Deprecated API

Contents

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

Deprecated Interfaces

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

Deprecated Classes

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

Deprecated Exceptions

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

Deprecated Fields

Field and 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.

Deprecated Methods

Method and Description
org.apache.kafka.streams.StreamsBuilder.addGlobalStore(StoreBuilder, String, String, Consumed, String, ProcessorSupplier) use StreamsBuilder.addGlobalStore(StoreBuilder, String, Consumed, ProcessorSupplier) instead
org.apache.kafka.streams.kstream.KGroupedStream.aggregate(Initializer, Aggregator, Merger, SessionWindows, Serde) use windowedBy(sessionWindows) followed by aggregate(initializer, aggregator, sessionMerger, Materialized.with(null, aggValueSerde))
org.apache.kafka.streams.kstream.KGroupedStream.aggregate(Initializer, Aggregator, Merger, SessionWindows, Serde, StateStoreSupplier) use windowedBy(sessionWindows) followed by aggregate(initializer, aggregator, sessionMerger, Materialized.as(KeyValueByteStoreSupplier).withValueSerde(aggValueSerde))
org.apache.kafka.streams.kstream.KGroupedStream.aggregate(Initializer, Aggregator, Merger, SessionWindows, Serde, String) use windowedBy(sessionWindows) followed by aggregate(initializer, aggregator, sessionMerger, Materialized.as(queryableStoreName).withValueSerde(aggValueSerde))
org.apache.kafka.streams.kstream.KGroupedTable.aggregate(Initializer, Aggregator, Aggregator, Serde) use aggregate(initializer, adder, subtractor, Materialized.with(null, aggValueSerde))
org.apache.kafka.streams.kstream.KGroupedTable.aggregate(Initializer, Aggregator, Aggregator, Serde, String) use aggregate(initializer, adder, subtractor, Materialized.as(queryableStoreName).withValueSerde(aggValueSerde))
org.apache.kafka.streams.kstream.KGroupedTable.aggregate(Initializer, Aggregator, Aggregator, StateStoreSupplier) use aggregate(initializer, adder, subtractor, Materialized.as(KeyValueByteStoreSupplier))
org.apache.kafka.streams.kstream.KGroupedTable.aggregate(Initializer, Aggregator, Aggregator, String) use aggregate(initializer, adder, subtractor, Materialized.as(queryableStoreName))
org.apache.kafka.streams.kstream.KGroupedStream.aggregate(Initializer, Aggregator, Serde) use aggregate(initializer, aggregator, Materialized.with(null, aggValueSerde))
org.apache.kafka.streams.kstream.KGroupedStream.aggregate(Initializer, Aggregator, Serde, String) use aggregate(initializer, aggregator, Materialized.as(queryableStoreName).withValueSerde(aggValueSerde))
org.apache.kafka.streams.kstream.KGroupedStream.aggregate(Initializer, Aggregator, StateStoreSupplier) use aggregate(initializer, aggregator, Materialized.as(KeyValueByteStoreSupplier))
org.apache.kafka.streams.kstream.KGroupedStream.aggregate(Initializer, Aggregator, Windows, Serde) use windowedBy(windows) followed by TimeWindowedKStream.aggregate(Initializer, Aggregator, Materialized) aggregate(initializer, aggregator, Materialized.with(null, aggValueSerde))}
org.apache.kafka.streams.kstream.KGroupedStream.aggregate(Initializer, Aggregator, Windows, Serde, String) use windowedBy(windows) followed by aggregate(initializer, aggregator, Materialized.as(queryableStoreName).withValueSerde(aggValueSerde))
org.apache.kafka.streams.kstream.KGroupedStream.aggregate(Initializer, Aggregator, Windows, StateStoreSupplier) use windowedBy(windows) followed by aggregate(initializer, aggregator, Materialized.as(KeyValueByteStoreSupplier))
