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Course Curriculum

Bigdata-Hadoop
Basics
Why we need Hadoop? Details 00:00:00
Why Hadoop? Details 00:00:00
Definition of BigData Details 00:00:00
Hadoop Ecosystem Details 00:00:00
Hadoop Storage – HDFS Details 00:00:00
HDFS
Why HDFS? Details 00:00:00
What is HDFS? Details 00:00:00
Regular Files System Vs HDFS Details 00:00:00
HDFS Characteristics Details 00:00:00
HDFS Architecture Details 00:00:00
High Availability Details 00:00:00
Hadoop FS Shell Details 00:00:00
Classic MapReduce
How Map Reduce works as Processing Framework? Details 00:00:00
End to End execution flow of Map Reduce job Details 00:00:00
Different tasks in Map Reduce job Details 00:00:00
Why Reducer is optional while Mapper is mandatory? Details 00:00:00
Introduction to Combiner Details 00:00:00
Introduction to Partitioner Details 00:00:00
Map Side Join Vs Reducer Side join Details 00:00:00
Map Reduce Programming Details 00:00:00
YARN
What is YARN? Details 00:00:00
Advantages of YARN Details 00:00:00
YARN Architecture Details 00:00:00
Classic Mapreduce vs YARN Details 00:00:00
Scheduling in YARN Details 00:00:00
Fair Scheduler Details 00:00:00
Capacity Scheduler Details 00:00:00
Pig
Introduction to Pig Latin Details 00:00:00
History and evolution of Pig latin Details 00:00:00
Pig architecture Details 00:00:00
Pig Specific Data types Details 00:00:00
Complex Data types Details 00:00:00
Working with Grunt Shell. Details 00:00:00
Pig Data input techniques for flat files(comma separated, tab delimited and fixed width) Details 00:00:00
How to attach schema to a file/table in pig. Details 00:00:00
Schema referencing for similar tables and files Details 00:00:00
Working with delimiters Details 00:00:00
Data Transformation using Pig Details 00:00:00
HIVE
Introduction Details 00:00:00
HIVE Architecture Details 00:00:00
Interacting HDFS using HIVE Details 00:00:00
HIVE Data Types Details 00:00:00
HIVE Scripting HQL (DDL+DML) Details 00:00:00
Loading, Filtering, Grouping Details 00:00:00
Data types, Operators Details 00:00:00
Joins, Groups. Alter and Delete in Hive Details 00:00:00
Partition, Bucketing in Hive Details 00:00:00
Joins, Unions, Parameterization in Hive Details 00:00:00
UDFs in Hive Details 00:00:00
HCatalog
What is HCatalog? Details 00:00:00
Why we need it? Details 00:00:00
HCatalog CLI Commands Details 00:00:00
Pig using HCatalog Details 00:00:00
Sqoop
Getting Sqoop Details 00:00:00
A Sample Import Details 00:00:00
Database Imports Details 00:00:00
Controlling the Imports Details 00:00:00
Imports and consistency Details 00:00:00
Direct-mode imports Details 00:00:00
Performing an Export Details 00:00:00
Import and Export to Hive using sqoop Details 00:00:00
Flume
What is Apache Flume? Details 00:00:00
Basic Flume Architecture Details 00:00:00
Flume Sources, Sinks, Channels Details 00:00:00
Deploying an agent onto a single node cluster Details 00:00:00
Create a Sample Application to capture logs using flume Details 00:00:00
Oozie
introduction to oozie Details 00:00:00
How to schedule jobs using Oozie Details 00:00:00
What kind of jobs can be scheduled using Oozie Details 00:00:00
Hbase and Zookeeper
Introduction to Zookeeper Details 00:00:00
Hbase Architecture Details 00:00:00
Zookeeper and Hbase integration Details 00:00:00
Region servers and their implementation Details 00:00:00
HBase table and column family structure Details 00:00:00
HBase versioning concept Details 00:00:00
HBase flexible schema Details 00:00:00
Introduction to Spark
Hortonworks and Cloudera Certification Guidance