Added extract_weight(string featureVectors)::weights UDF

scripts/ddl/define-all.hive

@@ -176,6 +176,9 @@ create temporary function sortByFeature as 'hivemall.ftvec.SortByFeatureUDF';
 drop temporary function extract_feature;
 create temporary function extract_feature as 'hivemall.ftvec.ExtractFeatureUDF';
 
+drop temporary function extract_weight;
+create temporary function extract_weight as 'hivemall.ftvec.ExtractWeightUDF';
+
 --------------------------
 -- Regression functions --
 --------------------------

scripts/ddl/define-ftvec-udf.hive

@@ -57,3 +57,5 @@ create temporary function sortByFeature as 'hivemall.ftvec.SortByFeatureUDF';
 drop temporary function extract_feature;
 create temporary function extract_feature as 'hivemall.ftvec.ExtractFeatureUDF';
 
+drop temporary function extract_weight;
+create temporary function extract_weight as 'hivemall.ftvec.ExtractWeightUDF';

src/main/hivemall/ftvec/ExtractWeightUDF.java

@@ -0,0 +1,65 @@
+/*
+ * Hivemall: Hive scalable Machine Learning Library
+ *
+ * Copyright (C) 2013
+ *   National Institute of Advanced Industrial Science and Technology (AIST)
+ *   Registration Number: H25PRO-1520
+ *
+ * This library is free software; you can redistribute it and/or
+ * modify it under the terms of the GNU Lesser General Public
+ * License as published by the Free Software Foundation.
+ *
+ * This library is distributed in the hope that it will be useful,
+ * but WITHOUT ANY WARRANTY; without even the implied warranty of
+ * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
+ * Lesser General Public License for more details.
+ *
+ * You should have received a copy of the GNU Lesser General Public
+ * License along with this library; if not, write to the Free Software
+ * Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA  02110-1301  USA
+ */
+package hivemall.ftvec;
+
+import java.util.Arrays;
+import java.util.List;
+
+import org.apache.hadoop.hive.ql.exec.Description;
+import org.apache.hadoop.hive.ql.exec.UDF;
+import org.apache.hadoop.hive.ql.exec.UDFArgumentException;
+import org.apache.hadoop.hive.ql.udf.UDFType;
+import org.apache.hadoop.io.FloatWritable;
+
+@Description(name = "extract_weight", value = "_FUNC_(feature_vector in array<string>) - Returns the weights of features in array<string>")
+@UDFType(deterministic = true, stateful = false)
+public class ExtractWeightUDF extends UDF {
+
+    public FloatWritable evaluate(String featureVector) throws UDFArgumentException {
+        return extractWeights(featureVector);
+    }
+
+    public List<FloatWritable> evaluate(List<String> featureVectors) throws UDFArgumentException {
+        if(featureVectors == null) {
+            return null;
+        }
+        final int size = featureVectors.size();
+        final FloatWritable[] output = new FloatWritable[size];
+        for(int i = 0; i < size; i++) {
+            String ftvec = featureVectors.get(i);
+            output[i] = extractWeights(ftvec);
+        }
+        return Arrays.asList(output);
+    }
+
+    private static FloatWritable extractWeights(String ftvec) throws UDFArgumentException {
+        if(ftvec == null) {
+            return null;
+        }
+        String[] splits = ftvec.split(":");
+        if(splits.length != 2) {
+            throw new UDFArgumentException("Unexpected feature vector representation: " + ftvec);
+        }
+        float f = Float.valueOf(splits[1]);
+        return new FloatWritable(f);
+    }
+
+}