Big Data Hadoop training will enable you to master the concepts of the Hadoop framework and its deployment in a cluster environment. ... Understand the different components of Hadoop ecosystem such as Hadoop 2.7, Yarn, MapReduce, Pig, Hive, Impala, HBase, Sqoop, Flume, and Apache Spark with this Hadoop course.Hadoop is not a type of database, but rather a software ecosystem that allows for massively parallel computing. It is an enabler of certain types NoSQL distributed databases (such as HBase), which can allow for data to be spread across thousands of servers with little reduction in performance.
Introduction to Big Data & Hadoop Fundamentals
Dimensions of Big data
Type of Data generation
Apache ecosystem & its projects
Hadoop distributors
HDFS core concepts
Modes of Hadoop employment
HDFS Flow architecture
HDFS MrV1 vs. MrV2 architecture
Types of Data compression techniques
Rack topology
HDFS utility commands
Min h/w requirements for a cluster & property files changes
MapReduce Design flow
MapReduce Program (Job) execution
Types of Input formats & Output Formats
MapReduce Datatypes
Performance tuning of MapReduce jobs
Counters techniques
Hive architecture flow
Types of hive tables flow
DML/DDL commands explanation
Partitioning logic
Bucketing logic
Hive script execution in shell & HUE
Introduction to Pig concepts
Pig modes of execution/storage concepts
Pig program logics explanation
Pig basic commands
Pig script execution in shell/HUE
Introduction to Sqoop concepts
Sqoop internal design/architecture
Sqoop Import statements concepts
Sqoop Export Statements concepts
Quest Data connectors flow
Incremental updating concepts
Creating a database in MySQL for importing to HDFS
Sqoop commands execution in shell/HUE
Introduction to Flume & features
Flume topology & core concepts
Property file parameters logic
Introduction to Hue design
Hue architecture flow/UI interface
Principles of Hadoop administration & its importance
Hadoop admin commands explanation
Balancer concepts
Rolling upgrade mechanism explanation