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Posted to commits@ignite.apache.org by ch...@apache.org on 2019/01/24 15:25:44 UTC
[ignite] branch master updated: IGNITE-11002: [ML] Add parser for
Spark Decision tree classifier model
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 7c369fe IGNITE-11002: [ML] Add parser for Spark Decision tree classifier model
7c369fe is described below
commit 7c369fef0211ecfadfbca5361d95b010b29da01a
Author: zaleslaw <za...@gmail.com>
AuthorDate: Thu Jan 24 18:25:24 2019 +0300
IGNITE-11002: [ML] Add parser for Spark Decision tree classifier model
This closes #5909
---
.../modelparser/DecisionTreeFromSparkExample.java | 85 +++++++++++
.../models/spark/serialized/dt/data/._SUCCESS.crc | Bin 0 -> 8 bytes
...-48b3-8356-9a26f9a6eb0f-c000.snappy.parquet.crc | Bin 0 -> 44 bytes
.../models/spark/serialized/dt/data/_SUCCESS | 0
...df49-48b3-8356-9a26f9a6eb0f-c000.snappy.parquet | Bin 0 -> 4193 bytes
.../spark/serialized/dt/metadata/._SUCCESS.crc | Bin 0 -> 8 bytes
.../spark/serialized/dt/metadata/.part-00000.crc | Bin 0 -> 12 bytes
.../models/spark/serialized/dt/metadata/_SUCCESS | 0
.../models/spark/serialized/dt/metadata/part-00000 | 1 +
.../ml/sparkmodelparser/SparkModelParser.java | 155 +++++++++++++++++++++
.../ml/sparkmodelparser/SupportedSparkModels.java | 3 +
11 files changed, 244 insertions(+)
diff --git a/examples/src/main/java/org/apache/ignite/examples/ml/inference/spark/modelparser/DecisionTreeFromSparkExample.java b/examples/src/main/java/org/apache/ignite/examples/ml/inference/spark/modelparser/DecisionTreeFromSparkExample.java
new file mode 100644
index 0000000..f220271
--- /dev/null
+++ b/examples/src/main/java/org/apache/ignite/examples/ml/inference/spark/modelparser/DecisionTreeFromSparkExample.java
@@ -0,0 +1,85 @@
+/*
+ * 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 org.apache.ignite.Ignite;
+import org.apache.ignite.IgniteCache;
+import org.apache.ignite.Ignition;
+import org.apache.ignite.examples.ml.tutorial.TitanicUtils;
+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.selection.scoring.evaluator.BinaryClassificationEvaluator;
+import org.apache.ignite.ml.selection.scoring.metric.Accuracy;
+import org.apache.ignite.ml.sparkmodelparser.SparkModelParser;
+import org.apache.ignite.ml.sparkmodelparser.SupportedSparkModels;
+import org.apache.ignite.ml.tree.DecisionTreeNode;
+
+/**
+ * Run Decision Tree 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 DecisionTreeFromSparkExample {
+ /** Path to Spark DT model. */
+ public static final String SPARK_MDL_PATH = "examples/src/main/resources/models/spark/serialized/dt/data" +
+ "/part-00000-86bc0f70-df49-48b3-8356-9a26f9a6eb0f-c000.snappy.parquet";
+
+ /** Run example. */
+ public static void main(String[] args) throws FileNotFoundException {
+ System.out.println();
+ System.out.println(">>> Decision Tree 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[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];
+
+ return VectorUtils.of(data);
+ };
+
+ IgniteBiFunction<Integer, Object[], Double> lbExtractor = (k, v) -> (double)v[1];
+
+ DecisionTreeNode mdl = (DecisionTreeNode)SparkModelParser.parse(
+ SPARK_MDL_PATH,
+ SupportedSparkModels.DECISION_TREE
+ );
+
+ System.out.println(">>> DT: " + mdl);
