Hadoop Admin Training

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Spark Online Offering Best Hadoop Administration  Training in Hyderabad,Ameerpet. Contact Sampath@09493389934.

Hadoop Admin Training includes the basics of Hadoop Development Topics.
Hadoop Training Course Prerequisites

Basic Unix/Linux Commands, will be thought as part of Course

Core Java Knowledge (OOPS Concepts, Collections , Exception Handlng ) — For Map-Reduce Programming
Basic SQL Query knowledge – For Hive

Hadoop Installed VM Software is provided for Practise.

Hadoop Training Course Duration
30 Sessions,45 Hours

 

Hadoop Online Training in Hyderabad,Ameerpet Course Content:

Introduction to Big Data

Big Data Concepts

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

Introduction to Hadoop

 

HDFS at Hadoop Online Training in Hyderabad:

Industries using Hadoop.
Data Locality.
Hadoop Architecture.
Map Reduce & HDFS.
The 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
File Read
File Write
Block Placement Policy and Modes
HDFS Configuration files.
Metadata, FS image, Edit log, Secondary Name Node and Safe Mode.
How to add New Data Node dynamically.
How to decommission a Data Node dynamically (Without stopping cluster).
FSCK Utility. (Block report).
overriding default configuration at system level and Programming level.
HDFS Federation.
ZOOKEEPER Leader Election Algorithm.
Exercise and small use case on HDFS.

Map Reduce at Hadoop Online Training in Hyderabad

Functional Programming Basics.
Map and Reduce Basics
How Map Reduce Works
Map Reduce Architecture
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 at Hadoop Training Hyderabad

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.
Map/Reduce Programming – Java Programming

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

HBase at Hadoop Training Hyderabad,Ameerpet

HBase Installation
HBase 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 Coprocessors (Endpoints and Observers with programs).
Real world use case consisting of HDFS,MR and HBASE.

Hive Hadoop Admin Training Hyderabad:

Hive Installation
Hive Architecture.
Hive Services, Hive Shell, Hive Server, HWI
Meta store
Hive Query Language
OLTP vs. OLAP
Working with Tables.
Primitive data types and complex data types.
Working with Partitions.
UDFs
Hive Bucketed Tables and Sampling.
External partitioned tables
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
HBASE Integration with Hive
Real Time Exercises

Pig at Big Data Online Training in Hyderabad,Ameerpet

Pig Installation
Execution Types
Grunt Shell
Pig Latin
Data Processing
Schema on read
Primitive data types and complex data types.
Tuple schema, BAG Schema and MAP Schema.
Loading and Storing
Filtering
Grouping & Joining
Debugging commands (Illustrate and Explain).
Validations in PIG.
Type casting in PIG.
Working with Functions
User Defined Functions
Types of JOINS in pig and Replicated Join in detail.
SPLITS and Multiquery execution.
Error Handling, FLATTEN and ORDER BY.
Parameter Substitution.
Nested For Each.
User Defined Functions, Dynamic Invokers and Macros.
HBASE intgration with PIG.
Piggy Bank.
Real Time Exercises

SQOOP Hadoop Training Hyderabad,Ameerpet

Sqoop Installation
Import Data.(Full table, Only Subset, Target Directory, protecting Password, file format other than CSV,Compressing,Control Parallelism, All tables Import)
Incremental Import(Import only New data, Last Imported data, storing Password in Metastore, Sharing Metastore between Sqoop Clients)
Free Form Query Import
Export data to RDBMS,HIVE and HBASE
Hands on Exercises.

HCATALOG.

HCATALOG Installation.
Introduction to HCATALOG.
About Hcatalog with PIG,HIVE and MR.
Hands on Exercises.

FLUME at Hadoop Training Hyderabad:

FLUME Installation
Introduction to Flume
Flume Agents: Sources, Channels and Sinks
Log User information using Java program in to HDFS using LOG4J and Avro Source
Log User information using Java program in to HDFS using Tail Source
Log User information using Java program in to HBASE using LOG4J and Avro Source
Log User information using Java program in to HBASE using Tail Source
Flume Commands
Use case of Flume: Extract the data from twitter in to HDFS and HBASE. analysing data using HIVE and PIG
Analyzing Movie Reviews using Twitter Tweets

More Ecosystems

Hortonworks,Cloudera& MapR