Best Hadoop Traning in Delhi Ncr
What is Hadoop?
Hadoop is a great open up resource, a Java-based development platform that helps the control and storage space of extremely large data units in a distributed processing environment. This is usually the component of the Indien task subsidized by the Indien Software program Basis.
Hadoop assists you to work applications on devices with hundreds of product equipment nodes, and also to deal with hundreds of terabytes of information. It's sent out document program facilitates quick data transfer prices among nodes and enables the program to continue working in case of a node failing. This strategy decreases the chance of catastrophic program failing and unpredicted info reduction, actually if a significant quantity of nodes become inoperative. As a result, Hadoop quickly surfaced as a basis for big data digesting jobs, such as medical analytics, sales, and business planning, and digesting tremendous quantities of messfühler data, incorporating from the internet of points detectors.
Hadoop was developed by PC scientists Doug Trimming and Mike Cafarella in 2006 to aid distribution intended for the Nutch search engine.
Now Here we are talking about Hadoop Training, training most important part in our life, what we learn and how we increase our knowledge, that always chooses the best institute for learning.
List of Big Data and Hadoop training institute Delhi :
- Techstack
- Simplilearn
- Analytixlabs
- Edupristine
- Madrid
Why i am telling you Techstack is best. They are handling their students very well. From my recommendation . Techstack institute is best for big data hadoop.
There are three parts in Hadoop
- Developer | Fee 15,000 | 3 Month Course
- Admin | Fee 15,000 | 3 Month Course
- Analytics | Fee 15,000 | 3 Month Course
Introduction of Big Data & Hadoop
- Big Data & Hadoop Introduction
- What is Hadoop?
- Why & Who use Hadoop?
- What is Hadoop History?
- How many Different types of Components in Hadoop?
- Detailed information on HDFS, MapReduce, PIG, Hive, SQOOP, HBASE, OOZIE, Flume, Zookeeper and so on…
- What is the scope of an Hadoop in an industry ?
Deep Drive in HDFS (for Storing the Data)
- HDFS Introduction
- Design of HDFS
- Role of HDFS in Hadoop
- HDFS Feature
- Intro of Hadoop Daemons and its functionality
- Name Node
- Secondary Name Node
- Job Tracker
- Data Node
- Task Tracker
- Anatomy of File Wright
- Anatomy of File Read
- Network Topology
- Nodes
- Racks
- Data Center
- Parallel Copying using DistCp
- Basic Configuration for HDFS
- Data Organization
- Blocks and
- Replication
- Heartbeat Signal
- How to Store the Data into HDFS
- How to Read the Data from HDFS
- Accessing HDFS (Introduction of Basic UNIX commands)
- CLI commands
MapReduce using Java (Processing the Data)
- The introduction of MapReduce.
- MapReduce Architecture
- Data flow in MapReduce
- Splits
- Mapper
- Portioning
- Sort and shuffle
- Combiner
- Reducer
- Understand Difference Between Block and InputSplit
- Role of RecordReader
- Basic Configuration of MapReduce
- MapReduce life cycle
- Driver Code
- Mapper and Reducer
- How MapReduce Works
- Writing and Executing the Basic MapReduce Program using Java
- Submission & Initialization of MapReduce Job.
- File Input/Output Formats in MapReduce Jobs
- Text Input Format
- Key Value Input Format
- Sequence File Input Format
- NLine Input Format
- Joins
- Map-side Joins
- Reducer-side Joins
- Word Count Example
- Partition MapReduce Program
- Side Data Distribution
- Distributed Cache (with Program)
- Counters (with Program)
- Types of Counters
- Task Counters
- Job Counters
- User Defined Counters
- Propagation of Counters
- Job Scheduling
PIG
- Introduction to Apache PIG
- Introduction to PIG Data Flow Engine
- MapReduce vs. PIG in detail
- When should PIG use?
- Data Types in PIG
- Basic PIG programming
- Modes of Execution in PIG
- Local Mode and
- Execution Mechanisms
- Grunt Shell
- Script
- Embedded
- Operators/Transformations in PIG
- PIG UDF's with Program
- Word Count Example in PIG
- The difference between the MapReduce and PIG
SQOOP
- Introduction to SQOOP
- Use of SQOOP
- Connect to MySQL database
- SQOOP commands
- Import
- Export
- Evala
- Joins in SQOOP
- Export to MySQL
- Export to HBase
- OOZIE
- Introduction to OOZIE
- Use of OOZIE
- Where to use?
Apache HIVE
- Introduction to HIVE
- HIVE Meta Store
- HIVE Architecture
- Tables in HIVE
- Managed Tables
- External Tables
- Hive Data Types
- Primitive Types
- Partition
- Joins in HIVE
- HIVE UDF's and UADF's with Programs
- Word Count Example
- Mango DB
- What is MongoDB?
- Where to Use?
- Configuration On Windows
- Inserting the data into MongoDB?
- Reading the MongoDB data.
Apache HBase
- Introduction to HBASE
- Basic Configurations of HBASE
- Fundamentals of HBase
- What is NoSQL?
- HBase Data Model
- Table and Row
- Column Family and Column Qualifier
- Categories of NoSQL Data Bases
- Key-Value Database
- Document Database
- Column Family Database
- HBASE Architecture
- HMaster
- Region Servers
- Regions
- MemStore
- SQL vs. NOSQL
- How HBASE differs from RDBMS
- HDFS vs. HBase
- Client-side buffering or bulk uploads
- HBase Designing Tables
- HBase Operations
- Get
- Scan
- Put
- Delete
Cluster Setup
- Downloading and installing the Ubuntu12.x
- Installing Java
- Installing Hadoop
- Creating Cluster
- Increasing Decreasing the Cluster size
- Monitoring the Cluster Health
- Starting and Stopping the Nodes
- Zookeeper
- Introduction Zookeeper
- Data Modal
- Operations
Flume
- Introduction to Flume
- Uses of Flume
- Flume Architecture
- Flume Master
- Flume Collectors
- Flume Agents
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