Big Data Online Course

Learn Big Data Analytics courses using Hadoop and Apache Spark from India’s top-ranked Big Data training and placement institute, which offers award-winning faculty, real-world projects, and extensive job placement assistance, all of which are designed to help you become a Big Data Engineer.

The most in-depth online Big Data Analytics courses using SQL, NoSQL, Hadoop, Spark, and Cloud computing. Attend this Big Data Hadoop Certification Training Course in our Classroom or Online Training with an Instructor.

Needintech’s Big Data Course in Chennai is taught by Big Data Hadoop industry experts and covers everything you need to know about Big Data Hadoop course content tools like MapReduce, Hive, Pig, HBase, Spark, Oozie, Flume, Sqoop HDFS, and YARN.

Syllabus of Big Data Hadoop Certification Course

Module 1: Introduction to Big Data Hadoop Certification

• High Availability
• Scaling
• Advantages and Challenges

Module 2: Introduction to Big Data

• What is Big data
• Big Data opportunities,Challenges
• Characteristics of Big data

Module 3: Introduction to Big Data Hadoop Certification

• Big Data Hadoop Certification Distributed File System
• Comparing Big Data Hadoop Certification & SQL
• Industries using Big Data Hadoop Certification
• Data Locality
• Big Data Hadoop Certification Architecture
• Map Reduce & HDFS
• Using the Big Data Hadoop Certification single node image (Clone)

Module 4: Big Data Hadoop Certification Distributed File System (HDFS)

• HDFS Design & Concepts
• Blocks, Name nodes and Data nodes
• HDFS High-Availability and HDFS Federation
• Big Data Hadoop Certification DFS The Command-Line Interface
• Basic File System Operations
• Anatomy of File Read,File Write
• Block Placement Policy and Modes
• More detailed explanation about Configuration files
• Metadata, FS image, Edit log, Secondary Name Node and Safe Mode
• How to add New Data Node dynamically,decommission a Data Node dynamically (Without stopping cluster)
• FSCK Utility. (Block report)
• How to override default configuration at system level and Programming level
• HDFS Federation
• ZOOKEEPER Leader Election Algorithm
• Exercise and small use case on HDFS

Module 5: Map Reduce

• Map Reduce Functional Programming Basics
• Map and Reduce Basics
• How Map Reduce Works
• Anatomy of a Map Reduce Job Run
• Legacy Architecture ->Job Submission, Job Initialization, Task Assignment, Task Execution, Progress and Status Updates
• Job Completion, Failures
• Shuffling and Sorting
• Splits, Record reader, Partition, Types of partitions & Combiner
• Optimization Techniques -> Speculative Execution, JVM Reuse and No. Slots
• Types of Schedulers and Counters
• Comparisons between Old and New API at code and Architecture Level
• Getting the data from RDBMS into HDFS using Custom data types
• Distributed Cache and Big Data Hadoop Certification Streaming (Python, Ruby and R)
• YARN
• Sequential Files and Map Files
• Enabling Compression Codec’s
• Map side Join with distributed Cache
• Types of I/O Formats: Multiple outputs, NLINEinputformat
• Handling small files using CombineFileInputFormat

Module 6: Map Reduce Programming – Java Programming

• Hands on “Word Count” in Map Reduce in standalone and Pseudo distribution Mode
• Sorting files using Big Data Hadoop Certification Configuration API discussion
• Emulating “grep” for searching inside a file in Big Data Hadoop Certification
• DBInput Format
• Job Dependency API discussion
• Input Format API discussion,Split API discussion
• Custom Data type creation in Big Data Hadoop Certification

Module 7: NOSQL

• ACID in RDBMS and BASE in NoSQL
• CAP Theorem and Types of Consistency
• Types of NoSQL Databases in detail
• Columnar Databases in Detail (HBASE and CASSANDRA)
• TTL, Bloom Filters and