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Updated flink 1.8 -> 1.17. Added smoke tests for Flink (#9046)
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107 changes: 107 additions & 0 deletions
107
...example/src/main/java/ml/dmlc/xgboost4j/java/example/flink/DistTrainWithFlinkExample.java
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| Original file line number | Diff line number | Diff line change |
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| /* | ||
| Copyright (c) 2014-2021 by Contributors | ||
| Licensed 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 ml.dmlc.xgboost4j.java.example.flink; | ||
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| import java.nio.file.Path; | ||
| import java.util.Arrays; | ||
| import java.util.HashMap; | ||
| import java.util.List; | ||
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| import org.apache.flink.api.common.typeinfo.TypeHint; | ||
| import org.apache.flink.api.common.typeinfo.TypeInformation; | ||
| import org.apache.flink.api.java.DataSet; | ||
| import org.apache.flink.api.java.ExecutionEnvironment; | ||
| import org.apache.flink.api.java.operators.MapOperator; | ||
| import org.apache.flink.api.java.tuple.Tuple13; | ||
| import org.apache.flink.api.java.tuple.Tuple2; | ||
| import org.apache.flink.api.java.utils.DataSetUtils; | ||
| import org.apache.flink.ml.linalg.DenseVector; | ||
| import org.apache.flink.ml.linalg.Vector; | ||
| import org.apache.flink.ml.linalg.Vectors; | ||
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| import ml.dmlc.xgboost4j.java.flink.XGBoost; | ||
| import ml.dmlc.xgboost4j.java.flink.XGBoostModel; | ||
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| public class DistTrainWithFlinkExample { | ||
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| static Tuple2<XGBoostModel, DataSet<Float[]>> runPrediction( | ||
| ExecutionEnvironment env, | ||
| java.nio.file.Path trainPath, | ||
| int percentage) throws Exception { | ||
| // reading data | ||
| final DataSet<Tuple2<Long, Tuple2<Vector, Double>>> data = | ||
| DataSetUtils.zipWithIndex(parseCsv(env, trainPath)); | ||
| final long size = data.count(); | ||
| final long trainCount = Math.round(size * 0.01 * percentage); | ||
| final DataSet<Tuple2<Vector, Double>> trainData = | ||
| data | ||
| .filter(item -> item.f0 < trainCount) | ||
| .map(t -> t.f1) | ||
| .returns(TypeInformation.of(new TypeHint<Tuple2<Vector, Double>>(){})); | ||
| final DataSet<Vector> testData = | ||
| data | ||
| .filter(tuple -> tuple.f0 >= trainCount) | ||
| .map(t -> t.f1.f0) | ||
| .returns(TypeInformation.of(new TypeHint<Vector>(){})); | ||
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| // define parameters | ||
| HashMap<String, Object> paramMap = new HashMap<String, Object>(3); | ||
| paramMap.put("eta", 0.1); | ||
| paramMap.put("max_depth", 2); | ||
| paramMap.put("objective", "binary:logistic"); | ||
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| // number of iterations | ||
| final int round = 2; | ||
| // train the model | ||
| XGBoostModel model = XGBoost.train(trainData, paramMap, round); | ||
| DataSet<Float[]> predTest = model.predict(testData); | ||
| return new Tuple2<XGBoostModel, DataSet<Float[]>>(model, predTest); | ||
| } | ||
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| private static MapOperator<Tuple13<Double, String, Double, Double, Double, Integer, Integer, | ||
| Integer, Integer, Integer, Integer, Integer, Integer>, | ||
| Tuple2<Vector, Double>> parseCsv(ExecutionEnvironment env, Path trainPath) { | ||
| return env.readCsvFile(trainPath.toString()) | ||
| .ignoreFirstLine() | ||
| .types(Double.class, String.class, Double.class, Double.class, Double.class, | ||
| Integer.class, Integer.class, Integer.class, Integer.class, Integer.class, | ||
| Integer.class, Integer.class, Integer.class) | ||
| .map(DistTrainWithFlinkExample::mapFunction); | ||
| } | ||
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| private static Tuple2<Vector, Double> mapFunction(Tuple13<Double, String, Double, Double, Double, | ||
