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Informatica

Implementing Informatica Persistent Cache

Updated on Sep 30, 2020

You must have noticed that the "time" Informatica takes to build the lookup cache can be too much sometimes depending on the lookup table size/volume. Using Persistent Cache, you may save lot of your time. This article describes how to do it.

What is Persistent Cache?

Lookups are cached by default in Informatica. This means that Informatica by default brings in the entire data of the lookup table from database server to Informatica Server as a part of lookup cache building activity during session run. If the lookup table is too huge, this ought to take quite some time. Now consider this scenario - what if you are looking up to the same table different times using different lookups in different mappings?

Do you want to spend the time of building the lookup cache again and again for each lookup? Off course not! Just use persistent cache option!

Yes, Lookup cache can be either non-persistent or persistent. The Integration Service saves or deletes lookup cache files after a successful session run based on whether the Lookup cache is checked as persistent or not.

Where and when we shall use Persistent Cache

Suppose we have a lookup table with same lookup condition and return/output ports and the lookup table is used many times in multiple mappings. Let us say a Customer Dimension table is used in many mappings to populate the surrogate key in the fact tables based on their source system keys. Now if we cache the same Customer Dimension table multiple times in multiple mappings that would definitely affect the SLA loading timeline.

There can be some functional reasons also for selecting to use persistent cache. Please read the article Advantage and Disadvantage of Persistent Cache Lookup to know how persistent cache can be used to ensure data integrity in long running ETL sessions where underlying tables are also changing.

So the solution is to use Named Persistent Cache

In the first mapping we will create the Named Persistent Cache file by setting three properties in the Properties tab of Lookup transformation.

session property
session property
  • Lookup cache persistent:

To be checked i.e. a Named Persistent Cache will be used.

  • Cache File Name Prefix:

user_defined_cache_file_name i.e. the Named Persistent cache file name that will be used in all the other mappings using the same lookup table. Enter the prefix name only. Do not enter .idx or .dat

  • Re-cache from lookup source:

To be checked i.e. the Named Persistent Cache file will be rebuilt or refreshed with the current data of the lookup table.

Next in all the mappings where we want to use the same already built Named Persistent Cache we need to set two properties in the Properties tab of Lookup transformation.

session property using cache
session property using cache
  • Lookup cache persistent:

To be checked i.e. the lookup will be using a Named Persistent Cache that is already saved in Cache Directory and if the cache file is not there the session will not fail it will just create the cache file instead.

  • Cache File Name Prefix:

user_defined_cache_file_name i.e. the Named Persistent cache file name that was defined in the mapping where the persistent cache file was created.

If there is any Lookup SQL Override, then the SQL statement in all the lookups should match exactly even also an extra blank space will fail the session that is using the already built persistent cache file.

So if the incoming source data volume is high, the lookup table’s data volume that need to be cached is also high, and the same lookup table is used in many mappings then the best way to handle the situation is to use one-time build, already created persistent named cache.