How to implement a custom state store in leftJoin using Kafka Streams?

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To implement a custom state store in a leftJoin using Kafka Streams, you need to follow these steps:

1. Define your custom state store: Implement the KeyValueStore interface to create your custom state store. This requires implementing methods such as put(), get(), and delete(). This state store will store the values that you want to join with the stream.

2. Create a custom Processor that initializes the store: Implement the Processor interface to create a custom processor that initializes your state store. In the processor's init() method, create an instance of your custom state store and configure it as a persistent store.

3. Implement the transform() method of the Transformer interface: Implement the Transformer interface to create a custom transformer that performs the left join operation. In the transform() method, retrieve the value from your state store with the key that matches the key of the stream record. If the value exists, the transformer can emit a new record with the value included in the result of the left join. If the value does not exist, the transformer can emit a new record with a null value.

4. Chain your custom transformer to your Kafka Streams topology: Add your custom transformer to the Kafka Streams topology by chaining it to the relevant KStream using the transform() method.

5. Run your Kafka Streams application: Start your Kafka Streams application and verify that the left join is performing as expected.

Example Code:

Here's an example code snippet that demonstrates how to create a custom state store and implement a left join using Kafka Streams:

KeyValueBytesStoreSupplier customStoreSupplier = Stores.persistentKeyValueStore("custom-store");

Processor<byte[], byte[]> customProcessor = new AbstractProcessor<byte[], byte[]>() {
    private KeyValueStore<String, String> customStore;

    @Override
    public void init(ProcessorContext context) {
        super.init(context);
        customStore = (KeyValueStore<String, String>) context.getStateStore("custom-store");
    }

    @Override
    public void process(byte[] key, byte[] value) {
        // apply any custom logic or transformations to the input stream record
    }
};

Transformer<byte[], byte[], KeyValue<String, String>> customTransformer = new Transformer<byte[], byte[], KeyValue<String, String>>() {
    private KeyValueStore<String, String> customStore;

    @Override
    public void init(ProcessorContext context) {
        customStore = (KeyValueStore<String, String>) context.getStateStore("custom-store");
    }

    @Override
    public KeyValue<String, String> transform(byte[] key, byte[] value) {
        String joinValue = customStore.get(key); // retrieve the value from the state store using the key
        return new KeyValue<String, String>(new String(key), joinValue); // emit a new record with the join value included
    }

    @Override
    public void close() {
        // clean up if needed
    }
};

StreamsBuilder builder = new StreamsBuilder();
KStream<byte[], byte[]> input = builder.stream("input-topic");
KStream<byte[], byte[]> result = input
        .transform(customTransformer, "custom-store") // use the custom transformer with the custom state store
        .leftJoin(anotherStream, (v1, v2) -> v1 + " " + v2); // perform the left join operation

result.to("output-topic");

KafkaStreams streams = new KafkaStreams(builder.build(), config);
streams.start();