IBM InfoSphere Advanced DataStage - Parallel Framework v11.5

Course Outline: 

1. Introduction to the Parallel Framework Architecture

• Describe the parallel processing architecture
• Describe pipeline and partition parallelism
• Describe the role of the configuration file

2. Compiling and Executing Jobs

• Describe the main parts of the configuration file
• Describe the compile process and the OSH that the compilation process generates
• Describe the role and the main parts of the Score

3. Partitioning and Collecting Data

• Understand how partitioning works in the Framework
• Viewing partitioners in the Score
• Selecting partitioning algorithms

4. Sorting Data

• Sort data in the parallel framework
• Find inserted sorts in the Score
• Reduce the number of inserted sorts
• Optimize Fork-Join jobs
• Use Sort stages to determine the last row in a group

5. Buffering in Parallel Jobs

• Describe how buffering works in parallel jobs
• Tune buffers in parallel jobs
• Avoid buffer contentions

6. Parallel Framework Data Types

• Describe virtual data sets
• Describe schemas
• Describe data type mappings and conversions
• Describe how external data is processed
• Handle nulls

7. Reusable Components

• Create a schema file
• Read a sequential file using a schema
• Describe Runtime Column Propagation (RCP)
• Enable and disable RCP
• Create and use shared containers

8. Balanced Optimization

• Enable Balanced Optimization functionality in Designer
• List the different Balanced Optimization options.
• Push stage processing to a data source
• Push stage processing to a data target
• Optimize a job accessing Hadoop HDFS file system
• Understand the limitations of Balanced Optimizations

Course Outline: 

1. Introduction to the Parallel Framework Architecture

• Describe the parallel processing architecture
• Describe pipeline and partition parallelism
• Describe the role of the configuration file

2. Compiling and Executing Jobs

• Describe the main parts of the configuration file
• Describe the compile process and the OSH that the compilation process generates
• Describe the role and the main parts of the Score

3. Partitioning and Collecting Data

• Understand how partitioning works in the Framework
• Viewing partitioners in the Score
• Selecting partitioning algorithms

4. Sorting Data

• Sort data in the parallel framework
• Find inserted sorts in the Score
• Reduce the number of inserted sorts
• Optimize Fork-Join jobs
• Use Sort stages to determine the last row in a group

5. Buffering in Parallel Jobs

• Describe how buffering works in parallel jobs
• Tune buffers in parallel jobs
• Avoid buffer contentions

6. Parallel Framework Data Types

• Describe virtual data sets
• Describe schemas
• Describe data type mappings and conversions
• Describe how external data is processed
• Handle nulls

7. Reusable Components

• Create a schema file
• Read a sequential file using a schema
• Describe Runtime Column Propagation (RCP)
• Enable and disable RCP
• Create and use shared containers

8. Balanced Optimization

• Enable Balanced Optimization functionality in Designer
• List the different Balanced Optimization options.
• Push stage processing to a data source
• Push stage processing to a data target
• Optimize a job accessing Hadoop HDFS file system
• Understand the limitations of Balanced Optimizations

Course Outline: 

1. Introduction to the Parallel Framework Architecture

• Describe the parallel processing architecture
• Describe pipeline and partition parallelism
• Describe the role of the configuration file

2. Compiling and Executing Jobs

• Describe the main parts of the configuration file
• Describe the compile process and the OSH that the compilation process generates
• Describe the role and the main parts of the Score

3. Partitioning and Collecting Data

• Understand how partitioning works in the Framework
• Viewing partitioners in the Score
• Selecting partitioning algorithms

4. Sorting Data

• Sort data in the parallel framework
• Find inserted sorts in the Score
• Reduce the number of inserted sorts
• Optimize Fork-Join jobs
• Use Sort stages to determine the last row in a group

5. Buffering in Parallel Jobs

• Describe how buffering works in parallel jobs
• Tune buffers in parallel jobs
• Avoid buffer contentions

6. Parallel Framework Data Types

• Describe virtual data sets
• Describe schemas
• Describe data type mappings and conversions
• Describe how external data is processed
• Handle nulls

7. Reusable Components

• Create a schema file
• Read a sequential file using a schema
• Describe Runtime Column Propagation (RCP)
• Enable and disable RCP
• Create and use shared containers

8. Balanced Optimization

• Enable Balanced Optimization functionality in Designer
• List the different Balanced Optimization options.
• Push stage processing to a data source
• Push stage processing to a data target
• Optimize a job accessing Hadoop HDFS file system
• Understand the limitations of Balanced Optimizations

Labs:

You'll participate in hands-on labs.

Labs:

You'll participate in hands-on labs.

Labs:

You'll participate in hands-on labs.