KafkaStream.KTable如何将数据写入(压缩)KV样式的kafka主题

时间:2017-09-21 11:15:53

标签: java apache-kafka apache-kafka-streams

在Kafka(0.11.0.1)Streams中,一个演示应用Play with a Streams Application

// Serializers/deserializers (serde) for String and Long types
final Serde<String> stringSerde = Serdes.String();
final Serde<Long> longSerde = Serdes.Long();

// Construct a `KStream` from the input topic "streams-plaintext-input", where message values
// represent lines of text (for the sake of this example, we ignore whatever may be stored
// in the message keys).
KStream<String, String> textLines = builder.stream(stringSerde, stringSerde, "streams-plaintext-input");

KTable<String, Long> wordCounts = textLines
    // Split each text line, by whitespace, into words.
    .flatMapValues(value -> Arrays.asList(value.toLowerCase().split("\\W+")))

    // Group the text words as message keys
    .groupBy((key, value) -> value)

    // Count the occurrences of each word (message key).
    .count("Counts")

    // Store the running counts as a changelog stream to the output topic.
    wordCounts.to(stringSerde, longSerde, "streams-wordcount-output");

第5步,在处理完一些数据后,我们可以在汇主题 streams-wordcount-output 中看到压缩的KV对(例如流2 ),

> bin/kafka-console-consumer.sh --bootstrap-server localhost:9092
    --topic streams-wordcount-output \
    --from-beginning \
    --formatter kafka.tools.DefaultMessageFormatter \
    --property print.key=true \
    --property print.value=true \
    --property key.deserializer=org.apache.kafka.common.serialization.StringDeserializer \
    --property value.deserializer=org.apache.kafka.common.serialization.LongDeserializer 

all     1 
streams 1 
lead    1 
to      1 
kafka   1 
hello   1 
kafka   2 
streams 2

问题是上述数据中的 KTable wordCounts 如何以键值样式将数据写入主题 streams-wordcount-output

主题 streams-wordcount-output 的选项 cleanup.policy 似乎是默认值delete,而不是compact(通过箱/ kafka-configs.sh)

1 个答案:

答案 0 :(得分:1)

所有输入和输出主题都超出范围&#34;卡夫卡流。用户有责任创建和配置这些主题。

因此,您的主题"streams-wordcount-output"将具有您在创建主题时指定的配置。

比照https://docs.confluent.io/current/streams/developer-guide.html#managing-topics-of-a-kafka-streams-application