Search in sources :

Example 16 with ShipStrategyType

use of org.apache.flink.runtime.operators.shipping.ShipStrategyType in project flink by apache.

the class ReplicatingDataSourceTest method checkJoinWithReplicatedSourceInputBehindMap.

/**
 * Tests join program with replicated data source behind map.
 */
@Test
public void checkJoinWithReplicatedSourceInputBehindMap() {
    ExecutionEnvironment env = ExecutionEnvironment.createLocalEnvironment();
    env.setParallelism(DEFAULT_PARALLELISM);
    TupleTypeInfo<Tuple1<String>> typeInfo = TupleTypeInfo.getBasicTupleTypeInfo(String.class);
    ReplicatingInputFormat<Tuple1<String>, FileInputSplit> rif = new ReplicatingInputFormat<Tuple1<String>, FileInputSplit>(new TupleCsvInputFormat<Tuple1<String>>(new Path("/some/path"), typeInfo));
    DataSet<Tuple1<String>> source1 = env.createInput(rif, new TupleTypeInfo<Tuple1<String>>(BasicTypeInfo.STRING_TYPE_INFO));
    DataSet<Tuple1<String>> source2 = env.readCsvFile("/some/otherpath").types(String.class);
    DataSink<Tuple2<Tuple1<String>, Tuple1<String>>> out = source1.map(new IdMap()).join(source2).where("*").equalTo("*").writeAsText("/some/newpath");
    Plan plan = env.createProgramPlan();
    // submit the plan to the compiler
    OptimizedPlan oPlan = compileNoStats(plan);
    // check the optimized Plan
    // when join should have forward strategy on both sides
    SinkPlanNode sinkNode = oPlan.getDataSinks().iterator().next();
    DualInputPlanNode joinNode = (DualInputPlanNode) sinkNode.getPredecessor();
    ShipStrategyType joinIn1 = joinNode.getInput1().getShipStrategy();
    ShipStrategyType joinIn2 = joinNode.getInput2().getShipStrategy();
    Assert.assertEquals("Invalid ship strategy for an operator.", ShipStrategyType.FORWARD, joinIn1);
    Assert.assertEquals("Invalid ship strategy for an operator.", ShipStrategyType.FORWARD, joinIn2);
}
Also used : Path(org.apache.flink.core.fs.Path) ExecutionEnvironment(org.apache.flink.api.java.ExecutionEnvironment) Plan(org.apache.flink.api.common.Plan) OptimizedPlan(org.apache.flink.optimizer.plan.OptimizedPlan) OptimizedPlan(org.apache.flink.optimizer.plan.OptimizedPlan) ShipStrategyType(org.apache.flink.runtime.operators.shipping.ShipStrategyType) DualInputPlanNode(org.apache.flink.optimizer.plan.DualInputPlanNode) FileInputSplit(org.apache.flink.core.fs.FileInputSplit) ReplicatingInputFormat(org.apache.flink.api.common.io.ReplicatingInputFormat) Tuple1(org.apache.flink.api.java.tuple.Tuple1) Tuple2(org.apache.flink.api.java.tuple.Tuple2) SinkPlanNode(org.apache.flink.optimizer.plan.SinkPlanNode) Test(org.junit.Test)

Example 17 with ShipStrategyType

use of org.apache.flink.runtime.operators.shipping.ShipStrategyType in project flink by apache.

the class ReplicatingDataSourceTest method checkJoinWithReplicatedSourceInputBehindFilter.

