Post by LEARN BIG DATA ONLINE on Jun 3, 2014 16:42:43 GMT
Course Highlights
1) 30 hrs of live online classes by highly qualified Hadoop professionals
2) In-session practice exercises for gaining practical understanding
3) Suitable for database developers, programmers, BI developers and DBA’s
4) All live online classes are recorded and can be accessed for 6 months.
Course Description
Hadoop Big Data Training course helps you learn the core techniques and concepts of Big Data and Hadoop ecosystem. It equips you with in-depth knowledge of writing codes using MapReduce framework and managing large data sets with HBase. The topics covered in this course mainly includes- Hive, Pig and setup of Hadoop Cluster.
Pre-requisites
Knowledge of programming in C++ or Java or any other Object Oriented Programming language is preferred, else you can enroll for our Java course free of cost to acquire the necessary skills to learn Hadoop.
Hardware/Software Requirements:
1) 64 bit or 64 bit ready PC/Laptop (Intel Core 2 Duo or above)
2) 8 GB RAM
3) 80 GB HDD
Course Content :
Module 1 : a) Virtual Box/VM Ware : Basics, Installations, Backups, Snapshots
b) ClouderaVM : Installations
c) Hadoop : Why Hadoop, Scaling, Distributed Framework, Hadoop v/s RDBMS, Brief history of Hadoop, Problems with traditional large-scale systems, Requirements for a new approach, Anatomy of a Hadoop cluster, Other Hadoop Ecosystem components
d) Setup Hadoop : Pseudo mode, Cluster mode, Installation of Java, Hadoop, Configurations of Hadoop, Hadoop Processes ( NN, SNN, JT, DN, TT), Temporary directory, UI, Common errors when running Hadoop cluster, Solutions
Module 2 : a) HDFS- Hadoop Distributed File System : HDFS design and architecture, HDFS concepts, Interacting HDFS using command line,Dataflow, Blocks, Replica
b) Hadoop Processes : Name node, Secondary name node, Job tracker, Task tracker, Data node
Module 3 : a) MapReduce : Developing MapReduce application, Phases in MapReduce framework, MapReduce input and output formats, Advanced concepts, Sample applications, Combiner
b) Writing a MapReduce Program : The MapReduce flow, Examining a sample MapReduce program, Basic MapReduce API concepts, Driver code, Mapper, Reducer, Hadoop’s streaming API, Using Eclipse for rapid development, Hands-on exercise, New MapReduce API
c) Common MapReduce Algorithms : Sorting and Searching, Indexing, Term Frequency – Inverse Document Frequency, Word Co-occurrence, Hands-on exercise
d) Writing advance map reduce programs : Building multivalue writable data, Accessing and using counters,Partitioner - Hashpartitioner,Hands on Exercises.
Module 4 : a) Hadoop Programming Languages : HIVE: Introduction, Installation, Configuration, Interacting HDFS using HIVE, MapReduce programs through HIVE, HIVE commands, Loading, Filtering, Grouping, Data types, Operators, Joins, Groups, Sample programs in HIVE
PIG: Basics, Configuration, Commands,Loading, Filtering, Grouping, Data types, Operators, Joins, Groups, Sample programs in PIG
b) HBase : What is HBase, HBase architecture, HBase API, Managing large data sets with HBase, Using HBase in Hadoop applications.
Module 5 : Integrating Hadoop into the Enterprise Workflow : Integrating Hadoop into an Existing Enterprise, Loading Data from an RDBMS into HDFS by Using Sqoop, Managing Real-Time Data Using Flume.
Sample Video :
## Any Queries? Post in the comment section below and you can win discount coupons while enrolling! ##
1) 30 hrs of live online classes by highly qualified Hadoop professionals
2) In-session practice exercises for gaining practical understanding
3) Suitable for database developers, programmers, BI developers and DBA’s
4) All live online classes are recorded and can be accessed for 6 months.
Course Description
Hadoop Big Data Training course helps you learn the core techniques and concepts of Big Data and Hadoop ecosystem. It equips you with in-depth knowledge of writing codes using MapReduce framework and managing large data sets with HBase. The topics covered in this course mainly includes- Hive, Pig and setup of Hadoop Cluster.
Pre-requisites
Knowledge of programming in C++ or Java or any other Object Oriented Programming language is preferred, else you can enroll for our Java course free of cost to acquire the necessary skills to learn Hadoop.
Hardware/Software Requirements:
1) 64 bit or 64 bit ready PC/Laptop (Intel Core 2 Duo or above)
2) 8 GB RAM
3) 80 GB HDD
Course Content :
Module 1 : a) Virtual Box/VM Ware : Basics, Installations, Backups, Snapshots
b) ClouderaVM : Installations
c) Hadoop : Why Hadoop, Scaling, Distributed Framework, Hadoop v/s RDBMS, Brief history of Hadoop, Problems with traditional large-scale systems, Requirements for a new approach, Anatomy of a Hadoop cluster, Other Hadoop Ecosystem components
d) Setup Hadoop : Pseudo mode, Cluster mode, Installation of Java, Hadoop, Configurations of Hadoop, Hadoop Processes ( NN, SNN, JT, DN, TT), Temporary directory, UI, Common errors when running Hadoop cluster, Solutions
Module 2 : a) HDFS- Hadoop Distributed File System : HDFS design and architecture, HDFS concepts, Interacting HDFS using command line,Dataflow, Blocks, Replica
b) Hadoop Processes : Name node, Secondary name node, Job tracker, Task tracker, Data node
Module 3 : a) MapReduce : Developing MapReduce application, Phases in MapReduce framework, MapReduce input and output formats, Advanced concepts, Sample applications, Combiner
b) Writing a MapReduce Program : The MapReduce flow, Examining a sample MapReduce program, Basic MapReduce API concepts, Driver code, Mapper, Reducer, Hadoop’s streaming API, Using Eclipse for rapid development, Hands-on exercise, New MapReduce API
c) Common MapReduce Algorithms : Sorting and Searching, Indexing, Term Frequency – Inverse Document Frequency, Word Co-occurrence, Hands-on exercise
d) Writing advance map reduce programs : Building multivalue writable data, Accessing and using counters,Partitioner - Hashpartitioner,Hands on Exercises.
Module 4 : a) Hadoop Programming Languages : HIVE: Introduction, Installation, Configuration, Interacting HDFS using HIVE, MapReduce programs through HIVE, HIVE commands, Loading, Filtering, Grouping, Data types, Operators, Joins, Groups, Sample programs in HIVE
PIG: Basics, Configuration, Commands,Loading, Filtering, Grouping, Data types, Operators, Joins, Groups, Sample programs in PIG
b) HBase : What is HBase, HBase architecture, HBase API, Managing large data sets with HBase, Using HBase in Hadoop applications.
Module 5 : Integrating Hadoop into the Enterprise Workflow : Integrating Hadoop into an Existing Enterprise, Loading Data from an RDBMS into HDFS by Using Sqoop, Managing Real-Time Data Using Flume.
Sample Video :
## Any Queries? Post in the comment section below and you can win discount coupons while enrolling! ##
