flink-issues mailing list archives

Site index · List index
Message view « Date » · « Thread »
Top « Date » · « Thread »
From greghogan <...@git.apache.org>
Subject [GitHub] flink pull request #2885: [FLINK-1707] Affinity propagation
Date Fri, 24 Feb 2017 18:31:57 GMT
Github user greghogan commented on a diff in the pull request:

    https://github.com/apache/flink/pull/2885#discussion_r102995195
  
    --- Diff: flink-examples/flink-examples-batch/src/main/java/org/apache/flink/examples/java/ap/AffinityPropagationBulk.java
---
    @@ -0,0 +1,449 @@
    +/*
    + * 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.flink.examples.java.ap;
    +
    +import org.apache.flink.api.common.aggregators.ConvergenceCriterion;
    +import org.apache.flink.api.common.aggregators.LongSumAggregator;
    +import org.apache.flink.api.common.functions.FilterFunction;
    +import org.apache.flink.api.common.functions.GroupReduceFunction;
    +import org.apache.flink.api.common.functions.JoinFunction;
    +import org.apache.flink.api.common.functions.MapFunction;
    +import org.apache.flink.api.common.functions.RichJoinFunction;
    +import org.apache.flink.api.common.operators.Order;
    +import org.apache.flink.api.java.DataSet;
    +import org.apache.flink.api.java.ExecutionEnvironment;
    +import org.apache.flink.api.java.operators.IterativeDataSet;
    +import org.apache.flink.api.java.tuple.Tuple3;
    +import org.apache.flink.api.java.tuple.Tuple4;
    +import org.apache.flink.examples.java.ap.util.AffinityPropagationData;
    +import org.apache.flink.types.DoubleValue;
    +import org.apache.flink.types.LongValue;
    +import org.apache.flink.util.Collector;
    +import org.apache.flink.api.java.functions.FunctionAnnotation.ForwardedFieldsFirst;
    +import org.apache.flink.api.java.functions.FunctionAnnotation.ForwardedFieldsSecond;
    +import org.apache.flink.api.java.functions.FunctionAnnotation.ForwardedFields;
    +
    +/**
    + * Created by joseprubio on 9/22/16.
    + */
    +
    +public class AffinityPropagationBulk {
    +
    +	private static final double DAMPING_FACTOR = 0.9;
    +	private static final double CONVERGENCE_THRESHOLD = 0.12;
    +	private static final String CONVERGENCE_MESSAGES = "message convergence";
    +
    +	public static void main(String[] args) throws Exception {
    +
    +		ExecutionEnvironment env = ExecutionEnvironment.getExecutionEnvironment();
    +		env.getConfig().enableObjectReuse();
    +
    +		// Get input similarities Tuple3<src, target, similarity>
    +		DataSet<Tuple3<LongValue, LongValue, DoubleValue>> similarities =
    +			AffinityPropagationData.getTuplesFromFile(env);
    +
    +		// Init input to iteration
    +		DataSet<Tuple4<LongValue, LongValue, DoubleValue, DoubleValue>> initMessages
    +			= similarities.map(new InitMessage());
    +
    +		// Iterate
    +		IterativeDataSet<Tuple4<LongValue, LongValue, DoubleValue, DoubleValue>>
messages
    +			= initMessages.iterate(20);
    +
    +		// Create aggregator
    +		messages.registerAggregationConvergenceCriterion(CONVERGENCE_MESSAGES, new LongSumAggregator(),
    +			new MessageConvergence(similarities.count() * 2));
    +
    +		// Start responsibility message calculation
    +		// r(i,k) <- s(i,k) - max {a(i,K) + s(i,K)} st K != k
    +		// Iterate over Tuple6 <Source, Target, Responsibility , Availability, IsExemplar,
ConvergenceCounter>
    +
    +		DataSet<Tuple3<LongValue, LongValue, DoubleValue>> responsibilities = similarities
    +
    +			// Get a list of a(i,K) + s(i,K) values joining similarities with messages
