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Posted to commits@hivemall.apache.org by my...@apache.org on 2017/01/16 07:03:17 UTC
[1/6] incubator-hivemall git commit: Close #13: Implement Kernel
Expansion Passive Aggressive Classification
Repository: incubator-hivemall
Updated Branches:
refs/heads/master 273851f39 -> 391e7f1c6
http://git-wip-us.apache.org/repos/asf/incubator-hivemall/blob/391e7f1c/resources/ddl/define-all-as-permanent.hive
----------------------------------------------------------------------
diff --git a/resources/ddl/define-all-as-permanent.hive b/resources/ddl/define-all-as-permanent.hive
index 72835b1..fe7b6f7 100644
--- a/resources/ddl/define-all-as-permanent.hive
+++ b/resources/ddl/define-all-as-permanent.hive
@@ -43,6 +43,12 @@ CREATE FUNCTION train_scw2 as 'hivemall.classifier.SoftConfideceWeightedUDTF$SCW
DROP FUNCTION IF EXISTS train_adagrad_rda;
CREATE FUNCTION train_adagrad_rda as 'hivemall.classifier.AdaGradRDAUDTF' USING JAR '${hivemall_jar}';
+DROP FUNCTION IF EXISTS train_kpa;
+CREATE FUNCTION train_kpa as 'hivemall.classifier.KernelExpansionPassiveAggressiveUDTF' USING JAR '${hivemall_jar}';
+
+DROP FUNCTION IF EXISTS kpa_predict;
+CREATE FUNCTION kpa_predict as 'hivemall.classifier.KPAPredictUDAF' USING JAR '${hivemall_jar}';
+
--------------------------------
-- Multiclass classification --
--------------------------------
@@ -186,6 +192,9 @@ CREATE FUNCTION polynomial_features as 'hivemall.ftvec.pairing.PolynomialFeature
DROP FUNCTION IF EXISTS powered_features;
CREATE FUNCTION powered_features as 'hivemall.ftvec.pairing.PoweredFeaturesUDF' USING JAR '${hivemall_jar}';
+DROP FUNCTION IF EXISTS feature_pairs;
+CREATE FUNCTION feature_pairs as 'hivemall.ftvec.pairing.FeaturePairsUDTF' USING JAR '${hivemall_jar}';
+
-----------------------
-- scaling functions --
-----------------------
http://git-wip-us.apache.org/repos/asf/incubator-hivemall/blob/391e7f1c/resources/ddl/define-all.hive
----------------------------------------------------------------------
diff --git a/resources/ddl/define-all.hive b/resources/ddl/define-all.hive
index 351303e..b0a0226 100644
--- a/resources/ddl/define-all.hive
+++ b/resources/ddl/define-all.hive
@@ -39,6 +39,12 @@ create temporary function train_scw2 as 'hivemall.classifier.SoftConfideceWeight
drop temporary function train_adagrad_rda;
create temporary function train_adagrad_rda as 'hivemall.classifier.AdaGradRDAUDTF';
+drop temporary function train_kpa;
+create temporary function train_kpa as 'hivemall.classifier.KernelExpansionPassiveAggressiveUDTF';
+
+drop temporary function kpa_predict;
+create temporary function kpa_predict as 'hivemall.classifier.KPAPredictUDAF';
+
--------------------------------
-- Multiclass classification --
--------------------------------
@@ -182,6 +188,9 @@ create temporary function polynomial_features as 'hivemall.ftvec.pairing.Polynom
drop temporary function powered_features;
create temporary function powered_features as 'hivemall.ftvec.pairing.PoweredFeaturesUDF';
+drop temporary function feature_pairs;
+create temporary function feature_pairs as 'hivemall.ftvec.pairing.FeaturePairsUDTF';
+
-----------------------
-- scaling functions --
-----------------------
[6/6] incubator-hivemall git commit: Close #13: Implement Kernel
Expansion Passive Aggressive Classification
Posted by my...@apache.org.
Close #13: Implement Kernel Expansion Passive Aggressive Classification
Project: http://git-wip-us.apache.org/repos/asf/incubator-hivemall/repo
Commit: http://git-wip-us.apache.org/repos/asf/incubator-hivemall/commit/391e7f1c
Tree: http://git-wip-us.apache.org/repos/asf/incubator-hivemall/tree/391e7f1c
Diff: http://git-wip-us.apache.org/repos/asf/incubator-hivemall/diff/391e7f1c
Branch: refs/heads/master
Commit: 391e7f1c65c7084acfbfe6b2491765a4dcd8212a
Parents: 273851f
Author: Sotaro Sugimoto <so...@gmail.com>
Authored: Mon Jan 16 16:01:46 2017 +0900
Committer: myui <yu...@gmail.com>
Committed: Mon Jan 16 16:01:46 2017 +0900
----------------------------------------------------------------------
.../src/main/java/hivemall/LearnerBaseUDTF.java | 4 +-
.../anomaly/SingularSpectrumTransformUDF.java | 22 +-
.../classifier/BinaryOnlineClassifierUDTF.java | 11 +-
.../hivemall/classifier/KPAPredictUDAF.java | 228 +
.../KernelExpansionPassiveAggressiveUDTF.java | 378 +
.../hivemall/ensemble/bagging/VotedAvgUDAF.java | 8 +-
.../ensemble/bagging/WeightVotedAvgUDAF.java | 8 +-
.../ftvec/pairing/FeaturePairsUDTF.java | 232 +
.../main/java/hivemall/model/FeatureValue.java | 29 +-
.../utils/collections/FloatArrayList.java | 152 +
.../collections/Int2FloatOpenHashTable.java | 3 +
.../java/hivemall/utils/hadoop/HiveUtils.java | 51 +
.../hivemall/utils/hashing/HashFunction.java | 14 +
.../java/hivemall/utils/lang/Preconditions.java | 18 +-
.../java/hivemall/utils/math/MathUtils.java | 18 +-
.../hivemall/anomaly/ChangeFinder1DTest.java | 2 +-
.../hivemall/anomaly/ChangeFinder2DTest.java | 2 +-
...ernelExpansionPassiveAggressiveUDTFTest.java | 158 +
.../fm/FactorizationMachineUDTFTest.java | 16 +-
.../FieldAwareFactorizationMachineUDTFTest.java | 16 +-
.../mf/BPRMatrixFactorizationUDTFTest.java | 16 +-
.../collections/Int2FloatOpenHashMapTest.java | 13 +
.../utils/io/Base91OutputStreamTest.java | 2 +-
.../hivemall/utils/lang/PreconditionsTest.java | 2 +-
.../test/resources/hivemall/anomaly/cf1d.csv | 2503 -
.../test/resources/hivemall/anomaly/cf1d.csv.gz | Bin 0 -> 17417 bytes
.../hivemall/classifier/news20-small.binary.gz | Bin 0 -> 121787 bytes
core/src/test/resources/hivemall/fm/5107786.txt | 200 -
.../test/resources/hivemall/fm/5107786.txt.gz | Bin 0 -> 2712 bytes
.../test/resources/hivemall/fm/bigdata.tr.txt | 200 -
.../resources/hivemall/fm/bigdata.tr.txt.gz | Bin 0 -> 4544 bytes
core/src/test/resources/hivemall/mf/ml1k.test | 20000 -----
.../src/test/resources/hivemall/mf/ml1k.test.gz | Bin 0 -> 78568 bytes
core/src/test/resources/hivemall/mf/ml1k.train | 80000 -----------------
.../test/resources/hivemall/mf/ml1k.train.gz | Bin 0 -> 311183 bytes
resources/ddl/define-all-as-permanent.hive | 9 +
resources/ddl/define-all.hive | 9 +
37 files changed, 1367 insertions(+), 102957 deletions(-)
----------------------------------------------------------------------
http://git-wip-us.apache.org/repos/asf/incubator-hivemall/blob/391e7f1c/core/src/main/java/hivemall/LearnerBaseUDTF.java
----------------------------------------------------------------------
diff --git a/core/src/main/java/hivemall/LearnerBaseUDTF.java b/core/src/main/java/hivemall/LearnerBaseUDTF.java
index f1ad99e..17c3ebc 100644
--- a/core/src/main/java/hivemall/LearnerBaseUDTF.java
+++ b/core/src/main/java/hivemall/LearnerBaseUDTF.java
@@ -161,11 +161,13 @@ public abstract class LearnerBaseUDTF extends UDTFWithOptions {
return cl;
}
+ @Nullable
protected PredictionModel createModel() {
return createModel(null);
}
- protected PredictionModel createModel(String label) {
+ @Nonnull
+ protected PredictionModel createModel(@Nullable String label) {
PredictionModel model;
final boolean useCovar = useCovariance();
if (dense_model) {
http://git-wip-us.apache.org/repos/asf/incubator-hivemall/blob/391e7f1c/core/src/main/java/hivemall/anomaly/SingularSpectrumTransformUDF.java
----------------------------------------------------------------------
diff --git a/core/src/main/java/hivemall/anomaly/SingularSpectrumTransformUDF.java b/core/src/main/java/hivemall/anomaly/SingularSpectrumTransformUDF.java
index d699a95..1fac3e7 100644
--- a/core/src/main/java/hivemall/anomaly/SingularSpectrumTransformUDF.java
+++ b/core/src/main/java/hivemall/anomaly/SingularSpectrumTransformUDF.java
@@ -125,19 +125,17 @@ public final class SingularSpectrumTransformUDF extends UDFWithOptions {
this._params.changepointThreshold = Primitives.parseDouble(cl.getOptionValue("th"),
_params.changepointThreshold);
- Preconditions.checkArgument(_params.w >= 2, "w must be greather than 1: " + _params.w,
- UDFArgumentException.class);
- Preconditions.checkArgument(_params.r >= 1, "r must be greater than 0: " + _params.r,
- UDFArgumentException.class);
- Preconditions.checkArgument(_params.k >= 1, "k must be greater than 0: " + _params.k,
- UDFArgumentException.class);
- Preconditions.checkArgument(_params.k >= _params.r,
- "k must be equals to or greather than r: k=" + _params.k + ", r" + _params.r,
- UDFArgumentException.class);
+ Preconditions.checkArgument(_params.w >= 2, UDFArgumentException.class,
+ "w must be greather than 1: " + _params.w);
+ Preconditions.checkArgument(_params.r >= 1, UDFArgumentException.class,
+ "r must be greater than 0: " + _params.r);