/**
 * Tests join program with replicated data source behind filter.
 */
@Test
public void checkJoinWithReplicatedSourceInputBehindFilter() {
    ExecutionEnvironment env = ExecutionEnvironment.createLocalEnvironment();
    env.setParallelism(DEFAULT_PARALLELISM);
    TupleTypeInfo<Tuple1<String>> typeInfo = TupleTypeInfo.getBasicTupleTypeInfo(String.class);
    ReplicatingInputFormat<Tuple1<String>, FileInputSplit> rif = new ReplicatingInputFormat<Tuple1<String>, FileInputSplit>(new TupleCsvInputFormat<Tuple1<String>>(new Path("/some/path"), typeInfo));
    DataSet<Tuple1<String>> source1 = env.createInput(rif, new TupleTypeInfo<Tuple1<String>>(BasicTypeInfo.STRING_TYPE_INFO));
    DataSet<Tuple1<String>> source2 = env.readCsvFile("/some/otherpath").types(String.class);
    DataSink<Tuple2<Tuple1<String>, Tuple1<String>>> out = source1.filter(new NoFilter()).join(source2).where("*").equalTo("*").writeAsText("/some/newpath");
    Plan plan = env.createProgramPlan();
    // submit the plan to the compiler
    OptimizedPlan oPlan = compileNoStats(plan);
    // check the optimized Plan
    // when join should have forward strategy on both sides
    SinkPlanNode sinkNode = oPlan.getDataSinks().iterator().next();
    DualInputPlanNode joinNode = (DualInputPlanNode) sinkNode.getPredecessor();
    ShipStrategyType joinIn1 = joinNode.getInput1().getShipStrategy();
    ShipStrategyType joinIn2 = joinNode.getInput2().getShipStrategy();
    Assert.assertEquals("Invalid ship strategy for an operator.", ShipStrategyType.FORWARD, joinIn1);
    Assert.assertEquals("Invalid ship strategy for an operator.", ShipStrategyType.FORWARD, joinIn2);
}
Also used : Path(org.apache.flink.core.fs.Path) ExecutionEnvironment(org.apache.flink.api.java.ExecutionEnvironment) Plan(org.apache.flink.api.common.Plan) OptimizedPlan(org.apache.flink.optimizer.plan.OptimizedPlan) OptimizedPlan(org.apache.flink.optimizer.plan.OptimizedPlan) ShipStrategyType(org.apache.flink.runtime.operators.shipping.ShipStrategyType) DualInputPlanNode(org.apache.flink.optimizer.plan.DualInputPlanNode) FileInputSplit(org.apache.flink.core.fs.FileInputSplit) ReplicatingInputFormat(org.apache.flink.api.common.io.ReplicatingInputFormat) Tuple1(org.apache.flink.api.java.tuple.Tuple1) Tuple2(org.apache.flink.api.java.tuple.Tuple2) SinkPlanNode(org.apache.flink.optimizer.plan.SinkPlanNode) Test(org.junit.Test)

Example 18 with ShipStrategyType

use of org.apache.flink.runtime.operators.shipping.ShipStrategyType in project flink by apache.

the class ReplicatingDataSourceTest method checkJoinWithReplicatedSourceInputBehindMultiMaps.

/**
 * Tests join program with replicated data source behind multiple map ops.
 */
@Test
public void checkJoinWithReplicatedSourceInputBehindMultiMaps() {
    ExecutionEnvironment env = ExecutionEnvironment.createLocalEnvironment();
    env.setParallelism(DEFAULT_PARALLELISM);
    TupleTypeInfo<Tuple1<String>> typeInfo = TupleTypeInfo.getBasicTupleTypeInfo(String.class);
    ReplicatingInputFormat<Tuple1<String>, FileInputSplit> rif = new ReplicatingInputFormat<Tuple1<String>, FileInputSplit>(new TupleCsvInputFormat<Tuple1<String>>(new Path("/some/path"), typeInfo));
    DataSet<Tuple1<String>> source1 = env.createInput(rif, new TupleTypeInfo<Tuple1<String>>(BasicTypeInfo.STRING_TYPE_INFO));
    DataSet<Tuple1<String>> source2 = env.readCsvFile("/some/otherpath").types(String.class);
    DataSink<Tuple2<Tuple1<String>, Tuple1<String>>> out = source1.filter(new NoFilter()).mapPartition(new IdPMap()).flatMap(new IdFlatMap()).map(new IdMap()).join(source2).where("*").equalTo("*").writeAsText("/some/newpath");
    Plan plan = env.createProgramPlan();
    // submit the plan to the compiler
    OptimizedPlan oPlan = compileNoStats(plan);
    // check the optimized Plan
    // when join should have forward strategy on both sides
    SinkPlanNode sinkNode = oPlan.getDataSinks().iterator().next();
    DualInputPlanNode joinNode = (DualInputPlanNode) sinkNode.getPredecessor();
    ShipStrategyType joinIn1 = joinNode.getInput1().getShipStrategy();
    ShipStrategyType joinIn2 = joinNode.getInput2().getShipStrategy();
    Assert.assertEquals("Invalid ship strategy for an operator.", ShipStrategyType.FORWARD, joinIn1);
    Assert.assertEquals("Invalid ship strategy for an operator.", ShipStrategyType.FORWARD, joinIn2);
}
Also used : Path(org.apache.flink.core.fs.Path) ExecutionEnvironment(org.apache.flink.api.java.ExecutionEnvironment) Plan(org.apache.flink.api.common.Plan) OptimizedPlan(org.apache.flink.optimizer.plan.OptimizedPlan) OptimizedPlan(org.apache.flink.optimizer.plan.OptimizedPlan) ShipStrategyType(org.apache.flink.runtime.operators.shipping.ShipStrategyType) DualInputPlanNode(org.apache.flink.optimizer.plan.DualInputPlanNode) FileInputSplit(org.apache.flink.core.fs.FileInputSplit) ReplicatingInputFormat(org.apache.flink.api.common.io.ReplicatingInputFormat) Tuple1(org.apache.flink.api.java.tuple.Tuple1) Tuple2(org.apache.flink.api.java.tuple.Tuple2) SinkPlanNode(org.apache.flink.optimizer.plan.SinkPlanNode) Test(org.junit.Test)

