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Posted to commits@ignite.apache.org by ch...@apache.org on 2019/02/05 12:04:07 UTC
[ignite] branch master updated: IGNITE-11041: [ML] Add parser for
Spark Gradient-boosted tree regressor
This is an automated email from the ASF dual-hosted git repository.
chief pushed a commit to branch master
in repository https://gitbox.apache.org/repos/asf/ignite.git
The following commit(s) were added to refs/heads/master by this push:
new 963e2c2 IGNITE-11041: [ML] Add parser for Spark Gradient-boosted tree regressor
963e2c2 is described below
commit 963e2c2abaabbd9a098cd74c967f9f59d58de2a8
Author: zaleslaw <za...@gmail.com>
AuthorDate: Tue Feb 5 15:03:43 2019 +0300
IGNITE-11041: [ML] Add parser for Spark Gradient-boosted tree regressor
This closes #6013
---
.../modelparser/GBTRegressionFromSparkExample.java | 95 +++++++++++++++++++++
.../spark/serialized/gbtreg/data/._SUCCESS.crc | Bin 0 -> 8 bytes
...-4944-b933-7897869a29d3-c000.snappy.parquet.crc | Bin 0 -> 688 bytes
.../models/spark/serialized/gbtreg/data/_SUCCESS | 0
...888b-4944-b933-7897869a29d3-c000.snappy.parquet | Bin 0 -> 86992 bytes
.../spark/serialized/gbtreg/metadata/._SUCCESS.crc | Bin 0 -> 8 bytes
.../serialized/gbtreg/metadata/.part-00000.crc | Bin 0 -> 12 bytes
.../spark/serialized/gbtreg/metadata/_SUCCESS | 0
.../spark/serialized/gbtreg/metadata/part-00000 | 1 +
.../serialized/gbtreg/treesMetadata/._SUCCESS.crc | Bin 0 -> 8 bytes
...-48b3-bad7-07c343405928-c000.snappy.parquet.crc | Bin 0 -> 80 bytes
.../spark/serialized/gbtreg/treesMetadata/_SUCCESS | 0
...1326-48b3-bad7-07c343405928-c000.snappy.parquet | Bin 0 -> 8925 bytes
.../ml/sparkmodelparser/SparkModelParser.java | 41 +++++++--
.../ml/sparkmodelparser/SupportedSparkModels.java | 3 +
15 files changed, 134 insertions(+), 6 deletions(-)
diff --git a/examples/src/main/java/org/apache/ignite/examples/ml/inference/spark/modelparser/GBTRegressionFromSparkExample.java b/examples/src/main/java/org/apache/ignite/examples/ml/inference/spark/modelparser/GBTRegressionFromSparkExample.java
new file mode 100644
index 0000000..4c2837c
--- /dev/null
+++ b/examples/src/main/java/org/apache/ignite/examples/ml/inference/spark/modelparser/GBTRegressionFromSparkExample.java
@@ -0,0 +1,95 @@
+/*
+ * 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.ignite.examples.ml.inference.spark.modelparser;
+
+import java.io.FileNotFoundException;
+import javax.cache.Cache;
+import org.apache.ignite.Ignite;
+import org.apache.ignite.IgniteCache;
+import org.apache.ignite.Ignition;
+import org.apache.ignite.cache.query.QueryCursor;
+import org.apache.ignite.cache.query.ScanQuery;
+import org.apache.ignite.examples.ml.tutorial.TitanicUtils;
+import org.apache.ignite.ml.composition.ModelsComposition;
+import org.apache.ignite.ml.math.functions.IgniteBiFunction;
+import org.apache.ignite.ml.math.primitives.vector.Vector;
+import org.apache.ignite.ml.math.primitives.vector.VectorUtils;
+import org.apache.ignite.ml.sparkmodelparser.SparkModelParser;
+import org.apache.ignite.ml.sparkmodelparser.SupportedSparkModels;
+
+/**
+ * Run GBT Regression model loaded from snappy.parquet file.
+ * The snappy.parquet file was generated by Spark MLLib model.write.overwrite().save(..) operator.