+ Preconditions.checkArgument(_params.k >= 1, UDFArgumentException.class,
+ "k must be greater than 0: " + _params.k);
+ Preconditions.checkArgument(_params.k >= _params.r, UDFArgumentException.class,
+ "k must be equals to or greather than r: k=" + _params.k + ", r" + _params.r);
Preconditions.checkArgument(_params.changepointThreshold > 0.d
- && _params.changepointThreshold < 1.d,
- "changepointThreshold must be in range (0, 1): " + _params.changepointThreshold,
- UDFArgumentException.class);
+ && _params.changepointThreshold < 1.d, UDFArgumentException.class,
+ "changepointThreshold must be in range (0, 1): " + _params.changepointThreshold);
return cl;
}
http://git-wip-us.apache.org/repos/asf/incubator-hivemall/blob/391e7f1c/core/src/main/java/hivemall/classifier/BinaryOnlineClassifierUDTF.java
----------------------------------------------------------------------
diff --git a/core/src/main/java/hivemall/classifier/BinaryOnlineClassifierUDTF.java b/core/src/main/java/hivemall/classifier/BinaryOnlineClassifierUDTF.java
index c9274e4..b0e2efd 100644
--- a/core/src/main/java/hivemall/classifier/BinaryOnlineClassifierUDTF.java
+++ b/core/src/main/java/hivemall/classifier/BinaryOnlineClassifierUDTF.java
@@ -51,8 +51,8 @@ import org.apache.hadoop.io.FloatWritable;
public abstract class BinaryOnlineClassifierUDTF extends LearnerBaseUDTF {
private static final Log logger = LogFactory.getLog(BinaryOnlineClassifierUDTF.class);
- private ListObjectInspector featureListOI;
- private PrimitiveObjectInspector labelOI;
+ protected ListObjectInspector featureListOI;
+ protected PrimitiveObjectInspector labelOI;
private boolean parseFeature;
protected PredictionModel model;
@@ -122,7 +122,7 @@ public abstract class BinaryOnlineClassifierUDTF extends LearnerBaseUDTF {
}
@Nullable
- protected final FeatureValue[] parseFeatures(@Nonnull final List<?> features) {
+ FeatureValue[] parseFeatures(@Nonnull final List<?> features) {
final int size = features.size();
if (size == 0) {
return null;
@@ -151,6 +151,7 @@ public abstract class BinaryOnlineClassifierUDTF extends LearnerBaseUDTF {
assert (label == -1 || label == 0 || label == 1) : label;
}
+ //@VisibleForTesting
void train(List<?> features, int label) {
FeatureValue[] featureVector = parseFeatures(features);
train(featureVector, label);
@@ -166,7 +167,7 @@ public abstract class BinaryOnlineClassifierUDTF extends LearnerBaseUDTF {
}
}
- protected float predict(@Nonnull final FeatureValue[] features) {
+ float predict(@Nonnull final FeatureValue[] features) {
float score = 0.f;
for (FeatureValue f : features) {// a += w[i] * x[i]
if (f == null) {
@@ -247,7 +248,7 @@ public abstract class BinaryOnlineClassifierUDTF extends LearnerBaseUDTF {
}
@Override
- public final void close() throws HiveException {
+ public void close() throws HiveException {
super.close();
if (model != null) {
int numForwarded = 0;
http://git-wip-us.apache.org/repos/asf/incubator-hivemall/blob/391e7f1c/core/src/main/java/hivemall/classifier/KPAPredictUDAF.java
----------------------------------------------------------------------
diff --git a/core/src/main/java/hivemall/classifier/KPAPredictUDAF.java b/core/src/main/java/hivemall/classifier/KPAPredictUDAF.java
new file mode 100644
index 0000000..72409d9
--- /dev/null
+++ b/core/src/main/java/hivemall/classifier/KPAPredictUDAF.java
@@ -0,0 +1,228 @@
+/*
+ * 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 hivemall.classifier;
+
+import hivemall.utils.hadoop.HiveUtils;
+import hivemall.utils.lang.Preconditions;
+
+import javax.annotation.Nonnull;
+import javax.annotation.Nullable;
+
+import org.apache.hadoop.hive.ql.exec.Description;
+import org.apache.hadoop.hive.ql.exec.UDFArgumentException;
+import org.apache.hadoop.hive.ql.exec.UDFArgumentTypeException;
+import org.apache.hadoop.hive.ql.metadata.HiveException;
+import org.apache.hadoop.hive.ql.parse.SemanticException;
+import org.apache.hadoop.hive.ql.udf.generic.AbstractGenericUDAFResolver;
+import org.apache.hadoop.hive.ql.udf.generic.GenericUDAFEvaluator;
+import org.apache.hadoop.hive.ql.udf.generic.GenericUDAFEvaluator.AbstractAggregationBuffer;
+import org.apache.hadoop.hive.ql.udf.generic.GenericUDAFEvaluator.AggregationType;
+import org.apache.hadoop.hive.ql.util.JavaDataModel;
+import org.apache.hadoop.hive.serde2.io.DoubleWritable;
+import org.apache.hadoop.hive.serde2.objectinspector.ObjectInspector;
+import org.apache.hadoop.hive.serde2.objectinspector.PrimitiveObjectInspector;
+import org.apache.hadoop.hive.serde2.objectinspector.primitive.PrimitiveObjectInspectorFactory;
+import org.apache.hadoop.hive.serde2.typeinfo.TypeInfo;
+
+@Description(
+ name = "kpa_predict",
+ value = "_FUNC_(@Nonnull double xh, @Nonnull double xk, @Nullable float w0, @Nonnull float w1, @Nonnull float w2, @Nullable float w3)"
+ + " - Returns a prediction value in Double")
+public final class KPAPredictUDAF extends AbstractGenericUDAFResolver {
+
+ @Override
+ public GenericUDAFEvaluator getEvaluator(TypeInfo[] parameters) throws SemanticException {
+ if (parameters.length != 6) {
+ throw new UDFArgumentException(
+ "_FUNC_(double xh, double xk, float w0, float w1, float w2, float w3) takes exactly 6 arguments but got: "
+ + parameters.length);
+ }
+ if (!HiveUtils.isNumberTypeInfo(parameters[0])) {
+ throw new UDFArgumentTypeException(0, "Number type is expected for xh (1st argument): "
+ + parameters[0].getTypeName());
+ }
+ if (!HiveUtils.isNumberTypeInfo(parameters[1])) {
+ throw new UDFArgumentTypeException(1, "Number type is expected for xk (2nd argument): "
+ + parameters[1].getTypeName());
+ }
+ if (!HiveUtils.isNumberTypeInfo(parameters[2])) {
+ throw new UDFArgumentTypeException(2, "Number type is expected for w0 (3rd argument): "
+ + parameters[2].getTypeName());
+ }
+ if (!HiveUtils.isNumberTypeInfo(parameters[3])) {
+ throw new UDFArgumentTypeException(3, "Number type is expected for w1 (4th argument): "
+ + parameters[3].getTypeName());
+ }
+ if (!HiveUtils.isNumberTypeInfo(parameters[4])) {
+ throw new UDFArgumentTypeException(4, "Number type is expected for w2 (5th argument): "
+ + parameters[4].getTypeName());
+ }
+ if (!HiveUtils.isNumberTypeInfo(parameters[5])) {
+ throw new UDFArgumentTypeException(5, "Number type is expected for w3 (6th argument): "
+ + parameters[5].getTypeName());
+ }
+
+ return new Evaluator();
+ }
+
+ public static class Evaluator extends GenericUDAFEvaluator {
+
+ @Nullable
+ private transient PrimitiveObjectInspector xhOI, xkOI;
+ @Nullable
+ private transient PrimitiveObjectInspector w0OI, w1OI, w2OI, w3OI;
+
+ public Evaluator() {}
+
+ @Override
+ public ObjectInspector init(Mode m, ObjectInspector[] parameters) throws HiveException {
+ super.init(m, parameters);
+
+ // initialize input
+ if (m == Mode.PARTIAL1 || m == Mode.COMPLETE) {// from original data
+ this.xhOI = HiveUtils.asNumberOI(parameters[0]);
+ this.xkOI = HiveUtils.asNumberOI(parameters[1]);
+ this.w0OI = HiveUtils.asNumberOI(parameters[2]);
+ this.w1OI = HiveUtils.asNumberOI(parameters[3]);
+ this.w2OI = HiveUtils.asNumberOI(parameters[4]);
+ this.w3OI = HiveUtils.asNumberOI(parameters[5]);
+ }
+
+ return PrimitiveObjectInspectorFactory.writableDoubleObjectInspector;
+ }
+
+ @Override
+ public AggrBuffer getNewAggregationBuffer() throws HiveException {
+ return new AggrBuffer();
+ }
+
+ @Override
+ public void reset(@SuppressWarnings("deprecation") AggregationBuffer agg)
+ throws HiveException {
+ AggrBuffer aggr = (AggrBuffer) agg;
+ aggr.reset();
+ }
+
+ @Override
+ public void iterate(@SuppressWarnings("deprecation") AggregationBuffer agg,
+ Object[] parameters) throws HiveException {
+ Preconditions.checkArgument(parameters.length == 6, HiveException.class);
+
+ final AggrBuffer aggr = (AggrBuffer) agg;
+
+ if (parameters[0] /* xh */!= null) {
+ double xh = HiveUtils.getDouble(parameters[0], xhOI);
+ if (parameters[1] /* xk */!= null) {
+ if (parameters[5] /* w3hk */== null) {
+ return;
+ }
+ // xh, xk, w3hk
+ double xk = HiveUtils.getDouble(parameters[1], xkOI);
+ double w3hk = HiveUtils.getDouble(parameters[5], w3OI);
+ aggr.addW3(xh, xk, w3hk);
+ } else {
+ if (parameters[3] /* w1h */== null) {
+ return;
+ }
+ // xh, w1h, w2h
+ Preconditions.checkNotNull(parameters[4], HiveException.class);
+ double w1h = HiveUtils.getDouble(parameters[3], w1OI);
+ double w2h = HiveUtils.getDouble(parameters[4], w2OI);
+ aggr.addW1W2(xh, w1h, w2h);
+ }
+ } else if (parameters[2] /* w0 */!= null) {
+ // w0
+ double w0 = HiveUtils.getDouble(parameters[2], w0OI);
+ aggr.addW0(w0);
+ }
+ }
+
+ @Override