org.apache.kafka.streams.kstream.KGroupedStream.count(SessionWindows) use windowedBy(sessionWindows) followed by count()
org.apache.kafka.streams.kstream.KGroupedStream.count(SessionWindows, StateStoreSupplier) use windowedBy(sessionWindows) followed by count(Materialized.as(KeyValueByteStoreSupplier))
org.apache.kafka.streams.kstream.KGroupedStream.count(SessionWindows, String) use windowedBy(sessionWindows) followed by count(Materialized.as(queryableStoreName))
org.apache.kafka.streams.kstream.KGroupedTable.count(StateStoreSupplier) use count(Materialized.as(KeyValueByteStoreSupplier)
org.apache.kafka.streams.kstream.KGroupedStream.count(StateStoreSupplier) use count(Materialized.as(KeyValueByteStoreSupplier))
org.apache.kafka.streams.kstream.KGroupedTable.count(String) use count(Materialized.as(queryableStoreName))
org.apache.kafka.streams.kstream.KGroupedStream.count(String) use count(Materialized.as(queryableStoreName))
org.apache.kafka.streams.kstream.KGroupedStream.count(Windows) use windowedBy(windows) followed by count()
org.apache.kafka.streams.kstream.KGroupedStream.count(Windows, StateStoreSupplier) use windowedBy(windows) followed by count(Materialized.as(KeyValueByteStoreSupplier))
org.apache.kafka.streams.kstream.KGroupedStream.count(Windows, String) use windowedBy(windows) followed by count(Materialized.as(queryableStoreName))
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.kstream.KTable.filter(Predicate, StateStoreSupplier) use filter(predicate, Materialized.as(KeyValueByteStoreSupplier))
org.apache.kafka.streams.kstream.KTable.filter(Predicate, String) use filter(predicate, Materialized.as(queryableStoreName))
org.apache.kafka.streams.kstream.KTable.filterNot(Predicate, StateStoreSupplier) use filterNot(predicate, Materialized.as(KeyValueByteStoreSupplier))
org.apache.kafka.streams.kstream.KTable.filterNot(Predicate, String) use filterNot(predicate, Materialized.as(queryableStoreName))
org.apache.kafka.streams.kstream.KTable.foreach(ForeachAction) 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>, Serde, Serde) use groupBy(selector, Serialized.with(keySerde, valueSerde)
org.apache.kafka.streams.kstream.KStream.groupBy(KeyValueMapper, Serde, Serde) use groupBy(selector, Serialized.with(keySerde, valSerde))
org.apache.kafka.streams.kstream.KStream.groupByKey(Serde, Serde) use groupByKey(Serialized.with(keySerde, valSerde))
org.apache.kafka.streams.kstream.KStream.join(KStream, ValueJoiner, JoinWindows, Serde, Serde, Serde) use join(otherStream, joiner, windows, Joined.with(keySerde, thisValueSerde, otherValueSerde))
org.apache.kafka.streams.kstream.KTable.join(KTable, ValueJoiner, Serde, String) use join(other, joiner, Materialized.as(queryableStoreName).withValueSerde(joinSerde)
org.apache.kafka.streams.kstream.KTable.join(KTable, ValueJoiner, StateStoreSupplier) use join(other, joiner, Materialized.as(KeyValueByteStoreSupplier)
org.apache.kafka.streams.kstream.KStream.join(KTable, ValueJoiner, Serde, Serde) use join(table, joiner, Joined.with(keySerde, valSerde, null))
org.apache.kafka.streams.StreamsConfig.keySerde()
org.apache.kafka.streams.kstream.KStream.leftJoin(KStream, ValueJoiner, JoinWindows, Serde, Serde, Serde) use leftJoin(otherStream, joiner, windows, Joined.with(keySerde, thisValSerde, otherValueSerde))
org.apache.kafka.streams.kstream.KTable.leftJoin(KTable, ValueJoiner, Serde, String) use leftJoin(other, joiner, Materialized.as(queryableStoreName).withValueSerde(joinSerde)
