yy created SPARK-25367:
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Summary: Hive table created by Spark dataFrame has incompatiable
schema in spark and hive
Key: SPARK-25367
URL: https://issues.apache.org/jira/browse/SPARK-25367
Project: Spark
Issue Type: Bug
Components: Spark Shell
Affects Versions: 2.2.1
Environment: spark2.2.1
hive1.2.1
spark conf: hive-site.xml configured the metastore information, which is the
same as in hive.
Reporter: yy
We save the created dataframe object as a hive table in orc/parquet format in
the spark shell.
After we modified the column type (int to double) of this table in hive jdbc,
we found the column type queried in spark-shell didn't change, but changed in
hive jdbc. After we restarted the spark-shell, this table's column type is
still incompatible as showed in hive jdbc.
The coding process are as follows:
spark-shell:
val df = spark.read.json("examples/src/main/resources/people.json");
df.write.format("orc").saveAsTable("people_test");
spark.catalog.refreshTable("people_test")
spark.sql("desc people").show()
hive:
alter table people_test change column age age1 double;
desc people_test;
spark-shell:
spark.sql("desc people").show()
We also tested in spark-shell by creating a table using spark.sql("create table
XXX()"), and the modified columns also changed in spark.
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