+ public Object terminatePartial(@SuppressWarnings("deprecation") AggregationBuffer agg)
+ throws HiveException {
+ AggrBuffer aggr = (AggrBuffer) agg;
+ double v = aggr.get();
+ return new DoubleWritable(v);
+ }
+
+ @Override
+ public void merge(@SuppressWarnings("deprecation") AggregationBuffer agg, Object partial)
+ throws HiveException {
+ if (partial == null) {
+ return;
+ }
+
+ AggrBuffer aggr = (AggrBuffer) agg;
+ DoubleWritable other = (DoubleWritable) partial;
+ double v = other.get();
+ aggr.merge(v);
+ }
+
+ @Override
+ public DoubleWritable terminate(@SuppressWarnings("deprecation") AggregationBuffer agg)
+ throws HiveException {
+ AggrBuffer aggr = (AggrBuffer) agg;
+ double v = aggr.get();
+ return new DoubleWritable(v);
+ }
+
+ }
+
+ @AggregationType(estimable = true)
+ static class AggrBuffer extends AbstractAggregationBuffer {
+
+ double score;
+
+ AggrBuffer() {
+ super();
+ reset();
+ }
+
+ @Override
+ public int estimate() {
+ return JavaDataModel.PRIMITIVES2;
+ }
+
+ void reset() {
+ this.score = 0.d;
+ }
+
+ double get() {
+ return score;
+ }
+
+ void addW0(@Nonnull double w0) {
+ this.score += w0;
+ }
+
+ void addW1W2(final double xh, final double w1h, final double w2h) {
+ this.score += (w1h * xh + w2h * xh * xh);
+ }
+
+ void addW3(final double xh, final double xk, final double w3hk) {
+ this.score += (w3hk * xh * xk);
+ }
+
+ void merge(final double other) {
+ this.score += other;
+ }
+
+ }
+
+}
http://git-wip-us.apache.org/repos/asf/incubator-hivemall/blob/391e7f1c/core/src/main/java/hivemall/classifier/KernelExpansionPassiveAggressiveUDTF.java
----------------------------------------------------------------------
diff --git a/core/src/main/java/hivemall/classifier/KernelExpansionPassiveAggressiveUDTF.java b/core/src/main/java/hivemall/classifier/KernelExpansionPassiveAggressiveUDTF.java
new file mode 100644
index 0000000..3e28932
--- /dev/null
+++ b/core/src/main/java/hivemall/classifier/KernelExpansionPassiveAggressiveUDTF.java
@@ -0,0 +1,378 @@
+/*
+ * 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 hivemall.classifier;
+
+import hivemall.common.LossFunctions;
+import hivemall.model.FeatureValue;
+import hivemall.model.PredictionModel;
+import hivemall.model.PredictionResult;
+import hivemall.utils.collections.Int2FloatOpenHashTable;
+import hivemall.utils.collections.Int2FloatOpenHashTable.IMapIterator;
+import hivemall.utils.hashing.HashFunction;
+import hivemall.utils.lang.Preconditions;
+
+import java.util.ArrayList;
+import java.util.List;
+
+import javax.annotation.Nonnull;
+import javax.annotation.Nullable;
+
+import org.apache.commons.cli.CommandLine;
+import org.apache.commons.cli.Options;
+import org.apache.hadoop.hive.ql.exec.Description;
+import org.apache.hadoop.hive.ql.exec.UDFArgumentException;
+import org.apache.hadoop.hive.ql.metadata.HiveException;
+import org.apache.hadoop.hive.serde2.objectinspector.ObjectInspector;
+import org.apache.hadoop.hive.serde2.objectinspector.ObjectInspectorFactory;
+import org.apache.hadoop.hive.serde2.objectinspector.StructObjectInspector;
+import org.apache.hadoop.hive.serde2.objectinspector.primitive.PrimitiveObjectInspectorFactory;
+import org.apache.hadoop.io.FloatWritable;
+import org.apache.hadoop.io.IntWritable;
+
+/**
+ * Degree-2 polynomial kernel expansion Passive Aggressive.
+ *
+ * <pre>
+ * Hideki Isozaki and Hideto Kazawa: Efficient Support Vector Classifiers for Named Entity Recognition, Proc.COLING, 2002
+ * </pre>
+ */
+@Description(name = "train_kpa",
+ value = "_FUNC_(array<string|int|bigint> features, int label [, const string options])"
+ + " - returns a relation <h int, hk int, float w0, float w1, float w2, float w3>")
+public final class KernelExpansionPassiveAggressiveUDTF extends BinaryOnlineClassifierUDTF {
+
+ // ------------------------------------
+ // Hyper parameters
+ private float _pkc;
+ // Algorithm
+ private Algorithm _algo;
+
+ // ------------------------------------
+ // Model parameters
+
+ private float _w0;
+ private Int2FloatOpenHashTable _w1;
+ private Int2FloatOpenHashTable _w2;
+ private Int2FloatOpenHashTable _w3;
+
+ // ------------------------------------
+
+ private float _loss;
+
+ public KernelExpansionPassiveAggressiveUDTF() {}
+
+ //@VisibleForTesting
+ float getLoss() {//only used for testing purposes at the moment
+ return _loss;
+ }
+
+ @Override
+ protected Options getOptions() {
+ Options opts = new Options();
+ opts.addOption("pkc", true,
+ "Constant c inside polynomial kernel K = (dot(xi,xj) + c)^2 [default 1.0]");
+ opts.addOption("algo", "algorithm", true,
+ "Algorithm for calculating loss [pa, pa1 (default), pa2]");
+ opts.addOption("c", "aggressiveness", true,
+ "Aggressiveness parameter C for PA-1 and PA-2 [default 1.0]");
+ return opts;
+ }
+
+ @Override
+ protected CommandLine processOptions(ObjectInspector[] argOIs) throws UDFArgumentException {
+ float pkc = 1.f;
+ float c = 1.f;
+ String algo = "pa1";
+
+ final CommandLine cl = super.processOptions(argOIs);
+ if (cl != null) {
+ String pkc_str = cl.getOptionValue("pkc");
+ if (pkc_str != null) {
+ pkc = Float.parseFloat(pkc_str);
+ }
+ String c_str = cl.getOptionValue("c");
+ if (c_str != null) {
+ c = Float.parseFloat(c_str);
+ if (c <= 0.f) {
+ throw new UDFArgumentException("Aggressiveness parameter C must be C > 0: " + c);
+ }
+ }
+ algo = cl.getOptionValue("algo", algo);
+ }
+
+ if ("pa1".equalsIgnoreCase(algo)) {
+ this._algo = new PA1(c);
+ } else if ("pa2".equalsIgnoreCase(algo)) {
+ this._algo = new PA2(c);
+ } else if ("pa".equalsIgnoreCase(algo)) {
+ this._algo = new PA();
+ } else {
+ throw new UDFArgumentException("Unsupported algorithm: " + algo);
+ }
+ this._pkc = pkc;
+
+ return cl;
+ }
+
+ interface Algorithm {
+ float eta(final float loss, @Nonnull final PredictionResult margin);
+ }
+
+ static class PA implements Algorithm {
+
+ PA() {}
+
+ @Override
+ public float eta(float loss, PredictionResult margin) {
+ return loss / margin.getSquaredNorm();
+ }
+ }
+
+ static class PA1 implements Algorithm {
+ private final float c;
+
+ PA1(float c) {
+ this.c = c;
+ }
+
+ @Override
+ public float eta(float loss, PredictionResult margin) {
+ float squared_norm = margin.getSquaredNorm();
+ float eta = loss / squared_norm;
+ return Math.min(c, eta);
+ }
+ }
+
+ static class PA2 implements Algorithm {
+ private final float c;
+
+ PA2(float c) {
+ this.c = c;
+ }
+
+ @Override
+ public float eta(float loss, PredictionResult margin) {
+ float squared_norm = margin.getSquaredNorm();
+ float eta = loss / (squared_norm + (0.5f / c));
+ return eta;
+ }
+ }
+
+ @Override
+ protected PredictionModel createModel() {
+ this._w0 = 0.f;
+ this._w1 = new Int2FloatOpenHashTable(16384);
+ _w1.defaultReturnValue(0.f);
+ this._w2 = new Int2FloatOpenHashTable(16384);
+ _w2.defaultReturnValue(0.f);
+ this._w3 = new Int2FloatOpenHashTable(16384);
+ _w3.defaultReturnValue(0.f);
+
+ return null;
+ }
+
+ @Override
+ protected StructObjectInspector getReturnOI(ObjectInspector featureRawOI) {
+ ArrayList<String> fieldNames = new ArrayList<String>();
+ ArrayList<ObjectInspector> fieldOIs = new ArrayList<ObjectInspector>();
+
+ fieldNames.add("h");
+ fieldOIs.add(PrimitiveObjectInspectorFactory.writableIntObjectInspector);
+ fieldNames.add("w0");
+ fieldOIs.add(PrimitiveObjectInspectorFactory.writableFloatObjectInspector);
+ fieldNames.add("w1");
+ fieldOIs.add(PrimitiveObjectInspectorFactory.writableFloatObjectInspector);
+ fieldNames.add("w2");
+ fieldOIs.add(PrimitiveObjectInspectorFactory.writableFloatObjectInspector);
+ fieldNames.add("hk");
+ fieldOIs.add(PrimitiveObjectInspectorFactory.writableIntObjectInspector);
+ fieldNames.add("w3");
+ fieldOIs.add(PrimitiveObjectInspectorFactory.writableFloatObjectInspector);
+
+ return ObjectInspectorFactory.getStandardStructObjectInspector(fieldNames, fieldOIs);
+ }
+
+ @Nullable
+ FeatureValue[] parseFeatures(@Nonnull final List<?> features) {
+ final int size = features.size();
+ if (size == 0) {
+ return null;
+ }
+
+ final FeatureValue[] featureVector = new FeatureValue[size];
+ for (int i = 0; i < size; i++) {
+ Object f = features.get(i);
+ if (f == null) {
+ continue;
+ }
+ FeatureValue fv = FeatureValue.parse(f, true);
+ featureVector[i] = fv;
+ }
+ return featureVector;
+ }
+
+ @Override
+ protected void train(@Nonnull final FeatureValue[] features, final int label) {
+ final float y = label > 0 ? 1.f : -1.f;
+
+ PredictionResult margin = calcScoreWithKernelAndNorm(features);
+ float p = margin.getScore();
+ float loss = LossFunctions.hingeLoss(p, y); // 1.0 - y * p
+ this._loss = loss;
+
+ if (loss > 0.f) { // y * p < 1
