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Hadoop Training in Bangalore

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Hadoop Training in Bangalore 2018-07-31T15:59:31+00:00

Learn Big Data Hadoop Training in Marathahalli Bangalore from Hadoop Certified  Experts.We are Rated as the Best Hadoop Training Institute in Marathahalli with 100%  Placement Assistance. Call us @ +917624941772 for booking free Big Data Hadoop Demo Classes.

Besant Technologies offers the best Hadoop Training in Bangalore  with the aid of the most talented and well experienced professionals. Our instructors are working in Hadoop and related technologies for quite a number of years in leading multi-national companies around the world. What makes us trusted masters in this field is the fact that we are clearly aware of industry needs and we are offering training in a very much practical way.
Our team of Hadoop trainers offers Hadoop Training in various different modes such as Classroom training, Hadoop Online Training, Hadoop Corporate Training, Fast track training and One-to-One training. Our team of experts has framed our Hadoop syllabus to match with the real world requirements and industry expectations right from beginner level to advanced level. Our training will be held either on weekdays or weekends depending on the participant’s requirement.

The major topics we cover under this Hadoop course Syllabus are INTRODUCTION, HDFS, MapReduce, ADVANCED MapReduce PROGRAMMING, ADMINISTRATION – Information required at the Developer level, HBase, HIVE, OTHER HADOOP ECOSYSTEMS with real-time experience.

Every topic will be covered in the most practical way with the assistance of various real-time examples. And also we will give the overview of Advanced MapReduce Concepts, Advanced PIG, Advanced Hive, Advanced HBase, Oozie & Sqoop, Zookeeper & Flume.

Besant Technologies Provides Hadoop Training Courses in Marathahalli . Our Training Institute has now started providing certification oriented Hadoop Training in Bangalore. Our participants will be eligible to clear all type of interviews at the end of our sessions. We are building a team of Hadoop trainers and participants for their future help and assistance in the subject. Our training will be focused on assisting in placements as well. We have a separate HR team professionals who will take care of all your interview needs. Our Hadoop Training Course Fees is very moderate compared to others. We are the only Hadoop training institute who can share video reviews of all our students. We mentioned the course timings and start date as well below.

Why Hadoop Course in Marathahalli ?

Big Data represents the large and rapidly growing volume of information such as high-volume sensor data and social networking data from websites – Facebook and Twitter to name a few. Many Organizations are keen in capturing this data and analyzing the same as this can add immense value to make appropriate strategic decisions. However, it is important to note that such big data comes in many forms.
It also has many different uses – real-time fraud detection, web display advertising and competitive analysis, call center optimization, social media and sentiment analysis, intelligent traffic management and smart power grids, and so on. All of these also involve growing volumes of structured, multi-structured, and unstructured data.
Analyzing these were not possible previously because they were too costly to implement, or because analytical processing technologies were not capable of handling the large volumes of data involved in a timely manner. New and evolving analytical processing technologies, such as Big Data and Hadoop, now make this analyses possible.
The market for Big Data analytics is growing across the world and this strong growth pattern translates into a great opportunity for all the IT Professionals.

    Here are the few Professional IT groups, who are continuously enjoying the benefits moving into Big data domain:
  • Developers and Architects
  • BI /ETL/DW professionals
  • Senior IT Professionals
  • Testing professionals
  • Mainframe professionals
  • Fresher
Hadoop practitioners are among the highest paid IT professionals today with salaries ranging till $85K (source: indeed job portal), and the market demand for them is growing rapidly.

Hadoop Training Syllabus

                                                                                                           Total Duration: 31:00:00

Module 1 – Introduction to Big Data & Hadoop Fundamentals                         Duration :06:00:00

Goal : In this module, you will understand Big Data, the limitations of the existing solutions for Big Data problem, how Hadoop solves the Big Data problem, the common Hadoop ecosystem components, Hadoop Architecture, HDFS, Anatomy of File Write and Read, how MapReduce Framework works.
Objectives – Upon completing this Module, you should be able to understand Big Data is a term applied to data sets that cannot be captured, managed, and processed within a tolerable elapsed and specified time frame by commonly used software tools.

