Understanding Datastage Jobs, Sequences, and Containers in Data Warehousing
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Parallel jobs:
Executed under the control of DataStage Server runtime environment
Built-in functionality for Pipeline and Partitioning Parallelism
Compiled into Orchestrate Scripting Language (OSH)
Runtime monitoring in DataStage Director
Job Sequences (Batch jobs, Controlling jobs):
Master Server jobs that kick-off jobs and other activities
Can kick-off Server or Parallel jobs
Runtime monitoring in DataStage Director
Containers:
A container is a group of stages and links.
Types of containers:
Local: The main purpose of local container is to convert complex job designs into simple, readable job designs.
Shared: Similar to local container but can be reused in multiple jobs within the same project.
Job Sequences:
A job sequence allows you to specify a sequence of Data Stage jobs to be executed, and actions to be taken depending on results.
Server jobs (Requires Server Edition license):
Executed by the DataStage Server Edition
Compiled into Basic (interpreted pseudo-code)
Runtime monitoring in DataStage Director
Mainframe jobs (Requires Mainframe Edition license):
Compiled into COBOL
Executed on the Mainframe, outside of DataStage
**Understanding DataStage Jobs, Sequences, and Containers**
DataStage, a powerful ETL (Extract, Transform, Load) tool from IBM, provides an efficient way to create and manage data integration processes. A key component of DataStage is the ability to organize tasks into **Jobs**, **Sequences**, and **Containers**. Let's explore these concepts.
**Jobs**
A DataStage job consists of one or more tasks that are grouped together to perform a specific ETL function. Each job has an entry point, which triggers the execution of all tasks within it. Jobs can be executed in parallel, allowing for efficient processing when working with large datasets.
```java
DEFINE JOB job_name AS BEGIN OF JOB
TASK task1;
TASK task2;
-- more tasks...
END OF JOB;
```
**Sequences**
A sequence in DataStage represents a logical unit of work within a job. Sequences can be used to group related tasks and control their order of execution. This helps in organizing complex ETL processes and improving maintainability.
```java
DEFINE SEQUENCE sequence_name AS BEGIN OF SEQUENCE
TASK task1;
TASK task2;
-- more tasks...
END OF SEQUENCE;
```
**Containers**
A container in DataStage is a special type of sequence that can hold multiple sequences and/or jobs. Containers are useful when you want to reuse groups of tasks across different jobs, thereby improving code maintainability.
**Container Usage in a Job**
You can include a container within a job by using the `USE` statement. This will make all sequences and jobs defined inside the container available for use within the job.
```java
DEFINE JOB job_name AS BEGIN OF JOB
USE container_name;
-- tasks using sequences and jobs from the container...
END OF JOB;
```
By understanding DataStage jobs, sequences, and containers, you can effectively design and manage complex ETL processes with improved efficiency and maintainability.