Deprecated API

Contents

• Interfaces
• Classes
• Exceptions
• Fields
• Methods
• Constructors

Interfaces

Interface	Description
org.apache.kafka.streams.processor.StateStoreSupplier	use StoreSupplier
org.apache.kafka.streams.state.Stores.InMemoryKeyValueFactory
org.apache.kafka.streams.state.Stores.PersistentKeyValueFactory

Classes

Class	Description
org.apache.kafka.streams.kstream.KStreamBuilder	Use StreamsBuilder instead
org.apache.kafka.streams.processor.TopologyBuilder	use Topology instead

Exceptions

Exceptions	Description
org.apache.kafka.streams.errors.TopologyBuilderException	use Topology instead of TopologyBuilder

Fields

Field	Description
org.apache.kafka.streams.StreamsConfig.KEY_SERDE_CLASS_CONFIG	Use StreamsConfig.DEFAULT_KEY_SERDE_CLASS_CONFIG instead.
org.apache.kafka.streams.StreamsConfig.TIMESTAMP_EXTRACTOR_CLASS_CONFIG	Use StreamsConfig.DEFAULT_TIMESTAMP_EXTRACTOR_CLASS_CONFIG instead.
org.apache.kafka.streams.StreamsConfig.VALUE_SERDE_CLASS_CONFIG	Use StreamsConfig.DEFAULT_VALUE_SERDE_CLASS_CONFIG instead.
org.apache.kafka.streams.StreamsConfig.ZOOKEEPER_CONNECT_CONFIG	Kakfa Streams does not use Zookeeper anymore and this parameter will be ignored.

