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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.ml.feature
import org.apache.spark.SparkFunSuite
import org.apache.spark.ml.param.ParamsSuite
import org.apache.spark.ml.util.DefaultReadWriteTest
import org.apache.spark.mllib.util.MLlibTestSparkContext
class SQLTransformerSuite
extends SparkFunSuite with MLlibTestSparkContext with DefaultReadWriteTest {
test("params") {
ParamsSuite.checkParams(new SQLTransformer())
}
test("transform numeric data") {
val original = sqlContext.createDataFrame(
Seq((0, 1.0, 3.0), (2, 2.0, 5.0))).toDF("id", "v1", "v2")
val sqlTrans = new SQLTransformer().setStatement(
"SELECT *, (v1 + v2) AS v3, (v1 * v2) AS v4 FROM __THIS__")
val result = sqlTrans.transform(original)
val resultSchema = sqlTrans.transformSchema(original.schema)
val expected = sqlContext.createDataFrame(
Seq((0, 1.0, 3.0, 4.0, 3.0), (2, 2.0, 5.0, 7.0, 10.0)))
.toDF("id", "v1", "v2", "v3", "v4")
assert(result.schema.toString == resultSchema.toString)
assert(resultSchema == expected.schema)
assert(result.collect().toSeq == expected.collect().toSeq)
}
test("read/write") {
val t = new SQLTransformer()
.setStatement("select * from __THIS__")
testDefaultReadWrite(t)
}
}
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