+ * <p>
+ * You can change the test data used in this example and re-run it to explore this algorithm further.</p>
+ */
+public class GBTRegressionFromSparkExample {
+ /** Path to Spark GBT Regression model. */
+ public static final String SPARK_MDL_PATH = "examples/src/main/resources/models/spark/serialized/gbtreg/data" +
+ "/part-00000-db4215b8-888b-4944-b933-7897869a29d3-c000.snappy.parquet";
+
+ /** Spark model metadata path. */
+ private static final String SPARK_MDL_METADATA_PATH = "examples/src/main/resources/models/spark/serialized/gbtreg/treesMetadata" +
+ "/part-00000-999806a9-1326-48b3-bad7-07c343405928-c000.snappy.parquet";
+
+ /** Run example. */
+ public static void main(String[] args) throws FileNotFoundException {
+ System.out.println();
+ System.out.println(">>> GBT Regression model loaded from Spark through serialization over partitioned dataset usage example started.");
+ // Start ignite grid.
+ try (Ignite ignite = Ignition.start("examples/config/example-ignite.xml")) {
+ System.out.println(">>> Ignite grid started.");
+
+ IgniteCache<Integer, Object[]> dataCache = TitanicUtils.readPassengers(ignite);
+
+ IgniteBiFunction<Integer, Object[], Vector> featureExtractor = (k, v) -> {
+ double[] data = new double[] {(double)v[0], (double)v[1], (double)v[5], (double)v[6]};
+ data[0] = Double.isNaN(data[0]) ? 0 : data[0];
+ data[1] = Double.isNaN(data[1]) ? 0 : data[1];
+ data[2] = Double.isNaN(data[2]) ? 0 : data[2];
+ data[3] = Double.isNaN(data[3]) ? 0 : data[3];
+ return VectorUtils.of(data);
+ };
+
+ IgniteBiFunction<Integer, Object[], Double> lbExtractor = (k, v) -> (double)v[4];
+
+ ModelsComposition mdl = (ModelsComposition)SparkModelParser.parseWithMetadata(
+ SPARK_MDL_PATH, SPARK_MDL_METADATA_PATH,
+ SupportedSparkModels.GRADIENT_BOOSTED_TREES_REGRESSION
+ );
+
+ System.out.println(">>> GBT Regression model: " + mdl);
+
+ System.out.println(">>> ---------------------------------");
+ System.out.println(">>> | Prediction\t| Ground Truth\t|");
+ System.out.println(">>> ---------------------------------");
+
+ try (QueryCursor<Cache.Entry<Integer, Object[]>> observations = dataCache.query(new ScanQuery<>())) {
+ for (Cache.Entry<Integer, Object[]> observation : observations) {
+ Vector inputs = featureExtractor.apply(observation.getKey(), observation.getValue());
+ double groundTruth = lbExtractor.apply(observation.getKey(), observation.getValue());
+ double prediction = mdl.predict(inputs);
+
+ System.out.printf(">>> | %.4f\t\t| %.4f\t\t|\n", prediction, groundTruth);
+ }
+ }
+
+ System.out.println(">>> ---------------------------------");
+ }
+ }
+}
diff --git a/examples/src/main/resources/models/spark/serialized/gbtreg/data/._SUCCESS.crc b/examples/src/main/resources/models/spark/serialized/gbtreg/data/._SUCCESS.crc
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diff --git a/examples/src/main/resources/models/spark/serialized/gbtreg/data/_SUCCESS b/examples/src/main/resources/models/spark/serialized/gbtreg/data/_SUCCESS
new file mode 100644
index 0000000..e69de29
diff --git a/examples/src/main/resources/models/spark/serialized/gbtreg/data/part-00000-db4215b8-888b-4944-b933-7897869a29d3-c000.snappy.parquet b/examples/src/main/resources/models/spark/serialized/gbtreg/data/part-00000-db4215b8-888b-4944-b933-7897869a29d3-c000.snappy.parquet
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diff --git a/examples/src/main/resources/models/spark/serialized/gbtreg/metadata/._SUCCESS.crc b/examples/src/main/resources/models/spark/serialized/gbtreg/metadata/._SUCCESS.crc
new file mode 100644
index 0000000..3b7b044
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diff --git a/examples/src/main/resources/models/spark/serialized/gbtreg/metadata/.part-00000.crc b/examples/src/main/resources/models/spark/serialized/gbtreg/metadata/.part-00000.crc
