From our Hadoop Online Training learner can understand the fundamental
concepts of Hadoop Tool. Our training program is packed with tips, exercises,
hints and examples. Our training sessions makes you to learn Hadoop quickly and
effectively and also helps you to pass Bigdata
Certification easily.
Hadoop Online Training Highlights
·
Detailed course material with real time examples
·
Hadoop classes with expert trainers
·
24x7 customer support
·
We are giving placement support in companies in USA, Canada and
India
·
Certification oriented Hadoop training
Hadoop
Online Certification Course Benefits
·
Industry Expert Trainer
·
Real time Scenario
·
Doubt session Support
·
Topic to Topic Assignments
·
Resume Preparation
·
Interview Q/A
·
Record Sessions
·
Detailed Study Material
·
24/7 Support
Bigadata
Hadoop Certification Training Curriculum
·
Understanding BigData
o What
is Big Data?
o Big-Data
characteristics
·
Hadoop Distributions
o Hortonworks
o Cloudera
o Pivotal
HD
o Greenplum
·
Introduction to Apache Hadoop
o Flavors
of Hadoop: Big-Insights, Google Query etc..
·
Hadoop Eco-system components: Introduction
o MapReduce
o HDFS
o Apache
Pig
o Apache
Hive
o HBASE
o Apache
Oozie
o FLUME
o SQOOP
o Apache
Mahout
o KIJI
o LUCENE
o SOLR
o KiteSDK
o Impala
o Chukwa
o Shark
o Cascading
·
Understanding Hadoop Cluster
·
Hadoop Core-Components
o NameNode
o JobTracker
o TaskTracker
o DataNode
o SecondaryNameNode
·
HDFS Architecture
o Why
64MB?
o Why
Block?
o Why
replication factor 3?
·
Discuss NameNode and DataNode
·
Discuss JobTracker and TaskTracker
·
Typical workflow of Hadoop application
·
Rack Awareness
o Network
Topology
o Assignment
of Blocks to Racks and Nodes
o Block
Reports
o Heart
Beat
o Block
Management Service
·
Anatomy of File Write
·
Anatomy of File Read
·
Heart Beats and Block Reports
o Discuss
Secondary NameNode
o Usage
of FsImage and Edits log
§ Map
Reduce Overview
§ Best
Practices to setup Hadoop cluster
§ Cluster
Configuration
§ Core-default.xml
§ Hdfs-default.xml
§ Mapred-default.xml
§ Hadoop-env.sh
§ Slaves
§ Masters
§ Need
of *-site.xml
§ Map
Reduce Framework
§ Why
Map Reduce?
§ Use
cases where Map Reduce is used
§ Hello
world program with Weather Use Case
§ Setup
environment for the programs
§ Possible
ways of writing Map Reduce program with sample codes find the best code and
discuss
§ Configured,
Tool, GenericOptionParser and queues usage
§ Demo
for calculating maximum temperature and Minimum temperature
§ Limitations
of traditional way of solving word count with large dataset
§ Map
Reduce way of solving the problem
§ Complete
overview of MapReduce
§ Split
Size
§ Combiners
§ Multi
Reducers
§ Parts
of Map Reduce
§ Algorithms
§ Apache
Hadoop Single Node Installation Demo
§ Namenode
format
§ Apache
Hadoop Multi Node Installation Demo
§ Add
nodes dynamically to a cluster with Demo
§ Remove
nodes dynamically to a cluster with Demo
§ Safe
Mode
§ Hadoop
cluster modes
§ Standalone
Mode
§ Psuedo
distributed Mode
§ Fully
distributed mode
§ Revision
§ HDFS
Practicals(HDFS Commands)
§ Map
Reduce Anatomy
§ Job
Submission
§ Job
Initialization
§ Task
Assignments
§ Task
Execution
§ Schedulers
§ Quiz
§ Map
Reduce Failure Scenarios
§ Speculative
Execution
§ Sequence
File
§ Input
File Formats
§ Output
File Formats
§ Writable
DataTypes
§ Custom
Input Formats
§ Custom
keys, Values usage of writables
§ Walkthrough
the installation process through the cloudera manager
§ Example
List, show sample example list for the installation
§ Demo
on teragen, wordcount, inverted index, examples
§ Debugging
Map Reduce Programs
§ Map
Reduce Advance Concepts
§ Partitioning
and Custom Partitioner
§ Joins
§ Multi
outputs
§ Counters
§ MR
unit testcases
§ MR
Design patterns
§ Distributed
Cache
§ Command
line implementation
§ MapReduce
API implementation
§ Map
Reduce Advance concepts examples
§ Introduction
to course Project
§ Data
loading techniques
§ Hadoop
Copy commands
§ Put,get,copyFromLocal,copyToLocal,mv,chmod,rmr,rmr
–skipTrash,distcp,ls,lsr,df,du,cp,moveFromLocal,moveToLocal,text,touhz,tail,mkdir,help
§ Flume
§ Sqoop
§ Demo
for Hadoop Copy Commands
§ Sqoop
Theory
§ Demo
for Sqoop
§ Need
of Pig?
