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Example 16 with OptimizedPlan

use of org.apache.flink.optimizer.plan.OptimizedPlan in project flink by apache.

the class PregelCompilerTest method testPregelCompilerWithBroadcastVariable.

@SuppressWarnings("serial")
@Test
public void testPregelCompilerWithBroadcastVariable() {
    try {
        final String BC_VAR_NAME = "borat variable";
        ExecutionEnvironment env = ExecutionEnvironment.getExecutionEnvironment();
        env.setParallelism(DEFAULT_PARALLELISM);
        // compose test program
        {
            DataSet<Long> bcVar = env.fromElements(1L);
            DataSet<Vertex<Long, Long>> initialVertices = env.fromElements(new Tuple2<>(1L, 1L), new Tuple2<>(2L, 2L)).map(new Tuple2ToVertexMap<Long, Long>());
            DataSet<Edge<Long, NullValue>> edges = env.fromElements(new Tuple2<>(1L, 2L)).map(new MapFunction<Tuple2<Long, Long>, Edge<Long, NullValue>>() {

                public Edge<Long, NullValue> map(Tuple2<Long, Long> edge) {
                    return new Edge<>(edge.f0, edge.f1, NullValue.getInstance());
                }
            });
            Graph<Long, Long, NullValue> graph = Graph.fromDataSet(initialVertices, edges, env);
            VertexCentricConfiguration parameters = new VertexCentricConfiguration();
            parameters.addBroadcastSet(BC_VAR_NAME, bcVar);
            DataSet<Vertex<Long, Long>> result = graph.runVertexCentricIteration(new CCCompute(), null, 100, parameters).getVertices();
            result.output(new DiscardingOutputFormat<Vertex<Long, Long>>());
        }
        Plan p = env.createProgramPlan("Pregel Connected Components");
        OptimizedPlan op = compileNoStats(p);
        // check the sink
        SinkPlanNode sink = op.getDataSinks().iterator().next();
        assertEquals(ShipStrategyType.FORWARD, sink.getInput().getShipStrategy());
        assertEquals(DEFAULT_PARALLELISM, sink.getParallelism());
        // check the iteration
        WorksetIterationPlanNode iteration = (WorksetIterationPlanNode) sink.getInput().getSource();
        assertEquals(DEFAULT_PARALLELISM, iteration.getParallelism());
        // check the solution set delta
        PlanNode ssDelta = iteration.getSolutionSetDeltaPlanNode();
        assertTrue(ssDelta instanceof SingleInputPlanNode);
        SingleInputPlanNode ssFlatMap = (SingleInputPlanNode) ((SingleInputPlanNode) (ssDelta)).getInput().getSource();
        assertEquals(DEFAULT_PARALLELISM, ssFlatMap.getParallelism());
        assertEquals(ShipStrategyType.FORWARD, ssFlatMap.getInput().getShipStrategy());
        // check the computation coGroup
        DualInputPlanNode computationCoGroup = (DualInputPlanNode) (ssFlatMap.getInput().getSource());
        assertEquals(DEFAULT_PARALLELISM, computationCoGroup.getParallelism());
        assertEquals(ShipStrategyType.FORWARD, computationCoGroup.getInput1().getShipStrategy());
        assertEquals(ShipStrategyType.PARTITION_HASH, computationCoGroup.getInput2().getShipStrategy());
        assertTrue(computationCoGroup.getInput2().getTempMode().isCached());
        assertEquals(new FieldList(0), computationCoGroup.getInput2().getShipStrategyKeys());
        // check that the initial partitioning is pushed out of the loop
        assertEquals(ShipStrategyType.PARTITION_HASH, iteration.getInput1().getShipStrategy());
        assertEquals(new FieldList(0), iteration.getInput1().getShipStrategyKeys());
    } catch (Exception e) {
        System.err.println(e.getMessage());
        e.printStackTrace();
        fail(e.getMessage());
    }
}
Also used : ExecutionEnvironment(org.apache.flink.api.java.ExecutionEnvironment) Tuple2ToVertexMap(org.apache.flink.graph.utils.Tuple2ToVertexMap) DataSet(org.apache.flink.api.java.DataSet) WorksetIterationPlanNode(org.apache.flink.optimizer.plan.WorksetIterationPlanNode) MapFunction(org.apache.flink.api.common.functions.MapFunction) Plan(org.apache.flink.api.common.Plan) OptimizedPlan(org.apache.flink.optimizer.plan.OptimizedPlan) DiscardingOutputFormat(org.apache.flink.api.java.io.DiscardingOutputFormat) OptimizedPlan(org.apache.flink.optimizer.plan.OptimizedPlan) FieldList(org.apache.flink.api.common.operators.util.FieldList) SingleInputPlanNode(org.apache.flink.optimizer.plan.SingleInputPlanNode) DualInputPlanNode(org.apache.flink.optimizer.plan.DualInputPlanNode) NullValue(org.apache.flink.types.NullValue) Graph(org.apache.flink.graph.Graph) WorksetIterationPlanNode(org.apache.flink.optimizer.plan.WorksetIterationPlanNode) DualInputPlanNode(org.apache.flink.optimizer.plan.DualInputPlanNode) PlanNode(org.apache.flink.optimizer.plan.PlanNode) SinkPlanNode(org.apache.flink.optimizer.plan.SinkPlanNode) SingleInputPlanNode(org.apache.flink.optimizer.plan.SingleInputPlanNode) Tuple2(org.apache.flink.api.java.tuple.Tuple2) SinkPlanNode(org.apache.flink.optimizer.plan.SinkPlanNode) Edge(org.apache.flink.graph.Edge) Test(org.junit.Test)

