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SOLR-11862: Add fuzzyKmeans Stream Evaluatory

This commit is contained in:
Joel Bernstein 2018-01-23 12:17:34 -05:00
parent 4a6110ce01
commit 50a6cb1b05
5 changed files with 288 additions and 19 deletions
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2
solr/core/src/java/org/apache/solr/handler/StreamHandler.java
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@ -310,6 +310,8 @@ public class StreamHandler extends RequestHandlerBase implements SolrCoreAware,
.withFunctionName("indexOf", IndexOfEvaluator.class)
.withFunctionName("columnCount", ColumnCountEvaluator.class)
.withFunctionName("rowCount", RowCountEvaluator.class)
.withFunctionName("fuzzyKmeans", FuzzyKmeansEvaluator.class)
.withFunctionName("getMembershipMatrix", GetMembershipMatrixEvaluator.class)
// Boolean Stream Evaluators

106
solr/solrj/src/java/org/apache/solr/client/solrj/io/eval/FuzzyKmeansEvaluator.java Normal file
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@ -0,0 +1,106 @@
/*
* Licensed to the Apache Software Foundation (ASF) under one or more
* contributor license agreements. See the NOTICE file distributed with
* this work for additional information regarding copyright ownership.
* The ASF licenses this file to You under the Apache License, Version 2.0
* (the "License"); you may not use this file except in compliance with
* the License. You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
package org.apache.solr.client.solrj.io.eval;
import java.io.IOException;
import java.util.ArrayList;
import java.util.List;
import java.util.Map;
import java.util.HashMap;
import org.apache.commons.math3.linear.RealMatrix;
import org.apache.commons.math3.ml.clustering.CentroidCluster;
import org.apache.commons.math3.ml.distance.EuclideanDistance;
import org.apache.commons.math3.ml.clustering.FuzzyKMeansClusterer;
import org.apache.solr.client.solrj.io.stream.expr.StreamExpression;
import org.apache.solr.client.solrj.io.stream.expr.StreamExpressionNamedParameter;
import org.apache.solr.client.solrj.io.stream.expr.StreamFactory;
public class FuzzyKmeansEvaluator extends RecursiveObjectEvaluator implements TwoValueWorker {
protected static final long serialVersionUID = 1L;
private int maxIterations = 1000;
private double fuzziness = 1.2;
public FuzzyKmeansEvaluator(StreamExpression expression, StreamFactory factory) throws IOException{
super(expression, factory);
List<StreamExpressionNamedParameter> namedParams = factory.getNamedOperands(expression);
for(StreamExpressionNamedParameter namedParam : namedParams){
if(namedParam.getName().equals("fuzziness")){
this.fuzziness = Double.parseDouble(namedParam.getParameter().toString().trim());
} else if(namedParam.getName().equals("maxIterations")) {
this.maxIterations = Integer.parseInt(namedParam.getParameter().toString().trim());
} else {
throw new IOException("Unexpected named parameter:"+namedParam.getName());
}
}
}
@Override
public Object doWork(Object value1, Object value2) throws IOException {
Matrix matrix = null;
int k = 0;
if(value1 instanceof Matrix) {
matrix = (Matrix)value1;
} else {
throw new IOException("The first parameter for fuzzyKmeans should be the observation matrix.");
}
if(value2 instanceof Number) {
k = ((Number)value2).intValue();
} else {
throw new IOException("The second parameter for fuzzyKmeans should be k.");
}
FuzzyKMeansClusterer<KmeansEvaluator.ClusterPoint> kmeans = new FuzzyKMeansClusterer(k,
fuzziness,
maxIterations,
new EuclideanDistance());
List<KmeansEvaluator.ClusterPoint> points = new ArrayList();
double[][] data = matrix.getData();
List<String> ids = matrix.getRowLabels();
for(int i=0; i<data.length; i++) {
double[] vec = data[i];
points.add(new KmeansEvaluator.ClusterPoint(ids.get(i), vec));
}
Map fields = new HashMap();
fields.put("k", k);
fields.put("fuzziness", fuzziness);
fields.put("distance", "euclidean");
fields.put("maxIterations", maxIterations);
List<CentroidCluster<KmeansEvaluator.ClusterPoint>> clusters = kmeans.cluster(points);
RealMatrix realMatrix = kmeans.getMembershipMatrix();
double[][] mmData = realMatrix.getData();
Matrix mmMatrix = new Matrix(mmData);
mmMatrix.setRowLabels(matrix.getRowLabels());
return new KmeansEvaluator.ClusterTuple(fields, clusters, matrix.getColumnLabels(),mmMatrix);
}
}

42
solr/solrj/src/java/org/apache/solr/client/solrj/io/eval/GetMembershipMatrixEvaluator.java Normal file
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@ -0,0 +1,42 @@
/*
* Licensed to the Apache Software Foundation (ASF) under one or more
* contributor license agreements. See the NOTICE file distributed with
* this work for additional information regarding copyright ownership.
