Data?  What is Hadoop?  Need of Hadoop  Challenges with Big Data  i.Storage  ii.Processing  Comparison with Other Technologies  Hadoop Echo System components
  • 3.  HDFS (Hadoop Distributed File System) • Features of HDFS • Configuring Block size, • HDFS Architecture( 5 Daemons) Name Node Data Node Job Tracker Task Tracker Secondary Name node • Replication in Hadoop • Configuring Custom Replication • Fault Tolerance in Hadoop • HDFS Commands
  • 4.  MAP REDUCE • Map Reduce Architecture • Processing Daemons of Hadoop • Job Tracker (Roles and Responsibilities) • Task Tracker(Roles and Responsibilities) • Input split • Input split vs Block size • Data Types in Map Reduce • Map Reduce Programming Model • Driver Code • Mapper Code • Reducer Code • Combiner in Map Reduce • Partitioner in Map Reduce • File input formats • File output formats • Compression Techniques in Map Reduce • Joins in Map Reduce
  • 5.  PIG • Introduction to pig • Pig Latin Script • Pig Console / Grunt Shell • Execting Pig Latin Script • Pig Relations, Bags, Tuples, Fields • Data Types • Nulls • Constants • Expressions • Schemas • Parameter Substitution • Arithmetic Operators • Comparison Operators • Null Operators • Boolean Operators • Sign Operators • Flatten Operators
  • 6.  Relational Operators in Pig • COGROUP • CROSS • DISTINCT • FILTER • FOREACH • GROUP • JOIN (INNER) • JOIN (OUTER) • LIMIT • LOAD • ORDER • SAMPLE • SPILT • STORE • UNION
  • 7.  Diagnostic Operators in Pig • Describe • Dump • Explain • Illustrate  Eval Functions in Pig • AVG • CONCAT • COUNT • DIFF • IS EMPTY • MAX • MIN • SIZE • SUM • TOKENIZE • writing Custom UDFS in Pig
  • 8.  HIVE • Introduction • Hive Architecture • Hive Metastore • Hive Query Launguage • Difference between HQL and SQL • Hive Built in Functions • Hive UDF (user defined functions) • Hive UDAF (user defined Aggregated functions) • Hive UDTF (user defined table Generated functions) • Hive Serde? • Hive & Hbase Integration • Hive Working with unstructured data • Hive Working With Xml Data • Hive Working With Json Data
  • 9. • Hive Working With Urls And Weblog Data • Hive – Json – Serde • Loading Data From Local Files To Hive Tables • Loading Data From Hdfs Files To Hive Tables • Tables Types • Inner Tables • External Tables • Partitioned Tables • Non – Partitioned Tables • Dynamic Partitions In Hive • Bucketing in hive • Hive Unions • Hive Joins • Multi Table / File Inserts • Inserting Into Local Files • Inserting Into Hdfs Files • Array Operations In Hive
  • 10.  SQOOP (SQL + HADOOP) • Introduction to Sqoop • SQOOP Import • SQOOP Export • Importing Data From RDBMS to HDFS • Importing Data From RDBMS to HIVE • Importing Data From RDBMS to HBASE • Exporting From HASE to RDBMS • Exporting From HBASE to RDBMS • Exporting From HIVE to RDBMS • Exporting From HDFS to RDBMS • Transformations While Importing / Exporting • Defining SQOOP Jobs
  • 11.  NOSQL • What is “Not only SQL” • NOSQL Advantages • What is problem with RDBMS for Large • Data Scaling Systems • Types of NOSQL & Purposes • Key Value Store • Columer Store • Document Store • Graph Store • Introduction to cassandra – NOSQL Database • Introduction to MangoDB and CouchDB Database • Introduction to Neo4j – NOSQL Database • Intergration of NOSQL Databases with Hadoop
  • 12.  HBASE • Introduction to big table • What is NOSQL and colummer store Database • HBASE Introduction • Hbase use cases • Hbase basics • Column families • Scans • Hbase Architecture • Thrift • Map Reduce Integration • Map Reduce Over Hbase • Hbase data Modeling • Hbase Schema design • Hbase CRUD operators • Hive & Hbase interagation • Hbase storage handles
  • 13.  FLUME • Introduction to FLUME • What is the streaming File • FLUME Architecture • FLUME Nodes & FLUME Manager • FLUME Local & Physical Node • FLUME Agents & FLUME Collector  KAFKA • Introduction to KAFKA • KAFKA Architecture • Kafka components • BROKER • Topics • Producers • Consumers • Configurations
  • 14.  OOZIE • Introduction to OOZIE • OOZIE as a seheduler • OOZIE as a Workflow designer • Seheduling jobs (OOZIE CODE) • Defining Dependences between jobs • (OOZIE Code Examples) • Conditionally controlling jobs • (OOZIE Code Examples) • Defining parallel jobs (OOZIE Code Examples)  YARN • YARN Architecture • Resource Manager • Application Master • Node Manager • MR vs. YARN
  • 15.  IMPALA • What is Impala? • Impala for query processing • HIVE vs Impala • Usecases with impala  MONGODB • Introduction to MongoDB • Features of MongoDB • MongoDB Basic operations  Additional benefits from NBITS • Course Material • Sample resumes and Fine tuning of Resume • Interview Questions • Mock Interviews by Real time Consultants • Certification Questions • Job Assistance