use of org.apache.flink.optimizer.plan.OptimizedPlan in project flink by apache.
the class CoGroupCustomPartitioningTest method testIncompatibleHashAndCustomPartitioning.
@Test
public void testIncompatibleHashAndCustomPartitioning() {
try {
ExecutionEnvironment env = ExecutionEnvironment.getExecutionEnvironment();
DataSet<Tuple3<Long, Long, Long>> input = env.fromElements(new Tuple3<Long, Long, Long>(0L, 0L, 0L));
DataSet<Tuple3<Long, Long, Long>> partitioned = input.partitionCustom(new Partitioner<Long>() {
@Override
public int partition(Long key, int numPartitions) {
return 0;
}
}, 0).map(new IdentityMapper<Tuple3<Long, Long, Long>>()).withForwardedFields("0", "1", "2");
DataSet<Tuple3<Long, Long, Long>> grouped = partitioned.distinct(0, 1).groupBy(1).sortGroup(0, Order.ASCENDING).reduceGroup(new IdentityGroupReducerCombinable<Tuple3<Long, Long, Long>>()).withForwardedFields("0", "1");
grouped.coGroup(partitioned).where(0).equalTo(0).with(new DummyCoGroupFunction<Tuple3<Long, Long, Long>, Tuple3<Long, Long, Long>>()).output(new DiscardingOutputFormat<Tuple2<Tuple3<Long, Long, Long>, Tuple3<Long, Long, Long>>>());
Plan p = env.createProgramPlan();
OptimizedPlan op = compileNoStats(p);
SinkPlanNode sink = op.getDataSinks().iterator().next();
DualInputPlanNode coGroup = (DualInputPlanNode) sink.getInput().getSource();
assertEquals(ShipStrategyType.PARTITION_HASH, coGroup.getInput1().getShipStrategy());
assertTrue(coGroup.getInput2().getShipStrategy() == ShipStrategyType.PARTITION_HASH || coGroup.getInput2().getShipStrategy() == ShipStrategyType.FORWARD);
} catch (Exception e) {
e.printStackTrace();
fail(e.getMessage());
}
}
use of org.apache.flink.optimizer.plan.OptimizedPlan in project flink by apache.
the class CoGroupCustomPartitioningTest method testCoGroupWithTuples.
@Test
public void testCoGroupWithTuples() {
try {
final Partitioner<Long> partitioner = new TestPartitionerLong();
ExecutionEnvironment env = ExecutionEnvironment.getExecutionEnvironment();
DataSet<Tuple2<Long, Long>> input1 = env.fromElements(new Tuple2<Long, Long>(0L, 0L));
DataSet<Tuple3<Long, Long, Long>> input2 = env.fromElements(new Tuple3<Long, Long, Long>(0L, 0L, 0L));
input1.coGroup(input2).where(1).equalTo(0).withPartitioner(partitioner).with(new DummyCoGroupFunction<Tuple2<Long, Long>, Tuple3<Long, Long, Long>>()).output(new DiscardingOutputFormat<Tuple2<Tuple2<Long, Long>, Tuple3<Long, Long, Long>>>());
Plan p = env.createProgramPlan();
OptimizedPlan op = compileNoStats(p);
SinkPlanNode sink = op.getDataSinks().iterator().next();
DualInputPlanNode join = (DualInputPlanNode) sink.getInput().getSource();
assertEquals(ShipStrategyType.PARTITION_CUSTOM, join.getInput1().getShipStrategy());
assertEquals(ShipStrategyType.PARTITION_CUSTOM, join.getInput2().getShipStrategy());
assertEquals(partitioner, join.getInput1().getPartitioner());
assertEquals(partitioner, join.getInput2().getPartitioner());
} catch (Exception e) {
e.printStackTrace();
fail(e.getMessage());
}
}
use of org.apache.flink.optimizer.plan.OptimizedPlan in project flink by apache.
the class CustomPartitioningGlobalOptimizationTest method testJoinReduceCombination.