Example 17 with OptimizedPlan

use of org.apache.flink.optimizer.plan.OptimizedPlan in project flink by apache.

the class SpargelCompilerTest method testSpargelCompilerWithBroadcastVariable.

@SuppressWarnings("serial")
@Test
public void testSpargelCompilerWithBroadcastVariable() {
    try {
        final String BC_VAR_NAME = "borat variable";
        ExecutionEnvironment env = ExecutionEnvironment.getExecutionEnvironment();
        env.setParallelism(DEFAULT_PARALLELISM);
        // compose test program
        {
            DataSet<Long> bcVar = env.fromElements(1L);
            DataSet<Vertex<Long, Long>> initialVertices = env.fromElements(new Tuple2<>(1L, 1L), new Tuple2<>(2L, 2L)).map(new Tuple2ToVertexMap<Long, Long>());
            DataSet<Edge<Long, NullValue>> edges = env.fromElements(new Tuple2<>(1L, 2L)).map(new MapFunction<Tuple2<Long, Long>, Edge<Long, NullValue>>() {

                public Edge<Long, NullValue> map(Tuple2<Long, Long> edge) {
                    return new Edge<>(edge.f0, edge.f1, NullValue.getInstance());
                }
            });
            Graph<Long, Long, NullValue> graph = Graph.fromDataSet(initialVertices, edges, env);
            ScatterGatherConfiguration parameters = new ScatterGatherConfiguration();
            parameters.addBroadcastSetForScatterFunction(BC_VAR_NAME, bcVar);
            parameters.addBroadcastSetForGatherFunction(BC_VAR_NAME, bcVar);
            DataSet<Vertex<Long, Long>> result = graph.runScatterGatherIteration(new ConnectedComponents.CCMessenger<Long, Long>(BasicTypeInfo.LONG_TYPE_INFO), new ConnectedComponents.CCUpdater<Long, Long>(), 100).getVertices();
            result.output(new DiscardingOutputFormat<Vertex<Long, Long>>());
        }
        Plan p = env.createProgramPlan("Spargel Connected Components");
        OptimizedPlan op = compileNoStats(p);
        // check the sink
        SinkPlanNode sink = op.getDataSinks().iterator().next();
        assertEquals(ShipStrategyType.FORWARD, sink.getInput().getShipStrategy());
        assertEquals(DEFAULT_PARALLELISM, sink.getParallelism());
        // check the iteration
        WorksetIterationPlanNode iteration = (WorksetIterationPlanNode) sink.getInput().getSource();
        assertEquals(DEFAULT_PARALLELISM, iteration.getParallelism());
        // check the solution set join and the delta
        PlanNode ssDelta = iteration.getSolutionSetDeltaPlanNode();
        // this is only true if the update functions preserves the partitioning
        assertTrue(ssDelta instanceof DualInputPlanNode);
        DualInputPlanNode ssJoin = (DualInputPlanNode) ssDelta;
        assertEquals(DEFAULT_PARALLELISM, ssJoin.getParallelism());