Example 19 with ShipStrategyType

use of org.apache.flink.runtime.operators.shipping.ShipStrategyType in project flink by apache.

the class ParallelismChangeTest method checkPropertyHandlingWithIncreasingGlobalParallelism1.

/**
 * Simple Job: Map -> Reduce -> Map -> Reduce. All functions preserve all fields (hence all
 * properties).
 *
 * <p>Increases parallelism between 1st reduce and 2nd map, so the hash partitioning from 1st
 * reduce is not reusable. Expected to re-establish partitioning between reduce and map, via
 * hash, because random is a full network transit as well.
 */
@Test
public void checkPropertyHandlingWithIncreasingGlobalParallelism1() {
    final int p = DEFAULT_PARALLELISM;
    // construct the plan
    ExecutionEnvironment env = ExecutionEnvironment.getExecutionEnvironment();
    env.setParallelism(p);
    DataSet<Long> set1 = env.generateSequence(0, 1).setParallelism(p);
    set1.map(new IdentityMapper<Long>()).withForwardedFields("*").setParallelism(p).name("Map1").groupBy("*").reduceGroup(new IdentityGroupReducer<Long>()).withForwardedFields("*").setParallelism(p).name("Reduce1").map(new IdentityMapper<Long>()).withForwardedFields("*").setParallelism(p * 2).name("Map2").groupBy("*").reduceGroup(new IdentityGroupReducer<Long>()).withForwardedFields("*").setParallelism(p * 2).name("Reduce2").output(new DiscardingOutputFormat<Long>()).setParallelism(p * 2).name("Sink");
    Plan plan = env.createProgramPlan();
    // submit the plan to the compiler
    OptimizedPlan oPlan = compileNoStats(plan);
    // check the optimized Plan
    // when reducer 1 distributes its data across the instances of map2, it needs to employ a
    // local hash method,
    // because map2 has twice as many instances and key/value pairs with the same key need to be
    // processed by the same
    // mapper respectively reducer
    SinkPlanNode sinkNode = oPlan.getDataSinks().iterator().next();
    SingleInputPlanNode red2Node = (SingleInputPlanNode) sinkNode.getPredecessor();
    SingleInputPlanNode map2Node = (SingleInputPlanNode) red2Node.getPredecessor();
    ShipStrategyType mapIn = map2Node.getInput().getShipStrategy();
    ShipStrategyType redIn = red2Node.getInput().getShipStrategy();
    Assert.assertEquals("Invalid ship strategy for an operator.", ShipStrategyType.PARTITION_HASH, mapIn);
    Assert.assertEquals("Invalid ship strategy for an operator.", ShipStrategyType.FORWARD, redIn);
}
Also used : ExecutionEnvironment(org.apache.flink.api.java.ExecutionEnvironment) Plan(org.apache.flink.api.common.Plan) OptimizedPlan(org.apache.flink.optimizer.plan.OptimizedPlan) OptimizedPlan(org.apache.flink.optimizer.plan.OptimizedPlan) ShipStrategyType(org.apache.flink.runtime.operators.shipping.ShipStrategyType) SingleInputPlanNode(org.apache.flink.optimizer.plan.SingleInputPlanNode) IdentityMapper(org.apache.flink.optimizer.testfunctions.IdentityMapper) IdentityGroupReducer(org.apache.flink.optimizer.testfunctions.IdentityGroupReducer) SinkPlanNode(org.apache.flink.optimizer.plan.SinkPlanNode) Test(org.junit.Test)

Example 20 with ShipStrategyType

use of org.apache.flink.runtime.operators.shipping.ShipStrategyType in project flink by apache.

the class ParallelismChangeTest method checkPropertyHandlingWithIncreasingLocalParallelism.

