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- Fixed a race condition bug in ResourceCoordinator that prevented
performing partition assignment in the correct order. It affects the
metrics processor and stream coordinator.
- Avoid the cancellation of delegation tokens upon completion of
Explore-launched MapReduce and Spark jobs, as these delegation tokens
are shared by CDAP system services.
- Removed 'SNAPSHOT' from the artifact version of apps created by
default by the CDAP UI. This fixes deploying Cask Tracker and Navigator
apps, enabling Cask Tracker from the CDAP UI.
- Fixed a bug that caused SDK builds to fail when using 3.3.x versions
of maven. (CDAP-5884)
- Fixed the Hydrator upgrade tool to correctly write out pipeline
configs that failed to upgrade.
- The CDAP Standalone now deploys and starts the Cask Tracker app in the
default namespace if the Tracker artifact is present.
- Shutdown external processes started by CDAP (Zookeeper and Kafka) when
there is an error during either startup or shutdown of CDAP.
- Fixed an issue where parsing of an AVRO schema was failing when it
included optional fields such as 'doc' or 'default'.
- Fixed a bug in the BatchReadableRDD so that it won't skip records when
used by DataFrame. (CDAP-5947)
- After upgrading CDAP from a pre-3.0 version, any unprocessed metrics
data in Kafka will be lost and WARN log messages will be logged that
tell about the inability to process old data in the old format.
- When running secure Hadoop clusters, debug logs from MapReduce
programs are not available.
- If the Hive Metastore is restarted while the CDAP Explore Service is
running, the Explore Service remains alive, but becomes unusable. To
correct, restart the CDAP Master — which will restart all services — as
described under "Starting CDAP Services" for your particular Hadoop
distribution in the Installation
- CDAP internally creates tables in the "user" space that begin with the
"system". User datasets with names starting with
can conflict if they were to match one of those names. To avoid this, do
not start any datasets with the word
- The application in the cdap-kafka-ingest-guide
does not run on Ubuntu 14.x as of CDAP 3.0.x. (CDAP-2632)
- Metrics for :ref:
FileSets <datasets-fileset>can show zero values
even if there is data present, because FileSets do not emit metrics
- A workflow that is scheduled by time will not be run between the
failure of the primary master and the time that the secondary takes
over. This scheduled run will not be triggered at all.
- Spark jobs on a Kerberos-enabled CDAP cluster cannot run longer than
the delegation token expiration.
- If the input partition filter for a PartitionedFileSet does not match
any partitions, MapReduce jobs can fail.
- The Workflow token is in an inconsistent state for nodes in a fork
while the nodes of the fork are still running. It becomes consistent
after the join. (CDAP-3000)
- When running in CDAP Standalone mode, if a MapReduce job fails
repeatedly, then the SDK hits an out-of-memory exception due to
perm gen. The Standalone needs restarting at this point.
- For Microsoft Windows, the CDAP Standalone scripts can fail when used
with a JAVA_HOME that is defined as a path with spaces in it. A
workaround is to use a definition of JAVA_HOME that does not include
spaces, such as
- In the CDAP CLI, executing
select *from a dataset with many
fields generates an error.
- A RESTful API call to retrieve workflow statistics hangs if units
(such as "s" for seconds) are not provided as part of the query.
- If a table schema contains a field name that is a reserved word in the
- During the upgrade to CDAP 3.4.1, publishing to Kafka is halted
because the CDAP Kafka service is not running. As a consequence, any
applications that sync to the CDAP metadata will become out-of-sync as
changes to the metadata made by the upgrade tool will not be published.