        assertEquals(ShipStrategyType.PARTITION_HASH, ssJoin.getInput1().getShipStrategy());
        assertEquals(new FieldList(0), ssJoin.getInput1().getShipStrategyKeys());
        // check the workset set join
        DualInputPlanNode edgeJoin = (DualInputPlanNode) ssJoin.getInput1().getSource();
        assertEquals(DEFAULT_PARALLELISM, edgeJoin.getParallelism());
        assertEquals(ShipStrategyType.PARTITION_HASH, edgeJoin.getInput1().getShipStrategy());
        assertEquals(ShipStrategyType.FORWARD, edgeJoin.getInput2().getShipStrategy());
        assertTrue(edgeJoin.getInput1().getTempMode().isCached());
        assertEquals(new FieldList(0), edgeJoin.getInput1().getShipStrategyKeys());
        // check that the initial partitioning is pushed out of the loop
        assertEquals(ShipStrategyType.PARTITION_HASH, iteration.getInput1().getShipStrategy());
        assertEquals(ShipStrategyType.PARTITION_HASH, iteration.getInput2().getShipStrategy());
        assertEquals(new FieldList(0), iteration.getInput1().getShipStrategyKeys());
        assertEquals(new FieldList(0), iteration.getInput2().getShipStrategyKeys());
    } catch (Exception e) {
        System.err.println(e.getMessage());
        e.printStackTrace();
        fail(e.getMessage());
    }
}
Also used : ExecutionEnvironment(org.apache.flink.api.java.ExecutionEnvironment) Tuple2ToVertexMap(org.apache.flink.graph.utils.Tuple2ToVertexMap) DataSet(org.apache.flink.api.java.DataSet) WorksetIterationPlanNode(org.apache.flink.optimizer.plan.WorksetIterationPlanNode) MapFunction(org.apache.flink.api.common.functions.MapFunction) Plan(org.apache.flink.api.common.Plan) OptimizedPlan(org.apache.flink.optimizer.plan.OptimizedPlan) DiscardingOutputFormat(org.apache.flink.api.java.io.DiscardingOutputFormat) OptimizedPlan(org.apache.flink.optimizer.plan.OptimizedPlan) FieldList(org.apache.flink.api.common.operators.util.FieldList) DualInputPlanNode(org.apache.flink.optimizer.plan.DualInputPlanNode) NullValue(org.apache.flink.types.NullValue) Graph(org.apache.flink.graph.Graph) WorksetIterationPlanNode(org.apache.flink.optimizer.plan.WorksetIterationPlanNode) DualInputPlanNode(org.apache.flink.optimizer.plan.DualInputPlanNode) PlanNode(org.apache.flink.optimizer.plan.PlanNode) SinkPlanNode(org.apache.flink.optimizer.plan.SinkPlanNode) ConnectedComponents(org.apache.flink.graph.library.ConnectedComponents) Tuple2(org.apache.flink.api.java.tuple.Tuple2) SinkPlanNode(org.apache.flink.optimizer.plan.SinkPlanNode) Edge(org.apache.flink.graph.Edge) Test(org.junit.Test)

Example 18 with OptimizedPlan

use of org.apache.flink.optimizer.plan.OptimizedPlan in project flink by apache.

the class GSACompilerTest method testGSACompiler.