§ Why
Pig Created?
§ Introduction
to skew Join
§ Why
go for Pig when Map Reduce is there?
§ Pig
use cases
§ Pig
built in operators
§ Pig
store schem
§ Operators
§ Load
§ Store
§ Dump
§ Filter
§ Distinct
§ Group
§ CoGroup
§ Join
§ Stream
§ Foreach
Generate
§ Parallel
§ Distinct
§ Limit
§ ORDER
§ CROSS
§ UNION
§ SPLIT
§ Sampling
§ Dump
Vs Store
§ DataTypes
§ Complex
§ Bag
§ Tuple
§ Atom
§ Map
§ Primitives
§ Integers
§ Float
§ Chararray
§ byteArray
§ Double
§ Diagnostic
Operators
§ Describe
§ Explain
§ Illustrate
§ UDFs
§ Filter
Function
§ Eval
Function
§ Macros
§ Demo
§ Storage
Handlers
§ Pig
Practicals and Usecases
§ Demo
using schema
§ Demo
using without schema
§ Hive
Background
§ What
is Hive?
§ Pig
Vs Hive
§ Where
to Use Hive?
§ Hive
Architecture
§ Metastore
§ Hive
execution modes
§ External,
Manged, Native and Non-native tables
§ Hive
Partitions
§ Dynamic
Partitions
§ Static
Partitions
§ Buckets
§ Hive
DataModel
§ Hive
DataTypes
§ Primitive
§ Complex
§ Queries
§ Create
Managed Table
§ Load
Data
§ Insert
overwrite table
§ Insert
into Local directory
§ CTAS
§ Insert
Overwrite table select
§ Joins
§ Inner
Joins
§ Outer
Joins
§ Skew
Joins
§ Multi-table
Inserts
§ Multiple
files, directories, table inserts
§ Serde
§ View
§ Index
§ UDF
§ UDAF
§ Hive
Practicals
§ Oozie
Architecture
§ Workflow
designing in Oozie
§ Oozie
practicals
§ YARN
Architecture
§ Hadoop
Classic vs YARN
§ YARN
Demo
§ Flume
Architecture
§ Flume
Practicals
§ Zoo
Keeper
§ Introduction
to NOSQL Databases
§ NOSql
Landscapes
§ Introduction
to HBASE
§ HBASE
vs RDBMS
§ Create
Table on HBASE using HBASE shell
§ Where
to use HBASE?
§ Where
not to use HBASE?
§ Write
Files to HBASE
§ Major
Components of HBASE
§ HBase
Master
§ HRegionServer
§ HBase
Client
§ Zookeeper
§ Region
§ HBase
Practicals
§ HBASE
–ROOT- Catalog table
§ CAP
Theorm
§ Compaction
§ Sharding
§ Sparse
Datastore
§ Cassandra
Architecture
§ Big
Table and Dynamo
§ Distributed
Hash Table, P2P Fault Tolerant
§ Data
Modelling
§ Column
Families
§ Installation
Demo on Cassandra
§ Practicals
§ Real
time Project Analysis
§ Design
§ Implementation
§ Execution
§ Debugging
§ Optimization
Techniques
§ Which
one to use where
§ Amazon
Web Services(Hadoop on Cloud) – Installations for MultiNode
§ EMR
and S3
§ Storm
Architecture
§ Real
time use case with Storm
§ Spark
§ What
is Spark?
§ Understanding
Spark
§ Spark
Architecture
§ RDD
§ Hadoop
RDD
§ RDDs
Partitioning
§ Lazy
Evaluation
§ Caching
§ Spark
Context
§ Map,
flatMap, filter
§ Actions
§ Serialization
§ Scala
§ Scala
Features
§ Scala
Functions
§ Collections
and Combiners
§ Spark
with Scala
§ Spark
with Yarn
§ Spark
on Cluster mode
§ Spark
CLI
§ Spark
programming with Java API
§ Spark
Streaming
§ Spark
SQL
§ Spark
SQL Context
§ Spark
SQL with Hive
§ Spark
MLib Algorithms(K-Means, Clustering,..)
§ Spark
GraphX Overview
§ Hands
On and Usecases
§ Impala
Architecture
§ Impala
Practicals
§ Adhoc
Querying in Impala
§ Compression
Techniques
§ Snappy
§ LZO
§ Bgzip
§ Image
processing in Hadoop
§ Certification
Preparation Guidelines
§ Best
Practices to setup Hadoop cluster
§ Commissioning
and Decommissioning Nodes
§ Benchmarking
the Hadoop cluster
§ Admin
monitoring tools
§ Routine
Admin tasks
§ Kafka
Architecture
§ Kafka
Usecase Execution
Contact for more details India: +91-9642373173, USA: : +1-845-915-8712, Mail: info@svsoftsolutions.com
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