- Introduction to Big Data
- Limitations and Solutions of existing Data Analytics Architecture
- Introduction to Hadoop
- Hadoop Features
- Hadoop Ecosystem
- Hadoop 2.x core components
- Hadoop Storage: HDFS
- Hadoop Processing: MapReduce Framework
- Hadoop Different Distributions.
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Hadoop Training in New York
Acquaint yourself with key concepts of Apache Hadoop and become a Certified Hadoop Professional with the Hadoop Training in New York.
Online
Quick facts
particular | details | ||
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Medium of instructions
English
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Mode of learning
Self study, Virtual Classroom
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Mode of Delivery
Video and Text Based
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Frequency of Classes
Weekdays, Weekends
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Course overview
Hadoop Training in New York Course is meant to introduce the learners to concepts of Apache Hadoop, an open framework that enables the function of storing and processing massive datasets. The learners will be exposed to the core aspects of Hadoop such as Apache Pig, optimizations of Big Data Hadoop, Flume, Sqoop, Oozie, HDFS, Apache Hive, YARN, etc and students will be equipped with enough knowledge to pass the Hadoop CAA175 certification
Administered by Mindmajix Technologies, the Hadoop Training in New York online course will train the learners to develop resolutions to handle the problems of Big data making use of troubleshooting and programming models. In the Hadoop Training in New York certification, the learners will be provided with the practical aspects of Hadoop under the supervision of well-experienced trainers with industry expertise by assigning various hands-on projects like Solution Advisor Analysis. Multiple options of enrolment are available for this programme; the learners can choose one of them as their preference.
The highlights
- 100% online course
- Offered by Mindmajix
- FREE Demo on Request
- Flexible Schedule
- Online Live and Self-paced Training Options
- 24/7 Lifetime Support
- Life-Time Self-Paced Videos Access
- One-on-One Doubt Clearing
- Certification Oriented Curriculum
Program offerings
- One-on-one doubt clearing sessions
- Certification oriented curriculum
- Real-time project use cases
- 20 hours of labs
- Free demo on request
- 24/7 lifetime support
- 30 hours of sessions
- Online live and self-paced training options
Course and certificate fees
certificate availability
certificate providing authority
What you will learn
After the completion of Hadoop Training in New York online certification, the students will study plenty of topics related to Hadoop such as Hadoop Storage, MapReduce, Hadoop Ecosystem, YARN Architecture, Hadoop Mapreduce Frameworks, NoSQL Databases, and whatnot.
Who it is for
The syllabus
Understanding Bigdata and Hadoop
YARN
- YARN (Yet another Resource Negotiator) – Next Gen.
- Map Reduce
- What is YARN?
- Difference between Map Reduce & amp; YARN
- YARN Architecture
- Resource Manager Application Master Node Manager.
Hadoop Architecture and HDFS
- Hadoop 2.x Cluster Architecture - Federation and High Availability
- A Typical Production Hadoop Cluster
- Hadoop Cluster Modes
- Common Hadoop Shell Commands
- Single node cluster and Multi node cluster set up Hadoop Administration
Hadoop Mapreduce Frameworks
- MapReduce Use Cases
- Why MapReduce
- Hadoop 2.x MapReduce Architecture
- Hadoop 2.x MapReduce Components
- YARN MR Application Execution Flow
- YARN Workflow
- Demo on MapReduce
- Input Splits
- Relation between Input Splits and HDFS Blocks
- MapReduce: Combiner & Partitioner
- Sequence Input Format
- Xml file Parsing using MapReduce
Pig
- Introduction to Pig
- MapReduce Vs Pig
- Pig Use Cases
- Programming Structure in Pig
- Pig Running Modes
- Pig components
- Pig Execution
- Pig Latin Program
- Data Models inPig
- Pig Data Types
- Shell and Utility Commands
- Pig Latin: Relational Operators
- Group Operator
- COGROUP Operator
- Joins and COGROUP
- Union
- Diagnostic Operators
- Specialized joins in Pig
- Built In Functions (Eval Function, Load and StoreFunctions, Math function, String Function, Date Function, Pig UDF, Piggybank, Parameter Substitution (PIG macros and Pig Parameter substitution)
Hive
- Hive Background
- Hive Use Case
- About Hive
- Hive Vs Pig
- Hive Architecture and Components
- Metastore in Hive
- Limitations of Hive
- Comparison with Traditional Database
- Hive Data Types and Data Models
- Partitions and Buckets
- Hive Tables(Managed Tables and External Tables)
- Importing Data
- Querying Data
- Managing Outputs
- Hive Script
- Hive UDF
- Retail use case in Hive
Advanced Hive and HBase
- Hive QL: Joining Tables
- Dynamic Partitioning
- Hive Indexes and views Hive query optimizers
- Hive: Thrift Server
- User Defined Functions
- HBase: Introduction to NoSQL Databases and HBase
- HBase v/s RDBMS
- HBase Components
- HBase Architecture
- Run Modes & Configuration
- HBase Cluster Deployment
Advanced HBase
- HBase Data Model
- HBase Shell
- Data Loading Techniques
- ZooKeeper Data Model
- Zookeeper Service
- Zookeeper
- Demos on Bulk Loading
- Getting and Inserting Data
- Filters in HBase
Sqoop
- Sqoop Architecture
- Sqoop Installation
- Sqoop Commands(Import, Hive-Import, EVal, Hbase Import, Import All tables, Export)
- Connectors to Existing DBs and DW
- Hands on Exercise
Flume
- Flume Introduction
- Flume Architecture
- Flume Master
- Flume Collector and Flume Agent
- Flume Configurations
- Real Time Use Case using Apache Flume
MongoDB (As part of NoSQL Databases)
- Need of NoSQL Databases
- Relational VS Non-Relational Databases
- Introduction to MongoDB
- Features of MongoDB
- Installation of MongoDB
- Mongo DB Basic operations
- REAL Time Use Cases on Hadoop &
- MongoDB Use Case
Spark
- Introduction to Apache Spark
- Role of Spark in Big data
- Who is using Spark
- Installation of SparkShell and StandAlone Cluster
- Configuration
- RDD Operations (Transformations and actions)
Hadoop Project
- A demo project using all the components of the above topics
Practice Test & Interview Questions
Instructors
Mr Ankith
Instructor
Mindmajix Technologies