@Test
public void testGSACompiler() {
    try {
        ExecutionEnvironment env = ExecutionEnvironment.getExecutionEnvironment();
        env.setParallelism(DEFAULT_PARALLELISM);
        // compose test program
        {
            DataSet<Edge<Long, NullValue>> edges = env.fromElements(new Tuple3<>(1L, 2L, NullValue.getInstance())).map(new Tuple3ToEdgeMap<Long, NullValue>());
            Graph<Long, Long, NullValue> graph = Graph.fromDataSet(edges, new InitVertices(), env);
            DataSet<Vertex<Long, Long>> result = graph.runGatherSumApplyIteration(new GatherNeighborIds(), new SelectMinId(), new UpdateComponentId(), 100).getVertices();
            result.output(new DiscardingOutputFormat<Vertex<Long, Long>>());
        }
        Plan p = env.createProgramPlan("GSA Connected Components");
        OptimizedPlan op = compileNoStats(p);
        // check the sink
        SinkPlanNode sink = op.getDataSinks().iterator().next();
        assertEquals(ShipStrategyType.FORWARD, sink.getInput().getShipStrategy());
        assertEquals(DEFAULT_PARALLELISM, sink.getParallelism());
        assertEquals(PartitioningProperty.HASH_PARTITIONED, sink.getGlobalProperties().getPartitioning());
        // check the iteration
        WorksetIterationPlanNode iteration = (WorksetIterationPlanNode) sink.getInput().getSource();
        assertEquals(DEFAULT_PARALLELISM, iteration.getParallelism());
        // check the solution set join and the delta
        PlanNode ssDelta = iteration.getSolutionSetDeltaPlanNode();
        // this is only true if the update function preserves the partitioning
        assertTrue(ssDelta instanceof DualInputPlanNode);
        DualInputPlanNode ssJoin = (DualInputPlanNode) ssDelta;
        assertEquals(DEFAULT_PARALLELISM, ssJoin.getParallelism());
        assertEquals(ShipStrategyType.PARTITION_HASH, ssJoin.getInput1().getShipStrategy());
        assertEquals(new FieldList(0), ssJoin.getInput1().getShipStrategyKeys());
        // check the workset set join
        SingleInputPlanNode sumReducer = (SingleInputPlanNode) ssJoin.getInput1().getSource();
        SingleInputPlanNode gatherMapper = (SingleInputPlanNode) sumReducer.getInput().getSource();
        DualInputPlanNode edgeJoin = (DualInputPlanNode) gatherMapper.getInput().getSource();
        assertEquals(DEFAULT_PARALLELISM, edgeJoin.getParallelism());
        // input1 is the workset
        assertEquals(ShipStrategyType.FORWARD, edgeJoin.getInput1().getShipStrategy());
        // input2 is the edges
        assertEquals(ShipStrategyType.PARTITION_HASH, edgeJoin.getInput2().getShipStrategy());
        assertTrue(edgeJoin.getInput2().getTempMode().isCached());
        assertEquals(new FieldList(0), edgeJoin.getInput2().getShipStrategyKeys());
    } catch (Exception e) {
        System.err.println(e.getMessage());
        e.printStackTrace();
        fail(e.getMessage());
    }
}
Also used : ExecutionEnvironment(org.apache.flink.api.java.ExecutionEnvironment) DataSet(org.apache.flink.api.java.DataSet) WorksetIterationPlanNode(org.apache.flink.optimizer.plan.WorksetIterationPlanNode) Plan(org.apache.flink.api.common.Plan) OptimizedPlan(org.apache.flink.optimizer.plan.OptimizedPlan) DiscardingOutputFormat(org.apache.flink.api.java.io.DiscardingOutputFormat) OptimizedPlan(org.apache.flink.optimizer.plan.OptimizedPlan) FieldList(org.apache.flink.api.common.operators.util.FieldList) DualInputPlanNode(org.apache.flink.optimizer.plan.DualInputPlanNode) SingleInputPlanNode(org.apache.flink.optimizer.plan.SingleInputPlanNode) NullValue(org.apache.flink.types.NullValue) Graph(org.apache.flink.graph.Graph) WorksetIterationPlanNode(org.apache.flink.optimizer.plan.WorksetIterationPlanNode) DualInputPlanNode(org.apache.flink.optimizer.plan.DualInputPlanNode) PlanNode(org.apache.flink.optimizer.plan.PlanNode) SinkPlanNode(org.apache.flink.optimizer.plan.SinkPlanNode) SingleInputPlanNode(org.apache.flink.optimizer.plan.SingleInputPlanNode) Tuple3ToEdgeMap(org.apache.flink.graph.utils.Tuple3ToEdgeMap) SinkPlanNode(org.apache.flink.optimizer.plan.SinkPlanNode) Test(org.junit.Test)

Example 19 with OptimizedPlan

use of org.apache.flink.optimizer.plan.OptimizedPlan in project flink by apache.

the class DistinctCompilationTest method testDistinctWithFieldPositionKeyCombinable.