* The ASF licenses this file to You under the Apache License, Version 2.0
* (the "License"); you may not use this file except in compliance with
* the License. You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
package org.apache.solr.client.solrj.io.eval;
import java.io.IOException;
import java.util.Locale;
import org.apache.solr.client.solrj.io.stream.expr.StreamExpression;
import org.apache.solr.client.solrj.io.stream.expr.StreamFactory;
public class GetMembershipMatrixEvaluator extends RecursiveObjectEvaluator implements OneValueWorker {
private static final long serialVersionUID = 1;
public GetMembershipMatrixEvaluator(StreamExpression expression, StreamFactory factory) throws IOException {
super(expression, factory);
}
@Override
public Object doWork(Object value) throws IOException {
if(!(value instanceof KmeansEvaluator.ClusterTuple)){
throw new IOException(String.format(Locale.ROOT,"Invalid expression %s - found type %s for value, expecting a clustering result",toExpression(constructingFactory), value.getClass().getSimpleName()));
} else {
KmeansEvaluator.ClusterTuple clusterTuple = (KmeansEvaluator.ClusterTuple)value;
return clusterTuple.getMembershipMatrix();
}
}
}

52
solr/solrj/src/java/org/apache/solr/client/solrj/io/eval/KmeansEvaluator.java
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@ -29,43 +29,46 @@ import org.apache.solr.client.solrj.io.Tuple;
import org.apache.commons.math3.ml.clustering.Clusterable;
import org.apache.commons.math3.ml.clustering.KMeansPlusPlusClusterer;
import org.apache.solr.client.solrj.io.stream.expr.StreamExpression;
import org.apache.solr.client.solrj.io.stream.expr.StreamExpressionNamedParameter;
import org.apache.solr.client.solrj.io.stream.expr.StreamFactory;
public class KmeansEvaluator extends RecursiveObjectEvaluator implements ManyValueWorker {
public class KmeansEvaluator extends RecursiveObjectEvaluator implements TwoValueWorker {
protected static final long serialVersionUID = 1L;
private int maxIterations = 1000;
public KmeansEvaluator(StreamExpression expression, StreamFactory factory) throws IOException{
super(expression, factory);
List<StreamExpressionNamedParameter> namedParams = factory.getNamedOperands(expression);
for(StreamExpressionNamedParameter namedParam : namedParams){
if(namedParam.getName().equals("maxIterations")) {
this.maxIterations = Integer.parseInt(namedParam.getParameter().toString().trim());
} else {
throw new IOException("Unexpected named parameter:"+namedParam.getName());
}
}
}
@Override
public Object doWork(Object... values) throws IOException {
if(values.length < 2) {
throw new IOException("kmeans expects atleast two parameters a Matrix of observations and k");
}
public Object doWork(Object value1, Object value2) throws IOException {
Matrix matrix = null;
int k = 0;
int maxIterations = 1000;
if(values[0] instanceof Matrix) {
matrix = (Matrix)values[0];
if(value1 instanceof Matrix) {
matrix = (Matrix)value1;
} else {
throw new IOException("The first parameter for kmeans should be the observation matrix.");
}
if(values[1] instanceof Number) {
k = ((Number)values[1]).intValue();
if(value2 instanceof Number) {
k = ((Number)value2).intValue();
} else {
throw new IOException("The second parameter for kmeans should be k.");