org.apache.kafka.streams.kstream.KTable.leftJoin(KTable, ValueJoiner, StateStoreSupplier) use leftJoin(other, joiner, Materialized.as(KeyValueByteStoreSupplier)
org.apache.kafka.streams.kstream.KStream.leftJoin(KTable, ValueJoiner, Serde, Serde) use leftJoin(table, joiner, Joined.with(keySerde, valSerde, null))
org.apache.kafka.streams.kstream.KTable.mapValues(ValueMapper, Serde, StateStoreSupplier) use mapValues(mapper, Materialized.as(KeyValueByteStoreSupplier).withValueSerde(valueSerde))
org.apache.kafka.streams.kstream.KTable.mapValues(ValueMapper, Serde, String) use mapValues(mapper, Materialized.as(queryableStoreName).withValueSerde(valueSerde))
org.apache.kafka.streams.kstream.KStream.outerJoin(KStream, ValueJoiner, JoinWindows, Serde, Serde, Serde) use outerJoin(otherStream, joiner, windows, Joined.with(keySerde, thisValueSerde, otherValueSerde))
org.apache.kafka.streams.kstream.KTable.outerJoin(KTable, ValueJoiner, Serde, String) use outerJoin(other, joiner, Materialized.as(queryableStoreName).withValueSerde(joinSerde)
org.apache.kafka.streams.kstream.KTable.outerJoin(KTable, ValueJoiner, StateStoreSupplier) use outerJoin(other, joiner, Materialized.as(KeyValueByteStoreSupplier)
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.KStream.print() use print(Printed)
org.apache.kafka.streams.kstream.KStream.print(KeyValueMapper) use print(Printed.toSysOut().withKeyValueMapper(mapper)
org.apache.kafka.streams.kstream.KStream.print(KeyValueMapper, Serde, Serde) use print(Printed.toSysOut().withKeyValueMapper(mapper)
org.apache.kafka.streams.kstream.KStream.print(KeyValueMapper, Serde, Serde, String) use print(Printed.toSysOut().withLabel(label).withKeyValueMapper(mapper)
org.apache.kafka.streams.kstream.KStream.print(KeyValueMapper, String) use print(Printed.toSysOut().withLabel(label).withKeyValueMapper(mapper)
org.apache.kafka.streams.kstream.KTable.print(Serde, Serde) 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().withKeyValueMapper(...) on the result.
org.apache.kafka.streams.kstream.KStream.print(Serde, Serde) use print(Printed.toSysOut().withKeyValueMapper(...)
org.apache.kafka.streams.kstream.KTable.print(Serde, Serde, 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.toSysOut().withLabel(label).withKeyValueMapper(...) on the result.
org.apache.kafka.streams.kstream.KStream.print(Serde, Serde, String) use print(Printed.toSysOut().withLabel(label).withKeyValueMapper(...)
org.apache.kafka.streams.kstream.KTable.print(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.toSysOut().withLabel(lable)) on the result.
org.apache.kafka.streams.kstream.KStream.print(String) use print(Printed.toSysOut()
org.apache.kafka.streams.processor.Processor.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.kstream.Transformer.punctuate(long) Please use Punctuator functional interface instead.
org.apache.kafka.streams.kstream.KGroupedTable.reduce(Reducer, Reducer, StateStoreSupplier) use reduce(adder, subtractor, Materialized.as(KeyValueByteStoreSupplier))
org.apache.kafka.streams.kstream.KGroupedTable.reduce(Reducer, Reducer, String) use reduce(adder, subtractor, Materialized.as(queryableStoreName))
org.apache.kafka.streams.kstream.KGroupedStream.reduce(Reducer, SessionWindows) use windowedBy(sessionWindows) followed by reduce(reducer)
org.apache.kafka.streams.kstream.KGroupedStream.reduce(Reducer, SessionWindows, StateStoreSupplier) use windowedBy(sessionWindows) followed by reduce(reducer, Materialized.as(KeyValueByteStoreSupplier))
org.apache.kafka.streams.kstream.KGroupedStream.reduce(Reducer, SessionWindows, String) use windowedBy(sessionWindows) followed by reduce(reducer, Materialized.as(queryableStoreName))
