Github user cloud-fan commented on a diff in the pull request:

    https://github.com/apache/spark/pull/16593#discussion_r96785016
  
    --- Diff: 
sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveDDLSuite.scala 
---
    @@ -1361,6 +1355,38 @@ class HiveDDLSuite
         }
       }
     
    +  test("create hive serde table as select with DataFrameWriter.saveAsTable 
with partitionBy") {
    +    withTable("t", "t1") {
    +      withSQLConf("hive.exec.dynamic.partition.mode" -> "nonstrict") {
    +        Seq(10 -> "y").toDF("i", 
"j").write.format("hive").partitionBy("i").saveAsTable("t")
    +        checkAnswer(spark.table("t"), Row("y", 10) :: Nil)
    +        var table = 
spark.sessionState.catalog.getTableMetadata(TableIdentifier("t"))
    +        var partitionSchema = table.partitionSchema
    +        assert(partitionSchema.size == 1 && partitionSchema.fields(0).name 
== "i" &&
    +          partitionSchema.fields(0).dataType == IntegerType)
    +
    +        Seq(11 -> "z").toDF("i", 
"j").write.mode("overwrite").format("hive")
    +          .partitionBy("j").saveAsTable("t")
    +        checkAnswer(spark.table("t"), Row(11, "z") :: Nil)
    +        table = 
spark.sessionState.catalog.getTableMetadata(TableIdentifier("t"))
    +        partitionSchema = table.partitionSchema
    +        assert(partitionSchema.size == 1 && partitionSchema.fields(0).name 
== "j" &&
    +          partitionSchema.fields(0).dataType == StringType)
    +
    +        Seq((1, 2, 3)).toDF("i", "j", 
"k").write.mode("overwrite").format("hive")
    +          .partitionBy("k", "j").saveAsTable("t")
    +        checkAnswer(spark.table("t"), Row(1, 3, 2) :: Nil)
    +
    +        Seq((1, 2, 3)).toDF("i", "j", 
"k").write.mode("overwrite").format("hive")
    --- End diff --
    
    I think we don't need to test `overwrite` behavior so many times, just 
create a table with `Seq(10 -> "y").toDF("i", "j").write.partitionBy("i")` and 
overwrite it with `Seq((1, 2, 3)).toDF("i", "j", "k").write.partitionBy("j", 
"k")`


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