}
if(values.length == 3) {
maxIterations = ((Number)values[2]).intValue();
}
KMeansPlusPlusClusterer<ClusterPoint> kmeans = new KMeansPlusPlusClusterer(k, maxIterations);
List<ClusterPoint> points = new ArrayList();
@ -110,6 +113,7 @@ public class KmeansEvaluator extends RecursiveObjectEvaluator implements ManyVal
private List<String> columnLabels;
private List<CentroidCluster<ClusterPoint>> clusters;
private Matrix membershipMatrix;
public ClusterTuple(Map fields,
List<CentroidCluster<ClusterPoint>> clusters,
@ -119,6 +123,20 @@ public class KmeansEvaluator extends RecursiveObjectEvaluator implements ManyVal
this.columnLabels = columnLabels;
}
public ClusterTuple(Map fields,
List<CentroidCluster<ClusterPoint>> clusters,
List<String> columnLabels,
Matrix membershipMatrix) {
super(fields);
this.clusters = clusters;
this.columnLabels = columnLabels;
this.membershipMatrix = membershipMatrix;
}
public Matrix getMembershipMatrix() {
return this.membershipMatrix;
}
public List<String> getColumnLabels() {
return this.columnLabels;
}
@ -126,10 +144,6 @@ public class KmeansEvaluator extends RecursiveObjectEvaluator implements ManyVal
public List<CentroidCluster<ClusterPoint>> getClusters() {
return this.clusters;
}
}
}

105
solr/solrj/src/test/org/apache/solr/client/solrj/io/stream/StreamExpressionTest.java
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@ -7076,6 +7076,111 @@ public class StreamExpressionTest extends SolrCloudTestCase {
}
}
@Test
public void testFuzzyKmeans() throws Exception {
String cexpr = "let(echo=true," +
" a=array(1,1,1,0,0,0)," +
" b=array(1,1,1,0,0,0)," +
" c=array(0,0,0,1,1,1)," +
" d=array(0,0,0,1,1,1)," +
" e=setRowLabels(matrix(a,b,c,d), " +
" array(doc1, doc2, doc3, doc4))," +
" f=fuzzyKmeans(e, 2)," +
" g=getCluster(f, 0)," +
" h=getCluster(f, 1)," +
" i=getCentroids(f)," +
" j=getRowLabels(g)," +
" k=getRowLabels(h)," +
" l=getMembershipMatrix(f))";
ModifiableSolrParams paramsLoc = new ModifiableSolrParams();
paramsLoc.set("expr", cexpr);
paramsLoc.set("qt", "/stream");
String url = cluster.getJettySolrRunners().get(0).getBaseUrl().toString()+"/"+COLLECTIONORALIAS;
TupleStream solrStream = new SolrStream(url, paramsLoc);
StreamContext context = new StreamContext();
solrStream.setStreamContext(context);
List<Tuple> tuples = getTuples(solrStream);
assertTrue(tuples.size() == 1);
List<List<Number>> cluster1 = (List<List<Number>>)tuples.get(0).get("g");
List<List<Number>> cluster2 = (List<List<Number>>)tuples.get(0).get("h");
List<List<Number>> centroids = (List<List<Number>>)tuples.get(0).get("i");
List<List<Number>> membership = (List<List<Number>>)tuples.get(0).get("l");
List<String> labels1 = (List<String>)tuples.get(0).get("j");
List<String> labels2 = (List<String>)tuples.get(0).get("k");
assertEquals(cluster1.size(), 2);
assertEquals(cluster2.size(), 2);
assertEquals(centroids.size(), 2);
//Assert that the docs are not in both clusters
assertTrue(!(labels1.contains("doc1") && labels2.contains("doc1")));
assertTrue(!(labels1.contains("doc2") && labels2.contains("doc2")));
assertTrue(!(labels1.contains("doc3") && labels2.contains("doc3")));
assertTrue(!(labels1.contains("doc4") && labels2.contains("doc4")));