Methods

Method	Description
org.apache.kafka.streams.KafkaStreams.toString()	Use KafkaStreams.localThreadsMetadata() to retrieve runtime information.
org.apache.kafka.streams.kstream.KGroupedStream.aggregate(Initializer<VR>, Aggregator<? super K, ? super V, VR>, Serde<VR>, String)	use aggregate(initializer, aggregator, Materialized.as(queryableStoreName).withValueSerde(aggValueSerde))
org.apache.kafka.streams.kstream.KGroupedStream.count(String)	use count(Materialized.as(queryableStoreName))
org.apache.kafka.streams.kstream.KGroupedStream.reduce(Reducer<V>, String)	use reduce(reducer, Materialized.as(queryableStoreName))
org.apache.kafka.streams.kstream.KGroupedTable.aggregate(Initializer<VR>, Aggregator<? super K, ? super V, VR>, Aggregator<? super K, ? super V, VR>, String)	use aggregate(initializer, adder, subtractor, Materialized.as(queryableStoreName))
org.apache.kafka.streams.kstream.KGroupedTable.count(String)	use count(Materialized.as(queryableStoreName))
org.apache.kafka.streams.kstream.KGroupedTable.reduce(Reducer<V>, Reducer<V>, String)	use reduce(adder, subtractor, Materialized.as(queryableStoreName))
org.apache.kafka.streams.kstream.KStream.groupBy(KeyValueMapper<? super K, ? super V, KR>, Serde<KR>, Serde<V>)	use groupBy(selector, Serialized.with(keySerde, valSerde))
org.apache.kafka.streams.kstream.KStream.groupByKey(Serde<K>, Serde<V>)	use groupByKey(Serialized.with(keySerde, valSerde))
org.apache.kafka.streams.kstream.KStream.join(KStream<K, VO>, ValueJoiner<? super V, ? super VO, ? extends VR>, JoinWindows, Serde<K>, Serde<V>, Serde<VO>)	use join(otherStream, joiner, windows, Joined.with(keySerde, thisValueSerde, otherValueSerde))
org.apache.kafka.streams.kstream.KStream.leftJoin(KStream<K, VO>, ValueJoiner<? super V, ? super VO, ? extends VR>, JoinWindows, Serde<K>, Serde<V>, Serde<VO>)	use leftJoin(otherStream, joiner, windows, Joined.with(keySerde, thisValSerde, otherValueSerde))
org.apache.kafka.streams.kstream.KStream.outerJoin(KStream<K, VO>, ValueJoiner<? super V, ? super VO, ? extends VR>, JoinWindows, Serde<K>, Serde<V>, Serde<VO>)	use outerJoin(otherStream, joiner, windows, Joined.with(keySerde, thisValueSerde, otherValueSerde))
org.apache.kafka.streams.kstream.KStream.print()	use print(Printed)
org.apache.kafka.streams.kstream.KStream.through(StreamPartitioner<? super K, ? super V>, String)	use through(topic, Produced.withStreamPartitioner(partitioner))
org.apache.kafka.streams.kstream.KStream.to(StreamPartitioner<? super K, ? super V>, String)	use to(topic, Produced.withStreamPartitioner(partitioner))
org.apache.kafka.streams.kstream.KStream.writeAsText(String)	use print(Printed.toFile(filePath)
org.apache.kafka.streams.kstream.KTable.filter(Predicate<? super K, ? super V>, String)	use filter(predicate, Materialized.as(queryableStoreName))
org.apache.kafka.streams.kstream.KTable.filterNot(Predicate<? super K, ? super V>, StateStoreSupplier<KeyValueStore>)	use filterNot(predicate, Materialized.as(KeyValueByteStoreSupplier))
org.apache.kafka.streams.kstream.KTable.foreach(ForeachAction<? super K, ? super V>)	Use the Interactive Queries APIs (e.g., KafkaStreams.store(String, QueryableStoreType) followed by ReadOnlyKeyValueStore.all()) to iterate over the keys of a KTable. Alternatively convert to a KStream using KTable.toStream() and then use foreach(action) on the result.
org.apache.kafka.streams.kstream.KTable.groupBy(KeyValueMapper<? super K, ? super V, KeyValue<KR, VR>>, Serde<KR>, Serde<VR>)	use groupBy(selector, Serialized.with(keySerde, valueSerde)
org.apache.kafka.streams.kstream.KTable.join(KTable<K, VO>, ValueJoiner<? super V, ? super VO, ? extends VR>, Serde<VR>, String)	use join(other, joiner, Materialized.as(queryableStoreName).withValueSerde(joinSerde)
org.apache.kafka.streams.kstream.KTable.leftJoin(KTable<K, VO>, ValueJoiner<? super V, ? super VO, ? extends VR>, Serde<VR>, String)	use leftJoin(other, joiner, Materialized.as(queryableStoreName).withValueSerde(joinSerde)
org.apache.kafka.streams.kstream.KTable.mapValues(ValueMapper<? super V, ? extends VR>, Serde<VR>, String)	use mapValues(mapper, Materialized.as(queryableStoreName).withValueSerde(valueSerde))
org.apache.kafka.streams.kstream.KTable.outerJoin(KTable<K, VO>, ValueJoiner<? super V, ? super VO, ? extends VR>, Serde<VR>, String)	use outerJoin(other, joiner, Materialized.as(queryableStoreName).withValueSerde(joinSerde)
org.apache.kafka.streams.kstream.KTable.print()	Use the Interactive Queries APIs (e.g., KafkaStreams.store(String, QueryableStoreType) followed by ReadOnlyKeyValueStore.all()) to iterate over the keys of a KTable. Alternatively convert to a KStream using KTable.toStream() and then use print(Printed.toSysOut()) on the result.
org.apache.kafka.streams.kstream.KTable.through(String, String)	use KTable.toStream() followed by to(topic) and StreamsBuilder#table(topic, Materialized.as(queryableStoreName)) to read back as a KTable
org.apache.kafka.streams.kstream.KTable.to(String)	use KTable.toStream() followed by to(topic)
org.apache.kafka.streams.kstream.KTable.writeAsText(String)	Use the Interactive Queries APIs (e.g., KafkaStreams.store(String, QueryableStoreType) followed by ReadOnlyKeyValueStore.all()) to iterate over the keys of a KTable. Alternatively convert to a KStream using KTable.toStream() and then use print(Printed.toFile(filePath) on the result.
org.apache.kafka.streams.kstream.Transformer.punctuate(long)	Please use Punctuator functional interface instead.
org.apache.kafka.streams.kstream.ValueTransformer.punctuate(long)	Please use Punctuator functional interface instead.
org.apache.kafka.streams.processor.Processor.punctuate(long)	Please use Punctuator functional interface instead.
org.apache.kafka.streams.processor.ProcessorContext.schedule(long)	Please use ProcessorContext.schedule(long, PunctuationType, Punctuator) instead.
org.apache.kafka.streams.state.Stores.create(String)	use Stores.persistentKeyValueStore(String), Stores.persistentWindowStore(String, long, int, long, boolean) Stores.persistentSessionStore(String, long), Stores.lruMap(String, int), or Stores.inMemoryKeyValueStore(String)
org.apache.kafka.streams.StreamsBuilder.addGlobalStore(StoreBuilder, String, String, Consumed, String, ProcessorSupplier)	use StreamsBuilder.addGlobalStore(StoreBuilder, String, Consumed, ProcessorSupplier) instead
org.apache.kafka.streams.StreamsConfig.keySerde()
org.apache.kafka.streams.StreamsConfig.valueSerde()

Constructors

Constructor	Description
org.apache.kafka.streams.KafkaStreams(TopologyBuilder, Properties)	use KafkaStreams(Topology, Properties) instead