How can we improve throughput in Informatica?

Filter Transformation

  1. Use filter transformation as early as possible inside the mapping. If the unwanted data can be discarded early in the mapping, it would increase the throughput.
  2. Use source qualifier to filter the data.

How do you handle performance issues in Informatica?

Complete the following tasks to improve session performance:

  1. Optimize the target.
  2. Optimize the source.
  3. Optimize the mapping.
  4. Optimize the transformation.
  5. Optimize the session.
  6. Optimize the grid deployments.
  7. Optimize the PowerCenter components.
  8. Optimize the system.

Why do rows get rejected in Informatica?

If the Informatica Writer or the Target Database rejects data due to any valid reason the integration service logs the rejected records into the reject file. Every time we run the session the integration service appends the rejected records to the reject file.

How do you identify performance bottlenecks in Informatica?

Use the following methods to identify performance bottlenecks:

  1. Run test sessions. You can configure a test session to read from a flat file source or to write to a flat file target to identify source and target bottlenecks.
  2. Analyze performance details.
  3. Analyze thread statistics.
  4. Monitor system performance.

What is performance bottleneck in Informatica?

Bottleneck is the reason by which the performance of the Informatica ETL process gets slower. There are different types of Bottlenecks in Informatica. It can happen either while writing to the target or while reading from source and many more.

What is bad file in Informatica?

What do we mean by Bad Files in Informatica? Bad Files are often termed as Rejected Files that holds the data for the entire row, which is rejected by the Target while writing. A bad file will contain data that could not load into a target because of constraints or validations employed in the logic.

How do you handle rejected rows in Informatica?

5. How to load rejected data?

  1. You can configure the Update Strategy transformation to either pass rejected rows to the next transformation or drop them.
  2. If you enable row error handling, the Integration Service writes the rejected rows and the dropped rows to the row error logs.

What is pushdown optimization in Informatica?

Pushdown optimization is a concept using which you can push the transformation logic on the source or target database side. When you have a source as the database table, you can make use of a SQL override to remove the logic written in the transformation.

How do you resolve a target bottleneck in Informatica?

  1. Partitioned Mapping Optimization Overview.
  2. Use Multiple CPUs.
  3. Increase the Maximum Parallelism Value.
  4. Optimize Flat Files for Partitioning. Optimize Flat File Sources for Partitioning.
  5. Optimize Relational Databases for Partitioning. Optimize the Source Database for Partitioning.
  6. Optimize Transformations for Partitioning.

How do you identify the bottlenecks in mappings?

To identify mapping bottlenecks, complete the following tasks:

  1. Read the thread statistics and work time statistics in the session log.
  2. Analyze performance counters.
  3. Add a Filter transformation before each target definition.

How many tasks can a task developer make?

You can create three types of reusable tasks in task developer.