Known Issues in Apache Hive

This topic describes known issues and workarounds for using Hive in this release of Cloudera Runtime.

CDPD-23041: DROP TABLE on a table having an index does not work: If you migrate a Hive table to CDP having an index, DROP TABLE does not drop the table. Hive no longer supports indexes (HIVE-18448). A foreign key constraint on the indexed table prevents dropping the table. Attempting to drop such a table results in the following error:
java.sql.BatchUpdateException: Cannot delete or update a parent row: a foreign key constraint fails ("hive"."IDXS", CONSTRAINT "IDXS_FK1" FOREIGN KEY ("ORIG_TBL_ID") REFERENCES "TBLS ("TBL_ID")); There are two workarounds:

Drop the foreign key "IDXS_FK1" on the "IDXS" table within the metastore. You can also manually drop indexes, but do not cascade any drops because the IDXS table includes references to "TBLS".

Launch an older version of Hive, such as Hive 2.3 that includes IDXS in the DDL, and then drop the indexes as described in Language Manual Indexing.; Apache Issue: Hive-24815

CDPD-676: Generate Oozie workflow for microstrategy: Workaround: None; Apache JIRA: none

Technical Service Bulletins

TSB 2021-480/1: Hive produces incorrect query results when skipping a header in a binary file: In CDP, setting the table property skip.header.line.count to greater than 0 in a table stored in a binary format, such as Parquet, can cause incorrect query results. The skip header property is intended for use with Text files and typically used with CSV files. The issue is not present when you run the query on a Text file that sets the skip header property to 1 or greater.
Upstream JIRA: Apache Jira: HIVE-24827
Knowledge article: For the latest update on this issue see the corresponding Knowledge article: TSB 2021-480.1: Hive produces incorrect query results when skipping a header in a binary file

TSB 2021-480/2: Hive ignores the property to skip a header or footer in a compressed file: In CDP, setting the table properties skip.header.line.count and skip.footer.line.count to greater than 0 in a table stored in a compressed format, such as bzip2, can cause incorrect results from SELECT * or SELECT COUNT ( * ) queries.
Upstream JIRA: Apache Jira: HIVE-24224
Knowledge article: For the latest update on this issue see the corresponding Knowledge article: TSB 2021-480.2: Hive ignores the property to skip a header or footer in a compressed file

TSB 2021-482: Race condition in subdirectory delete/rename causes hive jobs to fail: Multiple threads try to perform a rename operation on s3. One of the threads fails to perform a rename operation, causing an error. Hive logs will report "HiveException: Error moving ..." and the log will contain an error line starting with " Exception when loading partition " -all paths listed with s3a:// prefixes.
Knowledge article: For the latest update on this issue see the corresponding Knowledge article: TSB 2021-482: Race condition in subdirectory delete/rename causes Hive jobs to fail

TSB 2021-501: JOIN queries return wrong result for join keys with large size in Hive: JOIN queries return wrong results when performing joins on large size keys (larger than 255 bytes). This happens when the fast hash table join algorithm is enabled, which is enabled by default.
Knowledge article: For the latest update on this issue see the corresponding Knowledge article: TSB 2021-501: JOIN queries return wrong result for join keys with large size in Hive

TSB 2021-518: Incorrect results returned when joining two tables with different bucketing versions: Incorrect results are returned when joining two tables with different bucketing versions, and with the following Hive configurations: set hive.auto.convert.join = false and set mapreduce.job.reduces = any custom value.
Knowledge article: For the latest update on this issue see the corresponding Knowledge article: TSB 2021-518: Incorrect results returned when joining two tables with different bucketing versions

TSB 2023-627: IN/OR predicate on binary column returns wrong result: An IN or an OR predicate involving a binary datatype column may produce wrong results. The OR predicate is converted to an IN due to the setting hive.optimize.point.lookup which is true by default. Only binary data types are affected by this issue. See https://issues.apache.org/jira/browse/HIVE-26235 for example queries which may be affected.
Upstream JIRA: HIVE-26235
Knowledge article: For the latest update on this issue, see the corresponding Knowledge article: TSB 2023-627: IN/OR predicate on binary column returns wrong result