Herd/Spark - LoadDataFrame using Herd Partition service instead of DDL -- revert previous change until service side code for Singleton Generate Partition is deployed to prod, revert unit test change
@@ -486,24 +486,6 @@ class DefaultSourceSuite extends FunSuite with BeforeAndAfterAll with Matchers {
}
}
- test("save subPartitioned data, one level") {
- FileUtils.deleteDirectory(new java.io.File("./test-output"))
-
- val df = spark.createDataFrame(EXPECTED_ROWS.asJava, EXPECTED_SCHEMA)
- .filter($"sdate" === "2017-01-01")
- .filter($"symbol" === "A")
-
- val params = defaultParams + ("partitionValue" -> "2017-01-01") + ("subPartitionKeys" -> "symbol") + ("subPartitionValues" -> "A")
-
- val parts = Map(
- ("2017-01-01", "") -> "businessObjectData1.json"
- )
-
- noException should be thrownBy {
- writeDataFrame(new BaseHerdApi("test-case-6", parts), params, df)
- }
- }
-
test("save complex dataType dataframe") {
FileUtils.deleteDirectory(new java.io.File("./test-output"))