+ updateKernel(y, loss, margin, features);
+ }
+ }
+
+ @Override
+ float predict(@Nonnull final FeatureValue[] features) {
+ float score = 0.f;
+
+ for (int i = 0; i < features.length; ++i) {
+ if (features[i] == null) {
+ continue;
+ }
+ int h = features[i].getFeatureAsInt();
+ float w1 = _w1.get(h);
+ float w2 = _w2.get(h);
+ double xi = features[i].getValue();
+ double xx = xi * xi;
+ score += w1 * xi;
+ score += w2 * xx;
+ for (int j = i + 1; j < features.length; ++j) {
+ int k = features[j].getFeatureAsInt();
+ int hk = HashFunction.hash(h, k, true);
+ float w3 = _w3.get(hk);
+ double xj = features[j].getValue();
+ score += xi * xj * w3;
+ }
+ }
+
+ return score;
+ }
+
+ @Nonnull
+ final PredictionResult calcScoreWithKernelAndNorm(@Nonnull final FeatureValue[] features) {
+ float score = _w0;
+ float norm = 0.f;
+ for (int i = 0; i < features.length; ++i) {
+ if (features[i] == null) {
+ continue;
+ }
+ int h = features[i].getFeatureAsInt();
+ float w1 = _w1.get(h);
+ float w2 = _w2.get(h);
+ double xi = features[i].getValue();
+ double xx = xi * xi;
+ score += w1 * xi;
+ score += w2 * xx;
+ norm += xx;
+ for (int j = i + 1; j < features.length; ++j) {
+ int k = features[j].getFeatureAsInt();
+ int hk = HashFunction.hash(h, k, true);
+ float w3 = _w3.get(hk);
+ double xj = features[j].getValue();
+ score += xi * xj * w3;
+ }
+ }
+ return new PredictionResult(score).squaredNorm(norm);
+ }
+
+ protected void updateKernel(final float label, final float loss,
+ @Nonnull final PredictionResult margin, @Nonnull final FeatureValue[] features) {
+ float eta = _algo.eta(loss, margin);
+ float coeff = eta * label;
+ expandKernel(features, coeff);
+ }
+
+ private void expandKernel(@Nonnull final FeatureValue[] supportVector, final float alpha) {
+ final float pkc = _pkc;
+ // W0 += \u03b1 c^2
+ this._w0 += alpha * pkc * pkc;
+
+ for (int i = 0; i < supportVector.length; ++i) {
+ final FeatureValue si = supportVector[i];
+ final int h = si.getFeatureAsInt();
+ float Zih = si.getValueAsFloat();
+
+ float alphaZih = alpha * Zih;
+ final float alphaZih2 = alphaZih * 2.f;
+
+ // W1[h] += 2 c \u03b1 Zi[h]
+ _w1.put(h, _w1.get(h) + pkc * alphaZih2);
+ // W2[h] += \u03b1 Zi[h]^2
+ _w2.put(h, _w2.get(h) + alphaZih * Zih);
+
+ for (int j = i + 1; j < supportVector.length; ++j) {
+ FeatureValue sj = supportVector[j];
+ int k = sj.getFeatureAsInt();
+ int hk = HashFunction.hash(h, k, true);
+ float Zjk = sj.getValueAsFloat();
+
+ // W3 += 2 \u03b1 Zi[h] Zi[k]
+ _w3.put(hk, _w3.get(hk) + alphaZih2 * Zjk);
+ }
+ }
+ }
+
+ @Override
+ public void close() throws HiveException {
+ final IntWritable h = new IntWritable(0); // row[0]
+ final FloatWritable w0 = new FloatWritable(_w0); // row[1]
+ final FloatWritable w1 = new FloatWritable(); // row[2]
+ final FloatWritable w2 = new FloatWritable(); // row[3]
+ final IntWritable hk = new IntWritable(0); // row[4]
+ final FloatWritable w3 = new FloatWritable(); // row[5]
+ final Object[] row = new Object[] {h, w0, null, null, null, null};
+ forward(row); // 0(f), w0
+ row[1] = null;
+
+ row[2] = w1;
+ row[3] = w2;
+ final Int2FloatOpenHashTable w2map = _w2;
+ final IMapIterator w1itor = _w1.entries();
+ while (w1itor.next() != -1) {
+ int k = w1itor.getKey();
+ Preconditions.checkArgument(k > 0, HiveException.class);
+ h.set(k);
+ w1.set(w1itor.getValue());
+ w2.set(w2map.get(k));
+ forward(row); // h(f), w1, w2
+ }
+ this._w1 = null;
+ this._w2 = null;
+
+ row[0] = null;
+ row[2] = null;
+ row[3] = null;
+ row[4] = hk;
+ row[5] = w3;
+ final IMapIterator w3itor = _w3.entries();
+ while (w3itor.next() != -1) {
+ int k = w3itor.getKey();
+ Preconditions.checkArgument(k > 0, HiveException.class);
+ hk.set(k);
+ w3.set(w3itor.getValue());
+ forward(row); // hk(f), w3
+ }
+ this._w3 = null;
+ }
+
+}
http://git-wip-us.apache.org/repos/asf/incubator-hivemall/blob/391e7f1c/core/src/main/java/hivemall/ensemble/bagging/VotedAvgUDAF.java
----------------------------------------------------------------------
diff --git a/core/src/main/java/hivemall/ensemble/bagging/VotedAvgUDAF.java b/core/src/main/java/hivemall/ensemble/bagging/VotedAvgUDAF.java
index 8b40142..a9bcab1 100644
--- a/core/src/main/java/hivemall/ensemble/bagging/VotedAvgUDAF.java
+++ b/core/src/main/java/hivemall/ensemble/bagging/VotedAvgUDAF.java
@@ -18,6 +18,8 @@
*/
package hivemall.ensemble.bagging;
+import javax.annotation.Nullable;
+
import org.apache.hadoop.hive.ql.exec.Description;
import org.apache.hadoop.hive.ql.exec.UDAF;
import org.apache.hadoop.hive.ql.exec.UDAFEvaluator;
@@ -53,11 +55,15 @@ public final class VotedAvgUDAF extends UDAF {
this.partial = null;
}
- public boolean iterate(double w) {
+ public boolean iterate(@Nullable DoubleWritable o) {
+ if (o == null) {
+ return true;
+ }
if (partial == null) {
this.partial = new PartialResult();
partial.init();
}
+ double w = o.get();
if (w > 0) {
partial.positiveSum += w;
partial.positiveCnt++;
http://git-wip-us.apache.org/repos/asf/incubator-hivemall/blob/391e7f1c/core/src/main/java/hivemall/ensemble/bagging/WeightVotedAvgUDAF.java
----------------------------------------------------------------------
diff --git a/core/src/main/java/hivemall/ensemble/bagging/WeightVotedAvgUDAF.java b/core/src/main/java/hivemall/ensemble/bagging/WeightVotedAvgUDAF.java
index a7d63be..4e7ea1b 100644
--- a/core/src/main/java/hivemall/ensemble/bagging/WeightVotedAvgUDAF.java
+++ b/core/src/main/java/hivemall/ensemble/bagging/WeightVotedAvgUDAF.java
@@ -18,6 +18,8 @@
*/
package hivemall.ensemble.bagging;
+import javax.annotation.Nullable;
+
import org.apache.hadoop.hive.ql.exec.Description;
import org.apache.hadoop.hive.ql.exec.UDAF;
import org.apache.hadoop.hive.ql.exec.UDAFEvaluator;
@@ -54,11 +56,15 @@ public final class WeightVotedAvgUDAF extends UDAF {
this.partial = null;
}
- public boolean iterate(double w) {
+ public boolean iterate(@Nullable DoubleWritable o) {
+ if (o == null) {
+ return true;
+ }
if (partial == null) {
this.partial = new PartialResult();
partial.init();
}
+ double w = o.get();
if (w > 0) {
partial.positiveSum += w;
partial.positiveCnt++;
http://git-wip-us.apache.org/repos/asf/incubator-hivemall/blob/391e7f1c/core/src/main/java/hivemall/ftvec/pairing/FeaturePairsUDTF.java
----------------------------------------------------------------------
diff --git a/core/src/main/java/hivemall/ftvec/pairing/FeaturePairsUDTF.java b/core/src/main/java/hivemall/ftvec/pairing/FeaturePairsUDTF.java
new file mode 100644
index 0000000..6aebd64
--- /dev/null
+++ b/core/src/main/java/hivemall/ftvec/pairing/FeaturePairsUDTF.java
@@ -0,0 +1,232 @@
+/*
+ * 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 hivemall.ftvec.pairing;
+
+import hivemall.UDTFWithOptions;
+import hivemall.model.FeatureValue;
+import hivemall.utils.hadoop.HiveUtils;
+import hivemall.utils.hashing.HashFunction;
+import hivemall.utils.lang.Preconditions;
+
+import java.util.ArrayList;
+import java.util.List;
+
+import javax.annotation.Nonnull;
+
+import org.apache.commons.cli.CommandLine;
+import org.apache.commons.cli.Options;
+import org.apache.hadoop.hive.ql.exec.Description;
+import org.apache.hadoop.hive.ql.exec.UDFArgumentException;
+import org.apache.hadoop.hive.ql.metadata.HiveException;
+import org.apache.hadoop.hive.serde2.io.DoubleWritable;
+import org.apache.hadoop.hive.serde2.objectinspector.ListObjectInspector;
+import org.apache.hadoop.hive.serde2.objectinspector.ObjectInspector;
+import org.apache.hadoop.hive.serde2.objectinspector.ObjectInspectorFactory;
+import org.apache.hadoop.hive.serde2.objectinspector.StructObjectInspector;
+import org.apache.hadoop.hive.serde2.objectinspector.primitive.PrimitiveObjectInspectorFactory;
+import org.apache.hadoop.io.IntWritable;
+import org.apache.hadoop.io.Writable;
+
+@Description(name = "feature_pairs",
+ value = "_FUNC_(feature_vector in array<string>, [, const string options])"
+ + " - Returns a relation <string i, string j, double xi, double xj>")
+public final class FeaturePairsUDTF extends UDTFWithOptions {
+
+ private Type _type;
+ private RowProcessor _proc;
+
+ public FeaturePairsUDTF() {}
+
+ @Override
+ protected Options getOptions() {
+ Options opts = new Options();
+ opts.addOption("kpa", false,
+ "Generate feature pairs for Kernel-Expansion Passive Aggressive [default:true]");
+ opts.addOption("ffm", false,
+ "Generate feature pairs for Field-aware Factorization Machines [default:false]");
+ return opts;
+ }
+
+ @Override
+ protected CommandLine processOptions(ObjectInspector[] argOIs) throws UDFArgumentException {
+ CommandLine cl = null;
+ if (argOIs.length == 2) {
+ String args = HiveUtils.getConstString(argOIs[1]);