+
+ double accuracy = BinaryClassificationEvaluator.evaluate(
+ dataCache,
+ mdl,
+ featureExtractor,
+ lbExtractor,
+ new Accuracy<>()
+ );
+
+ System.out.println("\n>>> Accuracy " + accuracy);
+ System.out.println("\n>>> Test Error " + (1 - accuracy));
+ }
+ }
+}
diff --git a/examples/src/main/resources/models/spark/serialized/dt/data/._SUCCESS.crc b/examples/src/main/resources/models/spark/serialized/dt/data/._SUCCESS.crc
new file mode 100644
index 0000000..3b7b044
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diff --git a/examples/src/main/resources/models/spark/serialized/dt/data/.part-00000-86bc0f70-df49-48b3-8356-9a26f9a6eb0f-c000.snappy.parquet.crc b/examples/src/main/resources/models/spark/serialized/dt/data/.part-00000-86bc0f70-df49-48b3-8356-9a26f9a6eb0f-c000.snappy.parquet.crc
new file mode 100644
index 0000000..81479fa
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diff --git a/examples/src/main/resources/models/spark/serialized/dt/data/_SUCCESS b/examples/src/main/resources/models/spark/serialized/dt/data/_SUCCESS
new file mode 100644
index 0000000..e69de29
diff --git a/examples/src/main/resources/models/spark/serialized/dt/data/part-00000-86bc0f70-df49-48b3-8356-9a26f9a6eb0f-c000.snappy.parquet b/examples/src/main/resources/models/spark/serialized/dt/data/part-00000-86bc0f70-df49-48b3-8356-9a26f9a6eb0f-c000.snappy.parquet
new file mode 100644
index 0000000..1d3d04e
Binary files /dev/null and b/examples/src/main/resources/models/spark/serialized/dt/data/part-00000-86bc0f70-df49-48b3-8356-9a26f9a6eb0f-c000.snappy.parquet differ
diff --git a/examples/src/main/resources/models/spark/serialized/dt/metadata/._SUCCESS.crc b/examples/src/main/resources/models/spark/serialized/dt/metadata/._SUCCESS.crc
new file mode 100644
index 0000000..3b7b044
Binary files /dev/null and b/examples/src/main/resources/models/spark/serialized/dt/metadata/._SUCCESS.crc differ
diff --git a/examples/src/main/resources/models/spark/serialized/dt/metadata/.part-00000.crc b/examples/src/main/resources/models/spark/serialized/dt/metadata/.part-00000.crc
new file mode 100644
index 0000000..cdb7c30
Binary files /dev/null and b/examples/src/main/resources/models/spark/serialized/dt/metadata/.part-00000.crc differ
diff --git a/examples/src/main/resources/models/spark/serialized/dt/metadata/_SUCCESS b/examples/src/main/resources/models/spark/serialized/dt/metadata/_SUCCESS
new file mode 100644
index 0000000..e69de29
diff --git a/examples/src/main/resources/models/spark/serialized/dt/metadata/part-00000 b/examples/src/main/resources/models/spark/serialized/dt/metadata/part-00000
new file mode 100644
index 0000000..b27a036
--- /dev/null
+++ b/examples/src/main/resources/models/spark/serialized/dt/metadata/part-00000
@@ -0,0 +1 @@
+{"class":"org.apache.spark.ml.classification.DecisionTreeClassificationModel","timestamp":1548167959360,"sparkVersion":"2.2.0","uid":"dtc_267ccbcc0d51","paramMap":{"impurity":"gini","maxDepth":5,"cacheNodeIds":false,"seed":159147643,"maxBins":32,"checkpointInterval":10,"labelCol":"survived","rawPredictionCol":"rawPrediction","minInstancesPerNode":1,"featuresCol":"features","maxMemoryInMB":256,"probabilityCol":"probability","minInfoGain":0.0,"predictionCol":"prediction"},"numFeatures":3," [...]
