MAPREDUCE PROGRAMMING MODEL TRAINING

<ul>
<li> What is Big Data?</li>
<li> What is Hadoop?</li>
<li> Relation between Big Data and Hadoop.</li>
<li> What is the need of going ahead with Hadoop?</li>
<li> Scenarios to apt Hadoop Technology in REAL-TIME Projects</li>
<li> Challenges with Big Data</li>
<ul>
<li> Storage</li>
<li> Processing</li> </ul></ul>



<ul>
<li> How Hadoop is addressing Big Data Changes</li>
<li> Comparison with Other Technologies</li>
<ul>
<li> RDBMS</li>
<li> Data Warehouse</li>
<li> Teradata</li> </ul> </ul>




<ul>
<li> Different Components of Hadoop Echo System</li>
<ul>
<li> Storage Components</li>
<li> Processing Components</li></ul></ul>

<ul>
<li> What is a Cluster Environment?</li>
<li> Cluster Vs Hadoop Cluster.</li>
<li> Significance of HDFS in Hadoop</li>
<li> Features of HDFS</li>
<li> Storage aspects of HDFS</li>
<li> HDFS Architecture 5 demons of Hadoop</li>

<ul>
<li> Block</li>
<li> How to Configure block size</li>
<li> Default Vs configurable block size</li>
<li> Why HDFS block size is so large</li>
<li> Design Principles of block size</li>
<li> NameNode and its functionality</li>
<li> Data node and its functionality</li>
<li> Job Tracker and its functionality</li> </ul></ul

<ul>
<li> Why Map Reduce is essential in Hadoop?</li>
<li> Processing Daemons of Hadoop</li>
<li> Input Split</li>
<li> Map Reduce Life Cycle</li>
<li> MapRedue Programming Model</li>
<ul><li> Job Tracker</li>
<ul>
<li> Roles Of Job Tracker</li>
<li> Drawbacks w.r.to Job Tracker failure in Hadoop Cluster</li>
<li> How to configure Job Tracker in Hadoop Cluster</li></ul>
<li> Task Tracker </li>
<ul>
<li> Roles of Task Tracker</li>
<li> Drawbacks w.r.to Task Tracker Failure in Hadoop Cluster</li></ul>
<li> InputSplit</li>
<li> Need Of Input Split in Map Reduce</li>
<li> InputSplit Size</li>
<li> InputSplit Size Vs Block Size</li>
<li> InputSplit Vs Mappers</li>
<li> Communication Mechanism of Job Tracker and Task Tracker</li>
<li> Input Format Class</li>
<li> Record Reader Class</li>
<li> Success Case Scenarios</li>
<li> Failure Case Scenario</li>
<li> Retry Mechanism in Map Reduce</li>
<li> Different phases of Map Reduce Algorithm</li>
<li> Different Data types in Map Reduce</li>
<ul>
<li> Primitive Data types Vs Map Reduce Data types</li></ul>
<li> How to write basic Map Reduce Program</li>
<ul>
<li> Driver Code</li>
<li> Mapper Code</li>
<li> Reducer Code</li></ul>
<li>Driver Code</li>
<ul>
<li> Importance of Driver Code in a Map Reduce program</li>
<li> How to Identify the Driver Code in Map Reduce program</li>
<li> Different sections of Driver code</li></ul>
<li> Mapper Code</li>
<ul>
<li> Importance of Mapper Phase in Map Reduce</li>
<li> How to Write a Mapper Class?</li>
<li> Methods in Mapper Class</li></ul>
<li> Reducer Code</li>
<ul>
<li> Importance of Reduce phase in Map Reduce</li>
<li> How to Write Reducer Class?</li>
<li> Methods in Reducer Class</li></ul>
<li> IDENTITY MAPPER & IDENTITY REDUCER</li>
<li> Input Format's in Map Reduce</li>
<ul>
<li> TextInputFormat</li>
<li> KeyValueTextInputFormat</li>
<li> NLinelnputFormat</li>
<li> DBlnputFormat</li>
<li> SequenceFilelnputFormat</li>
<li> How to use the specific input format in Map Reduce</li></ul>
<li> Output Format's in Map Reduce</li>
<ul>
<li> TextOutputFormat</li>
<li> KeyValueTextOutputFormat</li>
<li> NLineOutputFormat</li>
<li> DBOutputFormat</li>
<li> SequenceFileOutputFormat</li>
<li> How to use the specific Output format in Map reduce</li></ul>
<li> Map Reduce API(Application Programming</li>
<ul>
<li> New API</li>
<li> Deprecated API</li> </ul>
<li>Combiner in Map Reduce</li>
<ul>
<li> Is combiner mandate in Map Reduce</li>
<li> How to use the combiner class in Map Reduce</li>
<li> Performance tradeoffs w.r.to Combiner</li></ul>

