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/*
* Licensed to the Apache Software Foundation (ASF) under one or more
* contributor license agreements. See the NOTICE file distributed with
* this work for additional information regarding copyright ownership.
* The ASF licenses this file to You under the Apache License, Version 2.0
* (the "License"); you may not use this file except in compliance with
* the License. You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
package org.apache.spark.sql
import org.apache.spark.sql.test.SharedSQLContext
import org.apache.spark.sql.test.SQLTestData._
private case class FunctionResult(f1: String, f2: String)
class UDFSuite extends QueryTest with SharedSQLContext {
import testImplicits._
test("built-in fixed arity expressions") {
val df = sqlContext.emptyDataFrame
df.selectExpr("rand()", "randn()", "rand(5)", "randn(50)")
}
test("built-in vararg expressions") {
val df = Seq((1, 2)).toDF("a", "b")
df.selectExpr("array(a, b)")
df.selectExpr("struct(a, b)")
}
test("built-in expressions with multiple constructors") {
val df = Seq(("abcd", 2)).toDF("a", "b")
df.selectExpr("substr(a, 2)", "substr(a, 2, 3)").collect()
}
test("count") {
val df = Seq(("abcd", 2)).toDF("a", "b")
df.selectExpr("count(a)")
}
test("count distinct") {
val df = Seq(("abcd", 2)).toDF("a", "b")
df.selectExpr("count(distinct a)")
}
test("SPARK-8003 spark_partition_id") {
val df = Seq((1, "Tearing down the walls that divide us")).toDF("id", "saying")
df.registerTempTable("tmp_table")
checkAnswer(sql("select spark_partition_id() from tmp_table").toDF(), Row(0))
sqlContext.dropTempTable("tmp_table")
}
test("SPARK-8005 input_file_name") {
withTempPath { dir =>
val data = sparkContext.parallelize(0 to 10, 2).toDF("id")
data.write.parquet(dir.getCanonicalPath)
sqlContext.read.parquet(dir.getCanonicalPath).registerTempTable("test_table")
val answer = sql("select input_file_name() from test_table").head().getString(0)
assert(answer.contains(dir.getCanonicalPath))
assert(sql("select input_file_name() from test_table").distinct().collect().length >= 2)
sqlContext.dropTempTable("test_table")
}
}
test("error reporting for incorrect number of arguments") {
val df = sqlContext.emptyDataFrame
val e = intercept[AnalysisException] {
df.selectExpr("substr('abcd', 2, 3, 4)")
}
assert(e.getMessage.contains("arguments"))
}
test("error reporting for undefined functions") {
val df = sqlContext.emptyDataFrame
val e = intercept[AnalysisException] {
df.selectExpr("a_function_that_does_not_exist()")
}
assert(e.getMessage.contains("undefined function"))
}
test("Simple UDF") {
sqlContext.udf.register("strLenScala", (_: String).length)
assert(sql("SELECT strLenScala('test')").head().getInt(0) === 4)
}
test("ZeroArgument UDF") {
sqlContext.udf.register("random0", () => { Math.random()})
assert(sql("SELECT random0()").head().getDouble(0) >= 0.0)
}
test("TwoArgument UDF") {
sqlContext.udf.register("strLenScala", (_: String).length + (_: Int))
assert(sql("SELECT strLenScala('test', 1)").head().getInt(0) === 5)
}
test("UDF in a WHERE") {
sqlContext.udf.register("oneArgFilter", (n: Int) => { n > 80 })
val df = sparkContext.parallelize(
(1 to 100).map(i => TestData(i, i.toString))).toDF()
df.registerTempTable("integerData")
val result =
sql("SELECT * FROM integerData WHERE oneArgFilter(key)")
assert(result.count() === 20)
}
test("UDF in a HAVING") {
sqlContext.udf.register("havingFilter", (n: Long) => { n > 5 })
val df = Seq(("red", 1), ("red", 2), ("blue", 10),
("green", 100), ("green", 200)).toDF("g", "v")
df.registerTempTable("groupData")
val result =
sql(
"""
| SELECT g, SUM(v) as s
| FROM groupData
| GROUP BY g
| HAVING havingFilter(s)
""".stripMargin)
assert(result.count() === 2)