/**
 * Simple Job: Map -> Reduce -> Map -> Reduce. All functions preserve all fields (hence all
 * properties).
 *
 * <p>Increases parallelism between 1st reduce and 2nd map, such that more tasks are on one
 * instance. Expected to re-establish partitioning between map and reduce via a local hash.
 */
@Test
public void checkPropertyHandlingWithIncreasingLocalParallelism() {
    final int p = DEFAULT_PARALLELISM * 2;
    // construct the plan
    ExecutionEnvironment env = ExecutionEnvironment.getExecutionEnvironment();
    env.setParallelism(p);
    DataSet<Long> set1 = env.generateSequence(0, 1).setParallelism(p);
    set1.map(new IdentityMapper<Long>()).withForwardedFields("*").setParallelism(p).name("Map1").groupBy("*").reduceGroup(new IdentityGroupReducer<Long>()).withForwardedFields("*").setParallelism(p).name("Reduce1").map(new IdentityMapper<Long>()).withForwardedFields("*").setParallelism(p * 2).name("Map2").groupBy("*").reduceGroup(new IdentityGroupReducer<Long>()).withForwardedFields("*").setParallelism(p * 2).name("Reduce2").output(new DiscardingOutputFormat<Long>()).setParallelism(p * 2).name("Sink");
    Plan plan = env.createProgramPlan();
    // submit the plan to the compiler
    OptimizedPlan oPlan = compileNoStats(plan);
    // check the optimized Plan
    // when reducer 1 distributes its data across the instances of map2, it needs to employ a
    // local hash method,
    // because map2 has twice as many instances and key/value pairs with the same key need to be
    // processed by the same
    // mapper respectively reducer
    SinkPlanNode sinkNode = oPlan.getDataSinks().iterator().next();
    SingleInputPlanNode red2Node = (SingleInputPlanNode) sinkNode.getPredecessor();
    SingleInputPlanNode map2Node = (SingleInputPlanNode) red2Node.getPredecessor();
    ShipStrategyType mapIn = map2Node.getInput().getShipStrategy();
    ShipStrategyType reduceIn = red2Node.getInput().getShipStrategy();
    Assert.assertTrue("Invalid ship strategy for an operator.", (ShipStrategyType.PARTITION_RANDOM == mapIn && ShipStrategyType.PARTITION_HASH == reduceIn) || (ShipStrategyType.PARTITION_HASH == mapIn && ShipStrategyType.FORWARD == reduceIn));
}
Also used : ExecutionEnvironment(org.apache.flink.api.java.ExecutionEnvironment) Plan(org.apache.flink.api.common.Plan) OptimizedPlan(org.apache.flink.optimizer.plan.OptimizedPlan) OptimizedPlan(org.apache.flink.optimizer.plan.OptimizedPlan) ShipStrategyType(org.apache.flink.runtime.operators.shipping.ShipStrategyType) SingleInputPlanNode(org.apache.flink.optimizer.plan.SingleInputPlanNode) IdentityMapper(org.apache.flink.optimizer.testfunctions.IdentityMapper) IdentityGroupReducer(org.apache.flink.optimizer.testfunctions.IdentityGroupReducer) SinkPlanNode(org.apache.flink.optimizer.plan.SinkPlanNode) Test(org.junit.Test)

Aggregations

ShipStrategyType (org.apache.flink.runtime.operators.shipping.ShipStrategyType)23 Plan (org.apache.flink.api.common.Plan)13 OptimizedPlan (org.apache.flink.optimizer.plan.OptimizedPlan)13 Test (org.junit.Test)13 SinkPlanNode (org.apache.flink.optimizer.plan.SinkPlanNode)12 ExecutionEnvironment (org.apache.flink.api.java.ExecutionEnvironment)11 DualInputPlanNode (org.apache.flink.optimizer.plan.DualInputPlanNode)11 ReplicatingInputFormat (org.apache.flink.api.common.io.ReplicatingInputFormat)8 Tuple1 (org.apache.flink.api.java.tuple.Tuple1)8 Tuple2 (org.apache.flink.api.java.tuple.Tuple2)8 FileInputSplit (org.apache.flink.core.fs.FileInputSplit)8 Path (org.apache.flink.core.fs.Path)8 CompilerException (org.apache.flink.optimizer.CompilerException)8 SingleInputPlanNode (org.apache.flink.optimizer.plan.SingleInputPlanNode)8 Channel (org.apache.flink.optimizer.plan.Channel)5 PlanNode (org.apache.flink.optimizer.plan.PlanNode)5 DataExchangeMode (org.apache.flink.runtime.io.network.DataExchangeMode)5 ArrayList (java.util.ArrayList)4 NamedChannel (org.apache.flink.optimizer.plan.NamedChannel)4 Set (java.util.Set)3