- Well-educated and professional team of Hadoop instructors offering comprehensive coaching on all aspects
- Hands-on training with various real-world projects to impart practical knowledge to the candidates
- Fully updated and industry-led course material
- Job placement assistance & assurance
About Hadoop course
The Hadoop training in Wardha is specially designed to enable candidates to gain in-depth knowledge of all concepts of the Hadoop ecosystem and Big Data. Throughout the learning program, the candidates will be exposed to various real-world projects which are in line with the Hadoop certification exam. Most of the projects included in the curriculum are diverse, belonging to different domains such as banking, insurance, telecommunications, social media, e-commerce, etc.
Who should join the Hadoop course?
An increasing number of business enterprises are using Big Data to decipher significant trends and facilitate better decision making. This immense potential of Big Data opens up several job opportunities for IT professionals. Thus, getting Hadoop certification in Wardha is a great way to boost your career. This training program is best suited to:
- Software Architects
- Software Developers and Project Managers
- Data Engineers
- Data Warehousing Professionals
- Data Analysts
- Business Intelligence Professionals
- Mainframe Professionals
- Testing Engineers
- Senior IT Professionals
- DBAs and DB Professionals
- All aspirants looking to establish a career in this field
Hadoop Course Syllabus:
Installing Hadoop
- Hadoop Cluster Architecture
- Production Cluster Setup
- Cluster modes
- Shell commands in Hadoop
- Configuration files for Hadoop
- Single node cluster for Cloudera
- Hive and Pig
- Sqoop
- Flame
- Scala and Spark
Introduction to Big Data Hadoop
- What is Big data and Hadoop
- Hadoop Ecosystem - Map Reduce and HDFS
- Hadoop Distributed file system - Replication, Name node, Block size, and high availability
- YARN - Resource and Node Manager
- Replicating Data
- Determining block size
- NameNode and DataNode
Hive
- Introduction to Hadoop Hive
- Architecture of Hive
- Hive vs. Pig and RDBMS
- Hive Query Language
- Creating a database and table
- Types of Hive Tables
- HCatalog
- Storing Hive results
- Hive partitioning
- Hive Buckets
- Hive table partitioning
Advanced Hive and Impala
- Indexing in Hive
- Map side join
- Complex data types
- Hive user-defined functions
- Introduction to impala
- Hive vs. Impala
- Architecture of Impala
- Working with hive queries
Pig
- Introduction to Apache Pig
- Features of Pig
- Data types and schema in Hive
- Pig Functions
- Hive bags
- Tuples
- Fields
- Working with Pig in MapReduce
Flume, Sqoop & HBase
- Introduction to Apache Sqoop
- Imports and exports
- Improving Sqoop performance
- Limitations of Sqoop
- Flume architecture
- HBase
- CAP Theorem
- Generating sequence number with flume
Spark applications and Scala
- Apache spark applications and Scala
- Studying Scala
- Need for Scala
- Object-oriented programming concepts
- Scala code execution
- Classes in Scala - Getters, setters, constructors, extending objects
- Overriding methods
- Functional programming
- Anonymous functions
- Bobsrockets package
- Mutable and immutable collections
Spark Framework
- Apache spark introduction
- Features
- Comparing Spark with Hadoop
- Spark components
- HDFS and Spark
- Importance of Scala and RDD
- Spark and RDD
- Spark transformations
- Data loading
- MapReduce comparison
- Key-value pair
- RDD deployment with HDFS
Data Frames and Spark SQL
- Spark SQL in detail
- Significance of SQL in Spark
- JSON support
- XML data
- Parquet files
- Hive context creation
- Data frame to hive reading of JDBC
- Data Frames in Spark
- Working with CSV files
- JDBC tables
- Data frame to JDBC
- Shared variable
- Accumulators
- Query and data frames
- Hive on Spark as an execution engine
WMachine learning with Spark
- Algorithm types
- The iterative algorithm in Spark
- Spark graph processing
- K-means and machine learning
- Variables in Spark
- Accumulators
Spark Streaming
- Introduction to Spark streaming
- The architecture of spark streaming
- Spark streaming program
- Processing data
- DStream
- Sliding window operations
- Advanced data sources
Hadoop Administration
- Hadoop cluster setup
- MapReduce and Hadoop cluster
- MapReduce Code
- Cloudera Manager Setup
- Cluster configuration
- Hadoop configuration file
- Parameters and values for configuration
- HDFS parameters
- MapReduce parameters
- Hadoop environment setup
- Data node directory structure
- File system image
- Checkpoint procedure
ETL Connectivity with Hadoop
- How ETL tools work
- ETL and data warehousing
- End to End ETL
Types of Real-time Hadoop Projects
Most of the Hadoop training institutes listed at Sulekha offer highly relevant and updated real-world projects which are included in the curriculum. This will help you use all your acquired knowledge in the real-world industry set up and to test your skills.
Projects that focus on MapReduce, Hive, and Sqoop
- Learning how to write a MapReduce program
- Deploying Apache Pig
- Learning to work with Hive
A project to help with Hadoop YARN using real-life case studies
- Appending data
- Using Sqoop commands
- Using Sqoop commands
- Data processing using MapReduce
Projects for partitioning tables in Hive
- Manual and dynamic partitioning
- Bucketing
MultiNode cluster setup project
- Running Hadoop multi-node
- Deploying MapReduce on Hadoop cluster
Expert-level Hadoop Certification Exams
Below is the list of expert certification exams which you can apply after accomplishing this Hadoop training course from our service partners,
- CCDH (Cloudera Certified Developer for Apache Hadoop)
- CCAH (Cloudera Certified Administrator for Apache Hadoop)
- CCSHB (Cloudera Certified Specialist in Apache HBase)
- HDPCD (Hortonworks Data Platform Certified Developer)
- HDPCA (Hortonworks Data Platform Certified Administrator)
- HDPCD: Java (Hortonworks Data Platform Certified Developer: Java)
- MCHA (MapR Certified Hadoop Administrator)
- MCHD (MapR Certified Hadoop Developer)
- MCHBD (MapR Certified HBase Developer)
Hadoop Job Opportunities
Some of the most prominent Hadoop job roles along with their salaries are as follows:
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