{"action":"created","comment":{"url":"https://api.github.com/repos/caskdata/hydrator-plugins/pulls/comments/78109614","id":78109614,"diff_hunk":"@@ -0,0 +1,259 @@\n+/*\n+ * Copyright © 2016 Cask Data, Inc.\n+ *\n+ * Licensed under the Apache License, Version 2.0 (the \"License\"); you may not\n+ * use this file except in compliance with the License. You may obtain a copy of\n+ * the License at\n+ *\n+ * http://www.apache.org/licenses/LICENSE-2.0\n+ *\n+ * Unless required by applicable law or agreed to in writing, software\n+ * distributed under the License is distributed on an \"AS IS\" BASIS, WITHOUT\n+ * WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the\n+ * License for the specific language governing permissions and limitations under\n+ * the License.\n+ */\n+package co.cask.hydrator.plugin.spark;\n+\n+import co.cask.cdap.api.annotation.Description;\n+import co.cask.cdap.api.annotation.Name;\n+import co.cask.cdap.api.annotation.Plugin;\n+import co.cask.cdap.api.data.format.StructuredRecord;\n+import co.cask.cdap.api.data.schema.Schema;\n+import co.cask.cdap.api.dataset.lib.FileSet;\n+import co.cask.cdap.api.plugin.PluginConfig;\n+import co.cask.cdap.etl.api.PipelineConfigurer;\n+import co.cask.cdap.etl.api.batch.SparkExecutionPluginContext;\n+import co.cask.cdap.etl.api.batch.SparkPluginContext;\n+import co.cask.cdap.etl.api.batch.SparkSink;\n+import com.google.common.base.Preconditions;\n+import com.google.common.base.Splitter;\n+import com.google.common.primitives.Doubles;\n+import joptsimple.internal.Strings;\n+import org.apache.spark.api.java.JavaRDD;\n+import org.apache.spark.api.java.JavaSparkContext;\n+import org.apache.spark.api.java.function.Function;\n+import org.apache.spark.mllib.linalg.Vectors;\n+import org.apache.spark.mllib.regression.LabeledPoint;\n+import org.apache.spark.mllib.tree.DecisionTree;\n+import org.apache.spark.mllib.tree.model.DecisionTreeModel;\n+\n+import java.util.ArrayList;\n+import java.util.Arrays;\n+import java.util.HashMap;\n+import java.util.LinkedList;\n+import java.util.List;\n+import java.util.Map;\n+import javax.annotation.Nullable;\n+\n+/**\n+ * Spark Sink plugin that trains a model based upon a label in the structured record using Decision Tree Regression.\n+ * Writes this model to a FileSet.\n+ */\n+@Plugin(type = SparkSink.PLUGIN_TYPE)\n+@Name(DecisionTreeTrainer.PLUGIN_NAME)\n+@Description(\"Trains a regression model based upon a particular label and featuresToInclude of a record.\")\n+public class DecisionTreeTrainer extends SparkSink<StructuredRecord> {\n+  public static final String PLUGIN_NAME = \"DecisionTreeTrainer\";\n+  //Impurity measure of the homogeneity of the labels at the node. Expected value for regression is \"variance\".\n+  private static final String IMPURITY = \"variance\";\n+  private static final int DEFAULT_MAX_DEPTH = 10;\n+  private static final int DEFAULT_MAX_BINS = 100;\n+  private DecisionTreeTrainerConfig config;\n+\n+  @Override\n+  public void configurePipeline(PipelineConfigurer pipelineConfigurer) {\n+    pipelineConfigurer.createDataset(config.fileSetName, FileSet.class);\n+    Schema inputSchema = pipelineConfigurer.getStageConfigurer().getInputSchema();\n+    if (inputSchema != null) {\n+      config.validate(inputSchema);\n+    }\n+  }\n+\n+  @Override\n+  public void run(SparkExecutionPluginContext context, final JavaRDD<StructuredRecord> input) throws Exception {\n+\n+    Schema schema = input.first().getSchema();\n+    //categoricalFeaturesInfo : Specifies which features are categorical and how many categorical values each of those\n+    //features can take. This is given as a map from feature index to the number of categories for that feature.\n+    //Empty categoricalFeaturesInfo indicates all features are continuous.