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The Complete Big Data Course in Hindi

By: Yogesh Sharma

  • 4
  • (69)
  • 10:29:13
  • 72
  • 385
  • Language: Hindi

Course Summary

The world of Hadoop and "Big Data" can be intimidating - hundreds of different technologies with cryptic names form the Hadoop ecosystem.“Big data" analysis is a hot and highly valuable skill – and this course will teach

Read More

Target Audience

  1. This course can be opted by anyone (students, developer, manager) who is interested to learn big data. This course assumes everyone as a beginner, and teaches all fundamentals of Big Data, Hadoop and its complex architecture.
  2. Analysts who want to wrangle large, unstructured data into shape.
  3. Engineers who want to parse and extract useful information from large datasets
  4. Engineers who want to know more about managing Hive as their data warehousing solution.
  5. Engineers building an application with HDFS/HBase/Hive as the data store
  6. Engineers who want to port data from legacy data stores to HDFS.
  7. Anyone who want to fully understand how Apache Spark technology works and learn how Apache Spark is being used in the field.

Pre-Requisites

  1. A computer running Windows, OSX or Linux
  2. Java 8 experience is preferred but NOT required
  3. A basic familiarity with the Linux command line will be very helpful.
  4. A basic understanding of SQL and working with data
  5. A basic understanding of the Hadoop eco-system and MapReduce tasks
  6. Knowledge of HDFS.
  7. HDFS is required to run most of the examples, so you'll need to have a working installation of HDFS.
  8. The course covers everything you need to install Hive and run queries!

Curriculum

  • What is Data?
    05:50
  • DBMS(Database Management System)
    04:17
  • Introduction to Big Data
    04:04
  • Sources and Importance of Big Data
    05:09
  • Introduction to Hadoop
    05:44
  • Limitations of Distributed System
    07:18
  • Why Hadoop?
    09:40
  • Introduction to HDFS
    08:46
  • What is HDFS?
    04:36
  • HDFS Classic Mode
    12:32
  • HDFS Architecture
    06:47
  • What is HDFS High Availability Mode?
    05:48
  • Configuring VMware for practicals
    04:49
  • Enable Virtualization and start Virtual Machine
    07:05
  • Basic Linux Commands for HDFS
    11:56
  • HDFS ls and mkdir command
    13:08
  • HDFS cp, mv and move From Local command
    10:58
  • Hadoop User Experience web UI
    10:51
  • HDFS touchz appendToFile du and find command
    12:41
  • Job Processing in Classic Mode
    07:26
  • Job Processing using YARN
    06:02
  • Run a Yarn Job
    10:05
  • Introduction to SQOOP
    07:07
  • SQOOP incremental free form SQL queries
    06:50
  • SQOOP tools
    04:13
  • SQOOP list-databases, list-tables and eval
    08:46
  • SQOOP Import Part - 1
    09:52
  • SQOOP Import Part - 2
    05:49
  • SQOOP Import-all-tables Export
    10:43
  • SQOOP Incremental Import
    06:49
  • SQOOP Split by
    05:54
  • Introduction to Hive
    11:44
  • Hive Command Line and Database Creation
    06:01
  • Hive Table Creation
    10:55
  • External and Internal Hive tables
    05:20
  • Hive Table Creation with Meta store Browser
    04:02
  • Create Hive Table from SQOOP
    06:40
  • Query Hive Tables DDL and DML Part 1
    08:57
  • Query Hive Tables DDL and DML Part 2
    11:39
  • Hive Dynamic Partition Table
    13:39
  • Hive Static Partition Table
    09:02
  • Hadoop File Formats Text Avro Parquet
    07:11
  • Import data in Avro and Parquet Format
    12:51
  • Create table on Avro and Parquet data files
    06:43
  • Writing Joins on Hive Table Part -1
    09:49
  • Writing Joins on Hive Table Part-2
    08:22
  • Hive complex data types
    11:24
  • Apache Pig Introduction
    06:51
  • Apache Pig Features and Architecture
    07:45
  • Pig execution modes, reading and storing data in Pig Part-1
    10:18
  • Pig execution modes, reading and storing data in Pig Part-2
    07:44
  • Basic PIG Operations Part-1
    07:02
  • Basic PIG Operations Part-2
    07:05
  • PIG Joins Operation
    12:16
  • PIG other operations foreach, order, filter, split
    08:24
  • MapReduce and Growth of Big Data Asset
    09:59
  • Introduction to Spark
    10:02
  • Start Spark shell for Scala and Python
    11:08
  • Spark transformations map in Scala and Python
    09:33
  • Spark transformations filter in Scala and Python
    05:45
  • Spark Map and Filter on text Data using Scala and Python
    11:35
  • RDD operations flatMap, reduce, sortBy
    14:10
  • Processing Unstructured Text Data with Spark_Scala
    13:57
  • Processing Unstructured Text Data with Spark_Python
    07:29
  • Processing Structured Data with Spark_Scala Part-1
    06:33
  • Processing Structured Data with Spark_Scala Part-2
    11:04
  • Processing Structured Data with Spark_Python
    12:11
  • Key Value Pair RDD Operations_Scala Part - 1
    12:37
  • Key Value Pair RDD Operations_Scala Part - 2
    09:20
  • Key Value Pair RDD Operations_Python
    11:16
  • Word Count using Scala and Python
    08:18
  • Word Count and subtract using Scala and Python
    10:59

