weibozhao commented on a change in pull request #24:
URL: https://github.com/apache/flink-ml/pull/24#discussion_r764659169
##########
File path:
flink-ml-lib/src/test/java/org/apache/flink/ml/classification/knn/KnnTest.java
##########
@@ -0,0 +1,278 @@
+package org.apache.flink.ml.classification.knn;
+
+import org.apache.flink.api.common.functions.MapFunction;
+import org.apache.flink.api.common.restartstrategy.RestartStrategies;
+import org.apache.flink.api.java.tuple.Tuple2;
+import org.apache.flink.configuration.Configuration;
+import org.apache.flink.ml.linalg.DenseMatrix;
+import org.apache.flink.ml.linalg.DenseVector;
+import org.apache.flink.ml.linalg.Vectors;
+import org.apache.flink.ml.util.ReadWriteUtils;
+import org.apache.flink.streaming.api.datastream.DataStream;
+import
org.apache.flink.streaming.api.environment.ExecutionCheckpointingOptions;
+import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
+import org.apache.flink.table.api.DataTypes;
+import org.apache.flink.table.api.Schema;
+import org.apache.flink.table.api.Table;
+import org.apache.flink.table.api.bridge.java.StreamTableEnvironment;
+import org.apache.flink.table.api.internal.TableImpl;
+import org.apache.flink.types.Row;
+
+import org.apache.commons.collections.IteratorUtils;
+import org.junit.Assert;
+import org.junit.Before;
+import org.junit.Test;
+
+import java.nio.file.Files;
+import java.util.ArrayList;
+import java.util.Arrays;
+import java.util.List;
+import java.util.Objects;
+
+import static org.junit.Assert.assertEquals;
+
+/** Knn algorithm test. */
+public class KnnTest {
+ private StreamExecutionEnvironment env;
+ private StreamTableEnvironment tEnv;
+ private Table trainData;
+ private static final String LABEL_COL = "label";
+ private static final String PRED_COL = "pred";
+ private static final String VEC_COL = "vec";
+ List<Row> trainArray =
+ new ArrayList<>(
+ Arrays.asList(
+ Row.of("f", Vectors.dense(2.0, 3.0)),
+ Row.of("f", Vectors.dense(2.1, 3.1)),
+ Row.of("m", Vectors.dense(200.1, 300.1)),
+ Row.of("m", Vectors.dense(200.2, 300.2)),
+ Row.of("m", Vectors.dense(200.3, 300.3)),
+ Row.of("m", Vectors.dense(200.4, 300.4)),
+ Row.of("m", Vectors.dense(200.4, 300.4)),
+ Row.of("m", Vectors.dense(200.6, 300.6)),
+ Row.of("f", Vectors.dense(2.1, 3.1)),
+ Row.of("f", Vectors.dense(2.1, 3.1)),
+ Row.of("f", Vectors.dense(2.1, 3.1)),
+ Row.of("f", Vectors.dense(2.1, 3.1)),
+ Row.of("f", Vectors.dense(2.3, 3.2)),
+ Row.of("f", Vectors.dense(2.3, 3.2)),
+ Row.of("c", Vectors.dense(2.8, 3.2)),
+ Row.of("d", Vectors.dense(300., 3.2)),
+ Row.of("f", Vectors.dense(2.2, 3.2)),
+ Row.of("e", Vectors.dense(2.4, 3.2)),
+ Row.of("e", Vectors.dense(2.5, 3.2)),
+ Row.of("e", Vectors.dense(2.5, 3.2)),
+ Row.of("f", Vectors.dense(2.1, 3.1))));
+
+ List<Row> testArray =
+ new ArrayList<>(
+ Arrays.asList(
+ Row.of("e", Vectors.dense(4.0, 4.1)),
+ Row.of("m", Vectors.dense(300, 42))));
+ private Table testData;
+
+ @Before
+ public void before() {
+ Configuration config = new Configuration();
+
config.set(ExecutionCheckpointingOptions.ENABLE_CHECKPOINTS_AFTER_TASKS_FINISH,
true);
+ env = StreamExecutionEnvironment.getExecutionEnvironment(config);
+ env.setParallelism(4);
+ env.enableCheckpointing(100);
+ env.setRestartStrategy(RestartStrategies.noRestart());
+ tEnv = StreamTableEnvironment.create(env);
+
+ Schema schema =
+ Schema.newBuilder()
+ .column("f0", DataTypes.STRING())
+ .column("f1", DataTypes.of(DenseVector.class))
+ .build();
+
+ DataStream<Row> dataStream = env.fromCollection(trainArray);
+ trainData = tEnv.fromDataStream(dataStream, schema).as(LABEL_COL + ","
+ VEC_COL);
+
+ DataStream<Row> predDataStream = env.fromCollection(testArray);
+ testData = tEnv.fromDataStream(predDataStream, schema).as(LABEL_COL +
"," + VEC_COL);
+ }
+
+ // Executes the graph and returns a list which has true label and predict
label.
+ private static List<Tuple2<String, String>> executeAndCollect(Table
output) throws Exception {
+ StreamTableEnvironment tEnv =
+ (StreamTableEnvironment) ((TableImpl)
output).getTableEnvironment();
+
+ DataStream<Tuple2<String, String>> stream =
+ tEnv.toDataStream(output)
+ .map(
+ new MapFunction<Row, Tuple2<String, String>>()
{
+ @Override
+ public Tuple2<String, String> map(Row row)
{
+ return Tuple2.of(
+ (String)
row.getField(LABEL_COL),
+ (String)
row.getField(PRED_COL));
+ }
+ });
+ return IteratorUtils.toList(stream.executeAndCollect());
+ }
+
+ private static void verifyClusteringResult(List<Tuple2<String, String>>
result) {
+ for (Tuple2<String, String> t2 : result) {
+ Assert.assertEquals(t2.f0, t2.f1);
+ }
+ }
+
+ /** Tests Param. */
+ @Test
+ public void testParam() {
+ Knn knnOrigin = new Knn();
Review comment:
done
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