    +			.join(messages).where("f0","f1").equalTo("f0","f1").with(new joinAvailabilitySimilarity())
    +
    +			// Get a dataset with 2 higher values
    +			.groupBy("f1").sortGroup("f2", Order.DESCENDING).first(2)
    +
    +			// Create a Tuple4<Trg, MaxValue, MaxNeighbour, SecondMaxValue> reducing the
2 tuples with higher values
    +			.groupBy("f1").reduceGroup(new responsibilityReduceGroup())
    +
    +			// Calculate the R messages "r(i,k) <- s(i,k) - value" getting "value" joining
    +			// similarities with previous tuple
    +			.leftOuterJoin(similarities).where("f0").equalTo("f1").with(new responsibilityValue())
    +
    +			// Responsibility damping
    +			.join(messages).where("f0","f1").equalTo("f1","f0").with(new dampedRValue(DAMPING_FACTOR,
CONVERGENCE_THRESHOLD));
    +
    +		// Start availability message calculation
    +		// a(i,k) <- min {0, r(k,k) + sum{max{0,r(I,k)}} I st I not in {i,k}
    +		// a(k,k) <- sum{max{0,r(I,k)} I st I not in {i,k}
    +
    +		DataSet<Tuple4<LongValue, LongValue, DoubleValue, DoubleValue>> availabilities
= responsibilities
    +
    +			// Get the sum of the positive responsibilities and the self responsibility per target
    +			.groupBy("f1").reduceGroup(new availabilityReduceGroup())
    +
    +			// Calculate the availability
    +			.leftOuterJoin(responsibilities).where("f0").equalTo("f1").with(new availabilityValue())
    +
    +			// Availability damping
    +			.join(messages).where("f0","f1").equalTo("f0","f1").with(new dampedAValue(DAMPING_FACTOR,
CONVERGENCE_THRESHOLD));
    +
    +		// End iteration
    +		DataSet<Tuple4<LongValue, LongValue, DoubleValue, DoubleValue>> finalMessages
=
    +			messages.closeWith(availabilities);
    +
    +		// Get exemplars
    +		DataSet<Tuple4<LongValue, LongValue, DoubleValue, DoubleValue>>
    +			exemplars = finalMessages.filter(new FilterExemplars());
    +
    +		// Get clusters
    +		DataSet<Tuple3<LongValue, LongValue, DoubleValue>> clusters = exemplars
    +				.join(similarities).where("f0").equalTo("f1").projectSecond(0,1,2);
    +
    +		// Refine clusters assigning exemplars to themselves
    +		DataSet<Tuple3<LongValue, LongValue, DoubleValue>> refinedClusters = clusters
    +			.groupBy("f0").maxBy(2)
    +			.leftOuterJoin(exemplars).where("f0").equalTo("f0").with(new refineClusters());
    +
    +	}
    +
    +	// Init input messages
    +	private static class InitMessage implements MapFunction<Tuple3<LongValue, LongValue,
DoubleValue>,
    +		Tuple4<LongValue, LongValue, DoubleValue, DoubleValue>> {
    +
    +		Tuple4<LongValue, LongValue, DoubleValue, DoubleValue> output =
    +			new Tuple4<>(new LongValue(), new LongValue(), new DoubleValue(), new DoubleValue());
    +
    +		@Override
    +		public Tuple4<LongValue, LongValue, DoubleValue, DoubleValue>
    +		map(Tuple3<LongValue, LongValue, DoubleValue> in) {
    +			output.f0.setValue(in.f0.getValue());
    +			output.f1.setValue(in.f1.getValue());
    +			return output;
    +		}
    +	}
    +
    +	// Create a list of a(i,K) + s(i,K) values joining similarities with messages
    +	@ForwardedFieldsFirst("f0; f1")
    +	@ForwardedFieldsSecond("f0; f1")
    +	private static class joinAvailabilitySimilarity
    --- End diff --
    
    Capitalize class names.


---
If your project is set up for it, you can reply to this email and have your
reply appear on GitHub as well. If your project does not have this feature
enabled and wishes so, or if the feature is enabled but not working, please
contact infrastructure at infrastructure@apache.org or file a JIRA ticket
with INFRA.
---

Mime
View raw message