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saroviossarovios
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Merge pull request #4 from orientechnologies/master
Usage of new OrientDB OGraphBatchInsertSimple that is 10x faster than classic API
2 parents 28bb794 + a24bbae commit a3cd070

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‎config/input.properties‎

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!Select the dataset to populate the graph database
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DATASET = datasets/real/youtubeEdges.txt
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!ENRON DATASET
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REAL_DATASET = data/enronEdges.txt
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!When running CW select the evaluation dataset to check if the algorithms
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!works (communities ground-truth)
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EVALUATION_DATASET = datasets/synthetic/community30000.dat
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!YOUTUBE DATASET
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#REAL_DATASET = data/youtubeEdges.txt
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!AMAZON DATASET
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#REAL_DATASET = data/amazonEdges.txt
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!LIVEJOURNAL DATASET
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#REAL_DATASET = data/livejournalEdges.txt
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!SYNTETIC DATASET
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SYNTHETIC_DATASET = data/network.dat
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!Choose which databases you want to include in the benchmark. Right the databases
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! in a comma-separated list. Available dbs are titan, orientdb, neo4j, sparksee.
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DATABASES = sparksee
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!Please put a license key for Sparksee in order to run the benchmark with big graphs
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SPARKSEE_LICENCE_KEY =
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!Choose which benchmark you want to run. Please select one of the above: are MIW,
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!SIW, QW-FN, QW-FA, QW-FS and CW. You should choose only one benchmark. ONLY when
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!running QW-FA please set ORIENTDB_LW_EDGES to false. In all other cases you should
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!set ORIENTDB_LW_EDGES to true
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BENCHMARK = MIW
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ORIENTDB_LW_EDGES = true
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!There are two possible ways to set the cache value, by setting the amount of nodes or
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!a percentage of the total nodes for every cache value.
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!If to choose the first way you should explicitly set the amount of nodes every cache
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!value should have. The different values should be comma separated (e.g 500, 750, 1000).
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CACHE_VALUES =
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!If you choose the second way you should set the total nodes the graph has, the number
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!of cache values and the percentage factor you want to increment the initial cache value.
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!Note that the initial cache value is equal to the cache increment factor. For example
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!if CACHE_VALUES_CNT = 3 and CACHE_INCREMENT_FACTOR = 0.05 then the benchmark is going
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!to initialize with the following cache values: 0.05, 0.1 and 0.15.
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NODES_CNT = 30000
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CACHE_VALUES_CNT = 6
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CACHE_INCREMENT_FACTOR = 0.05
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!Select the path you want the results to be written
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RESULTS_PATH = results/
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DATABASES = titan,neo4j,sparksee
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!Choose which benchmark you want to run by removing the comments.
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#BENCHMARK = MIW
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#BENCHMARK = SIW
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BENCHMARK = QW-FN
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#BENCHMARK = QW-FA
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#BENCHMARK = QW-FS
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#BENCHMARK = CW
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!Choose the cache values you want run the CW benchmark. The property
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!should be comma delimited.
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CACHE_VALUES = 25,50,75,100,125,150
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!Benchmark class paths
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MIW_CLASS = eu.socialsensor.benchmarks.MassiveInsertionBenchmark
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SIW_CLASS = eu.socialsensor.benchmarks.SingleInsertionBenchmark
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QW-FN_CLASS = eu.socialsensor.benchmarks.FindNeighboursOfAllNodesBenchmark
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QW-FA_CLASS = eu.socialsensor.benchmarks.FindNodesOfAllEdgesBenchmark
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QW-FS_CLASS = eu.socialsensor.benchmarks.FindShortestPathBenchmark
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CW_CLASS = eu.socialsensor.benchmarks.ClusteringBenchmark
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CW_CLASS = eu.socialsensor.benchmarks.ClusteringBenchmark
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!Results folder path
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RESULTS_PATH = data/results/

‎images/SIWAmazon.png‎

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‎images/SIWEnron.png‎

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‎images/SIWLivejournal.png‎

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‎images/SIWYoutube.png‎

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‎pom.xml‎

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<properties>
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<blueprints.version>2.6.0</blueprints.version>
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<orientdb.version>2.0-M1</orientdb.version>
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<!--<orientdb.version>1.7.9-SNAPSHOT</orientdb.version>-->
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<orientdb.version>2.0-SNAPSHOT</orientdb.version>
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</properties>
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<dependencies>

