To process and store Big data, Hadoop is project of Apache that is an open source software. This is is the most promising and accelerating fields in overall technologies in IT market. In order to grab the opportunities of this field, you have to train in latest curriculum according to current industry requirements along with best practices.
Hadoop & Big Data Introduction
You can learn about how hadoop solved big data issues, hadoop architecture, ecosystem, HDFS, and many other.
About big data and challenges of big data
Limitation of big data architecture along with solutions
Hadoop with features, ecosystem, core components
Hadoop HDFS (Hadoop Distributed File System)storage
Mapreduce framework of Hadoop processing and various Hadoop distributions
HDFS And Architecture Of Hadoop
You learn the architecture of Hadoop cluster, configuration flestechniques of data loading using flume and sqoop.
Architecture of Hadoop cluster, configuration files, high availability & federation architecture, typical production
Modes of Hadoop cluster, common commands of Hadoop shell, basic administration of Hadoop
Single node and multi node cluster setup
MapReduce Framework Of Hadoop
You will learn indetail about mapreduce framework of Hadoop, working on stored data in HDFS, and advanced concepts of MapReduce.
Importance of MapReduce, comparison of MapReduce way vs traditional way
YARN architecture, components, workflow and execution flow of YARN mapreduce app
MapReduce Program Anatomay, partitioner & combiner of MapReduce
Relation in between HDFS blocks and input splits
Demo of weather dataset and healthcare dataset
Advanced Hadoop MapReduce
You can learn about advanced concepts of MapReduce like distributed cache, counters, custom input format, MRunit, XML parsing, and sequence input format.
Counters, distributed cache, MRunit, reduce join
Sequence & custom input format
Using MapReduce XML file parsing
Apache Hive & Pig
Here, you will learn about Hive concepts, querying & loading in hive, data types of hive, Hive UDF, and hive concepts running. You also learn about pig, types & uses of pig, pig & mapreduce tight coupling, run modes of pig, latin script of pig, UDF, streaming & testing of Pig scripts.
Apache Hive introduction, architecture & components
Hive vs pig, hive metastore, limitations of Hive, traditional database comparison
Hive data models and data types, partition, Bucketing, tables (external and managed tables)
Managing outputs, query data, import data
Hive script, UDF, retails use case
Apache pig introduction, execution, components, data types, data models
Pig vs MapReduce, Latin programs of pig, pig streaming & UDF
Utility and shell commands, use case of aviation in pig, testing scripts of pig
Pig and hive demo of healthcare dataset
Advanced HBase And Apache Hive
Here, you learn about advanced concepts of Apache Hive like dynamic partitioning, UDF, hive views & indexes, and optimization. You will also learn about HBase run modes, architecture and components.
Dynamic partitioning and join tables of Hive QL, custom scripts of MapReduce
Hive indexes, views, query optimizers, thrift server, UDF
HBase & NOSQL database introduction, RDBMS vs HBase
HBase architecture, components, run modes, configuration, cluster development
Advanced Apache HBase
You can learn advanced concepts of Apache HBase and also learn about zookeeper.
HBase shell, data model, client API
Techniques of hive data loading
Apache Zookeeper introduction, data model, service
HBase filters and bulk loading
Inserting and getting data
Apache Spark Process Distributed Data
In this section, you learn about apache spark, ecosystem, Sparkcontext. You also learn RDD (Resilient Distributed Datasets), run spark cluster, performance comparison of spark and MapReduce.
About spark, ecosystem, components
What is scala and its importance
Spark context and spark RDD
Hadoop And Oozie Project
You will learn about the multiple components of Hadoop ecosystem for solving big data issues.
About oozie, components, workflow, coordinator, commands, web console
Oozie scheduler, oozie for mapreduce, Hive in Oozie
Demo on hadoop project and oozie overflow
Integration of Hadoop talend