Type Members

1.  class AllWindowedStream[T, W <: Window] extends AnyRef

   A AllWindowedStream represents a data stream where the stream of elements is split into windows based on a org.apache.flink.streaming.api.windowing.assigners.WindowAssigner.

   A AllWindowedStream represents a data stream where the stream of elements is split into windows based on a org.apache.flink.streaming.api.windowing.assigners.WindowAssigner. Window emission is triggered based on a Trigger.

   If an Evictor is specified it will be used to evict elements from the window after evaluation was triggered by the Trigger but before the actual evaluation of the window. When using an evictor window performance will degrade significantly, since pre-aggregation of window results cannot be used.

   Note that the AllWindowedStream() is purely and API construct, during runtime the AllWindowedStream() will be collapsed together with the operation over the window into one single operation.

   T

   The type of elements in the stream.

   W

   The type of Window that the org.apache.flink.streaming.api.windowing.assigners.WindowAssigner assigns the elements to.

   Annotations

   @Public()

2.  class BroadcastConnectedStream[IN1, IN2] extends AnyRef
3.  trait CloseableIterator[T] extends Iterator[T] with AutoCloseable

   This interface represents an Iterator that is also AutoCloseable.

   This interface represents an Iterator that is also AutoCloseable. A typical use-case for this interface are iterators that are based on native-resources such as files, network, or database connections. Clients must call close after using the iterator.

4.  class CoGroupedStreams[T1, T2] extends AnyRef

   CoGroupedStreams represents two DataStreams that have been co-grouped.

   CoGroupedStreams represents two DataStreams that have been co-grouped. A streaming co-group operation is evaluated over elements in a window.

   To finalize the co-group operation you also need to specify a KeySelector for both the first and second input and a WindowAssigner

   Note: Right now, the groups are being built in memory so you need to ensure that they don't get too big. Otherwise the JVM might crash.

   Example:

   val one: DataStream[(String, Int)]  = ...
   val two: DataStream[(String, Int)] = ...
   
   val result = one.coGroup(two)
       .where(new MyFirstKeySelector())
       .equalTo(new MyFirstKeySelector())
       .window(TumblingEventTimeWindows.of(Time.of(5, TimeUnit.SECONDS)))
       .apply(new MyCoGroupFunction())
   }

   Annotations

   @Public()

5.  class ConnectedStreams[IN1, IN2] extends AnyRef

   ConnectedStreams represents two connected streams of (possibly) different data types.

   ConnectedStreams represents two connected streams of (possibly) different data types. Connected streams are useful for cases where operations on one stream directly affect the operations on the other stream, usually via shared state between the streams.

   An example for the use of connected streams would be to apply rules that change over time onto another stream. One of the connected streams has the rules, the other stream the elements to apply the rules to. The operation on the connected stream maintains the current set of rules in the state. It may receive either a rule update and update the state or a data element and apply the rules in the state to the element.

   The connected stream can be conceptually viewed as a union stream of an Either type, that holds either the first stream's type or the second stream's type.

   Annotations

   @Public()

6.  class DataStream[T] extends AnyRef

   Annotations

   @Public()

7.  class DataStreamUtils[T] extends AnyRef

   This class provides simple utility methods for collecting a DataStream, effectively enriching it with the functionality encapsulated by DataStreamUtils.

   This class provides simple utility methods for collecting a DataStream, effectively enriching it with the functionality encapsulated by DataStreamUtils.

   This experimental class is relocated from flink-streaming-contrib.

   Annotations

   @Experimental()

8.  class JavaKeySelector[IN, K] extends KeySelector[IN, K]

   Annotations

   @Internal()

9.  class JoinedStreams[T1, T2] extends AnyRef

   JoinedStreams represents two DataStreams that have been joined.

   JoinedStreams represents two DataStreams that have been joined. A streaming join operation is evaluated over elements in a window.

   To finalize the join operation you also need to specify a KeySelector for both the first and second input and a WindowAssigner

   Note: Right now, the groups are being built in memory so you need to ensure that they don't get too big. Otherwise the JVM might crash.

   Example:

   val one: DataStream[(String, Int)]  = ...
   val two: DataStream[(String, Int)] = ...
   
   val result = one.join(two)
       .where {t => ... }
       .equal {t => ... }
       .window(TumblingEventTimeWindows.of(Time.of(5, TimeUnit.SECONDS)))
       .apply(new MyJoinFunction())
   }

   Annotations

   @Public()

10.  class KeyedStream[T, K] extends DataStream[T]

    Annotations

    @Public()

11.  class OutputTag[T] extends flink.util.OutputTag[T]

    An OutputTag is a typed and named tag to use for tagging side outputs of an operator.

    An OutputTag is a typed and named tag to use for tagging side outputs of an operator.

    Example:

    val outputTag = OutputTag[String]("late-data")

    T

    the type of elements in the side-output stream.

    Annotations

    @PublicEvolving()

12.  class ReturnStatementInClosureException extends FlinkException
13.  class StreamExecutionEnvironment extends AnyRef

    Annotations

    @Public()

14.  class WindowedStream[T, K, W <: Window] extends AnyRef

    A WindowedStream represents a data stream where elements are grouped by key, and for each key, the stream of elements is split into windows based on a org.apache.flink.streaming.api.windowing.assigners.WindowAssigner.

    A WindowedStream represents a data stream where elements are grouped by key, and for each key, the stream of elements is split into windows based on a org.apache.flink.streaming.api.windowing.assigners.WindowAssigner. Window emission is triggered based on a Trigger.

    The windows are conceptually evaluated for each key individually, meaning windows can trigger at different points for each key.

    If an org.apache.flink.streaming.api.windowing.evictors.Evictor is specified it will be used to evict elements from the window after evaluation was triggered by the Trigger but before the actual evaluation of the window. When using an evictor window performance will degrade significantly, since pre-aggregation of window results cannot be used.

    Note that the WindowedStream is purely and API construct, during runtime the WindowedStream will be collapsed together with the KeyedStream and the operation over the window into one single operation.

    T

    The type of elements in the stream.

    K

    The type of the key by which elements are grouped.

    W

    The type of Window that the org.apache.flink.streaming.api.windowing.assigners.WindowAssigner assigns the elements to.

    Annotations

    @Public()