Details
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Bug
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Status: In Progress
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Major
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Resolution: Unresolved
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2.3.1, 2.4.5
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None
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None
Description
This is an issue that have caused us so many data errors.
1) using spark ( with hive context enabled )
df = spark.createDataFrame([{"a": "x", "b": "y", "c": "3"}])
df.write.format("orc").option("compression", "ZLIB").mode("overwrite").saveAsTable('test_spark');
2) from hive
alter table test_spark rename to test_spark2
3)from spark-sql from command line ( note : not pyspark or spark-shell )
select * from test_spark2
will give output
NULL NULL NULL Time taken: 0.334 seconds, Fetched 1 row(s)
This will throw NULL because , pyspark write API will add a serde property called path into the hive metastore. when hive renames the table , it do not understand this serde and hence keep it as it is. Now when spark-sql tries to read it , it will honor the serde property first and then tries to read from the non-existent hdfs location. If it had given an error , then also it would have been fine , but throwing out NULL will cause applications to fail pretty bad. Spark claims to support hive tables , hence it should respect hive metastore location property rather than spark serde property when trying to read a table. This cannot be classified as a expected behaviour.