+ cl = parseOptions(args);
+
+ Preconditions.checkArgument(cl.getOptions().length == 1, UDFArgumentException.class,
+ "Only one option can be specified: " + cl.getArgList());
+
+ if (cl.hasOption("kpa")) {
+ this._type = Type.kpa;
+ } else if (cl.hasOption("ffm")) {
+ this._type = Type.ffm;
+ } else {
+ throw new UDFArgumentException("Unsupported option: " + cl.getArgList().get(0));
+ }
+ } else {
+ throw new UDFArgumentException("MUST provide -kpa or -ffm in the option");
+ }
+
+ return cl;
+ }
+
+ @Override
+ public StructObjectInspector initialize(ObjectInspector[] argOIs) throws UDFArgumentException {
+ if (argOIs.length != 1 && argOIs.length != 2) {
+ throw new UDFArgumentException("_FUNC_ takes 1 or 2 arguments");
+ }
+ processOptions(argOIs);
+
+ ListObjectInspector fvOI = HiveUtils.asListOI(argOIs[0]);
+ HiveUtils.validateFeatureOI(fvOI.getListElementObjectInspector());
+
+ final List<String> fieldNames = new ArrayList<String>(4);
+ final List<ObjectInspector> fieldOIs = new ArrayList<ObjectInspector>(4);
+ switch (_type) {
+ case kpa: {
+ this._proc = new KPAProcessor(fvOI);
+ fieldNames.add("h");
+ fieldOIs.add(PrimitiveObjectInspectorFactory.writableIntObjectInspector);
+ fieldNames.add("hk");
+ fieldOIs.add(PrimitiveObjectInspectorFactory.writableIntObjectInspector);
+ fieldNames.add("xh");
+ fieldOIs.add(PrimitiveObjectInspectorFactory.writableDoubleObjectInspector);
+ fieldNames.add("xk");
+ fieldOIs.add(PrimitiveObjectInspectorFactory.writableDoubleObjectInspector);
+ break;
+ }
+ case ffm: {
+ throw new UDFArgumentException("-ffm is not supported yet");
+ //break;
+ }
+ default:
+ throw new UDFArgumentException("Illegal condition: " + _type);
+ }
+ return ObjectInspectorFactory.getStandardStructObjectInspector(fieldNames, fieldOIs);
+ }
+
+ @Override
+ public void process(Object[] args) throws HiveException {
+ Object arg0 = args[0];
+ if (arg0 == null) {
+ return;
+ }
+ _proc.process(arg0);
+ }
+
+ public enum Type {
+ kpa, ffm;
+ }
+
+ abstract class RowProcessor {
+
+ @Nonnull
+ protected final ListObjectInspector fvOI;
+
+ RowProcessor(@Nonnull ListObjectInspector fvOI) {
+ this.fvOI = fvOI;
+ }
+
+ void process(@Nonnull Object arg) throws HiveException {
+ final int size = fvOI.getListLength(arg);
+ if (size == 0) {
+ return;
+ }
+
+ final List<FeatureValue> features = new ArrayList<FeatureValue>(size);
+ for (int i = 0; i < size; i++) {
+ Object f = fvOI.getListElement(arg, i);
+ if (f == null) {
+ continue;
+ }
+ FeatureValue fv = FeatureValue.parse(f, true);
+ features.add(fv);
+ }
+
+ process(features);
+ }
+
+ abstract void process(@Nonnull List<FeatureValue> features) throws HiveException;
+
+ }
+
+ final class KPAProcessor extends RowProcessor {
+
+ @Nonnull
+ private final IntWritable f0, f1;
+ @Nonnull
+ private final DoubleWritable f2, f3;
+ @Nonnull
+ private final Writable[] forward;
+
+ KPAProcessor(@Nonnull ListObjectInspector fvOI) {
+ super(fvOI);
+ this.f0 = new IntWritable();
+ this.f1 = new IntWritable();
+ this.f2 = new DoubleWritable();
+ this.f3 = new DoubleWritable();
+ this.forward = new Writable[] {f0, null, null, null};
+ }
+
+ @Override
+ void process(@Nonnull List<FeatureValue> features) throws HiveException {
+ forward[0] = f0;
+ f0.set(0);
+ forward[1] = null;
+ forward[2] = null;
+ forward[3] = null;
+ forward(forward); // forward h(f0)
+
+ forward[2] = f2;
+ for (int i = 0, len = features.size(); i < len; i++) {
+ FeatureValue xi = features.get(i);
+ int h = xi.getFeatureAsInt();
+ double xh = xi.getValue();
+ forward[0] = f0;
+ f0.set(h);
+ forward[1] = null;
+ f2.set(xh);
+ forward[3] = null;
+ forward(forward); // forward h(f0), xh(f2)
+
+ forward[0] = null;
+ forward[1] = f1;
+ forward[3] = f3;
+ for (int j = i + 1; j < len; j++) {
+ FeatureValue xj = features.get(j);
+ int k = xj.getFeatureAsInt();
+ int hk = HashFunction.hash(h, k, true);
+ double xk = xj.getValue();
+ f1.set(hk);
+ f3.set(xk);
+ forward(forward);// forward hk(f1), xh(f2), xk(f3)
+ }
+ }
+ }
+ }
+
+
+ @Override
+ public void close() throws HiveException {
+ // clean up to help GC
+ this._proc = null;
+ }
+
+}
http://git-wip-us.apache.org/repos/asf/incubator-hivemall/blob/391e7f1c/core/src/main/java/hivemall/model/FeatureValue.java
----------------------------------------------------------------------
diff --git a/core/src/main/java/hivemall/model/FeatureValue.java b/core/src/main/java/hivemall/model/FeatureValue.java
index 8f2b728..7ff3383 100644
--- a/core/src/main/java/hivemall/model/FeatureValue.java
+++ b/core/src/main/java/hivemall/model/FeatureValue.java
@@ -18,6 +18,9 @@
*/
package hivemall.model;
+import hivemall.utils.hashing.MurmurHash3;
+import hivemall.utils.lang.Preconditions;
+
import javax.annotation.Nonnull;
import javax.annotation.Nullable;
@@ -44,6 +47,12 @@ public final class FeatureValue {
public <T> T getFeature() {
return (T) feature;
}
+
+ public int getFeatureAsInt() {
+ Preconditions.checkNotNull(feature);
+ Preconditions.checkArgument(feature instanceof Integer);
+ return ((Integer) feature).intValue();
+ }
public double getValue() {
return value;
@@ -63,30 +72,42 @@ public final class FeatureValue {
@Nullable
public static FeatureValue parse(final Object o) throws IllegalArgumentException {
+ return parse(o, false);
+ }
+
+ @Nullable
+ public static FeatureValue parse(final Object o, final boolean mhash)
+ throws IllegalArgumentException {
if (o == null) {
return null;
}
String s = o.toString();
- return parse(s);
+ return parse(s, mhash);
}
@Nullable
public static FeatureValue parse(@Nonnull final String s) throws IllegalArgumentException {
+ return parse(s, false);
+ }
+
+ @Nullable
+ public static FeatureValue parse(@Nonnull final String s, final boolean mhash)
+ throws IllegalArgumentException {
assert (s != null);
final int pos = s.indexOf(':');
if (pos == 0) {
throw new IllegalArgumentException("Invalid feature value representation: " + s);
}
- final Text feature;
+ final Object feature;
final double weight;
if (pos > 0) {
String s1 = s.substring(0, pos);
String s2 = s.substring(pos + 1);
- feature = new Text(s1);
+ feature = mhash ? Integer.valueOf(MurmurHash3.murmurhash3(s1)) : new Text(s1);
weight = Double.parseDouble(s2);
} else {
- feature = new Text(s);
+ feature = mhash ? Integer.valueOf(MurmurHash3.murmurhash3(s)) : new Text(s);
weight = 1.d;
}
return new FeatureValue(feature, weight);
http://git-wip-us.apache.org/repos/asf/incubator-hivemall/blob/391e7f1c/core/src/main/java/hivemall/utils/collections/FloatArrayList.java
----------------------------------------------------------------------
diff --git a/core/src/main/java/hivemall/utils/collections/FloatArrayList.java b/core/src/main/java/hivemall/utils/collections/FloatArrayList.java
new file mode 100644
index 0000000..cfdf504
--- /dev/null
+++ b/core/src/main/java/hivemall/utils/collections/FloatArrayList.java
@@ -0,0 +1,152 @@
+/*
+ * 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 hivemall.utils.collections;
+
+import java.io.Serializable;
+
+public final class FloatArrayList implements Serializable {
+ private static final long serialVersionUID = 8764828070342317585L;
+
+ public static final int DEFAULT_CAPACITY = 12;
+
+ /** array entity */
+ private float[] data;
+ private int used;
+
+ public FloatArrayList() {
+ this(DEFAULT_CAPACITY);
+ }
+
+ public FloatArrayList(int size) {
+ this.data = new float[size];
+ this.used = 0;
+ }
+
+ public FloatArrayList(float[] initValues) {
+ this.data = initValues;
+ this.used = initValues.length;
+ }
+
+ public void add(float value) {
+ if (used >= data.length) {
+ expand(used + 1);
+ }
+ data[used++] = value;
+ }
+
+ public void add(float[] values) {
+ final int needs = used + values.length;
+ if (needs >= data.length) {
+ expand(needs);
+ }
+ System.arraycopy(values, 0, data, used, values.length);
+ this.used = needs;
+ }
+
+ /**
+ * dynamic expansion.
+ */
+ private void expand(int max) {
+ while (data.length < max) {
+ final int len = data.length;
+ float[] newArray = new float[len * 2];
+ System.arraycopy(data, 0, newArray, 0, len);
+ this.data = newArray;
+ }
+ }
+
+ public float remove() {
+ return data[--used];
+ }
+
+ public float remove(int index) {
+ final float ret;
+ if (index > used) {
+ throw new IndexOutOfBoundsException();
+ } else if (index == used) {
+ ret = data[--used];
+ } else { // index < used
+ // removed value
+ ret = data[index];
+ final float[] newarray = new float[--used];
+ // prefix
+ System.arraycopy(data, 0, newarray, 0, index - 1);
+ // appendix
+ System.arraycopy(data, index + 1, newarray, index, used - index);
+ // set fields.