@Test
public void testJoinReduceCombination() {
try {
final Partitioner<Long> partitioner = new TestPartitionerLong();
ExecutionEnvironment env = ExecutionEnvironment.getExecutionEnvironment();
DataSet<Tuple2<Long, Long>> input1 = env.fromElements(new Tuple2<Long, Long>(0L, 0L));
DataSet<Tuple3<Long, Long, Long>> input2 = env.fromElements(new Tuple3<Long, Long, Long>(0L, 0L, 0L));
DataSet<Tuple3<Long, Long, Long>> joined = input1.join(input2).where(1).equalTo(0).projectFirst(0, 1).<Tuple3<Long, Long, Long>>projectSecond(2).withPartitioner(partitioner);
joined.groupBy(1).withPartitioner(partitioner).reduceGroup(new IdentityGroupReducerCombinable<Tuple3<Long, Long, Long>>()).output(new DiscardingOutputFormat<Tuple3<Long, Long, Long>>());
Plan p = env.createProgramPlan();
OptimizedPlan op = compileNoStats(p);
SinkPlanNode sink = op.getDataSinks().iterator().next();
SingleInputPlanNode reducer = (SingleInputPlanNode) sink.getInput().getSource();
assertTrue("Reduce is not chained, property reuse does not happen", reducer.getInput().getSource() instanceof DualInputPlanNode);
DualInputPlanNode join = (DualInputPlanNode) reducer.getInput().getSource();
assertEquals(ShipStrategyType.PARTITION_CUSTOM, join.getInput1().getShipStrategy());
assertEquals(ShipStrategyType.PARTITION_CUSTOM, join.getInput2().getShipStrategy());
assertEquals(partitioner, join.getInput1().getPartitioner());
assertEquals(partitioner, join.getInput2().getPartitioner());
assertEquals(ShipStrategyType.FORWARD, reducer.getInput().getShipStrategy());
} catch (Exception e) {
e.printStackTrace();
fail(e.getMessage());
}
}
use of org.apache.flink.optimizer.plan.OptimizedPlan in project flink by apache.
the class CustomPartitioningTest method testPartitionTuples.
@Test
public void testPartitionTuples() {
try {
final Partitioner<Integer> part = new TestPartitionerInt();
final int parallelism = 4;
ExecutionEnvironment env = ExecutionEnvironment.getExecutionEnvironment();
env.setParallelism(parallelism);
DataSet<Tuple2<Integer, Integer>> data = env.fromElements(new Tuple2<Integer, Integer>(0, 0)).rebalance();
data.partitionCustom(part, 0).mapPartition(new IdentityPartitionerMapper<Tuple2<Integer, Integer>>()).output(new DiscardingOutputFormat<Tuple2<Integer, Integer>>());
Plan p = env.createProgramPlan();
OptimizedPlan op = compileNoStats(p);
SinkPlanNode sink = op.getDataSinks().iterator().next();
SingleInputPlanNode mapper = (SingleInputPlanNode) sink.getInput().getSource();
SingleInputPlanNode partitioner = (SingleInputPlanNode) mapper.getInput().getSource();
SingleInputPlanNode balancer = (SingleInputPlanNode) partitioner.getInput().getSource();
assertEquals(ShipStrategyType.FORWARD, sink.getInput().getShipStrategy());
assertEquals(parallelism, sink.getParallelism());
assertEquals(ShipStrategyType.FORWARD, mapper.getInput().getShipStrategy());
assertEquals(parallelism, mapper.getParallelism());
assertEquals(ShipStrategyType.PARTITION_CUSTOM, partitioner.getInput().getShipStrategy());
assertEquals(part, partitioner.getInput().getPartitioner());
assertEquals(parallelism, partitioner.getParallelism());
assertEquals(ShipStrategyType.PARTITION_FORCED_REBALANCE, balancer.getInput().getShipStrategy());
assertEquals(parallelism, balancer.getParallelism());
} catch (Exception e) {
e.printStackTrace();
fail(e.getMessage());
}
}
use of org.apache.flink.optimizer.plan.OptimizedPlan in project flink by apache.
the class CustomPartitioningTest method testPartitionPojo.
@Test
public void testPartitionPojo() {
try {
final Partitioner<Integer> part = new TestPartitionerInt();
final int parallelism = 4;
ExecutionEnvironment env = ExecutionEnvironment.getExecutionEnvironment();
env.setParallelism(parallelism);
DataSet<Pojo> data = env.fromElements(new Pojo()).rebalance();
data.partitionCustom(part, "a").mapPartition(new IdentityPartitionerMapper<Pojo>()).output(new DiscardingOutputFormat<Pojo>());
Plan p = env.createProgramPlan();
OptimizedPlan op = compileNoStats(p);
SinkPlanNode sink = op.getDataSinks().iterator().next();
SingleInputPlanNode mapper = (SingleInputPlanNode) sink.getInput().getSource();
SingleInputPlanNode partitioner = (SingleInputPlanNode) mapper.getInput().getSource();
SingleInputPlanNode balancer = (SingleInputPlanNode) partitioner.getInput().getSource();
assertEquals(ShipStrategyType.FORWARD, sink.getInput().getShipStrategy());
assertEquals(parallelism, sink.getParallelism());
assertEquals(ShipStrategyType.FORWARD, mapper.getInput().getShipStrategy());
assertEquals(parallelism, mapper.getParallelism());
assertEquals(ShipStrategyType.PARTITION_CUSTOM, partitioner.getInput().getShipStrategy());
assertEquals(part, partitioner.getInput().getPartitioner());
assertEquals(parallelism, partitioner.getParallelism());
assertEquals(ShipStrategyType.PARTITION_FORCED_REBALANCE, balancer.getInput().getShipStrategy());
assertEquals(parallelism, balancer.getParallelism());
} catch (Exception e) {
e.printStackTrace();
fail(e.getMessage());
}
}
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