Informatica Data Quality
- Informatica Data Quality 10.4.1
- All Products
Issue
| Description
|
---|---|
BDM-36452
| When the Spark engine runs a mapping, the mapping fails with an error like:
SEVERE: Data integration service failed to create DTM instance because of the following error: java.lang.UnsupportedOperationException: PARAM_READ ...
|
BDM-35582
| When the Spark engine runs a mapping on an EMR 6.0 cluster using a Rank transformation that accesses flat file sources and targets, the mapping fails.
|
BDM-35519
| The Spark engine writes an incorrect date to a Hive target on Amazon EMR 6.0 when the mapping source is a flat file Hive source.
|
BDM-35036
| Mappings that use the Blaze engine cannot read or write to S3 buckets under certain restrictive EC2 access policies.
|
BDM-36351
| When you run an EDC Resource that profiles a high number of objects (400 or more), some of the DTM processes (pmdtmsvc2) hang permanently.
|
BDM-36561
| When the Spark execution stops unexpectedly, a Null Pointer Exception error occurs and data is not collected for subsequent mapping runs.
|
OCON-26500
| When the Spark engine runs a Sqoop mapping on the Amazon EMR 6.0 cluster to write data that contains the date or time data types to Netezza, Greenplum, or Microsoft SQL Server, the mapping fails.
|