[
https://issues.apache.org/jira/browse/SPARK-25367?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
yy updated SPARK-25367:
-----------------------
Environment:
spark2.2.1
hive1.2.1
was:
spark2.2.1
hive1.2.1
spark conf: hive-site.xml configured the metastore information, which is the
same as in hive.
> 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
> Reporter: yy
> Priority: Major
>
> 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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