<li> Partitioner in Map Reduce</li>
<ul>
<li> Importance of Pratitioner class in Map Reduce</li>
<li> How to use the Partitioner class in Map Reduce</li>
<li> hashPartitioner functionality</li>
<li> How to write a custom Partitioner</li></ul>
<li> Compression techniques in Map Reduce</li>
<ul>
<li> Importance of Compression in Map Reduce</li>
<li> What is CODEC</li>
<li> Compression Types</li>
<li> GzipCodec</li>
<li> BzipCodec</li>
<li> LZOCodec</li>
<li> SnappyCodec</li>
<li> Configurations w.r.to Compression Techniques</li>
<li> How to customize the Compression per one job Vs all the job</li></ul>
<li> Joins - in Map Reduce</li>
<ul>
<li> Map Side Join</li>
<li> Reduce Side Join</li>
<li> Performance Trade Off</li>
<li> Distributed cache</li></ul>
<li> How to debug MapReduce Jobs in Local and Pseudo cluster Mode.</li>
<li> Introduction to MapReduce Streaming</li>
<li> Data localization in Map Reduce</li>
<li> Task Track and its functionality</li>
<li> Secondary Name Node and its functionality</li></ul>
<li> Replication in Hadoop - Fail Over Mechanism</li>
<li> Accessing HDFS</li>
<ul>
<li> Data Storage in Data Nodes</li>
<li> Fail Over Mechanism in Hadoop - Replication</li>
<li> Replication Configuration</li>

<li> Design Constraints with Replication Factor</li>
<li> CLI (Command Line Interface) and HDFS Commands</li>
<li> Java Based Approach</li></ul>

<li> Hadoop Archives</li>
<li> Apache PIG</li>
<li> Introduction to Apache Pig</li>

<li> SQL Vs Apache Pig</li>
<li> Different data types in Pig</li>
<li> Modes Of Execution in Pig</li>
<li> Execution Mechanism</li>
<ul>
<li> Local Mode</li>
<li> Map Reduce OR Distributed Mode</li>
<li> Grunt Shell</li></ul>
<li> Embedded</li>
<li> Transformations in Pig</li>
<li> How to write a simple pig script</li>

<li> Bags, Tuples and fields in PIG</li>
<li> UDFs in Pig</li>
<ul>
<li> Need of using UDFs in PIG</li>
<li> How to use UDFs</li>
<li> REGISTER Key word in PIG</li></ul>
<li> When to use Map Reduce & Apace PIG in REAL TIME Projects</li></ul>

<ul>
<li> Hive Introduction</li>
<li> Need of Apache HIVE in Hadoop</li>
<li> Hive Architect</li>
<li> Meta Store in Hive</li>
<ul>
<li> Driver</li>
<li> Compiler</li>
<li> Executor(Semantic Analyzer)</li>
<li> Importance Of Hive Meta Store</li>
<li> External metastore configuration</li>
<li> Communication mechanism with Metastore</li></ul>
<li> Hive Integration with Hadoop</li>
<li> Hive Query Language(Hive QL)</li>
<li> Configuring Hive with MySQL MetaStore</li>
<li> SQL VS Hive QL</li>
<li> Data Slicing Mechanisms</li>
<li> Collection Data Types in HIVE</li>
<ul>
<li> Partitions In Hive</li>
<li> Buckets In Hive</li>
<li> Partitioning Vs Bucketing</li>
<li> Real Time Use Cases</li>
<li> Array</li>
<li> Struct</li>
<li> Map</li></ul>
<li>User-Defined Functions(UDFs) in HIVE</li>
<ul>
<li> UDFs</li>
<li> UDAFs</li>
<li> UDTFs</li>
<li> Need of UDFs in HIVE</li></ul>
<li> Hive Serializer/Deserializer SerDe</li>
<li> HIVE - HBASE Integration</li>
<li> Introduction to sqoop</li>
<li> MySQL client and Server Installation</li>
<li> How to connect to Relational database using Sqoop</li>
<li> different Sqoop Commands</li>
<ul>
<li> Different flavours of Improrts</li>
<li> Export</li>
<li> Hive-Imports</li></ul>
<li> HBASE Introduction</li>
<li> HDFS Vs HBase</li>
<li> Hbase use cases</li>
<li> Hbase basics</li>
<ul>
<li> Column families</li>
<li> Scans</li></ul>
<li> HBase Architecture</li>
<li> Clients</li>
<ul>
<li> </li>
<li> REST</li>
<li> Thrift</li>
<li> Java Based</li>
<li> Avro</li></ul>
<li> Map Reduce Integration</li>
<li> Map Reduce over HBase</li>
<li> HBase Admin</li>

