class KGroupedStream[K, V] extends AnyRef
Wraps the Java class KGroupedStream and delegates method calls to the underlying Java object.
- K
Type of keys
- V
Type of values
- See also
org.apache.kafka.streams.kstream.KGroupedStream
- Alphabetic
- By Inheritance
- KGroupedStream
- AnyRef
- Any
- Hide All
- Show All
- Public
- Protected
Instance Constructors
- new KGroupedStream(inner: kstream.KGroupedStream[K, V])
- inner
The underlying Java abstraction for KGroupedStream
Value Members
- final def !=(arg0: Any): Boolean
- Definition Classes
- AnyRef → Any
- final def ##: Int
- Definition Classes
- AnyRef → Any
- final def ==(arg0: Any): Boolean
- Definition Classes
- AnyRef → Any
- def aggregate[VR](initializer: => VR, named: Named)(aggregator: (K, V, VR) => VR)(implicit materialized: Materialized[K, VR, ByteArrayKeyValueStore]): KTable[K, VR]
Aggregate the values of records in this stream by the grouped key.
Aggregate the values of records in this stream by the grouped key.
- initializer
an
Initializer
that computes an initial intermediate aggregation result- named
a Named config used to name the processor in the topology
- aggregator
an
Aggregator
that computes a new aggregate result- materialized
an instance of
Materialized
used to materialize a state store.- returns
a KTable that contains "update" records with unmodified keys, and values that represent the latest (rolling) aggregate for each key
- See also
org.apache.kafka.streams.kstream.KGroupedStream#aggregate
- def aggregate[VR](initializer: => VR)(aggregator: (K, V, VR) => VR)(implicit materialized: Materialized[K, VR, ByteArrayKeyValueStore]): KTable[K, VR]
Aggregate the values of records in this stream by the grouped key.
Aggregate the values of records in this stream by the grouped key.
- initializer
an
Initializer
that computes an initial intermediate aggregation result- aggregator
an
Aggregator
that computes a new aggregate result- materialized
an instance of
Materialized
used to materialize a state store.- returns
a KTable that contains "update" records with unmodified keys, and values that represent the latest (rolling) aggregate for each key
- See also
org.apache.kafka.streams.kstream.KGroupedStream#aggregate
- final def asInstanceOf[T0]: T0
- Definition Classes
- Any
- def clone(): AnyRef
- Attributes
- protected[lang]
- Definition Classes
- AnyRef
- Annotations
- @throws(classOf[java.lang.CloneNotSupportedException]) @native()
- def cogroup[VR](aggregator: (K, V, VR) => VR): CogroupedKStream[K, VR]
Create a new CogroupedKStream from this grouped KStream to allow cogrouping other KGroupedStream to it.
Create a new CogroupedKStream from this grouped KStream to allow cogrouping other KGroupedStream to it.
- aggregator
an
Aggregator
that computes a new aggregate result- returns
an instance of CogroupedKStream
- See also
org.apache.kafka.streams.kstream.KGroupedStream#cogroup
- def count(named: Named)(implicit materialized: Materialized[K, Long, ByteArrayKeyValueStore]): KTable[K, Long]
Count the number of records in this stream by the grouped key.
Count the number of records in this stream by the grouped key. The result is written into a local
KeyValueStore
(which is basically an ever-updating materialized view) provided by the givenmaterialized
.- named
a Named config used to name the processor in the topology
- materialized
an instance of
Materialized
used to materialize a state store.- returns
a KTable that contains "update" records with unmodified keys and
Long
values that represent the latest (rolling) count (i.e., number of records) for each key
- See also
org.apache.kafka.streams.kstream.KGroupedStream#count
- def count()(implicit materialized: Materialized[K, Long, ByteArrayKeyValueStore]): KTable[K, Long]
Count the number of records in this stream by the grouped key.
