use of org.apache.flink.optimizer.plan.DualInputPlanNode in project flink by apache.
the class PartitioningReusageTest method reuseSinglePartitioningJoin5.
@Test
public void reuseSinglePartitioningJoin5() {
ExecutionEnvironment env = ExecutionEnvironment.getExecutionEnvironment();
DataSet<Tuple3<Integer, Integer, Integer>> set1 = env.readCsvFile(IN_FILE).types(Integer.class, Integer.class, Integer.class);
DataSet<Tuple3<Integer, Integer, Integer>> set2 = env.readCsvFile(IN_FILE).types(Integer.class, Integer.class, Integer.class);
DataSet<Tuple3<Integer, Integer, Integer>> joined = set1.join(set2.partitionByHash(2).map(new MockMapper()).withForwardedFields("2"), JoinOperatorBase.JoinHint.REPARTITION_HASH_FIRST).where(0, 1).equalTo(2, 1).with(new MockJoin());
joined.output(new DiscardingOutputFormat<Tuple3<Integer, Integer, Integer>>());
Plan plan = env.createProgramPlan();
OptimizedPlan oPlan = compileWithStats(plan);
SinkPlanNode sink = oPlan.getDataSinks().iterator().next();
DualInputPlanNode join = (DualInputPlanNode) sink.getInput().getSource();
checkValidJoinInputProperties(join);
}
use of org.apache.flink.optimizer.plan.DualInputPlanNode in project flink by apache.
the class PartitioningReusageTest method reuseBothPartitioningJoin6.
@Test
public void reuseBothPartitioningJoin6() {
ExecutionEnvironment env = ExecutionEnvironment.getExecutionEnvironment();
DataSet<Tuple3<Integer, Integer, Integer>> set1 = env.readCsvFile(IN_FILE).types(Integer.class, Integer.class, Integer.class);
DataSet<Tuple3<Integer, Integer, Integer>> set2 = env.readCsvFile(IN_FILE).types(Integer.class, Integer.class, Integer.class);
DataSet<Tuple3<Integer, Integer, Integer>> joined = set1.partitionByHash(0).map(new MockMapper()).withForwardedFields("0").join(set2.partitionByHash(1).map(new MockMapper()).withForwardedFields("1"), JoinOperatorBase.JoinHint.REPARTITION_HASH_FIRST).where(0, 2).equalTo(1, 2).with(new MockJoin());
joined.output(new DiscardingOutputFormat<Tuple3<Integer, Integer, Integer>>());
Plan plan = env.createProgramPlan();
OptimizedPlan oPlan = compileWithStats(plan);
SinkPlanNode sink = oPlan.getDataSinks().iterator().next();
DualInputPlanNode join = (DualInputPlanNode) sink.getInput().getSource();
checkValidJoinInputProperties(join);
}
use of org.apache.flink.optimizer.plan.DualInputPlanNode in project flink by apache.
the class PartitioningReusageTest method noPreviousPartitioningCoGroup1.
@Test
public void noPreviousPartitioningCoGroup1() {
ExecutionEnvironment env = ExecutionEnvironment.getExecutionEnvironment();
DataSet<Tuple3<Integer, Integer, Integer>> set1 = env.readCsvFile(IN_FILE).types(Integer.class, Integer.class, Integer.class);
DataSet<Tuple3<Integer, Integer, Integer>> set2 = env.readCsvFile(IN_FILE).types(Integer.class, Integer.class, Integer.class);
DataSet<Tuple3<Integer, Integer, Integer>> coGrouped = set1.coGroup(set2).where(0, 1).equalTo(0, 1).with(new MockCoGroup());
coGrouped.output(new DiscardingOutputFormat<Tuple3<Integer, Integer, Integer>>());
Plan plan = env.createProgramPlan();
OptimizedPlan oPlan = compileWithStats(plan);
SinkPlanNode sink = oPlan.getDataSinks().iterator().next();
DualInputPlanNode coGroup = (DualInputPlanNode) sink.getInput().getSource();
checkValidCoGroupInputProperties(coGroup);
}
use of org.apache.flink.optimizer.plan.DualInputPlanNode in project flink by apache.
the class PartitioningReusageTest method reuseBothPartitioningJoin1.
@Test
public void reuseBothPartitioningJoin1() {
ExecutionEnvironment env = ExecutionEnvironment.getExecutionEnvironment();
DataSet<Tuple3<Integer, Integer, Integer>> set1 = env.readCsvFile(IN_FILE).types(Integer.class, Integer.class, Integer.class);
DataSet<Tuple3<Integer, Integer, Integer>> set2 = env.readCsvFile(IN_FILE).types(Integer.class, Integer.class, Integer.class);
DataSet<Tuple3<Integer, Integer, Integer>> joined = set1.partitionByHash(0, 1).map(new MockMapper()).withForwardedFields("0;1").join(set2.partitionByHash(0, 1).map(new MockMapper()).withForwardedFields("0;1"), JoinOperatorBase.JoinHint.REPARTITION_HASH_FIRST).where(0, 1).equalTo(0, 1).with(new MockJoin());
joined.output(new DiscardingOutputFormat<Tuple3<Integer, Integer, Integer>>());
Plan plan = env.createProgramPlan();
OptimizedPlan oPlan = compileWithStats(plan);
SinkPlanNode sink = oPlan.getDataSinks().iterator().next();
DualInputPlanNode join = (DualInputPlanNode) sink.getInput().getSource();
checkValidJoinInputProperties(join);
}
use of org.apache.flink.optimizer.plan.DualInputPlanNode in project flink by apache.
the class PartitioningReusageTest method reuseBothPartitioningJoin4.
@Test
public void reuseBothPartitioningJoin4() {
ExecutionEnvironment env = ExecutionEnvironment.getExecutionEnvironment();
DataSet<Tuple3<Integer, Integer, Integer>> set1 = env.readCsvFile(IN_FILE).types(Integer.class, Integer.class, Integer.class);
DataSet<Tuple3<Integer, Integer, Integer>> set2 = env.readCsvFile(IN_FILE).types(Integer.class, Integer.class, Integer.class);
DataSet<Tuple3<Integer, Integer, Integer>> joined = set1.partitionByHash(0, 2).map(new MockMapper()).withForwardedFields("0;2").join(set2.partitionByHash(1).map(new MockMapper()).withForwardedFields("1"), JoinOperatorBase.JoinHint.REPARTITION_HASH_FIRST).where(0, 2).equalTo(2, 1).with(new MockJoin());
joined.output(new DiscardingOutputFormat<Tuple3<Integer, Integer, Integer>>());
Plan plan = env.createProgramPlan();
OptimizedPlan oPlan = compileWithStats(plan);
SinkPlanNode sink = oPlan.getDataSinks().iterator().next();
DualInputPlanNode join = (DualInputPlanNode) sink.getInput().getSource();
checkValidJoinInputProperties(join);
}
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