@Test
public void testDistinctWithFieldPositionKeyCombinable() {
    try {
        ExecutionEnvironment env = ExecutionEnvironment.getExecutionEnvironment();
        env.setParallelism(8);
        DataSet<Tuple2<String, Double>> data = env.readCsvFile("file:///will/never/be/read").types(String.class, Double.class).name("source").setParallelism(6);
        DistinctOperator<Tuple2<String, Double>> reduced = data.distinct(1).name("reducer");
        reduced.output(new DiscardingOutputFormat<Tuple2<String, Double>>()).name("sink");
        Plan p = env.createProgramPlan();
        OptimizedPlan op = compileNoStats(p);
        OptimizerPlanNodeResolver resolver = getOptimizerPlanNodeResolver(op);
        // get the original nodes
        SourcePlanNode sourceNode = resolver.getNode("source");
        SingleInputPlanNode reduceNode = resolver.getNode("reducer");
        SinkPlanNode sinkNode = resolver.getNode("sink");
        // get the combiner
        SingleInputPlanNode combineNode = (SingleInputPlanNode) reduceNode.getInput().getSource();
        // check wiring
        assertEquals(sourceNode, combineNode.getInput().getSource());
        assertEquals(reduceNode, sinkNode.getInput().getSource());
        // check that both reduce and combiner have the same strategy
        assertEquals(DriverStrategy.SORTED_REDUCE, reduceNode.getDriverStrategy());
        assertEquals(DriverStrategy.SORTED_PARTIAL_REDUCE, combineNode.getDriverStrategy());
        // check the keys
        assertEquals(new FieldList(1), reduceNode.getKeys(0));
        assertEquals(new FieldList(1), combineNode.getKeys(0));
        assertEquals(new FieldList(1), reduceNode.getInput().getLocalStrategyKeys());
        // check parallelism
        assertEquals(6, sourceNode.getParallelism());
        assertEquals(6, combineNode.getParallelism());
        assertEquals(8, reduceNode.getParallelism());
        assertEquals(8, sinkNode.getParallelism());
    } catch (Exception e) {
        System.err.println(e.getMessage());
        e.printStackTrace();
        fail(e.getClass().getSimpleName() + " in test: " + e.getMessage());
    }
}
Also used : ExecutionEnvironment(org.apache.flink.api.java.ExecutionEnvironment) Plan(org.apache.flink.api.common.Plan) OptimizedPlan(org.apache.flink.optimizer.plan.OptimizedPlan) DiscardingOutputFormat(org.apache.flink.api.java.io.DiscardingOutputFormat) OptimizedPlan(org.apache.flink.optimizer.plan.OptimizedPlan) FieldList(org.apache.flink.api.common.operators.util.FieldList) SingleInputPlanNode(org.apache.flink.optimizer.plan.SingleInputPlanNode) Tuple2(org.apache.flink.api.java.tuple.Tuple2) SourcePlanNode(org.apache.flink.optimizer.plan.SourcePlanNode) SinkPlanNode(org.apache.flink.optimizer.plan.SinkPlanNode) Test(org.junit.Test)

Example 20 with OptimizedPlan

use of org.apache.flink.optimizer.plan.OptimizedPlan in project flink by apache.

the class GroupOrderTest method testReduceWithGroupOrder.