  • Big Data relies on volume, velocity, and variety with respect to processing
  • Data can be divided into three types—unstructured data, semi-structured data, and structured data
  • Big Data technology understands and navigates big data sources, analyzes unstructured data, and ingests data at a high speed
  • Hadoop is a free, Java-based programming framework that supports the processing of large data sets in a distributed computing environment.
Topics:Apache Hadoop
  • Introduction to Big Data & Hadoop Fundamentals
  • Dimensions of Big data
  • Type of Data generation
  • Apache ecosystem & its projects
  • Hadoop distributors
  • HDFS core concepts
  • Modes of Hadoop employment
  • HDFS Flow architecture
  • HDFS MrV1 vs. MrV2 architecture
  • Types of Data compression techniques
  • Rack topology
  • HDFS utility commands
  • Min h/w requirements for a cluster & property files changes

Module 2 – MapReduce Framework                                                                               Duration :03:00:00

Goal : In this module, you will understand Hadoop MapReduce framework and the working of MapReduce on data stored in HDFS. You will understand concepts like Input Splits in MapReduce, Combiner & Partitioner and Demos on MapReduce using different data sets.
Objectives – Upon completing this Module, you should be able to understand MapReduce involves processing jobs using the batch processing technique.

  • MapReduce can be done using Java programming retrieved
  • Hadoop provides with Hadoop-examples jar file which is normally used by administrators and programmers to perform testing of the MapReduce applications
  • MapReduce contains steps like splitting, mapping, combining, reducing, and output
Topics:Introduction to MapReduce
  • MapReduce Design flow
  • MapReduce Program (Job) execution
  • Types of Input formats & Output Formats
  • MapReduce Datatypes
  • Performance tuning of MapReduce jobs
  • Counters techniques

Module 3 – Apache Hive                                                                                                   Duration :03:00:00

Goal : This module will help you in understanding Hive concepts, Hive Data types, Loading and Querying Data in Hive, running hive scripts and Hive UDF.
Objectives – Upon completing this Module, you should be able to understand Hive is a system for managing and querying unstructured data into a structured format.
The various components of Hive architecture are metastore, driver, execution engine, and so on
Metastore is a component that stores the system catalog and metadata about tables, columns, partitions, and so on
Hive installation starts with locating the latest version of tar file and downloading it in Ubuntu system using the wget command
While programming in Hive, use the show tables command to display the total number of tables
Topics:Introduction to Hive & features

  • Hive architecture flow
  • Types of hive tables flow
  • DML/DDL commands explanation
  • Partitioning logic
  • Bucketing logic
  • Hive script execution in shell & HUE

Module 4 – Apache Pig                                                                                                    Duration :03:00:00

Goal : In this module, you will learn Pig, types of use case we can use Pig, tight coupling between Pig and MapReduce, and Pig Latin scripting, PIG running modes, PIG UDF, Pig Streaming, Testing PIG Scripts. Demo on healthcare dataset.
Objectives – Upon completing this Module, you should be able to understand Pig is a high-level data flow scripting language and has two major components: Runtime engine and Pig Latin language.
Pig runs in two execution modes: Local mode and MapReduce mode. Pig script can be written in two modes: Interactive mode and Batch mode.
Pig engine can be installed by downloading the mirror web link from the website: pig.apache.org.
Topics:

  • Introduction to Pig concepts
  • Pig modes of execution/storage concepts
  • Pig program logics explanation
  • Pig basic commands
  • Pig script execution in shell/HUE

Module 5                                                                                                                            Duration :03:00:00

Goal : This module will cover Advanced HBase concepts. We will see demos on Bulk Loading, Filters. You will also learn what Zookeeper is all about, how it helps in monitoring a cluster, why HBase uses Zookeeper.
Objectives – Upon completing this Module, you should be able to understand HBasehas two types of Nodes—Master and RegionServer. Only one Master node runs at a time. But there can be multiple RegionServersat a time.
The data model of Hbasecomprises tables that are sorted by rows. The column families should be defined at the time of table creation.
There are eight steps that should be followed for installation of HBase.
Some of the commands related to HBaseshell are create, drop, list, count, get, and scan.
Topics:

  • Apache Hbase
  • GangBoard.com
  • Introduction to Hbase concepts
  • Introdcution to NoSQL/CAP theorem concepts
  • Hbase design/architecture flow
  • Hbase table commands
  • Hive + Hbase integration module/jars deployment
  • Hbase execution in shell/HUE

Module 6                                                                                                                            Duration :02:00:00

Goal : Sqoop is an Apache Hadoop Eco-system project whose responsibility is to import or export operations across relational databases. Some reasons to use Sqoop are as follows:

  • SQL servers are deployed worldwide
  • Nightly processing is done on SQL servers
  • Allows to move certain part of data from traditional SQL DB to Hadoop
  • Transferring data using script is inefficient and time-consuming
  • To handle large data through Ecosystem
  • To bring processed data from Hadoop to the applications
Objectives – Upon completing this Module, you should be able to understand Sqoop is a tool designed to transfer data between Hadoop and RDBs including MySQL, MS SQL, Postgre SQL, MongoDB, etc.
Sqoop allows the import data from an RDB, such as SQL, MySQL or Oracle into HDFS.

