PowerExchange Adapters for Informatica 10.2.2
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When you use Snowflake jars, version 2.11-2.4.3, the performance of the read operation of a Snowflake mapping on the Spark engine drops by 1.5X when compared to Snowflake jars of version 2.11-2.3.1.
Snowflake reference number: 00034954
When two Snowflake source tables contain the same column name, and you specify a Joiner condition in the Snowflake source properties, the mapping fails on the Spark engine.
When you run a mapping in the native environment to read large volumes of data from Snowflake, the mapping fails with an out of memory error.
Workaround: Increase the Java heap memory size in the Data Integration Service properties, and restart the Data Integration Service.
Snowflake reference number: 00028631
When you run a mapping on the Spark engine to write data of the Time data type, the Data Integration Service does not write the data to the Snowflake table even though the mapping runs successfully.
Snowflake reference number:00033380