@Test
public void testReduceWithGroupOrder() {
    // construct the plan
    ExecutionEnvironment env = ExecutionEnvironment.getExecutionEnvironment();
    env.setParallelism(DEFAULT_PARALLELISM);
    DataSet<Tuple4<Long, Long, Long, Long>> set1 = env.readCsvFile("/tmp/fake.csv").types(Long.class, Long.class, Long.class, Long.class);
    set1.groupBy(1).sortGroup(3, Order.DESCENDING).reduceGroup(new IdentityGroupReducer<Tuple4<Long, Long, Long, Long>>()).name("Reduce").output(new DiscardingOutputFormat<Tuple4<Long, Long, Long, Long>>()).name("Sink");
    Plan plan = env.createProgramPlan();
    OptimizedPlan oPlan;
    try {
        oPlan = compileNoStats(plan);
    } catch (CompilerException ce) {
        ce.printStackTrace();
        fail("The pact compiler is unable to compile this plan correctly.");
        // silence the compiler
        return;
    }
    OptimizerPlanNodeResolver resolver = getOptimizerPlanNodeResolver(oPlan);
    SinkPlanNode sinkNode = resolver.getNode("Sink");
    SingleInputPlanNode reducer = resolver.getNode("Reduce");
    // verify the strategies
    Assert.assertEquals(ShipStrategyType.FORWARD, sinkNode.getInput().getShipStrategy());
    Assert.assertEquals(ShipStrategyType.PARTITION_HASH, reducer.getInput().getShipStrategy());
    Channel c = reducer.getInput();
    Assert.assertEquals(LocalStrategy.SORT, c.getLocalStrategy());
    FieldList ship = new FieldList(1);
    FieldList local = new FieldList(1, 3);
    Assert.assertEquals(ship, c.getShipStrategyKeys());
    Assert.assertEquals(local, c.getLocalStrategyKeys());
    Assert.assertTrue(c.getLocalStrategySortOrder()[0] == reducer.getSortOrders(0)[0]);
    // check that we indeed sort descending
    Assert.assertEquals(false, c.getLocalStrategySortOrder()[1]);
}
Also used : ExecutionEnvironment(org.apache.flink.api.java.ExecutionEnvironment) Channel(org.apache.flink.optimizer.plan.Channel) Plan(org.apache.flink.api.common.Plan) OptimizedPlan(org.apache.flink.optimizer.plan.OptimizedPlan) DiscardingOutputFormat(org.apache.flink.api.java.io.DiscardingOutputFormat) OptimizedPlan(org.apache.flink.optimizer.plan.OptimizedPlan) FieldList(org.apache.flink.api.common.operators.util.FieldList) Tuple4(org.apache.flink.api.java.tuple.Tuple4) SingleInputPlanNode(org.apache.flink.optimizer.plan.SingleInputPlanNode) IdentityGroupReducer(org.apache.flink.optimizer.testfunctions.IdentityGroupReducer) SinkPlanNode(org.apache.flink.optimizer.plan.SinkPlanNode) Test(org.junit.Test)

Aggregations

OptimizedPlan (org.apache.flink.optimizer.plan.OptimizedPlan)221 Test (org.junit.Test)197 Plan (org.apache.flink.api.common.Plan)192 ExecutionEnvironment (org.apache.flink.api.java.ExecutionEnvironment)183 SinkPlanNode (org.apache.flink.optimizer.plan.SinkPlanNode)146 Tuple2 (org.apache.flink.api.java.tuple.Tuple2)91 SingleInputPlanNode (org.apache.flink.optimizer.plan.SingleInputPlanNode)83 DualInputPlanNode (org.apache.flink.optimizer.plan.DualInputPlanNode)82 JobGraphGenerator (org.apache.flink.optimizer.plantranslate.JobGraphGenerator)55 Tuple3 (org.apache.flink.api.java.tuple.Tuple3)54 SourcePlanNode (org.apache.flink.optimizer.plan.SourcePlanNode)48 DiscardingOutputFormat (org.apache.flink.api.java.io.DiscardingOutputFormat)33 InvalidProgramException (org.apache.flink.api.common.InvalidProgramException)27 FieldList (org.apache.flink.api.common.operators.util.FieldList)27 Channel (org.apache.flink.optimizer.plan.Channel)26 FieldSet (org.apache.flink.api.common.operators.util.FieldSet)25 GlobalProperties (org.apache.flink.optimizer.dataproperties.GlobalProperties)25 LocalProperties (org.apache.flink.optimizer.dataproperties.LocalProperties)25 IdentityMapper (org.apache.flink.optimizer.testfunctions.IdentityMapper)20 WorksetIterationPlanNode (org.apache.flink.optimizer.plan.WorksetIterationPlanNode)16