Day 1 Objective
- List the Three “V”s of Big Data
- List the Six Key Hadoop Data Types
- Describe Hadoop, YARN and Use Cases for Hadoop
- Describe Hadoop Ecosystem Tools and Frameworks
- Describe the Differences Between Relational Databases and Hadoop
- Describe What is New in Hadoop 2.x
- Describe the Hadoop Distributed File System (HDFS)
- Describe the Differences Between HDFS and an RDBMS
- Describe the Purpose of NameNodes and DataNodes
- List Common HDFS Commands
- Describe HDFS File Permissions
- List Options for Data Input
- Describe WebHDFS
- Describe the Purpose of Sqoop and Flume
- Describe How to Export to a Table
- Describe the Purpose of MapReduce
- Define Key/Value Pairs in MapReduce
- Describe the Map and Reduce Phases
- Describe Hadoop Streaming
Day 1 Demonstrations
- Starting a Hadoop Cluster
- Demonstration: Understanding Block Storage
- Using HDFS Commands
- Importing RDBMS Data into HDFS
- Exporting HDFS Data to an RDBMS
- Importing Log Data into HDFS Using Flume
- Demonstration: Understanding MapReduce
- Running a MapReduce Job
Day 1 Objective
- List the Three “V”s of Big Data
- List the Six Key Hadoop Data Types
- Describe Hadoop, YARN and Use Cases for Hadoop
- Describe Hadoop Ecosystem Tools and Frameworks
- Describe the Differences Between Relational Databases and Hadoop
- Describe What is New in Hadoop 2.x
- Describe the Hadoop Distributed File System (HDFS)
- Describe the Differences Between HDFS and an RDBMS
- Describe the Purpose of NameNodes and DataNodes
- List Common HDFS Commands
- Describe HDFS File Permissions
- List Options for Data Input
- Describe WebHDFS
- Describe the Purpose of Sqoop and Flume
- Describe How to Export to a Table
- Describe the Purpose of MapReduce
- Define Key/Value Pairs in MapReduce
- Describe the Map and Reduce Phases
- Describe Hadoop Streaming
Day 1 Demonstrations
- Starting a Hadoop Cluster
- Demonstration: Understanding Block Storage
- Using HDFS Commands
- Importing RDBMS Data into HDFS
- Exporting HDFS Data to an RDBMS
- Importing Log Data into HDFS Using Flume
- Demonstration: Understanding MapReduce
- Running a MapReduce Job
Day 2 Objective
- Describe the Purpose of Apache Pig
- Describe the Purpose of Pig Latin
- Demonstrate the Use of the Grunt Shell
- List Pig Latin Relation Names and Field Names
- List Pig Data Types
- Define a Schema
- Describe the Purpose of the GROUP Operator
- Describe Common Pig Operators, Including
o ORDER BY o CASE o DISTINCT o PARALLEL
o FLATTEN o FOREACH
- Perform an Inner, Outer and Replicated Join
- Describe the Purpose of the DataFu Library
Day 2 Demonstrations
- Demonstration: Understanding Apache Pig
- Getting Starting with Apache Pig
- Exploring Data with Apache Pig
- Splitting a Dataset
- Joining Datasets with Apache Pig
- Preparing Data for Apache Hive
- Demonstration: Computing Page Rank
- Analyzing Clickstream Data
- Analyzing Stock Market Data Using Quantiles
Day 3 Objective
- Describe the Purpose of Apache Hive
- Describe the Differences Between Apache Hive and SQL
- Describe the Apache Hive Architecture
- Demonstrate How to Submit Hive Queries
- Describe How to Define Tables
- Describe How to Load Date Into Hive
- Define Hive Partitions, Buckets and Skew
- Describe How to Sort Data
- List Hive Join Strategies
- Describe the Purpose of HCatalog
- Describe the HCatalog Ecosystem
- Define a New Schema
- Demonstrate the Use of HCatLoader and HCatStorer with Apache Pig
- Perform a Multi-table/File Insert
- Describe the Purpose of Views
- Describe the Purpose of the OVER Clause
- Describe the Purpose of Windows
- List Hive Analytics Functions
- List Hive File Formats
- Describe the Purpose of Hive SerDe
Day 3 Demonstrations
- Understanding Hive Tables
- Understanding Partition and Skew
- Analyzing Big Data with Apache Hive
- Demonstration: Computing NGrams
- Joining Datasets in Apache Hive
- Computing NGrams of Emails in Avro Format
- Using HCatalog with Apache Pig
Day 4 Objective
- Describe the Purpose HDFS Federation
- Describe the Purpose of HDFS High Availability (HA)
- Describe the Purpose of the Quorum Journal Manager
- Demonstrate How to Configure Automatic Failover
- Describe the Purpose of YARN
- List the Components of YARN
- Describe the Lifecycle of a YARN Application
- Describe the Purpose of a Cluster View
- Describe the Purpose of Apache Slider
- Describe the Origin and Purpose of Apache Spark
- List Common Spark Use Cases
- Describe the Differences Between Apache Spark and MapReduce
- Demonstrate the Use of the Spark Shell
- Describe the Purpose of an Resilient Distributed Dateset (RDD)
- Demonstrate How to Load Data and Perform a Word Count
- Define Lazy Evaluation
- Describe How to Load Multiple Types of Data
- Demonstrate How to Perform SQL Queries
- Demonstrate How to Perform DataFrame Operations
- Describe the Purpose of the Optimization Engine
- Describe the Purpose of Apache Oozie
- Describe Apache Pig Actions
- Describe Apache Hive Actions
- Describe MapReduce Actions
- Describe How to Submit an Apache Oozie Workflow
- Define an Oozie Coordinator Job
Day 4 Demonstrations
- Advanced Apache Hive Programming
- Running a YARN Application
- Getting Started with Apache Spark
- Exploring Apache Spark SQL
- Defining an Apache Oozie Workflow
Course Pre-Requisite
Students should be familiar with programming principles and have experience in software development. SQL knowledge is also helpful. No prior Hadoop knowledge is required.
Course Calendar
| Start Date | End Date | Duration | Locaton | Register Now |
|---|---|---|---|---|
| 11th July 2019 | 14th July 2019 | 4 Days | Pune, Bangalore | Register Now |
| 8th Aug 2019 | 11th Aug 2019 | 4 Days | Pune, Bangalore | Register Now |
| 5th Sep 2019 | 8th Sep 2019 | 4 Days | Pune, Bangalore | Register Now |
Course Calendar
| Stat Date |
End Date | Duration | Location |
|---|---|---|---|
| 11th July 2019 | 14th July 2019 | 4 Days | Pune, Bangalore |
| Stat Date |
End Date | Duration | Location |
|---|---|---|---|
| 8th Aug 2019 | 11th Aug 2019 | 4 Days | Pune, Bangalore |
| Stat Date |
End Date | Duration | Location |
|---|---|---|---|
| 5th Sep 2019 | 8th Sep 2019 | 4 Days | Pune, Bangalore |
