Informatica's recovery strategy is designed to ensure that data integration processes can be restarted and completed successfully after an unexpected interruption or failure. This is critical for maintaining data integrity and minimizing data loss. Here's a breakdown of the concept:
Core Concept :
- Recovery strategies define how Informatica handles failures during session or workflow execution.
- They aim to minimize the amount of reprocessing required after a failure, saving time and resources.
- The goal is to bring the target data back to a consistent and accurate state.
Key Components and Techniques :
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Checkpoints:
- Informatica uses checkpoints to record the progress of a session or workflow.
- Checkpoints store information about the last successfully processed row or transaction.
- When a session or workflow is restarted, it uses the checkpoint information to resume from the point of failure.
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Recovery Strategy Options :
- Resume from Checkpoint:
- This is the most common recovery strategy.
- The session or workflow resumes from the last checkpoint, reprocessing only the data that was not committed before the failure.
- Restart from Beginning:
- In some cases, it may be necessary to restart the session or workflow from the beginning.
- This option is used when checkpoints are not available or when data consistency requires a full reload.
- Failover and Recovery:
- Informatica can be configured for high availability, with failover capabilities.
- If a Node fails, the Integration Service can fail over to another Node, and the session or workflow can be recovered.
- Transactional Recovery:
- For transactional targets, Informatica can use transaction control to ensure that data is committed or rolled back consistently.
- This helps to maintain data integrity in transactional systems.
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Transaction Control Transformation:
- This transformation allows you to define transaction boundaries within a mapping.
- It enables you to commit or roll back transactions based on specific conditions.
- This is crucial for maintaining data consistency in transactional systems.
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Persistent Caches:
- When using cached lookups, or aggregator transformations, the ability to make those caches persistent, allows for the caches to be reused after a failure, or between sessions. This reduces the amount of time that it takes to rebuild those caches.
Importance of Recovery Strategies :
- Data Integrity:
- Recovery strategies ensure that target data is consistent and accurate, even after failures.
- Reduced Downtime:
- By minimizing reprocessing, recovery strategies help to reduce downtime and ensure that data is available when needed.
- Improved Reliability:
- Recovery strategies enhance the reliability of data integration processes.
- Auditing:
- Recovery strategies aid in auditing, by providing the ability to track the progress of a workflow, and to see where, and when a failure occured.