| Integer, Integer, Integer, Integer, Integer, Integer, Integer, Integer> tuple) { | ||
| final DenseVector dense = Vectors.dense(tuple.f2, tuple.f3, tuple.f4, tuple.f5, tuple.f6, | ||
| tuple.f7, tuple.f8, tuple.f9, tuple.f10, tuple.f11, tuple.f12); | ||
| if (tuple.f1.contains("inf")) { | ||
| return new Tuple2<Vector, Double>(dense, 1.0); | ||
| } else { | ||
| return new Tuple2<Vector, Double>(dense, 0.0); | ||
| } | ||
| } | ||
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| public static void main(String[] args) throws Exception { | ||
| final java.nio.file.Path parentPath = java.nio.file.Paths.get(Arrays.stream(args) | ||
| .findFirst().orElse(".")); | ||
| final ExecutionEnvironment env = ExecutionEnvironment.getExecutionEnvironment(); | ||
| Tuple2<XGBoostModel, DataSet<Float[]>> tuple2 = runPrediction( | ||
| env, parentPath.resolve("veterans_lung_cancer.csv"), 70 | ||
| ); | ||
| List<Float[]> list = tuple2.f1.collect(); | ||
| System.out.println(list.size()); | ||
| } | ||
| } |
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36 changes: 36 additions & 0 deletions
36
...e/src/test/scala/ml/dmlc/xgboost4j/java/example/flink/DistTrainWithFlinkExampleTest.scala
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| Original file line number | Diff line number | Diff line change |
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| @@ -0,0 +1,36 @@ | ||
| /* | ||
| Copyright (c) 2014-2023 by Contributors | ||
| Licensed 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 ml.dmlc.xgboost4j.java.example.flink | ||
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| import org.apache.flink.api.java.ExecutionEnvironment | ||
| import org.scalatest.Inspectors._ | ||
| import org.scalatest.funsuite.AnyFunSuite | ||
| import org.scalatest.matchers.should.Matchers._ | ||
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| import java.nio.file.Paths | ||
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| class DistTrainWithFlinkExampleTest extends AnyFunSuite { | ||
| private val parentPath = Paths.get("../../").resolve("demo").resolve("data") | ||
| private val data = parentPath.resolve("veterans_lung_cancer.csv") | ||
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| test("Smoke test for scala flink example") { | ||
| val env = ExecutionEnvironment.createLocalEnvironment(1) | ||
| val tuple2 = DistTrainWithFlinkExample.runPrediction(env, data, 70) | ||
| val results = tuple2.f1.collect() | ||
| results should have size 41 | ||
| forEvery(results)(item => item should have size 1) | ||
| } | ||
| } |
37 changes: 37 additions & 0 deletions
37
...xample/src/test/scala/ml/dmlc/xgboost4j/scala/example/flink/DistTrainWithFlinkSuite.scala
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,37 @@ | ||
| /* | ||
| Copyright (c) 2014-2023 by Contributors | ||
| Licensed 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 ml.dmlc.xgboost4j.scala.example.flink | ||
|
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| import org.apache.flink.api.java.ExecutionEnvironment | ||
| import org.scalatest.Inspectors._ | ||
| import org.scalatest.funsuite.AnyFunSuite | ||
| import org.scalatest.matchers.should.Matchers._ | ||
|
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| import java.nio.file.Paths | ||
| import scala.jdk.CollectionConverters._ | ||
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| class DistTrainWithFlinkSuite extends AnyFunSuite { | ||
| private val parentPath = Paths.get("../../").resolve("demo").resolve("data") | ||
| private val data = parentPath.resolve("veterans_lung_cancer.csv") | ||
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| test("Smoke test for scala flink example") { | ||
| implicit val env: ExecutionEnvironment = ExecutionEnvironment.createLocalEnvironment(1) | ||
| val (_, result) = DistTrainWithFlink.runPrediction(data, 70) | ||
| val results = result.collect().asScala | ||
| results should have size 41 | ||
| forEvery(results)(item => item should have size 1) | ||
| } | ||
| } |
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