+ this.data = newarray;
+ }
+ return ret;
+ }
+
+ public void set(int index, float value) {
+ if (index > used) {
+ throw new IllegalArgumentException("Index MUST be less than \"size()\".");
+ } else if (index == used) {
+ ++used;
+ }
+ data[index] = value;
+ }
+
+ public float get(int index) {
+ if (index >= used)
+ throw new IndexOutOfBoundsException();
+ return data[index];
+ }
+
+ public float fastGet(int index) {
+ return data[index];
+ }
+
+ public int size() {
+ return used;
+ }
+
+ public boolean isEmpty() {
+ return used == 0;
+ }
+
+ public void clear() {
+ this.used = 0;
+ }
+
+ public float[] toArray() {
+ final float[] newArray = new float[used];
+ System.arraycopy(data, 0, newArray, 0, used);
+ return newArray;
+ }
+
+ public float[] array() {
+ return data;
+ }
+
+ @Override
+ public String toString() {
+ final StringBuilder buf = new StringBuilder();
+ buf.append('[');
+ for (int i = 0; i < used; i++) {
+ if (i != 0) {
+ buf.append(", ");
+ }
+ buf.append(data[i]);
+ }
+ buf.append(']');
+ return buf.toString();
+ }
+}
http://git-wip-us.apache.org/repos/asf/incubator-hivemall/blob/391e7f1c/core/src/main/java/hivemall/utils/collections/Int2FloatOpenHashTable.java
----------------------------------------------------------------------
diff --git a/core/src/main/java/hivemall/utils/collections/Int2FloatOpenHashTable.java b/core/src/main/java/hivemall/utils/collections/Int2FloatOpenHashTable.java
index 49f27c8..a06cdb0 100644
--- a/core/src/main/java/hivemall/utils/collections/Int2FloatOpenHashTable.java
+++ b/core/src/main/java/hivemall/utils/collections/Int2FloatOpenHashTable.java
@@ -73,6 +73,9 @@ public class Int2FloatOpenHashTable implements Externalizable {
this(size, DEFAULT_LOAD_FACTOR, DEFAULT_GROW_FACTOR, true);
}
+ /**
+ * Only for {@link Externalizable}
+ */
public Int2FloatOpenHashTable() {// required for serialization
this._loadFactor = DEFAULT_LOAD_FACTOR;
this._growFactor = DEFAULT_GROW_FACTOR;
http://git-wip-us.apache.org/repos/asf/incubator-hivemall/blob/391e7f1c/core/src/main/java/hivemall/utils/hadoop/HiveUtils.java
----------------------------------------------------------------------
diff --git a/core/src/main/java/hivemall/utils/hadoop/HiveUtils.java b/core/src/main/java/hivemall/utils/hadoop/HiveUtils.java
index 8188b7a..5423c9d 100644
--- a/core/src/main/java/hivemall/utils/hadoop/HiveUtils.java
+++ b/core/src/main/java/hivemall/utils/hadoop/HiveUtils.java
@@ -308,6 +308,18 @@ public final class HiveUtils {
}
}
+ public static boolean isStringTypeInfo(@Nonnull TypeInfo typeInfo) {
+ if (typeInfo.getCategory() != ObjectInspector.Category.PRIMITIVE) {
+ return false;
+ }
+ switch (((PrimitiveTypeInfo) typeInfo).getPrimitiveCategory()) {
+ case STRING:
+ return true;
+ default:
+ return false;
+ }
+ }
+
public static boolean isConstString(@Nonnull final ObjectInspector oi) {
return ObjectInspectorUtils.isConstantObjectInspector(oi) && isStringOI(oi);
}
@@ -321,6 +333,20 @@ public final class HiveUtils {
return (ListTypeInfo) typeInfo;
}
+ public static float getFloat(@Nullable Object o, @Nonnull PrimitiveObjectInspector oi) {
+ if (o == null) {
+ return 0.f;
+ }
+ return PrimitiveObjectInspectorUtils.getFloat(o, oi);
+ }
+
+ public static double getDouble(@Nullable Object o, @Nonnull PrimitiveObjectInspector oi) {
+ if (o == null) {
+ return 0.d;
+ }
+ return PrimitiveObjectInspectorUtils.getDouble(o, oi);
+ }
+
@SuppressWarnings("unchecked")
@Nullable
public static <T extends Writable> T getConstValue(@Nonnull final ObjectInspector oi)
@@ -776,6 +802,7 @@ public final class HiveUtils {
return oi;
}
+ @Nonnull
public static PrimitiveObjectInspector asDoubleCompatibleOI(@Nonnull final ObjectInspector argOI)
throws UDFArgumentTypeException {
if (argOI.getCategory() != Category.PRIMITIVE) {
@@ -802,6 +829,30 @@ public final class HiveUtils {
}
@Nonnull
+ public static PrimitiveObjectInspector asNumberOI(@Nonnull final ObjectInspector argOI)
+ throws UDFArgumentTypeException {
+ if (argOI.getCategory() != Category.PRIMITIVE) {
+ throw new UDFArgumentTypeException(0, "Only primitive type arguments are accepted but "
+ + argOI.getTypeName() + " is passed.");
+ }
+ final PrimitiveObjectInspector oi = (PrimitiveObjectInspector) argOI;
+ switch (oi.getPrimitiveCategory()) {
+ case BYTE:
+ case SHORT:
+ case INT:
+ case LONG:
+ case FLOAT:
+ case DOUBLE:
+ break;
+ default:
+ throw new UDFArgumentTypeException(0,
+ "Only numeric or string type arguments are accepted but " + argOI.getTypeName()
+ + " is passed.");
+ }
+ return oi;
+ }
+
+ @Nonnull
public static ListObjectInspector asListOI(@Nonnull final ObjectInspector oi)
throws UDFArgumentException {
Category category = oi.getCategory();
http://git-wip-us.apache.org/repos/asf/incubator-hivemall/blob/391e7f1c/core/src/main/java/hivemall/utils/hashing/HashFunction.java
----------------------------------------------------------------------
diff --git a/core/src/main/java/hivemall/utils/hashing/HashFunction.java b/core/src/main/java/hivemall/utils/hashing/HashFunction.java
index eb44915..bd1b841 100644
--- a/core/src/main/java/hivemall/utils/hashing/HashFunction.java
+++ b/core/src/main/java/hivemall/utils/hashing/HashFunction.java
@@ -18,6 +18,8 @@
*/
package hivemall.utils.hashing;
+import hivemall.utils.math.MathUtils;
+
public abstract class HashFunction {
public int hash(Object data) {
@@ -25,6 +27,18 @@ public abstract class HashFunction {
return hash(s);
}
+ public static int hash(final int first, final int second, final boolean positive) {
+ final int h = first * 157 + second;
+ if (positive) {
+ int r = MathUtils.moduloPowerOfTwo(h, MurmurHash3.DEFAULT_NUM_FEATURES);
+ if (r < 0) {
+ r += MurmurHash3.DEFAULT_NUM_FEATURES;
+ }
+ return r;
+ }
+ return h;
+ }
+
public abstract int hash(String data);
}
http://git-wip-us.apache.org/repos/asf/incubator-hivemall/blob/391e7f1c/core/src/main/java/hivemall/utils/lang/Preconditions.java
----------------------------------------------------------------------
diff --git a/core/src/main/java/hivemall/utils/lang/Preconditions.java b/core/src/main/java/hivemall/utils/lang/Preconditions.java
index af63127..eabbc0a 100644
--- a/core/src/main/java/hivemall/utils/lang/Preconditions.java
+++ b/core/src/main/java/hivemall/utils/lang/Preconditions.java
@@ -98,19 +98,21 @@ public final class Preconditions {
}
public static <E extends Throwable> void checkArgument(boolean expression,
- @Nonnull String errorMessage, @Nonnull Class<E> clazz) throws E {
+ @Nonnull Class<E> clazz, @Nullable Object errorMessage) throws E {
if (!expression) {
+ Constructor<E> constructor;
+ try {
+ constructor = clazz.getConstructor(String.class);
+ } catch (NoSuchMethodException | SecurityException e) {
+ throw new IllegalStateException(
+ "Failed to get a constructor of " + clazz.getName(), e);
+ }
final E throwable;
try {
- Constructor<E> constructor = clazz.getConstructor(String.class);
throwable = constructor.newInstance(errorMessage);
- } catch (NoSuchMethodException | SecurityException e1) {
- throw new IllegalStateException("Failed to get a Constructor(String): "
- + clazz.getName(), e1);
- } catch (InstantiationException | IllegalAccessException | IllegalArgumentException
- | InvocationTargetException e2) {
+ } catch (ReflectiveOperationException | IllegalArgumentException e) {
throw new IllegalStateException(
- "Failed to instantiate a class: " + clazz.getName(), e2);
+ "Failed to instantiate a class: " + clazz.getName(), e);
}
throw throwable;
}
http://git-wip-us.apache.org/repos/asf/incubator-hivemall/blob/391e7f1c/core/src/main/java/hivemall/utils/math/MathUtils.java
----------------------------------------------------------------------
diff --git a/core/src/main/java/hivemall/utils/math/MathUtils.java b/core/src/main/java/hivemall/utils/math/MathUtils.java
index ae9f029..252ccf6 100644
--- a/core/src/main/java/hivemall/utils/math/MathUtils.java
+++ b/core/src/main/java/hivemall/utils/math/MathUtils.java
@@ -89,8 +89,7 @@ public final class MathUtils {
}
/**
- * <a href="https://en.wikipedia.org/wiki/Logit">Logit</a> is the inverse of
- * {@link #sigmoid(double)} function.
+ * <a href="https://en.wikipedia.org/wiki/Logit">Logit</a> is the inverse of {@link #sigmoid(double)} function.
*/
public static double logit(final double p) {
return Math.log(p / (1.d - p));
@@ -101,14 +100,11 @@ public final class MathUtils {
}
/**
- * Returns the inverse erf. This code is based on erfInv() in
- * org.apache.commons.math3.special.Erf.
+ * Returns the inverse erf. This code is based on erfInv() in org.apache.commons.math3.special.Erf.
* <p>
- * This implementation is described in the paper: <a
- * href="http://people.maths.ox.ac.uk/gilesm/files/gems_erfinv.pdf">Approximating the erfinv
- * function</a> by Mike Giles, Oxford-Man Institute of Quantitative Finance, which was published
- * in GPU Computing Gems, volume 2, 2010. The source code is available <a
- * href="http://gpucomputing.net/?q=node/1828">here</a>.
+ * This implementation is described in the paper: <a href="http://people.maths.ox.ac.uk/gilesm/files/gems_erfinv.pdf">Approximating the erfinv
+ * function</a> by Mike Giles, Oxford-Man Institute of Quantitative Finance, which was published in GPU Computing Gems, volume 2, 2010. The source
+ * code is available <a href="http://gpucomputing.net/?q=node/1828">here</a>.