About the Author

Yogesh Sharma, Developer

Corporate Instructor for Apache Spark, HIVE, PIG, IMPALA, HDFS, HBase, Kafka etc. Proficient in Spark Core, Spark ML, Spark SQL, HIVE, HUE, IMPALA, KAFKA, HBASE, FLUME etc. Data Science enthusiast with Spark Machine Learning and R Programming. 

Worked

      Real-time data processing with Spark Streaming and Kafka
      Data Ingestion using FLUME and SQOOP
      Spark SQL
      Data Analysis using Hive, Pig, Impala, Spark Core

More From Author

Reviews

Anitha Alex
5

This is very good big data course for beginners like me. It covers all the basics and tutor explained concepts very well.

Satpal Bhandari
4

Great for begineers...

Rajendra Ladkat
3

Good for new bie

Nur Mohammad Ha-Mim
5

It is great

Aninda Sundar Howlader
5

nice course

The Complete Big Data Course in Hindi

  • 10:29:13
  • 72
  • 385
  • Language: Hindi
  • 15 days Money back Gurantee
  • Unlimited Access
  • Android, iPhone and iPad Access
  • Certificate of Completion

Course Summary

The world of Hadoop and "Big Data" can be intimidating - hundreds of different technologies with cryptic names form the Hadoop ecosystem.“Big data" analysis is a hot and highly valuable skill – and this course will teach

Read More

Target Audience

  1. This course can be opted by anyone (students, developer, manager) who is interested to learn big data. This course assumes everyone as a beginner, and teaches all fundamentals of Big Data, Hadoop and its complex architecture.
  2. Analysts who want to wrangle large, unstructured data into shape.
  3. Engineers who want to parse and extract useful information from large datasets
  4. Engineers who want to know more about managing Hive as their data warehousing solution.
  5. Engineers building an application with HDFS/HBase/Hive as the data store
  6. Engineers who want to port data from legacy data stores to HDFS.
  7. Anyone who want to fully understand how Apache Spark technology works and learn how Apache Spark is being used in the field.

Pre-Requisites

  1. This course can be opted by anyone (students, developer, manager) who is interested to learn big data. This course assumes everyone as a beginner, and teaches all fundamentals of Big Data, Hadoop and its complex architecture.
  2. Analysts who want to wrangle large, unstructured data into shape.
  3. Engineers who want to parse and extract useful information from large datasets
  4. Engineers who want to know more about managing Hive as their data warehousing solution.
  5. Engineers building an application with HDFS/HBase/Hive as the data store
  6. Engineers who want to port data from legacy data stores to HDFS.
  7. Anyone who want to fully understand how Apache Spark technology works and learn how Apache Spark is being used in the field.

About the Author

Yogesh Sharma, Developer

Corporate Instructor for Apache Spark, HIVE, PIG, IMPALA, HDFS, HBase, Kafka etc. Proficient in Spark Core, Spark ML, Spark SQL, HIVE, HUE, IMPALA, KAFKA, HBASE, FLUME etc. Data Science enthusiast with Spark Machine Learning and R Programming. 

Worked

      Real-time data processing with Spark Streaming and Kafka
      Data Ingestion using FLUME and SQOOP
      Spark SQL
      Data Analysis using Hive, Pig, Impala, Spark Core

More From Author

Review & Rating

Anitha Alex 5

This is very good big data course for beginners like me. It covers all the basics and tutor explained concepts very well.

Satpal Bhandari 4

Great for begineers...

Rajendra Ladkat 3

Good for new bie

Nur Mohammad Ha-Mim 5

It is great

Aninda Sundar Howlader 5

nice course