\n+    Map<Integer, Integer> categoricalFeaturesInfo = config.getCategoricalFeatureInfo(schema);\n+    final List<String> fields = config.getFeatureList(schema);\n+\n+    JavaRDD<LabeledPoint> trainingData = input.map(new Function<StructuredRecord, LabeledPoint>() {\n+      @Override\n+      public LabeledPoint call(StructuredRecord record) throws Exception {\n+        List<Double> featureList = new ArrayList<>();\n+        for (String field : fields) {\n+          featureList.add(Double.valueOf(record.get(field).toString()));\n+        }\n+        Double prediction = record.get(config.labelField);\n+        if (prediction == null) {\n+          throw new IllegalArgumentException(String.format(\"Value of Prediction field %s value must not be null\",\n+                                                           config.labelField));\n+        }\n+        return new LabeledPoint(prediction, Vectors.dense(Doubles.toArray(featureList)));","path":"spark-plugins/src/main/java/co/cask/hydrator/plugin/spark/DecisionTreeTrainer.java","position":95,"original_position":95,"commit_id":"4bbcc1274d3800fb036aaea518b3df86a209867d","original_commit_id":"4bbcc1274d3800fb036aaea518b3df86a209867d","user":{"login":"albertshau","id":5215004,"avatar_url":"https://avatars.githubusercontent.com/u/5215004?v=3","gravatar_id":"","url":"https://api.github.com/users/albertshau","html_url":"https://github.com/albertshau","followers_url":"https://api.github.com/users/albertshau/followers","following_url":"https://api.github.com/users/albertshau/following{/other_user}","gists_url":"https://api.github.com/users/albertshau/gists{/gist_id}","starred_url":"https://api.github.com/users/albertshau/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/albertshau/subscriptions","organizations_url":"https://api.github.com/users/albertshau/orgs","repos_url":"https://api.github.com/users/albertshau/repos","events_url":"https://api.github.com/users/albertshau/events{/privacy}","received_events_url":"https://api.github.com/users/albertshau/received_events","type":"User","site_admin":false},"body":"it's common for the feature vector to be sparse, so we should use Vectors.sparse() instead.","created_at":"2016-09-08T23:51:07Z","updated_at":"2016-09-08T23:51:07Z","html_url":"https://github.com/caskdata/hydrator-plugins/pull/401#discussion_r78109614","pull_request_url":"https://api.github.com/repos/caskdata/hydrator-plugins/pulls/401","_links":{"self":{"href":"https://api.github.com/repos/caskdata/hydrator-plugins/pulls/comments/78109614"},"html":{"href":"https://github.com/caskdata/hydrator-plugins/pull/401#discussion_r78109614"},"pull_request":{"href":"https://api.github.com/repos/caskdata/hydrator-plugins/pulls/401"}}},"pull_request":{"url":"https://api.github.com/repos/caskdata/hydrator-plugins/pulls/401","id":81445135,"html_url":"https://github.com/caskdata/hydrator-plugins/pull/401","diff_url":"https://github.com/caskdata/hydrator-plugins/pull/401.diff","patch_url":"https://github.com/caskdata/hydrator-plugins/pull/401.patch","issue_url":"https://api.github.com/repos/caskdata/hydrator-plugins/issues/401","number":401,"state":"open","locked":false,"title":"[HYDRA-668] - Decision Tree Regression","user":{"login":"ananya-bhattacharya","id":10112217,"avatar_url":"https://avatars.githubusercontent.com/u/10112217?v=3","gravatar_id":"","url":"https://api.github.com/users/ananya-bhattacharya","html_url":"https://github.com/ananya-bhattacharya","followers_url":"https://api.github.com/users/ananya-bhattacharya/followers","following_url":"https://api.github.com/users/ananya-bhattacharya/following{/other_user}","gists_url":"https://api.github.com/users/ananya-bhattacharya/gists{/gist_id}","starred_url":"https://api.github.com/users/ananya-bhattacharya/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/ananya-bhattacharya/subscriptions","organizations_url":"https://api.github.com/users/ananya-bhattacharya/orgs","repos_url":"https://api.github.com/users/ananya-bhattacharya/repos","events_url":"https://api.github.com/users/ananya-bhattacharya/events{/privacy}","received_events_url":"https://api.github.com/users/ananya-bhattacharya/received_events","type":"User","site_admin":false},"body":"Spark plugins that trains and predicts label data based on Decision Tree Regression.