Github user gatorsmile commented on a diff in the pull request:
https://github.com/apache/spark/pull/16209#discussion_r107086057
--- Diff:
sql/core/src/test/scala/org/apache/spark/sql/jdbc/JDBCWriteSuite.scala ---
@@ -362,4 +363,80 @@ class JDBCWriteSuite extends SharedSQLContext with
BeforeAndAfter {
assert(sql("select * from people_view").count() == 2)
}
}
+
+ test("SPARK-10849: create table using user specified column type.") {
+ val data = Seq[Row](
+ Row(1, "dave", "Boston", "electric cars"),
+ Row(2, "mary", "Seattle", "building planes")
+ )
+ val schema = StructType(
+ StructField("id", IntegerType) ::
+ StructField("first#name", StringType) ::
+ StructField("city", StringType) ::
+ StructField("descr", StringType) ::
+ Nil)
+ val df = spark.createDataFrame(sparkContext.parallelize(data), schema)
+ // Use database specific CHAR/VARCHAR types instead of String data
type.
+ val createTableColTypes = "`first#name` VARCHAR(123), city CHAR(20)"
+ assert(JdbcUtils.schemaString(df.schema, url1,
Option(createTableColTypes)) ==
+ s""""id" INTEGER , "first#name" VARCHAR(123) , "city" CHAR(20) ,
"descr" TEXT """)
--- End diff --
This is the case that users specify all the columns. In this case, we
should mix the order of the columns.
In addition, we also need a case that users only specify one/two columns.
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