//Assert that (doc1 and doc2) or (doc3 and doc4) are in labels1
assertTrue((labels1.contains("doc1") && labels1.contains("doc2")) ||
((labels1.contains("doc3") && labels1.contains("doc4"))));
//Assert that (doc1 and doc2) or (doc3 and doc4) are in labels2
assertTrue((labels2.contains("doc1") && labels2.contains("doc2")) ||
((labels2.contains("doc3") && labels2.contains("doc4"))));
if(labels1.contains("doc1")) {
assertEquals(centroids.get(0).get(0).doubleValue(), 1.0, 0.0001);
assertEquals(centroids.get(0).get(1).doubleValue(), 1.0, 0.0001);
assertEquals(centroids.get(0).get(2).doubleValue(), 1.0, 0.0001);
assertEquals(centroids.get(0).get(3).doubleValue(), 0.0, 0.0001);
assertEquals(centroids.get(0).get(4).doubleValue(), 0.0, 0.0001);
assertEquals(centroids.get(0).get(5).doubleValue(), 0.0, 0.0001);
assertEquals(centroids.get(1).get(0).doubleValue(), 0.0, 0.0001);
assertEquals(centroids.get(1).get(1).doubleValue(), 0.0, 0.0001);
assertEquals(centroids.get(1).get(2).doubleValue(), 0.0, 0.0001);
assertEquals(centroids.get(1).get(3).doubleValue(), 1.0, 0.0001);
assertEquals(centroids.get(1).get(4).doubleValue(), 1.0, 0.0001);
assertEquals(centroids.get(1).get(5).doubleValue(), 1.0, 0.0001);
//Assert the membership matrix
assertEquals(membership.get(0).get(0).doubleValue(), 1.0, 0.0001);
assertEquals(membership.get(0).get(1).doubleValue(), 0.0, 0.0001);
assertEquals(membership.get(1).get(0).doubleValue(), 1.0, 0.0001);
assertEquals(membership.get(1).get(1).doubleValue(), 0.0, 0.0001);
assertEquals(membership.get(2).get(0).doubleValue(), 0.0, 0.0001);
assertEquals(membership.get(2).get(1).doubleValue(), 1.0, 0.0001);
assertEquals(membership.get(3).get(0).doubleValue(), 0.0, 0.0001);
assertEquals(membership.get(3).get(1).doubleValue(), 1.0, 0.0001);
} else {
assertEquals(centroids.get(0).get(0).doubleValue(), 0.0, 0.0001);
assertEquals(centroids.get(0).get(1).doubleValue(), 0.0, 0.0001);
assertEquals(centroids.get(0).get(2).doubleValue(), 0.0, 0.0001);
assertEquals(centroids.get(0).get(3).doubleValue(), 1.0, 0.0001);
assertEquals(centroids.get(0).get(4).doubleValue(), 1.0, 0.0001);
assertEquals(centroids.get(0).get(5).doubleValue(), 1.0, 0.0001);
assertEquals(centroids.get(1).get(0).doubleValue(), 1.0, 0.0001);
assertEquals(centroids.get(1).get(1).doubleValue(), 1.0, 0.0001);
assertEquals(centroids.get(1).get(2).doubleValue(), 1.0, 0.0001);
assertEquals(centroids.get(1).get(3).doubleValue(), 0.0, 0.0001);
assertEquals(centroids.get(1).get(4).doubleValue(), 0.0, 0.0001);
assertEquals(centroids.get(1).get(5).doubleValue(), 0.0, 0.0001);
//Assert the membership matrix
assertEquals(membership.get(0).get(0).doubleValue(), 0.0, 0.0001);
assertEquals(membership.get(0).get(1).doubleValue(), 1.0, 0.0001);
assertEquals(membership.get(1).get(0).doubleValue(), 0.0, 0.0001);
assertEquals(membership.get(1).get(1).doubleValue(), 1.0, 0.0001);
assertEquals(membership.get(2).get(0).doubleValue(), 1.0, 0.0001);
assertEquals(membership.get(2).get(1).doubleValue(), 0.0, 0.0001);
assertEquals(membership.get(3).get(0).doubleValue(), 1.0, 0.0001);
assertEquals(membership.get(3).get(1).doubleValue(), 0.0, 0.0001);
}
}
@Test
public void testEBEMultiply() throws Exception {
String cexpr = "ebeMultiply(array(2,4,6,8,10,12),array(1,2,3,4,5,6))";