Dear all,
I am using the kafkaIO sdk in my project (Beam 2.0.0 with Direct runner).
With using this sdk, there are a situation about data latency, and the
description of situation is in the following.
The data come from kafak with a fixed speed: 100 data size/ 1 sec.
I create a fixed window within 1 sec without delay. I found that the data size
is 70, 80, 104, or greater than or equal to 104.
After one day, the data latency happens in my running time, and the data size
will be only 10 in each window.
In order to clearly explain it, I also provide my code in the following.
" PipelineOptions readOptions = PipelineOptionsFactory.create();
final Pipeline p = Pipeline.create(readOptions);
PCollection<TimestampedValue<KV<String, String>>> readData =
p.apply(KafkaIO.<String, String>read()
.withBootstrapServers("127.0.0.1:9092")
.withTopic("kafkasink")
.withKeyDeserializer(StringDeserializer.class)
.withValueDeserializer(StringDeserializer.class)
.withoutMetadata())
.apply(ParDo.of(new DoFn<KV<String, String>, TimestampedValue<KV<String,
String>>>() {
@ProcessElement
public void test(ProcessContext c) throws ParseException {
String element = c.element().getValue();
try {
JsonNode arrNode = new ObjectMapper().readTree(element);
String t = arrNode.path("v").findValue("Timestamp").textValue();
DateTimeFormatter formatter =
DateTimeFormatter.ofPattern("MM/dd/uuuu HH:mm:ss.SSSS");
LocalDateTime dateTime = LocalDateTime.parse(t, formatter);
java.time.Instant java_instant =
dateTime.atZone(ZoneId.systemDefault()).toInstant();
Instant timestamp = new Instant(java_instant.toEpochMilli());
c.output(TimestampedValue.of(c.element(), timestamp));
} catch (JsonGenerationException e) {
e.printStackTrace();
} catch (JsonMappingException e) {
e.printStackTrace();
} catch (IOException e) {
e.printStackTrace();
}
}}));
PCollection<TimestampedValue<KV<String, String>>> readDivideData =
readData.apply(
Window.<TimestampedValue<KV<String, String>>>
into(FixedWindows.of(Duration.standardSeconds(1))
.withOffset(Duration.ZERO))
.triggering(AfterWatermark.pastEndOfWindow()
.withLateFirings(AfterProcessingTime.pastFirstElementInPane()
.plusDelayOf(Duration.ZERO)))
.withAllowedLateness(Duration.ZERO)
.discardingFiredPanes());"
In addition, the running result is as shown in the following.
"data-size=104
coming-data-time=2018-02-27 02:00:49.117
window-time=2018-02-27 02:00:49.999
data-size=70
coming-data-time=2018-02-27 02:00:50.318
window-time=2018-02-27 02:00:50.999
data-size=104
coming-data-time=2018-02-27 02:00:51.102
window-time=2018-02-27 02:00:51.999
After one day:
data-size=10
coming-data-time=2018-02-28 02:05:48.217
window-time=2018-03-01 10:35:16.999 "
For repeating my situation, my running environment is:
OS: Ubuntn 14.04.3 LTS
JAVA: JDK 1.7
Beam 2.0.0 (with Direct runner)
Kafka 2.10-0.10.1.1
Maven 3.5.0, in which dependencies are listed in pom.xml:
<dependency>
<groupId>org.apache.beam</groupId>
<artifactId>beam-sdks-java-core</artifactId>
<version>2.0.0</version>
</dependency>
<dependency>
<groupId>org.apache.beam</groupId>
<artifactId>beam-runners-direct-java</artifactId>
<version>2.0.0</version>
<scope>runtime</scope>
</dependency>
<dependency>
<groupId>org.apache.beam</groupId>
<artifactId>beam-sdks-java-io-kafka</artifactId>
<version>2.0.0</version>
</dependency>
<!-- https://mvnrepository.com/artifact/org.apache.kafka/kafka-clients -->
<dependency>
<groupId>org.apache.kafka</groupId>
<artifactId>kafka-clients</artifactId>
<version>0.10.0.1</version>
</dependency>
If you have any idea about the problem (data latency), I am looking forward to
hearing from you.
Thanks
Rick
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