org.apache.kafka.streams.kstream.KGroupedStream.reduce(Reducer, StateStoreSupplier) use reduce(reducer, Materialized.as(KeyValueByteStoreSupplier))
org.apache.kafka.streams.kstream.KGroupedStream.reduce(Reducer, String) use reduce(reducer, Materialized.as(queryableStoreName))
org.apache.kafka.streams.kstream.KGroupedStream.reduce(Reducer, Windows) use windowedBy(windows) followed by reduce(reducer)
org.apache.kafka.streams.kstream.KGroupedStream.reduce(Reducer, Windows, StateStoreSupplier) use windowedBy(windows) followed by reduce(reducer, Materialized.as(KeyValueByteStoreSupplier))
org.apache.kafka.streams.kstream.KGroupedStream.reduce(Reducer, Windows, String) use windowedBy(windows) followed by reduce(reducer, Materialized.as(queryableStoreName))
org.apache.kafka.streams.processor.ProcessorContext.schedule(long) Please use ProcessorContext.schedule(long, PunctuationType, Punctuator) instead.
org.apache.kafka.streams.kstream.KTable.through(Serde, Serde, StreamPartitioner, String) use KTable.toStream() followed by to(topic, Produced.with(keySerde, valSerde, partitioner)) and StreamsBuilder#table(topic) to read back as a KTable
org.apache.kafka.streams.kstream.KStream.through(Serde, Serde, StreamPartitioner, String) use through(topic, Produced.with(keySerde, valSerde, partitioner))
org.apache.kafka.streams.kstream.KTable.through(Serde, Serde, StreamPartitioner, String, StateStoreSupplier) use KTable.toStream() followed by to(topic, Produced.with(keySerde, valSerde, partitioner)) and StreamsBuilder#table(topic, Materialized.as(KeyValueBytesStoreSupplier)) to read back as a KTable
org.apache.kafka.streams.kstream.KTable.through(Serde, Serde, StreamPartitioner, String, String) use KTable.toStream() followed by to(topic, Produced.with(keySerde, valSerde, partitioner)) and StreamsBuilder#table(topic, Materialized.as(queryableStoreName)) to read back as a KTable
org.apache.kafka.streams.kstream.KTable.through(Serde, Serde, String) use KTable.toStream() followed by to(topic, Produced.with(keySerde, valSerde)) and StreamsBuilder#table(topic) to read back as a KTable
org.apache.kafka.streams.kstream.KStream.through(Serde, Serde, String) use through(topic, Produced.with(keySerde, valSerde))
org.apache.kafka.streams.kstream.KTable.through(Serde, Serde, String, StateStoreSupplier) use KTable.toStream() followed by to(topic, Produced.with(keySerde, valSerde)) and StreamsBuilder#table(topic, Materialized.as(KeyValueBytesStoreSupplier) to read back as a KTable
org.apache.kafka.streams.kstream.KTable.through(Serde, Serde, String, String) use KTable.toStream() followed by to(topic, Produced.with(keySerde, valSerde)) and StreamsBuilder#table(topic, Materialized.as(queryableStoreName)) to read back as a KTable
org.apache.kafka.streams.kstream.KTable.through(StreamPartitioner, String) use KTable.toStream() followed by to(topic, Produced.streamPartitioner(partitioner)) and StreamsBuilder#table(topic) to read back as a KTable
org.apache.kafka.streams.kstream.KStream.through(StreamPartitioner, String) use through(topic, Produced.withStreamPartitioner(partitioner))
org.apache.kafka.streams.kstream.KTable.through(StreamPartitioner, String, StateStoreSupplier) use KTable.toStream() followed by to(topic, Produced.streamPartitioner(partitioner)) and StreamsBuilder#table(topic, Materialized.as(KeyValueBytesStoreSupplier) to read back as a KTable
