org.apache.kafka.streams.kstream

Interface KGroupedStream<K,V>

Type Parameters:

K - Type of keys

V - Type of values

@InterfaceStability.Unstable
public interface KGroupedStream<K,V>

KGroupedStream is an abstraction of a grouped record stream of key-value pairs usually grouped on a different key than the original stream key

It is an intermediate representation of a KStream before an aggregation is applied to the new partitions resulting in a new KTable.

See Also:

KStream

Method Summary

Methods

Modifier and Type	Method and Description
<T> KTable<K,T>	aggregate(Initializer<T> initializer, Aggregator<K,V,T> aggregator, Serde<T> aggValueSerde, String storeName) Aggregate values of this stream by key into a new instance of a KTable.
<W extends Window,T> KTable<Windowed<K>,T>	aggregate(Initializer<T> initializer, Aggregator<K,V,T> aggregator, Windows<W> windows, Serde<T> aggValueSerde, String storeName) Aggregate values of this stream by key on a window basis into a new instance of windowed KTable.
KTable<K,Long>	count(String storeName) Count number of records of this stream by key into a new instance of a KTable.
<W extends Window> KTable<Windowed<K>,Long>	count(Windows<W> windows, String storeName) Count number of records of this stream by key on a window basis into a new instance of windowed KTable.
KTable<K,V>	reduce(Reducer<V> reducer, String storeName) Combine values of this stream by the grouped key into a new instance of ever-updating KTable.
<W extends Window> KTable<Windowed<K>,V>	reduce(Reducer<V> reducer, Windows<W> windows, String storeName) Combine values of this stream by key on a window basis into a new instance of windowed KTable.

Method Detail

reduce

KTable<K,V> reduce(Reducer<V> reducer,
                 String storeName)

Combine values of this stream by the grouped key into a new instance of ever-updating KTable. The resulting KTable will be materialized in a local state store with the given store name. Also a changelog topic named "${applicationId}-${storeName}-changelog" will be automatically created in Kafka for failure recovery, where "applicationID" is specified by the user in StreamsConfig.

Parameters:

reducer - the instance of Reducer

storeName - the name of the underlying KTable state store

Returns:

a KTable that contains records with unmodified keys and values that represent the latest (rolling) aggregate for each key

reduce

<W extends Window> KTable<Windowed<K>,V> reduce(Reducer<V> reducer,
                                              Windows<W> windows,
                                              String storeName)

Combine values of this stream by key on a window basis into a new instance of windowed KTable. The resulting KTable will be materialized in a local state store with the given store name. Also a changelog topic named "${applicationId}-${storeName}-changelog" will be automatically created in Kafka for failure recovery, where "applicationID" is specified by the user in StreamsConfig.

Parameters:

reducer - the instance of Reducer

windows - the specification of the aggregation Windows

storeName - the name of the state store created from this operation

Returns:

a windowed KTable which can be treated as a list of KTables where each table contains records with unmodified keys and values that represent the latest (rolling) aggregate for each key within that window

aggregate

<T> KTable<K,T> aggregate(Initializer<T> initializer,
                        Aggregator<K,V,T> aggregator,
                        Serde<T> aggValueSerde,
                        String storeName)

Aggregate values of this stream by key into a new instance of a KTable. The resulting KTable will be materialized in a local state store with the given store name. Also a changelog topic named "${applicationId}-${storeName}-changelog" will be automatically created in Kafka for failure recovery, where "applicationID" is specified by the user in StreamsConfig.

Type Parameters:

T - the value type of the resulting KTable

Parameters:

initializer - the instance of Initializer

aggregator - the instance of Aggregator

aggValueSerde - aggregate value serdes for materializing the aggregated table, if not specified the default serdes defined in the configs will be used

storeName - the name of the state store created from this operation

Returns:

a KTable that represents the latest (rolling) aggregate for each key

aggregate

<W extends Window,T> KTable<Windowed<K>,T> aggregate(Initializer<T> initializer,
                                                   Aggregator<K,V,T> aggregator,
                                                   Windows<W> windows,
                                                   Serde<T> aggValueSerde,
                                                   String storeName)

Aggregate values of this stream by key on a window basis into a new instance of windowed KTable. The resulting KTable will be materialized in a local state store with the given store name. Also a changelog topic named "${applicationId}-${storeName}-changelog" will be automatically created in Kafka for failure recovery, where "applicationID" is specified by the user in StreamsConfig.

Type Parameters:

T - the value type of the resulting KTable

Parameters:

initializer - the instance of Initializer

aggregator - the instance of Aggregator

windows - the specification of the aggregation Windows

aggValueSerde - aggregate value serdes for materializing the aggregated table, if not specified the default serdes defined in the configs will be used

storeName - the name of the state store created from this operation

Returns:

a windowed KTable which can be treated as a list of KTables where each table contains records with unmodified keys and values with type T that represent the latest (rolling) aggregate for each key within that window

count

KTable<K,Long> count(String storeName)

Count number of records of this stream by key into a new instance of a KTable. The resulting KTable will be materialized in a local state store with the given store name. Also a changelog topic named "${applicationId}-${storeName}-changelog" will be automatically created in Kafka for failure recovery, where "applicationID" is specified by the user in StreamsConfig.

Parameters:

storeName - the name of the underlying KTable state store

Returns:

a KTable that contains records with unmodified keys and values that represent the latest (rolling) count (i.e., number of records) for each key

count

<W extends Window> KTable<Windowed<K>,Long> count(Windows<W> windows,
                                                String storeName)

Count number of records of this stream by key on a window basis into a new instance of windowed KTable. The resulting KTable will be materialized in a local state store with the given store name. Also a changelog topic named "${applicationId}-${storeName}-changelog" will be automatically created in Kafka for failure recovery, where "applicationID" is specified by the user in StreamsConfig.

Parameters:

windows - the specification of the aggregation Windows

storeName - the name of the state store created from this operation

Returns:

a windowed KTable which can be treated as a list of KTables where each table contains records with unmodified keys and values that represent the latest (rolling) count (i.e., number of records) for each key within that window