Java Kafka流处理翻滚窗口
我正在使用JavaKStream API处理消息流。目前,我的代码每5分钟发出一次输出,但我希望在5分钟间隔的顶部发出输出(如17:10、17:15等) 目前,间隔取决于程序启动的时间。如果程序在17:08开始,数据将在17:13、17:18、17:23等时间间隔收集 是否有一种方法可以安排数据以5分钟的间隔(5的倍数)发出Java Kafka流处理翻滚窗口,java,apache-kafka,apache-kafka-streams,Java,Apache Kafka,Apache Kafka Streams,我正在使用JavaKStream API处理消息流。目前,我的代码每5分钟发出一次输出,但我希望在5分钟间隔的顶部发出输出(如17:10、17:15等) 目前,间隔取决于程序启动的时间。如果程序在17:08开始,数据将在17:13、17:18、17:23等时间间隔收集 是否有一种方法可以安排数据以5分钟的间隔(5的倍数)发出 class WindowedTransformerExample { public static void main(String[] args) { final Str
class WindowedTransformerExample {
public static void main(String[] args) {
final StreamsBuilder builder = new StreamsBuilder();
final String stateStoreName = "stateStore";
final StoreBuilder<KeyValueStore<String, String>> keyValueStoreBuilder =
Stores.keyValueStoreBuilder(Stores.inMemoryKeyValueStore(stateStoreName),
Serdes.String(),
Serdes.String());
builder.addStateStore(keyValueStoreBuilder);
builder.<String, String>stream("topic").transform(new
WindowedTransformer(stateStoreName), stateStoreName)
.filter((k, v) -> k != null && v != null)
// Here's where you do something with records emitted after 10 minutes
.foreach((k, v)-> System.out.println());
}
static final class WindowedTransformer implements TransformerSupplier<String, String, KeyValue<String, String>> {
private final String storeName;
public WindowedTransformer(final String storeName) {
this.storeName = storeName;
}
@Override
public Transformer<String, String, KeyValue<String, String>> get() {
return new Transformer<String, String, KeyValue<String, String>>() {
private KeyValueStore<String, String> keyValueStore;
private ProcessorContext processorContext;
@Override
public void init(final ProcessorContext context) {
processorContext = context;
keyValueStore = (KeyValueStore<String, String>) context.getStateStore(storeName);
// could change this to PunctuationType.STREAM_TIME if needed
context.schedule(Duration.ofMinutes(5), PunctuationType.WALL_CLOCK_TIME, (ts) -> {
try(final KeyValueIterator<String, String> iterator = keyValueStore.all()) {
while (iterator.hasNext()) {
final KeyValue<String, String> keyValue = iterator.next();
processorContext.forward(keyValue.key, keyValue.value);
}
}
});
}
@Override
public KeyValue<String, String> transform(String key, String value) {
if (key != null) {
keyValueStore.put(key, value);
}
return null;
}
@Override
public void close() {
}
};
}
}
class WindowedTransformerExample{
公共静态void main(字符串[]args){
最终StreamsBuilder生成器=新StreamsBuilder();
最后一个字符串stateStoreName=“stateStore”;
最终StoreBuilder键值StoreBuilder=
Stores.keyValueStoreBuilder(Stores.inMemoryKeyValueStore(stateStoreName),
Serdes.String(),
Serdes.String());
builder.addStateStore(keyValueStoreBuilder);
builder.stream(“主题”).transform(新
窗口变压器(stateStoreName),stateStoreName)
.filter((k,v)->k!=null&&v!=null)
//这里是处理10分钟后发出的记录的地方
.foreach((k,v)->System.out.println());
}
静态最终类WindowedTransformer实现TransformerSupplier{
私有最终字符串storeName;
公共窗口变压器(最终字符串存储名){
this.storeName=storeName;
}
@凌驾
公共变压器get(){
返回新变压器(){
private KeyValueStore KeyValueStore;
私有处理器Context处理器Context;
@凌驾
public void init(最终处理器上下文){
processorContext=上下文;
keyValueStore=(keyValueStore)context.getStateStore(storeName);
//如果需要,可以将此更改为标点类型.STREAM\u TIME
上下文.时间表(持续时间.分钟(5),标点类型.挂钟时间(ts)->{
try(final KeyValueIterator iterator=keyValueStore.all()){
while(iterator.hasNext()){
final KeyValue KeyValue=iterator.next();
processorContext.forward(keyValue.key,keyValue.value);
}
}
});
}
@凌驾
公钥值转换(字符串键、字符串值){
if(key!=null){
keyValueStore.put(键,值);
}
返回null;
}
@凌驾
公众假期结束(){
}
};
}
}
}