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  1. Abstract
  2. Installation and Upgrade
  3. Support Changes
  4. 10.5 Fixed Issues and Closed Enhancements
  5. 10.5 Known Issues
  6. Cumulative Known Issues
  7. Emergency Bug Fixes Merged into 10.5

Release Notes

Release Notes

Third-Party Known Issues (Cumulative)

Third-Party Known Issues (Cumulative)

The following table describes known limitations that are carried forward from previous releases:
Issue
Description
BDM-35662
The Spark engine version 3 fails mappings that contain a MAP function with a key of type "map."
Spark ticket number: SPARK-26071
BDM-35661
The Spark engine fails mappings on a Cloudera CDP Public Cloud cluster when the following conditions are true:
  • The mapping reads from a Hive source created with a custom query.
  • The query uses arithmetic operations for the column name. For example, to add 100 to every value in INT_1, you use the following query:
    SELECT INT_1 + 100 FROM Hive_table
    .
You might see the following exception in the log file:
java.lang.reflect.InvocationTargetException ... Caused by: org.apache.spark.sql.AnalysisException: cannot resolve '<column name>' given input columns: [<column names>]
In the SQL override query, provide an alias name for columns that use arithmetic operations in the query. For example,
SELECT INT_1 + 100 as <alias name> FROM Hive_table
.
Cloudera ticket number: CDPD-3293
BDM-34608
BDM-34615
When the Spark engine runs a mapping with a Hive WASBS source and a flat file target on a non-ESP-enabled Hadoop cluster, it creates separate staging directories for users other than the expected impersonation user.
Workaround for non-ESP-enabled HDInsight 4.0 clusters: Set the following properties on the cluster:
  • Set "Run as end user instead of Hive user" (doAs) to TRUE.
  • Enable hive.metastore.execute.setugi.
Workaround for ESP-enabled HDInsight 4.0 clusters: set "Run as end user instead of Hive user" (doAs) to FALSE.
Microsoft ticket number: 120072723000878.
BDM-34066
When you import a Cloudera CDH compute cluster configuration directly from the cluster, the cluster configuration does not include the hive-site.xml file.
Download all *-site.xml files from the Hadoop cluster as a .zip file and import the compute cluster configuration from the archive file.
Cloudera ticket: 697586
BDM-33828
When the Spark engine runs a mapping on a Cloudera CDP cluster, the mapping fails with the following SPARK_1003 error:
MetaException (message:Permission denied: user [<impersonation user>] does not have [SELECT] privilege on [default])
In Ranger, add SELECT privileges to the default database for all users who run Spark queries.
Cloudera ticket: CDPD-12622
For more information, see Cloudera 7.1.1 Release Notes.
BDM-28598
When the Spark engine processes an input value of zero in a decimal port that is configured with equivalent precision and scale, the engine treats the value as data overflow and the return value is NULL on a Hortonworks HDP 3.1 cluster.
Cloudera ticket reference number: 635063
BDM-25513
When you have a mapping with a Hive ACID source and target tables that runs on the Spark engine, the Summary Statistics view does not reflect any throughput statistics for the mapping job.
Cloudera ticket reference number: 00225986
BDM-23104
The Spark engine cannot write data to a bucketed Hive target if the Hadoop distribution is MapR.
MapR case number: 00074338
BDM-10455
Inserts into a bucketed table can sometimes fail when you use Hive on Tez as the execution engine. The issue is more probable if the table is a Hive ACID table and a delete operation is performed before the inserts.
Apache ticket reference number: TEZ-3814
BDM-4674
A mapping with an Update Strategy transformation fails at run time if the Hive target has more than one primary key.
Apache Hive ticket reference number: HIVE-19911

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