}
test("UDF in a GROUP BY") {
sqlContext.udf.register("groupFunction", (n: Int) => { n > 10 })
val df = Seq(("red", 1), ("red", 2), ("blue", 10),
("green", 100), ("green", 200)).toDF("g", "v")
df.registerTempTable("groupData")
val result =
sql(
"""
| SELECT SUM(v)
| FROM groupData
| GROUP BY groupFunction(v)
""".stripMargin)
assert(result.count() === 2)
}
test("UDFs everywhere") {
sqlContext.udf.register("groupFunction", (n: Int) => { n > 10 })
sqlContext.udf.register("havingFilter", (n: Long) => { n > 2000 })
sqlContext.udf.register("whereFilter", (n: Int) => { n < 150 })
sqlContext.udf.register("timesHundred", (n: Long) => { n * 100 })
val df = Seq(("red", 1), ("red", 2), ("blue", 10),
("green", 100), ("green", 200)).toDF("g", "v")
df.registerTempTable("groupData")
val result =
sql(
"""
| SELECT timesHundred(SUM(v)) as v100
| FROM groupData
| WHERE whereFilter(v)
| GROUP BY groupFunction(v)
| HAVING havingFilter(v100)
""".stripMargin)
assert(result.count() === 1)
}
test("struct UDF") {
sqlContext.udf.register("returnStruct", (f1: String, f2: String) => FunctionResult(f1, f2))
val result =
sql("SELECT returnStruct('test', 'test2') as ret")
.select($"ret.f1").head().getString(0)
assert(result === "test")
}
test("udf that is transformed") {
sqlContext.udf.register("makeStruct", (x: Int, y: Int) => (x, y))
// 1 + 1 is constant folded causing a transformation.
assert(sql("SELECT makeStruct(1 + 1, 2)").first().getAs[Row](0) === Row(2, 2))
}
test("type coercion for udf inputs") {
sqlContext.udf.register("intExpected", (x: Int) => x)
// pass a decimal to intExpected.
assert(sql("SELECT intExpected(1.0)").head().getInt(0) === 1)
}
test("udf in different types") {
sqlContext.udf.register("testDataFunc", (n: Int, s: String) => { (n, s) })
sqlContext.udf.register("decimalDataFunc",
(a: java.math.BigDecimal, b: java.math.BigDecimal) => { (a, b) })
sqlContext.udf.register("binaryDataFunc", (a: Array[Byte], b: Int) => { (a, b) })
sqlContext.udf.register("arrayDataFunc",
(data: Seq[Int], nestedData: Seq[Seq[Int]]) => { (data, nestedData) })
sqlContext.udf.register("mapDataFunc",
(data: scala.collection.Map[Int, String]) => { data })
sqlContext.udf.register("complexDataFunc",
(m: Map[String, Int], a: Seq[Int], b: Boolean) => { (m, a, b) } )
checkAnswer(
sql("SELECT tmp.t.* FROM (SELECT testDataFunc(key, value) AS t from testData) tmp").toDF(),
testData)
checkAnswer(
sql("""
| SELECT tmp.t.* FROM
| (SELECT decimalDataFunc(a, b) AS t FROM decimalData) tmp
""".stripMargin).toDF(), decimalData)
checkAnswer(
sql("""
| SELECT tmp.t.* FROM
| (SELECT binaryDataFunc(a, b) AS t FROM binaryData) tmp
""".stripMargin).toDF(), binaryData)
checkAnswer(
sql("""
| SELECT tmp.t.* FROM
| (SELECT arrayDataFunc(data, nestedData) AS t FROM arrayData) tmp
""".stripMargin).toDF(), arrayData.toDF())
checkAnswer(
sql("""
| SELECT mapDataFunc(data) AS t FROM mapData
""".stripMargin).toDF(), mapData.toDF())
checkAnswer(
sql("""
| SELECT tmp.t.* FROM
| (SELECT complexDataFunc(m, a, b) AS t FROM complexData) tmp
""".stripMargin).toDF(), complexData.select("m", "a", "b"))
}
test("SPARK-11716 UDFRegistration does not include the input data type in returned UDF") {
val myUDF = sqlContext.udf.register("testDataFunc", (n: Int, s: String) => { (n, s.toInt) })
// Without the fix, this will fail because we fail to cast data type of b to string
// because myUDF does not know its input data type. With the fix, this query should not
// fail.
checkAnswer(
testData2.select(myUDF($"a", $"b").as("t")),
testData2.selectExpr("struct(a, b)"))
checkAnswer(
sql("SELECT tmp.t.* FROM (SELECT testDataFunc(a, b) AS t from testData2) tmp").toDF(),
testData2)
}
}
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