new file mode 100644
index 0000000..b4fd7f8
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diff --git a/examples/src/main/resources/models/spark/serialized/gbtreg/metadata/_SUCCESS b/examples/src/main/resources/models/spark/serialized/gbtreg/metadata/_SUCCESS
new file mode 100644
index 0000000..e69de29
diff --git a/examples/src/main/resources/models/spark/serialized/gbtreg/metadata/part-00000 b/examples/src/main/resources/models/spark/serialized/gbtreg/metadata/part-00000
new file mode 100644
index 0000000..86432e8
--- /dev/null
+++ b/examples/src/main/resources/models/spark/serialized/gbtreg/metadata/part-00000
@@ -0,0 +1 @@
+{"class":"org.apache.spark.ml.regression.GBTRegressionModel","timestamp":1548339654834,"sparkVersion":"2.2.0","uid":"gbtr_31c6fb2bba5f","paramMap":{"labelCol":"age","minInstancesPerNode":1,"maxDepth":8,"predictionCol":"prediction","cacheNodeIds":false,"maxIter":100,"stepSize":0.1,"featuresCol":"features","subsamplingRate":1.0,"maxMemoryInMB":256,"lossType":"squared","minInfoGain":0.0,"checkpointInterval":10,"seed":-131597770,"impurity":"variance","maxBins":32},"numFeatures":4,"numTrees":100}
diff --git a/examples/src/main/resources/models/spark/serialized/gbtreg/treesMetadata/._SUCCESS.crc b/examples/src/main/resources/models/spark/serialized/gbtreg/treesMetadata/._SUCCESS.crc
new file mode 100644
index 0000000..3b7b044
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diff --git a/examples/src/main/resources/models/spark/serialized/gbtreg/treesMetadata/.part-00000-999806a9-1326-48b3-bad7-07c343405928-c000.snappy.parquet.crc b/examples/src/main/resources/models/spark/serialized/gbtreg/treesMetadata/.part-00000-999806a9-1326-48b3-bad7-07c343405928-c000.snappy.parquet.crc
new file mode 100644
index 0000000..e5efb27
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diff --git a/examples/src/main/resources/models/spark/serialized/gbtreg/treesMetadata/_SUCCESS b/examples/src/main/resources/models/spark/serialized/gbtreg/treesMetadata/_SUCCESS
new file mode 100644
index 0000000..e69de29
diff --git a/examples/src/main/resources/models/spark/serialized/gbtreg/treesMetadata/part-00000-999806a9-1326-48b3-bad7-07c343405928-c000.snappy.parquet b/examples/src/main/resources/models/spark/serialized/gbtreg/treesMetadata/part-00000-999806a9-1326-48b3-bad7-07c343405928-c000.snappy.parquet
new file mode 100644
index 0000000..0f1f46c
Binary files /dev/null and b/examples/src/main/resources/models/spark/serialized/gbtreg/treesMetadata/part-00000-999806a9-1326-48b3-bad7-07c343405928-c000.snappy.parquet differ
diff --git a/modules/ml/spark-model-parser/src/main/java/org/apache/ignite/ml/sparkmodelparser/SparkModelParser.java b/modules/ml/spark-model-parser/src/main/java/org/apache/ignite/ml/sparkmodelparser/SparkModelParser.java
index cc54848..db10814 100644
--- a/modules/ml/spark-model-parser/src/main/java/org/apache/ignite/ml/sparkmodelparser/SparkModelParser.java
+++ b/modules/ml/spark-model-parser/src/main/java/org/apache/ignite/ml/sparkmodelparser/SparkModelParser.java
@@ -58,6 +58,7 @@ import org.apache.parquet.io.RecordReader;
import org.apache.parquet.schema.MessageType;
import org.apache.parquet.schema.Type;
import org.jetbrains.annotations.NotNull;
+import org.jetbrains.annotations.Nullable;
/** Parser of Spark models. */
public class SparkModelParser {
@@ -187,22 +188,50 @@ public class SparkModelParser {
switch (parsedSparkMdl) {
case GRADIENT_BOOSTED_TREES:
return loadGBTClassifierModel(ignitePathToMdl, ignitePathToMdlMetaData);
+ case GRADIENT_BOOSTED_TREES_REGRESSION:
+ return loadGBTRegressionModel(ignitePathToMdl, ignitePathToMdlMetaData);
default:
throw new UnsupportedSparkModelException(ignitePathToMdl);
}
}
/**
- * Load GBT model.