Count the number of records in this stream by the grouped key. The result is written into a local
KeyValueStore
(which is basically an ever-updating materialized view) provided by the givenmaterialized
.- materialized
an instance of
Materialized
used to materialize a state store.- returns
a KTable that contains "update" records with unmodified keys and
Long
values that represent the latest (rolling) count (i.e., number of records) for each key
- See also
org.apache.kafka.streams.kstream.KGroupedStream#count
- final def eq(arg0: AnyRef): Boolean
- Definition Classes
- AnyRef
- def equals(arg0: AnyRef): Boolean
- Definition Classes
- AnyRef → Any
- def finalize(): Unit
- Attributes
- protected[lang]
- Definition Classes
- AnyRef
- Annotations
- @throws(classOf[java.lang.Throwable])
- final def getClass(): Class[_ <: AnyRef]
- Definition Classes
- AnyRef → Any
- Annotations
- @native()
- def hashCode(): Int
- Definition Classes
- AnyRef → Any
- Annotations
- @native()
- val inner: kstream.KGroupedStream[K, V]
- final def isInstanceOf[T0]: Boolean
- Definition Classes
- Any
- final def ne(arg0: AnyRef): Boolean
- Definition Classes
- AnyRef
- final def notify(): Unit
- Definition Classes
- AnyRef
- Annotations
- @native()
- final def notifyAll(): Unit
- Definition Classes
- AnyRef
- Annotations
- @native()
- def reduce(reducer: (V, V) => V, named: Named)(implicit materialized: Materialized[K, V, ByteArrayKeyValueStore]): KTable[K, V]
Combine the values of records in this stream by the grouped key.
Combine the values of records in this stream by the grouped key.
- reducer
a function
(V, V) => V
that computes a new aggregate result.- named
a Named config used to name the processor in the topology
- materialized
an instance of
Materialized
used to materialize a state store.- returns
a KTable that contains "update" records with unmodified keys, and values that represent the latest (rolling) aggregate for each key
- See also
org.apache.kafka.streams.kstream.KGroupedStream#reduce
- def reduce(reducer: (V, V) => V)(implicit materialized: Materialized[K, V, ByteArrayKeyValueStore]): KTable[K, V]
Combine the values of records in this stream by the grouped key.
Combine the values of records in this stream by the grouped key.
- reducer
a function
(V, V) => V
that computes a new aggregate result.- materialized
an instance of
Materialized
used to materialize a state store.- returns
a KTable that contains "update" records with unmodified keys, and values that represent the latest (rolling) aggregate for each key
- See also
org.apache.kafka.streams.kstream.KGroupedStream#reduce
- final def synchronized[T0](arg0: => T0): T0
- Definition Classes
- AnyRef
- def toString(): String
- Definition Classes
- AnyRef → Any
- final def wait(): Unit
- Definition Classes
- AnyRef
- Annotations
- @throws(classOf[java.lang.InterruptedException])
- final def wait(arg0: Long, arg1: Int): Unit
- Definition Classes
- AnyRef
- Annotations
- @throws(classOf[java.lang.InterruptedException])
- final def wait(arg0: Long): Unit
- Definition Classes
- AnyRef
- Annotations
- @throws(classOf[java.lang.InterruptedException]) @native()
- def windowedBy(windows: SessionWindows): SessionWindowedKStream[K, V]
Create a new SessionWindowedKStream instance that can be used to perform session windowed aggregations.
Create a new SessionWindowedKStream instance that can be used to perform session windowed aggregations.
- windows
the specification of the aggregation
SessionWindows
- returns
an instance of SessionWindowedKStream
- See also
org.apache.kafka.streams.kstream.KGroupedStream#windowedBy
- def windowedBy[W <: Window](windows: Windows[W]): TimeWindowedKStream[K, V]
Create a new TimeWindowedKStream instance that can be used to perform windowed aggregations.
Create a new TimeWindowedKStream instance that can be used to perform windowed aggregations.
- windows
the specification of the aggregation
Windows
- returns
an instance of TimeWindowedKStream
- See also
org.apache.kafka.streams.kstream.KGroupedStream#windowedBy