\r\nFor design please refer : https://wiki.cask.co/display/CE/Decision+Tree+Regression","created_at":"2016-08-16T10:03:19Z","updated_at":"2016-09-08T23:51:07Z","closed_at":null,"merged_at":null,"merge_commit_sha":"0e4f9de5e854d333a98a19b8926de8fab37ffc97","assignee":{"login":"russorat","id":4805997,"avatar_url":"https://avatars.githubusercontent.com/u/4805997?v=3","gravatar_id":"","url":"https://api.github.com/users/russorat","html_url":"https://github.com/russorat","followers_url":"https://api.github.com/users/russorat/followers","following_url":"https://api.github.com/users/russorat/following{/other_user}","gists_url":"https://api.github.com/users/russorat/gists{/gist_id}","starred_url":"https://api.github.com/users/russorat/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/russorat/subscriptions","organizations_url":"https://api.github.com/users/russorat/orgs","repos_url":"https://api.github.com/users/russorat/repos","events_url":"https://api.github.com/users/russorat/events{/privacy}","received_events_url":"https://api.github.com/users/russorat/received_events","type":"User","site_admin":false},"assignees":[{"login":"russorat","id":4805997,"avatar_url":"https://avatars.githubusercontent.com/u/4805997?v=3","gravatar_id":"","url":"https://api.github.com/users/russorat","html_url":"https://github.com/russorat","followers_url":"https://api.github.com/users/russorat/followers","following_url":"https://api.github.com/users/russorat/following{/other_user}","gists_url":"https://api.github.com/users/russorat/gists{/gist_id}","starred_url":"https://api.github.com/users/russorat/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/russorat/subscriptions","organizations_url":"https://api.github.com/users/russorat/orgs","repos_url":"https://api.github.com/users/russorat/repos","events_url":"https://api.github.com/users/russorat/events{/privacy}","received_events_url":"https://api.github.com/users/russorat/received_events","type":"User","site_admin":false},{"login":"abhinavbansal246","id":6788622,"avatar_url":"https://avatars.githubusercontent.com/u/6788622?v=3","gravatar_id":"","url":"https://api.github.com/users/abhinavbansal246","html_url":"https://github.com/abhinavbansal246","followers_url":"https://api.github.com/users/abhinavbansal246/followers","following_url":"https://api.github.com/users/abhinavbansal246/following{/other_user}","gists_url":"https://api.github.com/users/abhinavbansal246/gists{/gist_id}","starred_url":"https://api.github.com/users/abhinavbansal246/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/abhinavbansal246/subscriptions","organizations_url":"https://api.github.com/users/abhinavbansal246/orgs","repos_url":"https://api.github.com/users/abhinavbansal246/repos","events_url":"https://api.github.com/users/abhinavbansal246/events{/privacy}","received_events_url":"https://api.github.com/users/abhinavbansal246/received_events","type":"User","site_admin":false}],"milestone":null,"commits_url":"https://api.github.com/repos/caskdata/hydrator-plugins/pulls/401/commits","review_comments_url":"https://api.github.com/repos/caskdata/hydrator-plugins/pulls/401/comments","review_comment_url":"https://api.github.com/repos/caskdata/hydrator-plugins/pulls/comments{/number}","comments_url":"https://api.github.com/repos/caskdata/hydrator-plugins/issues/401/comments","statuses_url":"https://api.github.com/repos/caskdata/hydrator-plugins/statuses/4bbcc1274d3800fb036aaea518b3df86a209867d","head":{"label":"ananya-bhattacharya:feature/decision-tree-regression","ref":"feature/decision-tree-regression","sha":"4bbcc1274d3800fb036aaea518b3df86a209867d","user":{"login":"ananya-bhattacharya","id":10112217,"avatar_url":"https://avatars.githubusercontent.com/u/10112217?v=3","gravatar_id":"","url":"https://api.github.com/users/ananya-bhattacharya","html_url":"https://github.com/ananya-bhattacharya","followers_url":"https://api.github.com/users/ananya-bhattacharya/followers","following_url":"https://api.github.com/users/ananya-bhattacharya/following{/other_user}","gists_url":"https://api.github.com/users/ananya-bhattacharya/gists{/gist_id}","starred_url":"https://api.github.com/users/ananya-bhattacharya/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/ananya-bhattacharya/subscriptions","organizations_url":"https://api.github.com/users/ananya-bhattacharya/orgs","repos_url":"https://api.github.com/users/ananya-bhattacharya/repos","events_url":"https://api.github.com/users/ananya-bhattacharya/events{/privacy}","received_events_url":"https://api.github.com/users/ananya-bhattacharya/received_events","type":"User","site_admin":false},"repo":{"id":58439270,"name":"hydrator-plugins","full_name":"ananya-bhattacharya/hydrator-plugins","owner":{"login":"ananya-bhattacharya","id":10112217,"avatar_url":"https://avatars.githubusercontent.com/u/10112217?v=3","gravatar_id":"","url":"https://api.github.com/users/ananya-bhattacharya","html_url":"https://github.com/ananya-bhattac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