[jira] [Created] (SPARK-25367) Hive table created by Spark dataFrame has incompatiable schema in spark and hive

["yy (JIRA)" <ji...@apache.org>]

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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