* </p>
*
* @param x the value
@@ -227,8 +223,8 @@ public final class MathUtils {
return v < 0 ? -1 : 1;
}
- public static float sign(final float v) {
- return v < 0.f ? -1.f : 1.f;
+ public static int sign(final float v) {
+ return v < 0.f ? -1 : 1;
}
public static double log(final double n, final int base) {
http://git-wip-us.apache.org/repos/asf/incubator-hivemall/blob/391e7f1c/core/src/test/java/hivemall/anomaly/ChangeFinder1DTest.java
----------------------------------------------------------------------
diff --git a/core/src/test/java/hivemall/anomaly/ChangeFinder1DTest.java b/core/src/test/java/hivemall/anomaly/ChangeFinder1DTest.java
index d7bac75..1470ffb 100644
--- a/core/src/test/java/hivemall/anomaly/ChangeFinder1DTest.java
+++ b/core/src/test/java/hivemall/anomaly/ChangeFinder1DTest.java
@@ -46,7 +46,7 @@ public class ChangeFinder1DTest {
ChangeFinder1D cf = new ChangeFinder1D(params, oi);
double[] outScores = new double[2];
- BufferedReader reader = readFile("cf1d.csv");
+ BufferedReader reader = readFile("cf1d.csv.gz");
println("x outlier change");
String line;
int numOutliers = 0, numChangepoints = 0;
http://git-wip-us.apache.org/repos/asf/incubator-hivemall/blob/391e7f1c/core/src/test/java/hivemall/anomaly/ChangeFinder2DTest.java
----------------------------------------------------------------------
diff --git a/core/src/test/java/hivemall/anomaly/ChangeFinder2DTest.java b/core/src/test/java/hivemall/anomaly/ChangeFinder2DTest.java
index 240906c..43a0921 100644
--- a/core/src/test/java/hivemall/anomaly/ChangeFinder2DTest.java
+++ b/core/src/test/java/hivemall/anomaly/ChangeFinder2DTest.java
@@ -60,7 +60,7 @@ public class ChangeFinder2DTest {
double[] outScores = new double[2];
List<Double> x = new ArrayList<Double>(1);
- BufferedReader reader = readFile("cf1d.csv");
+ BufferedReader reader = readFile("cf1d.csv.gz");
println("x outlier change");
String line;
int i = 1, numOutliers = 0, numChangepoints = 0;
http://git-wip-us.apache.org/repos/asf/incubator-hivemall/blob/391e7f1c/core/src/test/java/hivemall/classifier/KernelExpansionPassiveAggressiveUDTFTest.java
----------------------------------------------------------------------
diff --git a/core/src/test/java/hivemall/classifier/KernelExpansionPassiveAggressiveUDTFTest.java b/core/src/test/java/hivemall/classifier/KernelExpansionPassiveAggressiveUDTFTest.java
new file mode 100644
index 0000000..a5c98e1
--- /dev/null
+++ b/core/src/test/java/hivemall/classifier/KernelExpansionPassiveAggressiveUDTFTest.java
@@ -0,0 +1,158 @@
+/*
+ * 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 hivemall.classifier;
+
+import hivemall.model.FeatureValue;
+import hivemall.utils.math.MathUtils;
+
+import java.io.BufferedReader;
+import java.io.IOException;
+import java.io.InputStream;
+import java.io.InputStreamReader;
+import java.text.ParseException;
+import java.util.ArrayList;
+import java.util.StringTokenizer;
+import java.util.zip.GZIPInputStream;
+
+import javax.annotation.Nonnull;
+
+import org.apache.hadoop.hive.ql.metadata.HiveException;
+import org.apache.hadoop.hive.serde2.objectinspector.ListObjectInspector;
+import org.apache.hadoop.hive.serde2.objectinspector.ObjectInspector;
+import org.apache.hadoop.hive.serde2.objectinspector.ObjectInspectorFactory;
+import org.apache.hadoop.hive.serde2.objectinspector.ObjectInspectorUtils;
+import org.apache.hadoop.hive.serde2.objectinspector.primitive.PrimitiveObjectInspectorFactory;
+import org.junit.Assert;
+import org.junit.Test;
+
+public class KernelExpansionPassiveAggressiveUDTFTest {
+
+ @Test
+ public void testNews20() throws IOException, ParseException, HiveException {
+ KernelExpansionPassiveAggressiveUDTF udtf = new KernelExpansionPassiveAggressiveUDTF();
+ ObjectInspector intOI = PrimitiveObjectInspectorFactory.javaIntObjectInspector;
+ ObjectInspector stringOI = PrimitiveObjectInspectorFactory.javaStringObjectInspector;
+ ListObjectInspector stringListOI = ObjectInspectorFactory.getStandardListObjectInspector(stringOI);
+ udtf.initialize(new ObjectInspector[] {stringListOI, intOI});
+
+ BufferedReader news20 = readFile("news20-small.binary.gz");
+ ArrayList<String> words = new ArrayList<String>();
+ String line = news20.readLine();
+ while (line != null) {
+ StringTokenizer tokens = new StringTokenizer(line, " ");
+ int label = Integer.parseInt(tokens.nextToken());
+ while (tokens.hasMoreTokens()) {
+ words.add(tokens.nextToken());
+ }
+ Assert.assertFalse(words.isEmpty());
+ udtf.process(new Object[] {words, label});
+
+ words.clear();
+ line = news20.readLine();
+ }
+
+ Assert.assertTrue(Math.abs(udtf.getLoss()) < 0.1f);
+
+ news20.close();
+ }
+
+ public void test_a9a() throws IOException, ParseException, HiveException {
+ KernelExpansionPassiveAggressiveUDTF udtf = new KernelExpansionPassiveAggressiveUDTF();
+ ObjectInspector intOI = PrimitiveObjectInspectorFactory.javaIntObjectInspector;
+ ObjectInspector stringOI = PrimitiveObjectInspectorFactory.javaStringObjectInspector;
+ ListObjectInspector stringListOI = ObjectInspectorFactory.getStandardListObjectInspector(stringOI);
+ ObjectInspector params = ObjectInspectorUtils.getConstantObjectInspector(
+ PrimitiveObjectInspectorFactory.javaStringObjectInspector, "-c 0.01");
+
+ udtf.initialize(new ObjectInspector[] {stringListOI, intOI, params});
+
+ final ArrayList<String> words = new ArrayList<String>();
+ BufferedReader trainData = readFile("a9a.gz");
+ String line = trainData.readLine();
+ while (line != null) {
+ StringTokenizer tokens = new StringTokenizer(line, " ");
+ String labelStr = tokens.nextToken();
+ final int label;
+ if ("+1".equals(labelStr)) {
+ label = 1;
+ } else if ("-1".equals(labelStr)) {
+ label = -1;
+ } else {
+ throw new IllegalStateException("Illegal label: " + labelStr);
+ }
+ while (tokens.hasMoreTokens()) {
+ words.add(tokens.nextToken());
+ }
+ Assert.assertFalse(words.isEmpty());
+ udtf.process(new Object[] {words, label});
+
+ words.clear();
+ line = trainData.readLine();
+ }
+ trainData.close();
+
+ int numTests = 0;
+ int numCorrect = 0;
+
+ BufferedReader testData = readFile("a9a.t.gz");
+ line = testData.readLine();
+ while (line != null) {
+ StringTokenizer tokens = new StringTokenizer(line, " ");
+ String labelStr = tokens.nextToken();
+ final int actual;
+ if ("+1".equals(labelStr)) {
+ actual = 1;
+ } else if ("-1".equals(labelStr)) {
+ actual = -1;
+ } else {
+ throw new IllegalStateException("Illegal label: " + labelStr);
+ }
+ while (tokens.hasMoreTokens()) {
+ words.add(tokens.nextToken());
+ }
+ Assert.assertFalse(words.isEmpty());
+
+ FeatureValue[] features = udtf.parseFeatures(words);
+ float score = udtf.predict(features);
+ int predicted = MathUtils.sign(score);
+
+ if (predicted == actual) {
+ ++numCorrect;
+ }
+ ++numTests;
+
+ words.clear();
+ line = testData.readLine();
+ }
+ testData.close();
+
+ float accuracy = numCorrect / (float) numTests;
+ Assert.assertTrue(accuracy > 0.82f);
+ }
+
+ @Nonnull
+ private static BufferedReader readFile(@Nonnull String fileName) throws IOException {
+ InputStream is = KernelExpansionPassiveAggressiveUDTFTest.class.getResourceAsStream(fileName);
+ if (fileName.endsWith(".gz")) {
+ is = new GZIPInputStream(is);
+ }
+ return new BufferedReader(new InputStreamReader(is));
+ }
+
+}
http://git-wip-us.apache.org/repos/asf/incubator-hivemall/blob/391e7f1c/core/src/test/java/hivemall/fm/FactorizationMachineUDTFTest.java
----------------------------------------------------------------------
diff --git a/core/src/test/java/hivemall/fm/FactorizationMachineUDTFTest.java b/core/src/test/java/hivemall/fm/FactorizationMachineUDTFTest.java
index eacfa8d..6d053de 100644
--- a/core/src/test/java/hivemall/fm/FactorizationMachineUDTFTest.java
+++ b/core/src/test/java/hivemall/fm/FactorizationMachineUDTFTest.java
@@ -20,10 +20,14 @@ package hivemall.fm;
import java.io.BufferedReader;
import java.io.IOException;
+import java.io.InputStream;
import java.io.InputStreamReader;
import java.util.ArrayList;
import java.util.List;
import java.util.StringTokenizer;
+import java.util.zip.GZIPInputStream;
+
+import javax.annotation.Nonnull;
import org.apache.hadoop.hive.ql.metadata.HiveException;
import org.apache.hadoop.hive.serde2.objectinspector.ObjectInspector;
@@ -56,8 +60,7 @@ public class FactorizationMachineUDTFTest {
double loss = 0.d;
double cumul = 0.d;
for (int trainingIteration = 1; trainingIteration <= ITERATIONS; ++trainingIteration) {
- BufferedReader data = new BufferedReader(new InputStreamReader(
- getClass().getResourceAsStream("5107786.txt")));
+ BufferedReader data = readFile("5107786.txt.gz");
loss = udtf._cvState.getCumulativeLoss();
int trExamples = 0;
String line = data.readLine();
@@ -78,8 +81,17 @@ public class FactorizationMachineUDTFTest {
println(trainingIteration + " " + loss + " " + cumul / (trainingIteration * trExamples));
data.close();
}
+
Assert.assertTrue("Loss was greater than 0.1: " + loss, loss <= 0.1);
+ }
+ @Nonnull
+ private static BufferedReader readFile(@Nonnull String fileName) throws IOException {
+ InputStream is = FactorizationMachineUDTFTest.class.getResourceAsStream(fileName);
+ if (fileName.endsWith(".gz")) {
+ is = new GZIPInputStream(is);
+ }
+ return new BufferedReader(new InputStreamReader(is));
}
private static void println(String line) {
http://git-wip-us.apache.org/repos/asf/incubator-hivemall/blob/391e7f1c/core/src/test/java/hivemall/fm/FieldAwareFactorizationMachineUDTFTest.java
----------------------------------------------------------------------
diff --git a/core/src/test/java/hivemall/fm/FieldAwareFactorizationMachineUDTFTest.java b/core/src/test/java/hivemall/fm/FieldAwareFactorizationMachineUDTFTest.java
index f4d4f80..792ede1 100644
--- a/core/src/test/java/hivemall/fm/FieldAwareFactorizationMachineUDTFTest.java
+++ b/core/src/test/java/hivemall/fm/FieldAwareFactorizationMachineUDTFTest.java