Topics:

  • Apache Sqoop
  • Introduction to Sqoop concepts
  • Sqoop internal design/architecture
  • Sqoop Import statements concepts
  • Sqoop Export Statements concepts
  • Quest Data connectors flow
  • Incremental updating concepts
  • Creating a database in MySQL for importing to HDFS
  • Sqoop commands execution in shell/HUE

Module 7                                                                                                                                       Duration :02:00:00

Goal : Apache Flume is a distributed data collection service that gets the flow of data from their source and aggregates them to where they need to be processed.
Objectives – Upon completing this Module, you should be able to understand Apache Flume is a distributed data collection service that gets the flow of data from their source and aggregates the data to sink.
Flume provides a reliable and scalable agent mode to ingest data into HDFS.
Topics:

  • Apache Flume
  • Introduction to Flume & features
  • Flume topology & core concepts
  • Property file parameters logic

Module 8                                                                                                                               Duration :02:00:00

Goal : Hue is a web front end offered by the ClouderaVM to Apache Hadoop.
Objectives – Upon completing this Module, you should be able to understand how to use hue for hive,pig,oozie.
Topics:

  • Apache HUE
  • Introduction to Hue design
  • Hue architecture flow/UI interface

Module 9                                                                                                                             Duration :02:00:00

Goal : Following are the goals of ZooKeeper:

  • Serialization ensures avoidance of delay in reading or write operations.
  • Reliability persists when an update is applied by a user in the cluster.
  • Atomicity does not allow partial results. Any user update can either succeed or fail.
  • Simple Application Programming Interface or API provides an interface for development and implementation.
  • Objectives – Upon completing this Module, you should be able to understand ZooKeeper provides a simple and high-performance kernel for building more complex clients.
    ZooKeeper has three basic entities—Leader, Follower, and Observer.

    Watch is used to get the notification of all followers and observers to the leaders.
    Topics:

    • Apache Zookeeper
    • Introduction to zookeeper concepts
    • Zookeeper principles & usage in Hadoop framework
    • Basics of Zookeeper

    Module 10                                                                                                                         Duration :05:00:00

    Goal:
    Explain different configurations of the Hadoop cluster
    Identify different parameters for performance monitoring and performance tuning
    Explain configuration of security parameters in Hadoop.
    Objectives – Upon completing this Module, you should be able to understand Hadoop can be optimized based on the infrastructure and available resources.
    Hadoop is an open-source application and the support provided for complicated optimization is less.
    Optimization is performed through xml files.
    Logs are the best medium through which an administrator can understand a problem and troubleshoot it accordingly.
    Hadoop relies on the Kerberos based security mechanism.
    Topics:

    • Administration concepts
    • Principles of Hadoop administration & its importance
    • Hadoop admin commands explanation
    • Balancer concepts
    • Rolling upgrade mechanism explanation

    Hadoop certification Training in Bangalore

    We will guide you to clear the Hadoop Certified Associate (HCA), Hadoop Certified Professional (HCP)  Certification  that we are providing is an integrated process that consists of a series of classes and expert lecture sessions. By the end of the certification process, we conduct assessments to test your skills and later award you with certificate as an indicator of your expertise in the subject and technology.

    I would like to thank Besant Technologies for their wonderful support and the assistance offered during the course of my Hadoop training in Marathahalli. The trainers were extremely experienced and resourceful which helped us in getting a better grasp on all the subjects. Also, the study materials which were provided was of immense value

    Kaviya

    The training I obtained in Besant Technologies has helped me a lot in gaining knowledge about Hadoop Technology. I will now recommend Besant Technologies to all my friends and family to Take Hadoop Courses  . Their training has played a major role in aligning my focus with technology and being able to comprehend it.

    Tharuna
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