Known Issues in Apache Spark
Learn about the known issues in Spark, the impact or changes to the functionality, and the workaround.
- CDPD-23817: In the upgraded Cluster, the permission of /tmp/spark is restricted due to the HDP configuration hive.exec.scratchdir=/tmp/spark.
- If you are using the /tmp/spark directory in the CDP cluster, you must provide the required additional Policies/ACL permissions.
- CDPD-22670 and CDPD-23103: There are two configurations in Spark, "Atlas dependency" and "spark_lineage_enabled", which are conflicted. The issue is when Atlas dependency is turned off but spark_lineage_enabled is turned on.
- Run Spark application, Spark will log some error message and cannot continue. That can be restored by correcting the configurations and restarting Spark component with distributing client configurations.
- CDPD-23007: Mismatch in the Spark Default DB Location. In HDP 3.1.5, hive_db entities have one attribute - 'location' which is configured to the '/managed' path. In fresh install of CDP 7.1.7, hive_db entities now have 2 attributes 'location' configured to '/external' path and 'managedLocation' configured to '/managed' path. In. the AM2CM migration (HDP 3.1.5 -> CDP 7.1.7), the 'location' attribute from hive_db entities in HDP 3.1.5 comes unaltered to CDP 7.1.7 and hence maps to '/managed' path.
- This issue arises only if you are upgrading from HDP 3.1.5 to CDP 7.1.7. If you are performing a fresh install of CDP 7.1.7, you can ignore this issue.
- CDPD-217: The Apache Spark connector is not supported
- The old Apache Spark - Apache HBase Connector
(
shc) is not supported in CDP releases. - CDPD-3038: Launching
pysparkdisplays several HiveConf warning messages - When
pysparkstarts, several Hive configuration warning messages are displayed, similar to the following:19/08/09 11:48:04 WARN conf.HiveConf: HiveConf of name hive.vectorized.use.checked.expressions does not exist 19/08/09 11:48:04 WARN conf.HiveConf: HiveConf of name hive.tez.cartesian-product.enabled does not exist - CDPD-2650: Spark cannot write ZSTD and LZ4 compressed Parquet to dynamically partitioned tables
- Use a different compression algorithm.
- CDPD-3783: Cannot create databases from Spark
- Attempting to create a database using Spark results in an error
similar to the
following:
org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: MetaException(message:Permission denied: user [sparkuser] does not have [ALL] privilege on [hdfs://ip-10-1-2-3.cloudera.site:8020/tmp/spark/warehouse/spark_database.db]);
Technical Service Bulletins
- TSB 2025-821: Jackson library default limit may truncate Spark Event log data
- Version 2.15.0 of the Jackson library used by Cloudera introduced a default limit that could lead to a problem where the Spark History Server is unable to read large Spark Event Logs.
The new default limit of 5 million characters (previously unlimited) may impact reading large Spark Event Logs. When using Spark 3.3.x or lower, this could lead to potential truncation of log data, when this limit is encountered during the Spark Event Log write.
- Knowledge article
- For the latest update on this issue, see the corresponding Knowledge article: TSB 2025-821: Jackson library default limit may truncate Spark Event log data
