Github user gatorsmile commented on the issue:
https://github.com/apache/spark/pull/16326
If we want to make it consistent with the managed Hive serde table, the
existing behavior is still not the same.
```
scala> spark.sql(s"create table newTab (fieldOne long, partCol int) using
parquet options (path
'file:/Users/xiaoli/sparkBin/spark-2.1.1-SNAPSHOT-bin-hadoop2.7/bin/spark-warehouse/test')
partitioned by (partCol)")
res3: org.apache.spark.sql.DataFrame = []
scala> spark.table("newTab").show()
+--------+-------+
|fieldOne|partCol|
+--------+-------+
+--------+-------+
scala> spark.sql("insert into newTab values (213, 0)")
16/12/17 23:39:18 WARN log: Updating partition stats fast for: newtab
16/12/17 23:39:18 WARN log: Updated size to 766
res8: org.apache.spark.sql.DataFrame = []
scala> spark.table("newTab").show()
+--------+-------+
|fieldOne|partCol|
+--------+-------+
| 213| 0|
| 0| 0|
+--------+-------+
```
For a managed partitioned Hive serde table, the output should not contain
the previous value. That means, it should output something like
```
+--------+-------+
|fieldOne|partCol|
+--------+-------+
| 213| 0|
+--------+-------+
```
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