Final answer:
SSIS parallelism refers to executing multiple tasks simultaneously to improve performance by using multiple processors. It can be done when tasks do not have data dependencies. Key considerations include hardware resources, data dependencies, task complexity, and network bandwidth.
Step-by-step explanation:
What is Parallelism in SSIS?
Parallelism in SQL Server Integration Services (SSIS) refers to the ability to run multiple tasks simultaneously within a package. This aspect of SSIS can greatly improve the performance of data integration and transformation processes by utilizing multiple processors and reducing overall execution time.
When Can Parallelism be Done?
Parallelism can be implemented when there are multiple tasks that can be executed at the same time without depending on the output or completion of each other. This can be during the data extraction phase, transformation phase, or the loading phase, as long as there are no data dependencies between the tasks.
Factors to Consider Before Implementing Parallelism
Before implementing parallelism in SSIS, it is important to consider several factors:
- Hardware resources, like CPU and memory availability, as parallel tasks require more resources.
- Data dependencies between tasks because tasks that depend on one another cannot be run in parallel.
- The complexity of tasks, as more complex tasks may not always benefit from parallel execution.
- Network bandwidth, especially when tasks involve moving large volumes of data across the network.