+ * Load GDB Regression model.
*
* @param pathToMdl Path to model.
- * @param ignitePathToMdlMetaData Ignite path to model meta data.
+ * @param pathToMdlMetaData Path to model meta data.
*/
- private static Model loadGBTClassifierModel(String pathToMdl, String ignitePathToMdlMetaData) {
+ private static Model loadGBTRegressionModel(String pathToMdl, String pathToMdlMetaData) {
+ IgniteFunction<Double, Double> lbMapper = lb -> lb;
+
+ return parseAndBuildGDBModel(pathToMdl, pathToMdlMetaData, lbMapper);
+ }
+
+ /**
+ * Load GDB Classification model.
+ *
+ * @param pathToMdl Path to model.
+ * @param pathToMdlMetaData Path to model meta data.
+ */
+ private static Model loadGBTClassifierModel(String pathToMdl, String pathToMdlMetaData) {
+ IgniteFunction<Double, Double> lbMapper = lb -> lb > 0.5 ? 1.0 : 0.0;
+
+ return parseAndBuildGDBModel(pathToMdl, pathToMdlMetaData, lbMapper);
+ }
+
+ /**
+ * Parse and build common GDB model with the custom label mapper.
+ *
+ * @param pathToMdl Path to model.
+ * @param pathToMdlMetaData Path to model meta data.
+ * @param lbMapper Label mapper.
+ */
+ @Nullable private static Model parseAndBuildGDBModel(String pathToMdl, String pathToMdlMetaData,
+ IgniteFunction<Double, Double> lbMapper) {
double[] treeWeights = null;
final Map<Integer, Double> treeWeightsByTreeID = new HashMap<>();
- try (ParquetFileReader r = ParquetFileReader.open(HadoopInputFile.fromPath(new Path(ignitePathToMdlMetaData), new Configuration()))) {
+ try (ParquetFileReader r = ParquetFileReader.open(HadoopInputFile.fromPath(new Path(pathToMdlMetaData), new Configuration()))) {
PageReadStore pagesMetaData;
final MessageType schema = r.getFooter().getFileMetaData().getSchema();
final MessageColumnIO colIO = new ColumnIOFactory().getColumnIO(schema);
@@ -219,7 +248,7 @@ public class SparkModelParser {
}
}
catch (IOException e) {
- System.out.println("Error reading parquet file with MetaData by the path: " + ignitePathToMdlMetaData);
+ System.out.println("Error reading parquet file with MetaData by the path: " + pathToMdlMetaData);
e.printStackTrace();
}
@@ -255,7 +284,7 @@ public class SparkModelParser {
final List<IgniteModel<Vector, Double>> models = new ArrayList<>();
nodesByTreeId.forEach((key, nodes) -> models.add(buildDecisionTreeModel(nodes)));
- IgniteFunction<Double, Double> lbMapper = lb -> lb > 0.5 ? 1.0 : 0.0;
+
return new GDBTrainer.GDBModel(models, new WeightedPredictionsAggregator(treeWeights), lbMapper);
}
catch (IOException e) {
diff --git a/modules/ml/spark-model-parser/src/main/java/org/apache/ignite/ml/sparkmodelparser/SupportedSparkModels.java b/modules/ml/spark-model-parser/src/main/java/org/apache/ignite/ml/sparkmodelparser/SupportedSparkModels.java
index 26d0394..fa4b8e1 100644
--- a/modules/ml/spark-model-parser/src/main/java/org/apache/ignite/ml/sparkmodelparser/SupportedSparkModels.java
+++ b/modules/ml/spark-model-parser/src/main/java/org/apache/ignite/ml/sparkmodelparser/SupportedSparkModels.java
@@ -47,6 +47,9 @@ public enum SupportedSparkModels {
/** Random forest regression. */
RANDOM_FOREST_REGRESSION,
+ /** Gradient boosted trees regression. */
+ GRADIENT_BOOSTED_TREES_REGRESSION,
+
/**
* Gradient boosted trees.
* NOTE: support binary classification only with raw labels 0 and 1