‎src/main/java/eu/socialsensor/benchmarks/FindNodesOfAllEdgesBenchmark.java‎

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package eu.socialsensor.benchmarks;
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import java.lang.reflect.InvocationTargetException;
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import java.lang.reflect.Method;
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import org.apache.log4j.Level;
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import org.apache.log4j.Logger;
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import eu.socialsensor.graphdatabases.GraphDatabase;
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import eu.socialsensor.graphdatabases.Neo4jGraphDatabase;
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import eu.socialsensor.graphdatabases.OrientGraphDatabase;
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import eu.socialsensor.utils.PermuteMethod;
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import eu.socialsensor.utils.Utils;
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import org.apache.log4j.Level;
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import org.apache.log4j.Logger;
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import java.lang.reflect.InvocationTargetException;
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import java.lang.reflect.Method;
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/**
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* FindNodesOfAllEdgesBenchmark implementation
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* @author sotbeis

‎src/main/java/eu/socialsensor/benchmarks/FindShortestPathBenchmark.java‎

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package eu.socialsensor.benchmarks;
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import java.lang.reflect.InvocationTargetException;
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import java.lang.reflect.Method;
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import java.util.HashSet;
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import java.util.Random;
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import java.util.Set;
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import org.apache.log4j.Level;
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import org.apache.log4j.Logger;
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import eu.socialsensor.graphdatabases.GraphDatabase;
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import eu.socialsensor.graphdatabases.Neo4jGraphDatabase;
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import eu.socialsensor.graphdatabases.OrientGraphDatabase;
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import eu.socialsensor.main.GraphDatabaseBenchmark;
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import eu.socialsensor.utils.PermuteMethod;
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import eu.socialsensor.utils.Utils;
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import org.apache.log4j.Level;
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import org.apache.log4j.Logger;
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import java.lang.reflect.InvocationTargetException;
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import java.lang.reflect.Method;
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import java.util.HashSet;
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import java.util.Random;
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import java.util.Set;
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/**
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* FindShortestPathBenchmark implementation

‎src/main/java/eu/socialsensor/benchmarks/MassiveInsertionBenchmark.java‎

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package eu.socialsensor.benchmarks;
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import java.lang.reflect.InvocationTargetException;
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import java.lang.reflect.Method;
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import org.apache.log4j.Level;
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import org.apache.log4j.Logger;
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import eu.socialsensor.graphdatabases.GraphDatabase;
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import eu.socialsensor.graphdatabases.Neo4jGraphDatabase;
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import eu.socialsensor.graphdatabases.OrientGraphDatabase;
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import eu.socialsensor.main.GraphDatabaseBenchmark;
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import eu.socialsensor.utils.PermuteMethod;
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import eu.socialsensor.utils.Utils;
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import org.apache.log4j.Level;
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import org.apache.log4j.Logger;
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import java.lang.reflect.InvocationTargetException;
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import java.lang.reflect.Method;
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/**
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* MassiveInsertionBenchmark implementation

‎src/main/java/eu/socialsensor/graphdatabases/Neo4jGraphDatabase.java‎

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package eu.socialsensor.graphdatabases;
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import java.io.File;
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import java.util.ArrayList;
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import java.util.HashMap;
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import java.util.HashSet;
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import java.util.List;
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import java.util.Map;
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import java.util.Set;
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import java.util.concurrent.TimeUnit;
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import com.google.common.collect.Iterables;
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import eu.socialsensor.insert.Insertion;
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import eu.socialsensor.insert.Neo4jMassiveInsertion;
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import eu.socialsensor.insert.Neo4jSingleInsertion;
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import eu.socialsensor.query.Neo4jQuery;
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import eu.socialsensor.query.Query;
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import eu.socialsensor.utils.Utils;
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import org.neo4j.graphdb.Direction;
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import org.neo4j.graphdb.DynamicLabel;
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import org.neo4j.graphdb.GraphDatabaseService;
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import org.neo4j.unsafe.batchinsert.BatchInserter;
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import org.neo4j.unsafe.batchinsert.BatchInserters;
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import com.google.common.collect.Iterables;
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import eu.socialsensor.insert.Insertion;
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import eu.socialsensor.insert.Neo4jMassiveInsertion;
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import eu.socialsensor.insert.Neo4jSingleInsertion;
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import eu.socialsensor.query.Neo4jQuery;
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import eu.socialsensor.query.Query;
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import eu.socialsensor.utils.Utils;
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import java.io.File;
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import java.util.ArrayList;
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import java.util.HashMap;
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import java.util.HashSet;
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import java.util.List;
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import java.util.Map;
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import java.util.Set;
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import java.util.concurrent.TimeUnit;
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/**
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* Neo4j graph database implementation
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return false;
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}
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}
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}

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