MrDLontheway commented on a change in pull request #26242:
[SPARK-29586][SQL]changge jdbc method param lowerBound and upperBound DataType
URL: https://github.com/apache/spark/pull/26242#discussion_r339484887
##########
File path: sql/core/src/test/scala/org/apache/spark/sql/jdbc/JDBCSuite.scala
##########
@@ -1658,4 +1673,56 @@ class JDBCSuite extends QueryTest
}
}
}
+
+ test("SPARK-29586 make jdbc method support date/timestamp types in
partitionColumn") {
+ val expectedResult = Seq(
+ ("2018-07-06", "2018-07-06 05:50:00.0"),
+ ("2018-07-06", "2018-07-06 08:10:08.0"),
+ ("2018-07-08", "2018-07-08 13:32:01.0"),
+ ("2018-07-12", "2018-07-12 09:51:15.0")
+ ).map { case (date, timestamp) =>
+ Row(Date.valueOf(date), Timestamp.valueOf(timestamp))
+ }
+
+ // DateType partition column
+ val df1 = spark.read.jdbc(
+ url = urlWithUserAndPass,
+ table = "TEST.DATETIME",
+ columnName = "d",
+ lowerBound = "2018-07-06",
+ upperBound = "2018-07-20",
+ numPartitions = 3,
+ connectionProperties = new Properties()
+ )
+
+ df1.logicalPlan match {
+ case LogicalRelation(JDBCRelation(_, parts, _), _, _, _) =>
+ val whereClauses =
parts.map(_.asInstanceOf[JDBCPartition].whereClause).toSet
+ assert(whereClauses === Set(
+ """"D" < '2018-07-10' or "D" is null""",
+ """"D" >= '2018-07-10' AND "D" < '2018-07-14'""",
+ """"D" >= '2018-07-14'"""))
+ }
+ checkAnswer(df1, expectedResult)
+
+ // TimestampType partition column
+ val df2 = spark.read.jdbc(
+ url = urlWithUserAndPass,
+ table = "TEST.DATETIME",
+ columnName = "t",
+ lowerBound = "2018-07-04 03:30:00.0",
+ upperBound = "2018-07-27 14:11:05.0",
+ numPartitions = 2,
+ connectionProperties = new Properties()
+ )
+
+ df2.logicalPlan match {
+ case LogicalRelation(JDBCRelation(_, parts, _), _, _, _) =>
+ val whereClauses =
parts.map(_.asInstanceOf[JDBCPartition].whereClause).toSet
+ assert(whereClauses === Set(
+ """"T" < '2018-07-15 20:50:32.5' or "T" is null""",
+ """"T" >= '2018-07-15 20:50:32.5'"""))
+ }
+ checkAnswer(df2, expectedResult)
+ }
Review comment:
@maropu
I didn't think of a good way, maybe maybe I can combine them like this
```
test("SPARK-22814 support date/timestamp types in partitionColumn") {
val expectedResult = Seq(
("2018-07-06", "2018-07-06 05:50:00.0"),
("2018-07-06", "2018-07-06 08:10:08.0"),
("2018-07-08", "2018-07-08 13:32:01.0"),
("2018-07-12", "2018-07-12 09:51:15.0")
).map { case (date, timestamp) =>
Row(Date.valueOf(date), Timestamp.valueOf(timestamp))
}
// DateType partition column
val df1 = spark.read.format("jdbc")
.option("url", urlWithUserAndPass)
.option("dbtable", "TEST.DATETIME")
.option("partitionColumn", "d")
.option("lowerBound", "2018-07-06")
.option("upperBound", "2018-07-20")
.option("numPartitions", 3)
.load()
val df2 = spark.read.jdbc(
url = urlWithUserAndPass,
table = "TEST.DATETIME",
columnName = "d",
lowerBound = "2018-07-06",
upperBound = "2018-07-20",
numPartitions = 3,
connectionProperties = new Properties()
)
dateMatch(df1)
dateMatch(df2)
checkAnswer(df1, expectedResult)
checkAnswer(df2, expectedResult)
def dateMatch(df: DataFrame): Unit ={
df.logicalPlan match {
case LogicalRelation(JDBCRelation(_, parts, _), _, _, _) =>
val whereClauses =
parts.map(_.asInstanceOf[JDBCPartition].whereClause).toSet
assert(whereClauses === Set(
""""D" < '2018-07-10' or "D" is null""",
""""D" >= '2018-07-10' AND "D" < '2018-07-14'""",
""""D" >= '2018-07-14'"""))
}
}
// TimestampType partition column
val df3 = spark.read.format("jdbc")
.option("url", urlWithUserAndPass)
.option("dbtable", "TEST.DATETIME")
.option("partitionColumn", "t")
.option("lowerBound", "2018-07-04 03:30:00.0")
.option("upperBound", "2018-07-27 14:11:05.0")
.option("numPartitions", 2)
.load()
val df4 = spark.read.jdbc(
url = urlWithUserAndPass,
table = "TEST.DATETIME",
columnName = "t",
lowerBound = "2018-07-04 03:30:00.0",
upperBound = "2018-07-27 14:11:05.0",
numPartitions = 2,
connectionProperties = new Properties()
)
timeStampMatch(df3)
timeStampMatch(df4)
checkAnswer(df3, expectedResult)
checkAnswer(df4, expectedResult)
def timeStampMatch(df: DataFrame): Unit ={
df.logicalPlan match {
case LogicalRelation(JDBCRelation(_, parts, _), _, _, _) =>
val whereClauses =
parts.map(_.asInstanceOf[JDBCPartition].whereClause).toSet
assert(whereClauses === Set(
""""T" < '2018-07-15 20:50:32.5' or "T" is null""",
""""T" >= '2018-07-15 20:50:32.5'"""))
}
}
}
```
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