@@ -20,8 +20,12 @@ package hivemall.fm;
import java.io.BufferedReader;
import java.io.IOException;
+import java.io.InputStream;
import java.io.InputStreamReader;
import java.util.ArrayList;
+import java.util.zip.GZIPInputStream;
+
+import javax.annotation.Nonnull;
import org.apache.commons.lang.StringUtils;
import org.apache.hadoop.hive.ql.metadata.HiveException;
@@ -87,8 +91,7 @@ public class FieldAwareFactorizationMachineUDTFTest {
double loss = 0.d;
double cumul = 0.d;
for (int trainingIteration = 1; trainingIteration <= ITERATIONS; ++trainingIteration) {
- BufferedReader data = new BufferedReader(new InputStreamReader(
- FieldAwareFactorizationMachineUDTFTest.class.getResourceAsStream("bigdata.tr.txt")));
+ BufferedReader data = readFile("bigdata.tr.txt.gz");
loss = udtf._cvState.getCumulativeLoss();
int lines = 0;
for (int lineNumber = 0; lineNumber < MAX_LINES; ++lineNumber, ++lines) {
@@ -131,6 +134,15 @@ public class FieldAwareFactorizationMachineUDTFTest {
Assert.assertTrue("Last loss was greater than expected: " + loss, loss < lossThreshold);
}
+ @Nonnull
+ private static BufferedReader readFile(@Nonnull String fileName) throws IOException {
+ InputStream is = FieldAwareFactorizationMachineUDTFTest.class.getResourceAsStream(fileName);
+ if (fileName.endsWith(".gz")) {
+ is = new GZIPInputStream(is);
+ }
+ return new BufferedReader(new InputStreamReader(is));
+ }
+
private static String[] toStringArray(ArrayList<StringFeature> x) {
final int size = x.size();
final String[] ret = new String[size];
http://git-wip-us.apache.org/repos/asf/incubator-hivemall/blob/391e7f1c/core/src/test/java/hivemall/mf/BPRMatrixFactorizationUDTFTest.java
----------------------------------------------------------------------
diff --git a/core/src/test/java/hivemall/mf/BPRMatrixFactorizationUDTFTest.java b/core/src/test/java/hivemall/mf/BPRMatrixFactorizationUDTFTest.java
index e28d318..41f1f97 100644
--- a/core/src/test/java/hivemall/mf/BPRMatrixFactorizationUDTFTest.java
+++ b/core/src/test/java/hivemall/mf/BPRMatrixFactorizationUDTFTest.java
@@ -18,11 +18,13 @@
*/
package hivemall.mf;
-import hivemall.utils.io.IOUtils;
import hivemall.utils.lang.StringUtils;
import java.io.BufferedReader;
import java.io.IOException;
+import java.io.InputStream;
+import java.io.InputStreamReader;
+import java.util.zip.GZIPInputStream;
import javax.annotation.Nonnull;
@@ -63,7 +65,7 @@ public class BPRMatrixFactorizationUDTFTest {
final IntWritable negItem = new IntWritable();
final Object[] args = new Object[] {user, posItem, negItem};
- BufferedReader train = IOUtils.bufferedReader(getClass().getResourceAsStream("ml1k.train"));
+ BufferedReader train = readFile("ml1k.train.gz");
String line;
while ((line = train.readLine()) != null) {
parseLine(line, user, posItem, negItem);
@@ -98,7 +100,7 @@ public class BPRMatrixFactorizationUDTFTest {
final IntWritable negItem = new IntWritable();
final Object[] args = new Object[] {user, posItem, negItem};
- BufferedReader train = IOUtils.bufferedReader(getClass().getResourceAsStream("ml1k.train"));
+ BufferedReader train = readFile("ml1k.train.gz");
String line;
while ((line = train.readLine()) != null) {
parseLine(line, user, posItem, negItem);
@@ -109,6 +111,14 @@ public class BPRMatrixFactorizationUDTFTest {
Assert.assertTrue("finishedIter: " + finishedIter, finishedIter < iterations);
}
+ @Nonnull
+ private static BufferedReader readFile(@Nonnull String fileName) throws IOException {
+ InputStream is = BPRMatrixFactorizationUDTFTest.class.getResourceAsStream(fileName);
+ if (fileName.endsWith(".gz")) {
+ is = new GZIPInputStream(is);
+ }
+ return new BufferedReader(new InputStreamReader(is));
+ }
private static void parseLine(@Nonnull String line, @Nonnull IntWritable user,
@Nonnull IntWritable posItem, @Nonnull IntWritable negItem) {
http://git-wip-us.apache.org/repos/asf/incubator-hivemall/blob/391e7f1c/core/src/test/java/hivemall/utils/collections/Int2FloatOpenHashMapTest.java
----------------------------------------------------------------------
diff --git a/core/src/test/java/hivemall/utils/collections/Int2FloatOpenHashMapTest.java b/core/src/test/java/hivemall/utils/collections/Int2FloatOpenHashMapTest.java
index 14635be..8a8a68d 100644
--- a/core/src/test/java/hivemall/utils/collections/Int2FloatOpenHashMapTest.java
+++ b/core/src/test/java/hivemall/utils/collections/Int2FloatOpenHashMapTest.java
@@ -80,4 +80,17 @@ public class Int2FloatOpenHashMapTest {
Assert.assertEquals(-1, itor.next());
}
+ @Test
+ public void testIterator2() {
+ Int2FloatOpenHashTable map = new Int2FloatOpenHashTable(100);
+ map.put(33, 3.16f);
+
+ Int2FloatOpenHashTable.IMapIterator itor = map.entries();
+ Assert.assertTrue(itor.hasNext());
+ Assert.assertNotEquals(-1, itor.next());
+ Assert.assertEquals(33, itor.getKey());
+ Assert.assertEquals(3.16f, itor.getValue(), 0.d);
+ Assert.assertEquals(-1, itor.next());
+ }
+
}
http://git-wip-us.apache.org/repos/asf/incubator-hivemall/blob/391e7f1c/core/src/test/java/hivemall/utils/io/Base91OutputStreamTest.java
----------------------------------------------------------------------
diff --git a/core/src/test/java/hivemall/utils/io/Base91OutputStreamTest.java b/core/src/test/java/hivemall/utils/io/Base91OutputStreamTest.java
index 99a132f..c7f41f9 100644
--- a/core/src/test/java/hivemall/utils/io/Base91OutputStreamTest.java
+++ b/core/src/test/java/hivemall/utils/io/Base91OutputStreamTest.java
@@ -50,7 +50,7 @@ public class Base91OutputStreamTest {
@Test
public void testLargeEncodeOutDecodeIn() throws IOException {
- InputStream in = ArrayModelTest.class.getResourceAsStream("bigdata.tr.txt");
+ InputStream in = ArrayModelTest.class.getResourceAsStream("bigdata.tr.txt.gz");
byte[] expected = IOUtils.toByteArray(in);
FastByteArrayOutputStream bos = new FastByteArrayOutputStream();
http://git-wip-us.apache.org/repos/asf/incubator-hivemall/blob/391e7f1c/core/src/test/java/hivemall/utils/lang/PreconditionsTest.java
----------------------------------------------------------------------
diff --git a/core/src/test/java/hivemall/utils/lang/PreconditionsTest.java b/core/src/test/java/hivemall/utils/lang/PreconditionsTest.java
index 4cbbd3f..cf27a75 100644
--- a/core/src/test/java/hivemall/utils/lang/PreconditionsTest.java
+++ b/core/src/test/java/hivemall/utils/lang/PreconditionsTest.java
@@ -52,7 +52,7 @@ public class PreconditionsTest {
public void testCheckArgumentBooleanClassOfE2() {
final String msg = "safdfvzfd";
try {
- Preconditions.checkArgument(false, msg, HiveException.class);
+ Preconditions.checkArgument(false, HiveException.class, msg);
} catch (HiveException e) {
if (e.getMessage().equals(msg)) {
return;
[3/6] incubator-hivemall git commit: Close #13: Implement Kernel
Expansion Passive Aggressive Classification
Posted by my...@apache.org.
http://git-wip-us.apache.org/repos/asf/incubator-hivemall/blob/391e7f1c/core/src/test/resources/hivemall/mf/ml1k.test
----------------------------------------------------------------------
diff --git a/core/src/test/resources/hivemall/mf/ml1k.test b/core/src/test/resources/hivemall/mf/ml1k.test
deleted file mode 100644
index e00b112..0000000
--- a/core/src/test/resources/hivemall/mf/ml1k.test
+++ /dev/null
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<TRUNCATED>
http://git-wip-us.apache.org/repos/asf/incubator-hivemall/blob/391e7f1c/core/src/test/resources/hivemall/mf/ml1k.test.gz
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diff --git a/core/src/test/resources/hivemall/mf/ml1k.test.gz b/core/src/test/resources/hivemall/mf/ml1k.test.gz
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[5/6] incubator-hivemall git commit: Close #13: Implement Kernel
Expansion Passive Aggressive Classification
Posted by my...@apache.org.
http://git-wip-us.apache.org/repos/asf/incubator-hivemall/blob/391e7f1c/core/src/test/resources/hivemall/anomaly/cf1d.csv
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diff --git a/core/src/test/resources/hivemall/anomaly/cf1d.csv b/core/src/test/resources/hivemall/anomaly/cf1d.csv
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http://git-wip-us.apache.org/repos/asf/incubator-hivemall/blob/391e7f1c/core/src/test/resources/hivemall/fm/5107786.txt.gz
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diff --git a/core/src/test/resources/hivemall/fm/5107786.txt.gz b/core/src/test/resources/hivemall/fm/5107786.txt.gz
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[2/6] incubator-hivemall git commit: Close #13: Implement Kernel
Expansion Passive Aggressive Classification
Posted by my...@apache.org.
http://git-wip-us.apache.org/repos/asf/incubator-hivemall/blob/391e7f1c/core/src/test/resources/hivemall/mf/ml1k.train
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diff --git a/core/src/test/resources/hivemall/mf/ml1k.train b/core/src/test/resources/hivemall/mf/ml1k.train
deleted file mode 100644
index 11c6177..0000000
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http://git-wip-us.apache.org/repos/asf/incubator-hivemall/blob/391e7f1c/core/src/test/resources/hivemall/mf/ml1k.train.gz
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diff --git a/core/src/test/resources/hivemall/mf/ml1k.train.gz b/core/src/test/resources/hivemall/mf/ml1k.train.gz
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[4/6] incubator-hivemall git commit: Close #13: Implement Kernel
Expansion Passive Aggressive Classification
Posted by my...@apache.org.
http://git-wip-us.apache.org/repos/asf/incubator-hivemall/blob/391e7f1c/core/src/test/resources/hivemall/fm/bigdata.tr.txt
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http://git-wip-us.apache.org/repos/asf/incubator-hivemall/blob/391e7f1c/core/src/test/resources/hivemall/fm/bigdata.tr.txt.gz
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