org.apache.kafka.streams.kstream.KTable.through(StreamPartitioner, String, String) use KTable.toStream() followed by to(topic, Produced.streamPartitioner(partitioner)) and StreamsBuilder#table(topic, Materialized.as(queryableStoreName)) to read back as a KTable
org.apache.kafka.streams.kstream.KTable.through(String) use KTable.toStream() followed by to(topic) and and StreamsBuilder#table(topic) to read back as a KTable
org.apache.kafka.streams.kstream.KTable.through(String, StateStoreSupplier) use KTable.toStream() followed by to(topic) and and StreamsBuilder#table(topic, Materialized.as(KeyValueBytesStoreSupplier)) to read back as a KTable
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(Serde, Serde, StreamPartitioner, String) use KTable.toStream() followed by to(topic, Produced.with(keySerde, valSerde, partioner)
org.apache.kafka.streams.kstream.KStream.to(Serde, Serde, StreamPartitioner, String) use to(topic, Produced.with(keySerde, valSerde, partitioner)
org.apache.kafka.streams.kstream.KTable.to(Serde, Serde, String) use KTable.toStream() followed by to(topic, Produced.with(keySerde, valSerde)
org.apache.kafka.streams.kstream.KStream.to(Serde, Serde, String) use to(topic, Produced.with(keySerde, valSerde))
org.apache.kafka.streams.kstream.KTable.to(StreamPartitioner, String) use KTable.toStream() followed by to(topic, Produced.withStreamPartitioner(partitioner)
org.apache.kafka.streams.kstream.KStream.to(StreamPartitioner, String) use to(topic, Produced.withStreamPartitioner(partitioner))
org.apache.kafka.streams.kstream.KTable.to(String) use KTable.toStream() followed by to(topic)
org.apache.kafka.streams.KafkaStreams.toString() Use KafkaStreams.localThreadsMetadata() to retrieve runtime information.
org.apache.kafka.streams.KafkaStreams.toString(String) Use KafkaStreams.localThreadsMetadata() to retrieve runtime information.
org.apache.kafka.streams.StreamsConfig.valueSerde()
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.KStream.writeAsText(String) use print(Printed.toFile(filePath)
org.apache.kafka.streams.kstream.KStream.writeAsText(String, KeyValueMapper) use print(Printed.toFile(filePath).withKeyValueMapper(mapper)
org.apache.kafka.streams.kstream.KTable.writeAsText(String, Serde, Serde) 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).withKeyValueMapper(...) on the result.
org.apache.kafka.streams.kstream.KStream.writeAsText(String, Serde, Serde) use print(Printed.toFile(filePath).withKeyValueMapper(...)
org.apache.kafka.streams.kstream.KStream.writeAsText(String, Serde, Serde, KeyValueMapper) use print(Printed.toFile(filePath).withKeyValueMapper(mapper)
org.apache.kafka.streams.kstream.KTable.writeAsText(String, 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).withLabel(label) on the result.
org.apache.kafka.streams.kstream.KStream.writeAsText(String, String) use print(Printed.toFile(filePath).withLabel(label)
org.apache.kafka.streams.kstream.KStream.writeAsText(String, String, KeyValueMapper) use print(Printed.toFile(filePath).withLabel(label).withKeyValueMapper(mapper)
org.apache.kafka.streams.kstream.KTable.writeAsText(String, String, Serde, Serde) 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).withLabel(label).withKeyValueMapper(...) on the result.
org.apache.kafka.streams.kstream.KStream.writeAsText(String, String, Serde, Serde) use print(Printed.toFile(filePath).withLabel(label).withKeyValueMapper(...)
org.apache.kafka.streams.kstream.KStream.writeAsText(String, String, Serde, Serde, KeyValueMapper) use print(Printed.toFile(filePath).withLabel(label).withKeyValueMapper(mapper)

Deprecated Constructors

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