Day 1 Objective
- Describe Hadoop 2.X and the Hadoop Distribute File System
- Describe the YARN framework
- Describe the Purpose of NameNodes and Data Nodes
- Describe the Purpose of HDFS High Availability (HA)
- Describe the Purpose of the Quorum Journal Manager
- List Common HDFS Commands
- Describe the Purpose of YARN
- List Open-Source YARN Use Cases
- List the Components of YARN
- Describe the Life Cycle of a YARN Application
- Define Map Aggregation
- Describe the Purpose of Combiners
- Describe the Purpose of In-Map Aggregation
- Describe the Purpose of Counters
- Describe the Purpose of User-Defined Counters
Day 1 Demonstrations
- Demonstration: Understanding Block Storage
- Configuring a Hadoop Development Environment
- Putting Files in HDFS with Java
- Demonstration: Understanding Map Reduce
- Word Count
- Distributed Grep
- Inverted Index
- Using a Combiner
- Computing an Average
Day 1 Objective
- Describe Hadoop 2.X and the Hadoop Distribute File System
- Describe the YARN framework
- Describe the Purpose of NameNodes and Data Nodes
- Describe the Purpose of HDFS High Availability (HA)
- Describe the Purpose of the Quorum Journal Manager
- List Common HDFS Commands
- Describe the Purpose of YARN
- List Open-Source YARN Use Cases
- List the Components of YARN
- Describe the Life Cycle of a YARN Application
- Define Map Aggregation
- Describe the Purpose of Combiners
- Describe the Purpose of In-Map Aggregation
- Describe the Purpose of Counters
- Describe the Purpose of User-Defined Counters
Day 1 Demonstrations
- Demonstration: Understanding Block Storage
- Configuring a Hadoop Development Environment
- Putting Files in HDFS with Java
- Demonstration: Understanding Map Reduce
- Word Count
- Distributed Grep
- Inverted Index
- Using a Combiner
- Computing an Average
Day 2 Objective
- Describe the Purpose of a Partitioner
- List the Steps for Writing a Custom Partitioner
- Describe How to Create and Distribute a Partition File
- Describe the Purpose of Sorting
- Describe the Purpose of Custom Keys
- Describe How to Write a Group Comparator
- List the Built-In Input Formats
- Describe the Purpose of Input Formats
- Define a Record Reader
- Describe How to Handle Records that Span Splits
- List the Built-In Output Formats
- Describe How to Write a Custom Output Format
- Describe the Purpose of the MultipleOutputs Class
Day 2 Demonstrations
- Writing a Custom Partitioner
- Using TotalOrderPartitioner
- Custom Sorting
- Demonstration: Combining Input Files
- Processing Multiple Inputs
- Writing a Custom Input Format
- Customizing Output
- Working with a Simple Moving Average
Day 3 Objective
- Describe the Purpose of a RawComparator
- Describe the Purpose of Localization
- List Scenarios for Performing Joins in MapReduce
- Describe the Purpose of the Bloom Filter
- Describe the Purpose of MRUnit and the MRUnit API
- Describe How to Set Up a Test
- Describe How to Test a Mapper
- Describe How to Test a Reducer
- Describe the Purpose of HBase
- Define the Differences Between a Relational Database and HBase
- Describe the HBase Architecture
- Demonstrate the Basics of HBase Programming
- Describe an HBase MapReduce Applications
Day 3 Demonstrations
- Using Data Compression
- Defining a RawComparator
- Performing a Map-Side Join
- Using a Bloom Filter
- Unit Testing a MapReduce Job
- Importing Data to HBase
- Creating an HBase Mapreduce Jo
Day 4 Objective
- Describe the Purpose of the FOREACH GENERATE Operator
- Describe the Purpose of Pig User Defined Functions (UDFs)
- Describe the Purpose of Filter Functions
- Describe the Purpose of Accumulator UDFs
- Describe the Purpose of Algebraic Functions
- Describe the Purpose of Apache Hive
- Describe the Differences Between Apache Hive and SQL
- Describe Apache Hive Architecture
- Describe How to Load Data Into Hive
- Demonstrate How to Perform Queries
- Describe the Purpose of Hive User Defined Functions (UDFs)
- Write a Hive UDF
- Describe the Purpose of HCatalog
- Describe the Purpose of Apache Oozie
- Describe How to Define an Oozie Workflow
- Describe Pig and Hive Actions
- Describe How to Define an Oozie Coordinator Job
Day 4 Demonstrations
- Demonstration: Understanding Pig
- Writing a Pig UDF
- Writing a Pig Accumulator
- Writing a Apache Hive UDF
- Defining an Oozie Workflow
- Working with TF-IDF and the JobControl Class
Course Pre-Requisite
Students must have experience developing Java applications and using a Java IDE. Labs are completed using the Eclipse IDE and Gradle. No prior Hadoop knowledge is required.
Course Calendar
| Start Date | End Date | Duration | Locaton | Register Now |
|---|---|---|---|---|
| 25th July 2019 | 28th July 2019 | 4 Days | Pune, Bangalore | Register Now |
| 28th Aug 2019 | 31th Aug 2019 | 4 Days | Pune, Bangalore | Register Now |
| 19th Sep 2019 | 22nd Sep 2019 | 4 Days | Pune, Bangalore | Register Now |
Course Calendar
| Stat Date |
End Date | Duration | Location |
|---|---|---|---|
| 25th July 2019 | 28th July 2019 | 4 Days | Pune, Bangalore |
| Stat Date |
End Date | Duration | Location |
|---|---|---|---|
| 28th Aug 2019 | 31st Aug 2019 | 4 Days | Pune, Bangalore |
| Stat Date |
End Date | Duration | Location |
|---|---|---|---|
| 19th Sep 2019 | 22nd Sep 2019 | 4 Days | Pune, Bangalore |
