Hadoop training in dilsukhnagar hyderabad

Module 2: Introduction to Big Data

Module 3: Introduction to Hadoop

Module 4: Hadoop Distributed File System (HDFS)

HDFS Design & Concepts
Blocks, Name nodes and Data nodes
HDFS High-Availability and HDFS Federation
Hadoop 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 Hadoop 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

Module 7: NOSQL

Module 8: HBase

HBase Installation, Concepts
HBase Data Model and Comparison between RDBMS and NOSQL
Master & Region Servers
HBase Operations (DDL and DML) through Shell and Programming and HBase Architecture
Catalog Tables
Block Cache and sharding
SPLITS
DATA Modeling (Sequential, Salted, Promoted and Random Keys)
Java API’s and Rest Interface
Client Side Buffering and Process 1 million records using Client side Buffering
HBase Counters
Enabling Replication and HBase RAW Scans
HBase Filters
Bulk Loading and Co processors (Endpoints and Observers with programs)
Real world use case consisting of HDFS,MR and HBASE

Module 9: Hive

Hive Installation, Introduction and Architecture
Hive Services, Hive Shell, Hive Server and Hive Web Interface (HWI)
Meta store, Hive QL
OLTP vs. OLAP
Working with Tables
Primitive data types and complex data types
Working with Partitions
User Defined Functions
Hive Bucketed Tables and Sampling
External partitioned tables, Map the data to the partition in the table, Writing the output of one query to another table, Multiple inserts
Dynamic Partition
Differences between ORDER BY, DISTRIBUTE BY and SORT BY
Bucketing and Sorted Bucketing with Dynamic partition
RC File
INDEXES and VIEWS
MAPSIDE JOINS
Compression on hive tables and Migrating Hive tables
Dynamic substation of Hive and Different ways of running Hive
How to enable Update in HIVE
Log Analysis on Hive
Access HBASE tables using Hive
Hands on Exercises

Module 10: Pig

Module 11: SQOOP

Module 12: HCatalog

Module 13: Flume

Module 14: More Ecosystems

Module 15: Oozie

Workflow (Action, Start, Action, End, Kill, Join and Fork), Schedulers, Coordinators and Bundles.,to show how to schedule Sqoop Job, Hive, MR and PIG
Real world Use case which will find the top websites used by users of certain ages and will be scheduled to run for every one hour
Zoo Keeper
HBASE Integration with HIVE and PIG
Phoenix
Proof of concept (POC)

Module 16: SPARK

Hadoop Course Content