Package org.apache.flink.runtime.io.network.partition.consumer

Class SingleInputGate

java.lang.Object
org.apache.flink.runtime.io.network.partition.consumer.InputGate
org.apache.flink.runtime.io.network.partition.consumer.IndexedInputGate
org.apache.flink.runtime.io.network.partition.consumer.SingleInputGate
All Implemented Interfaces:
AutoCloseable, AvailabilityProvider, ChannelStateHolder, CheckpointableInput, PullingAsyncDataInput<BufferOrEvent>
public class SingleInputGate extends IndexedInputGate
An input gate consumes one or more partitions of a single produced intermediate result.

Each intermediate result is partitioned over its producing parallel subtasks; each of these partitions is furthermore partitioned into one or more subpartitions.

As an example, consider a map-reduce program, where the map operator produces data and the reduce operator consumes the produced data. 


 +-----+              +---------------------+              +--------+
 | Map | = produce => | Intermediate Result | <= consume = | Reduce |
 +-----+              +---------------------+              +--------+

When deploying such a program in parallel, the intermediate result will be partitioned over its producing parallel subtasks; each of these partitions is furthermore partitioned into one or more subpartitions. 


                            Intermediate result
               +-----------------------------------------+
               |                      +----------------+ |              +-----------------------+
 +-------+     | +-------------+  +=> | Subpartition 1 | | <=======+=== | Input Gate | Reduce 1 |
 | Map 1 | ==> | | Partition 1 | =|   +----------------+ |         |    +-----------------------+
 +-------+     | +-------------+  +=> | Subpartition 2 | | <==+    |
               |                      +----------------+ |    |    | Subpartition request
               |                                         |    |    |
               |                      +----------------+ |    |    |
 +-------+     | +-------------+  +=> | Subpartition 1 | | <==+====+
 | Map 2 | ==> | | Partition 2 | =|   +----------------+ |    |         +-----------------------+
 +-------+     | +-------------+  +=> | Subpartition 2 | | <==+======== | Input Gate | Reduce 2 |
               |                      +----------------+ |              +-----------------------+
               +-----------------------------------------+

In the above example, two map subtasks produce the intermediate result in parallel, resulting in two partitions (Partition 1 and 2). Each of these partitions is further partitioned into two subpartitions -- one for each parallel reduce subtask.