Big Data / Hadoop Training in Electronic City , Bangalore

BIG DATA / HADOOP CLASSES

EMEXO TECHNOLOGIES

Big Data / Hadoop

15000 - 20000

5y ago

Course Duration: 3 Weeks

Course Details

Let eMexo Technologie in Electronic City Bangalore take you from the fundamentals of Hadoop to Advance Hadoop and make you an expert in developing real time Hadoop applications. Here are the major topics we cover under this Hadoop course Syllabus, Introduction to Big Data, Introduction Apache Hadoop, MapReduce, Apache Hive, Apache Pig, Apache Hbase, Apache Sqoop Apache Flume, Impala, Apache Spark and related Projects. Each topic will be covered in practical way with examples. Course Syllabus: Introduction to Big Data Big Data relies on volume, velocity, and variety with respect to processing. 30 min Data can be divided into three types—unstructured data, semi-structured data, and structured data. 30 min Big Data technology understands and navigates big data sources, analyzes unstructured data, and ingests data at a high speed. 30 min Introduction Apache Hadoop Type of Data generation 30 min Apache ecosystem & its projects 30 min Hadoop distributors 30 min HDFS core concepts 30 min Modes of Hadoop employment 30 min HDFS Flow architecture 30 min HDFS MrV1 vs. MrV2 architecture 30 min Yarn Architecture 30 min Unix commands 30 min Hadoop commands 30 min Hands on exercises 30 min MapReduce MapReduce Design flow 30 min MapReduce Program (Job) execution 30 min Types of Input formats & Output Formats 30 min MapReduce Data Types 30 min Performance tuning of MapReduce jobs 30 min Word-count program example explanation 30 min Hands on with word-count program 30 min Apache Hive Introduction to Hive 30 min Hive features 30 min Hive architecture flow 30 min Hive vs Pig 30 min HCatalog 30 min Hive Limitations 30 min Hive Data Types 30 min Hive Complex Data Types 30 min DML/DDL commands explanation 30 min Hive data loading 30 min Hive Functions 30 min Hive Joins 30 min Partitioning static & Dynamic logic 30 min Bucketing logic 30 min Skewed by logic 30 min Hive File formats 30 min Performance Techniques 30 min Hive script execution in shell & HUE 30 min Hive exercises 30 min Hive hands on 30 min Apache Pig Introduction to Pig concepts and Architecture 30 min Pig Components 30 min Pig Execution modes 30 min Pig Latin Basics 30 min Pig Data Flow 30 min Pig Latin Concepts 30 min Pig Commands 30 min Pig Data Types 30 min Pig Latin – Examples 30 min Advanced Pig Programming concepts like COGROUP, pig UDF 30 min Pig modes of execution 30 min Pig script execution in shell/HUE 30 min Pig hands on 30 min Apache Hbase Introduction to Hbase concepts 30 min Introduction to NoSQL/CAP theorem concepts 30 min Hbase design/architecture flow 30 min Hbase table commands 30 min HDFS vs Hbase 30 min RDBMS vs Hbase 30 min Hbase execution in shell/HUE 30 min Hbase Example 30 min Hands on 30 min Apache Sqoop Introduction to Sqoop concepts 30 min Sqoop internal design/architecture 30 min Sqoop Import statements concepts 30 min Sqoop Export Statements concepts 30 min Quest Data connectors flow 30 min Incremental updating concepts 30 min Creating a database in MySQL for importing to HDFS 30 min Sqoop commands execution in shell/HUE 30 min Sqoop Examples 30 min Sqoop Hands on 30 min Apache Flume Introduction to Flume & features 30 min Flume topology & core concepts 30 min Property file parameters logic 30 min Flume NetCat example & Spooldir example 30 min Flume Hands on 30 min Impala Impala Architecture 30 min Creating tables in Impala 30 min Accessing Hive Metastore 30 min Hands on 30 min Apache Spark About Spark 30 min Spark History 30 min MapReduce and Spark 30 min Spark – Layered Architecture 30 min Spark – Cluster Architecture 30 min Cluster Manager – Deployment Modes 30 min About Scala 30 min Word count example on Scala 30 min Project

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BIG DATA / HADOOP CLASSES

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