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 9a869e8..8156810 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
@@ -19,6 +19,9 @@ package org.apache.ignite.ml.sparkmodelparser;
import java.io.File;
import java.io.IOException;
+import java.util.Map;
+import java.util.NavigableMap;
+import java.util.TreeMap;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.Path;
import org.apache.ignite.internal.util.IgniteUtils;
@@ -28,6 +31,9 @@ import org.apache.ignite.ml.math.primitives.vector.impl.DenseVector;
import org.apache.ignite.ml.regressions.linear.LinearRegressionModel;
import org.apache.ignite.ml.regressions.logistic.LogisticRegressionModel;
import org.apache.ignite.ml.svm.SVMLinearClassificationModel;
+import org.apache.ignite.ml.tree.DecisionTreeConditionalNode;
+import org.apache.ignite.ml.tree.DecisionTreeLeafNode;
+import org.apache.ignite.ml.tree.DecisionTreeNode;
import org.apache.parquet.column.page.PageReadStore;
import org.apache.parquet.example.data.Group;
import org.apache.parquet.example.data.simple.SimpleGroup;
@@ -38,6 +44,8 @@ import org.apache.parquet.io.ColumnIOFactory;
import org.apache.parquet.io.MessageColumnIO;
import org.apache.parquet.io.RecordReader;
import org.apache.parquet.schema.MessageType;
+import org.apache.parquet.schema.Type;
+import org.jetbrains.annotations.NotNull;
/** Parser of Spark models. */
public class SparkModelParser {
@@ -62,12 +70,121 @@ public class SparkModelParser {
return loadLinRegModel(ignitePathToMdl);
case LINEAR_SVM:
return loadLinearSVMModel(ignitePathToMdl);
+ case DECISION_TREE:
+ return loadDecisionTreeModel(ignitePathToMdl);
default:
throw new UnsupportedSparkModelException(ignitePathToMdl);
}
}
/**
+ * Load Decision Tree model.
+ *
+ * @param pathToMdl Path to model.
+ */
+ private static Model loadDecisionTreeModel(String pathToMdl) {
+ try (ParquetFileReader r = ParquetFileReader.open(HadoopInputFile.fromPath(new Path(pathToMdl), new Configuration()))) {
+ PageReadStore pages;
+ final MessageType schema = r.getFooter().getFileMetaData().getSchema();
+ final MessageColumnIO colIO = new ColumnIOFactory().getColumnIO(schema);
+ final Map<Integer, NodeData> nodes = new TreeMap<>();
+ while (null != (pages = r.readNextRowGroup())) {
+ final long rows = pages.getRowCount();
+ final RecordReader recordReader = colIO.getRecordReader(pages, new GroupRecordConverter(schema));
+ for (int i = 0; i < rows; i++) {
+ final SimpleGroup g = (SimpleGroup)recordReader.read();
+ NodeData nodeData = extractNodeDataFromParquetRow(g);
+ nodes.put(nodeData.id, nodeData);
+ }
+ }
+ return buildDecisionTreeModel(nodes);
+ }
+ catch (IOException e) {
+ System.out.println("Error reading parquet file.");
+ e.printStackTrace();
+ }
+ return null;
+ }
+
+ /**
+ * Builds the DT model by the given sorted map of nodes.
+ *
+ * @param nodes The sorted map of nodes.
+ */
+ private static Model buildDecisionTreeModel(Map<Integer, NodeData> nodes) {
+ DecisionTreeNode mdl = null;
+ if (!nodes.isEmpty()) {
+ NodeData rootNodeData = (NodeData)((NavigableMap)nodes).firstEntry().getValue();
+ mdl = buildTree(nodes, rootNodeData);
+ return mdl;
+ }
+ return mdl;
+ }
+
+ /**
+ * Build tree or sub-tree based on indices and nodes sorted map as a dictionary.
+ *
+ * @param nodes The sorted map of nodes.