<ul>
<li> Schema Definition</li>
<li> Basic CRUD Operations</li></ul>
<li> Flume Introduction</li>
<li> Flume Architecture</li>
<li> Flume Master, Flume Collector and Flume Agent</li>
<li> Flume Configurations</li>
<li> Real Time Use Case using Apache Flume</li>
<li> Oozie Introduction</li>
<li> Oozie Architecture</li>
<li> Oozie Configuration Files</li>
<li> Oozie Job Submission</li>
<ul>
<li> Workflow.xml</li>
<li> Coordinatot:xml</li>
<li> job.coordinatonproperties</li></ul></ul>

<ul>
<li> What is YARN?</li>
<li> YARN Architecture</li>

<ul>
<li> Resource Manager</li>
<li> Application Master</li>
<li> Node Manager</li></ul>
<li> When should we go ahead with YARN</li>
<li> Classic Map Reduce Vs YARN Map Reduce</li>
<li> Different Configuration Files for YARN</li>
<li> What is Impala?</li>
<li> How can we use Impala for Query Processing</li>
<li> When should we go ahead with Impala</li>
<li> HIVE Vs Impala</li>
<li> REAL TIME Use Case with Impala</li></ul>

<ul>
<li> Need of NoSQL Databases</li>
<li> Relational Vs Non-Relational Databases</li>
<li> Introduction to MongoDB</li>
<li> Features of MongoDB</li>
<li> Installation of MongoDB</li>
<li> Mongo DB Basic operations</li></u>

<ul>
<li> Topics.</li>
<li> Producers</li>
<li> Consumers.</li>
<li> Brokers.</li></ul>

<ul>
<li> Spark SQL</li>
<li> Joins using spark SQL.</li></ul>

<ul><li> Hadoop Single Node Cluster Set Up (Hands on Installation on Laptops)</li>
<ul>
<li> Operating System Installation</li>
<li> JDK Installation</li>
<li> SSH Configuration</li>
<li> Dedicated Group & User Creation</li>
<li> Hadoop Installation</li>
<li> Different Configuration Files Setting</li>
<li> Name node format</li>
<li> Starting the Hadoop Daemons</li></ul>
<li> Multi Node Hadoop Cluster Set Up (Hands on Installation on Laptops) )</li>
<li> PIG Installation (Hands on Installation on Laptops)</li>
<li> SQOOP Installation (Hands on Installation on Laptops)</li>
<li> HIVE Installation (Hands on Installation on Laptops)</li>
<li> Hbase Installation (Hands on Installation on Laptops)</li>
<li> OOZIE Installation (Hands on Installation on Laptops)</li>
<li> MongoDB Installation (Hands on Installation on Laptops)</li>
<li> Commissioning of Nodes In Hadoop Cluster</li>
<li> Decommissioning of Nodes from Hadoop Cluster</li>
<ul>
<li> Network related settings</li>
<li> Hosts Configuration</li>
<li> Password less SSH Communication</li>
<li> Hadoop Installation</li>
<li> Configuration Files Setting</li>
<li> Name Node Format</li>
<li> Starting the Hadoop Daemons</li>
<li> Local Mode Clustered Mode Bashrc file configuration</li>
<li> Sqoop installation with MySQL Client</li>
<li> Local Mode Clustered Mode</li>
<li> Local Mode Clustered Mode</li></ul></ul>