我正在使用storm-kafka-client 1.0.3的风暴1.0.1和Kafka 0.10.0.0。KafkaSpout元组重播抛出空指针异常
请在下面找到代码配置。
kafkaConsumerProps.put(KafkaSpoutConfig.Consumer.KEY_DESERIALIZER, "org.apache.kafka.common.serialization.ByteArrayDeserializer");
kafkaConsumerProps.put(KafkaSpoutConfig.Consumer.VALUE_DESERIALIZER, "org.apache.kafka.common.serialization.ByteArrayDeserializer");
KafkaSpoutStreams kafkaSpoutStreams = new KafkaSpoutStreamsNamedTopics.Builder(new Fields(fieldNames), topics)
.build();
KafkaSpoutRetryService retryService = new KafkaSpoutRetryExponentialBackoff(TimeInterval.microSeconds(500),
TimeInterval.milliSeconds(2), Integer.MAX_VALUE, TimeInterval.seconds(10));
KafkaSpoutTuplesBuilder tuplesBuilder = new KafkaSpoutTuplesBuilderNamedTopics.Builder(new TestTupleBuilder(topics))
.build();
KafkaSpoutConfig kafkaSpoutConfig = new KafkaSpoutConfig.Builder<String, String>(kafkaConsumerProps, kafkaSpoutStreams, tuplesBuilder, retryService)
.setOffsetCommitPeriodMs(10_000)
.setFirstPollOffsetStrategy(LATEST)
.setMaxRetries(5)
.setMaxUncommittedOffsets(250)
.build();
当我失败的元组没有得到重播。 Spout抛出错误。 请让我知道它为什么抛出空指针异常。
53501 [Thread-359-test-spout-executor[295 295]] ERROR o.a.s.util - Async loop died!
java.lang.NullPointerException
at org.apache.storm.kafka.spout.KafkaSpout.doSeekRetriableTopicPartitions(KafkaSpout.java:260) ~[storm-kafka-client-1.0.3.jar:1.0.3]
at org.apache.storm.kafka.spout.KafkaSpout.pollKafkaBroker(KafkaSpout.java:248) ~[storm-kafka-client-1.0.3.jar:1.0.3]
at org.apache.storm.kafka.spout.KafkaSpout.nextTuple(KafkaSpout.java:203) ~[storm-kafka-client-1.0.3.jar:1.0.3]
at org.apache.storm.daemon.executor$fn__7885$fn__7900$fn__7931.invoke(executor.clj:645) ~[storm-core-1.0.1.jar:1.0.1]
at org.apache.storm.util$async_loop$fn__625.invoke(util.clj:484) [storm-core-1.0.1.jar:1.0.1]
at clojure.lang.AFn.run(AFn.java:22) [clojure-1.8.0.jar:?]
at java.lang.Thread.run(Thread.java:745) [?:1.8.0_102]
53501 [Thread-359-test-spout-executor[295 295]] ERROR o.a.s.d.executor -
java.lang.NullPointerException
at org.apache.storm.kafka.spout.KafkaSpout.doSeekRetriableTopicPartitions(KafkaSpout.java:260) ~[storm-kafka-client-1.0.3.jar:1.0.3]
at org.apache.storm.kafka.spout.KafkaSpout.pollKafkaBroker(KafkaSpout.java:248) ~[storm-kafka-client-1.0.3.jar:1.0.3]
at org.apache.storm.kafka.spout.KafkaSpout.nextTuple(KafkaSpout.java:203) ~[storm-kafka-client-1.0.3.jar:1.0.3]
at org.apache.storm.daemon.executor$fn__7885$fn__7900$fn__7931.invoke(executor.clj:645) ~[storm-core-1.0.1.jar:1.0.1]
at org.apache.storm.util$async_loop$fn__625.invoke(util.clj:484) [storm-core-1.0.1.jar:1.0.1]
at clojure.lang.AFn.run(AFn.java:22) [clojure-1.8.0.jar:?]
at java.lang.Thread.run(Thread.java:745) [?:1.8.0_102]
53527 [Thread-359-test-spout-executor[295 295]] ERROR o.a.s.util - Halting process: ("Worker died")
java.lang.RuntimeException: ("Worker died")
at org.apache.storm.util$exit_process_BANG_.doInvoke(util.clj:341) [storm-core-1.0.1.jar:1.0.1]
at clojure.lang.RestFn.invoke(RestFn.java:423) [clojure-1.8.0.jar:?]
at org.apache.storm.daemon.worker$fn__8554$fn__8555.invoke(worker.clj:761) [storm-core-1.0.1.jar:1.0.1]
at org.apache.storm.daemon.executor$mk_executor_data$fn__7773$fn__7774.invoke(executor.clj:271) [storm-core-1.0.1.jar:1.0.1]
at org.apache.storm.util$async_loop$fn__625.invoke(util.clj:494) [storm-core-1.0.1.jar:1.0.1]
at clojure.lang.AFn.run(AFn.java:22) [clojure-1.8.0.jar:?]
at java.lang.Thread.run(Thread.java:745) [?:1.8.0_102]
请在下面找到 {key.deserializer = org.apache.kafka.common.serialization.ByteArrayDeserializer,value.deserializer = org.apache.kafka.common.serialization.ByteArrayDeserializer,组完整的壶嘴CONFIGS。 id = test-group,ssl.keystore.location = C:/test.jks,bootstrap.servers = localhost:1000,auto.commit.interval.ms = 1000,security.protocol = SSL,enable.auto.commit = true ,ssl.truststore.location = C:/test1.jks,ssl.keystore.password = pass123,ssl.key.password = pass123,ssl.truststore.password = pass123,session.timeout.ms = 30000,auto.offset。重置=最新}
谢谢@Sriharsha Chintalapani我们还需要修复https://github.com/apache/storm/pull/1924。你能告诉我哪个版本的storm-kafka-client应该与Storm 1.0.1一起使用 –