+ * @param rootNodeData Root node data.
+ */
+ @NotNull private static DecisionTreeNode buildTree(Map<Integer, NodeData> nodes,
+ NodeData rootNodeData) {
+ return rootNodeData.isLeafNode ? new DecisionTreeLeafNode(rootNodeData.prediction) : new DecisionTreeConditionalNode(rootNodeData.featureIdx,
+ rootNodeData.threshold,
+ buildTree(nodes, nodes.get(rootNodeData.rightChildId)),
+ buildTree(nodes, nodes.get(rootNodeData.leftChildId)),
+ null);
+ }
+
+ /**
+ * Form the node data according data in parquet row.
+ *
+ * @param g The given group presenting the node data from Spark DT model.
+ */
+ @NotNull private static SparkModelParser.NodeData extractNodeDataFromParquetRow(SimpleGroup g) {
+ NodeData nodeData = new NodeData();
+ nodeData.id = g.getInteger(0, 0);
+ nodeData.prediction = g.getDouble(1, 0);
+ nodeData.leftChildId = g.getInteger(5, 0);
+ nodeData.rightChildId = g.getInteger(6, 0);
+
+ if (nodeData.leftChildId == -1 && nodeData.rightChildId == -1) {
+ nodeData.featureIdx = -1;
+ nodeData.threshold = -1;
+ nodeData.isLeafNode = true;
+ }
+ else {
+ final SimpleGroup splitGrp = (SimpleGroup)g.getGroup(7, 0);
+ nodeData.featureIdx = splitGrp.getInteger(0, 0);
+ nodeData.threshold = splitGrp.getGroup(1, 0).getGroup(0, 0).getDouble(0, 0);
+ }
+ return nodeData;
+ }
+
+ /**
+ * Prints the given group in the row of Parquet file.
+ *
+ * @param g The given group.
+ */
+ private static void printGroup(Group g) {
+ int fieldCnt = g.getType().getFieldCount();
+ for (int field = 0; field < fieldCnt; field++) {
+ int valCnt = g.getFieldRepetitionCount(field);
+
+ Type fieldType = g.getType().getType(field);
+ String fieldName = fieldType.getName();
+
+ for (int idx = 0; idx < valCnt; idx++) {
+ if (fieldType.isPrimitive())
+ System.out.println(fieldName + " " + g.getValueToString(field, idx));
+ else
+ printGroup(g.getGroup(field, idx));
+ }
+ }
+ System.out.println();
+ }
+
+ /**
* Load SVM model.
*
* @param pathToMdl Path to model.
@@ -258,4 +375,42 @@ public class SparkModelParser {
}
return coefficients;
}
+
+ /**
+ * Presenting data from one parquet row filled with NodeData in Spark DT model.
+ */
+ private static class NodeData {
+ /** Id. */
+ int id;
+
+ /** Prediction. */
+ double prediction;
+
+ /** Left child id. */
+ int leftChildId;
+
+ /** Right child id. */
+ int rightChildId;
+
+ /** Threshold. */
+ double threshold;
+
+ /** Feature index. */
+ int featureIdx;
+
+ /** Is leaf node. */
+ boolean isLeafNode;
+
+ @Override public String toString() {
+ return "NodeData{" +
+ "id=" + id +
+ ", prediction=" + prediction +
+ ", leftChildId=" + leftChildId +
+ ", rightChildId=" + rightChildId +
+ ", threshold=" + threshold +
+ ", featureIdx=" + featureIdx +
+ ", isLeafNode=" + isLeafNode +
+ '}';
+ }
+ }
}
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 c47ca01..2064a0c 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
@@ -29,6 +29,9 @@ public enum SupportedSparkModels {
/** Linear regression. */
LINEAR_REGRESSION,
+ /** Decision tree. */
+ DECISION_TREE,
+
/** Support Vector Machine . */
LINEAR_SVM
}