apache-kafka - Kafka 消费者测试和报告指标

Question

我想了解 kafka 消费者测试的工作原理以及如何解释报告的一些数字，

下面是我运行的测试和我得到的输出。我的问题是

1. rebalance.time.ms、fetch.time.ms、fetch.MB.sec、fetch.nMsg.sec 的报告值为 1593109326098、-1593108732333、-0.0003、-0.2800 ;你能解释一下它是如何报告如此高的负数的吗？他们对我来说没有意义。
2. Metric Name Value 行报告的所有内容都是由于 --print-metrics 标志而报告的。默认报告的指标和带有此标志的指标之间有什么区别？它们是如何计算的，我在哪里可以了解它们的含义？
3. 无论我扩展并行运行的消费者总数，还是扩展代理处的网络和 io 线程，consumer-fetch-manager-metrics:fetch-latency-avg 指标几乎保持不变。你能解释一下吗？随着更多消费者拉取数据，延迟应该会更高；类似地，对于给定的消费率，如果我减少 io 和代理的网络线程参数，延迟是否应该更高？

这是我运行的命令

[root@oak-clx17 kafka_2.12-2.5.0]# bin/kafka-consumer-perf-test.sh --topic topic_test8_cons_test1 --threads 1  --broker-list clx20:9092 --messages 500000000 --consumer.config config/consumer.properties --print-metrics

和结果

    start.time, end.time, data.consumed.in.MB, MB.sec, data.consumed.in.nMsg, nMsg.sec, rebalance.time.ms,fetch.time.ms, fetch.MB.sec, fetch.nMsg.sec
    WARNING: Exiting before consuming the expected number of messages: timeout (10000 ms) exceeded. You can use the --timeout option to increase the timeout.
    2020-06-25 11:22:05:814, 2020-06-25 11:31:59:579, 435640.7686, 733.6922, 446096147, 751300.8463, 1593109326098, -1593108732333, -0.0003, -0.2800
     
    Metric Name                                                                                                                                    Value
    consumer-coordinator-metrics:assigned-partitions:{client-id=consumer-perf-consumer-25533-1}                                                  : 0.000
    consumer-coordinator-metrics:commit-latency-avg:{client-id=consumer-perf-consumer-25533-1}                                                   : 2.700
    consumer-coordinator-metrics:commit-latency-max:{client-id=consumer-perf-consumer-25533-1}                                                   : 4.000
    consumer-coordinator-metrics:commit-rate:{client-id=consumer-perf-consumer-25533-1}                                                          : 0.230
    consumer-coordinator-metrics:commit-total:{client-id=consumer-perf-consumer-25533-1}                                                         : 119.000
    consumer-coordinator-metrics:failed-rebalance-rate-per-hour:{client-id=consumer-perf-consumer-25533-1}                                       : 0.000
    consumer-coordinator-metrics:failed-rebalance-total:{client-id=consumer-perf-consumer-25533-1}                                               : 1.000
    consumer-coordinator-metrics:heartbeat-rate:{client-id=consumer-perf-consumer-25533-1}                                                       : 0.337
    consumer-coordinator-metrics:heartbeat-response-time-max:{client-id=consumer-perf-consumer-25533-1}                                          : 6.000
    consumer-coordinator-metrics:heartbeat-total:{client-id=consumer-perf-consumer-25533-1}                                                      : 197.000
    consumer-coordinator-metrics:join-rate:{client-id=consumer-perf-consumer-25533-1}                                                            : 0.000
    consumer-coordinator-metrics:join-time-avg:{client-id=consumer-perf-consumer-25533-1}                                                        : NaN
    consumer-coordinator-metrics:join-time-max:{client-id=consumer-perf-consumer-25533-1}                                                        : NaN
    consumer-coordinator-metrics:join-total:{client-id=consumer-perf-consumer-25533-1}                                                           : 1.000
    consumer-coordinator-metrics:last-heartbeat-seconds-ago:{client-id=consumer-perf-consumer-25533-1}                                           : 2.000
    consumer-coordinator-metrics:last-rebalance-seconds-ago:{client-id=consumer-perf-consumer-25533-1}                                           : 593.000
    consumer-coordinator-metrics:partition-assigned-latency-avg:{client-id=consumer-perf-consumer-25533-1}                                       : NaN
    consumer-coordinator-metrics:partition-assigned-latency-max:{client-id=consumer-perf-consumer-25533-1}                                       : NaN
    consumer-coordinator-metrics:partition-lost-latency-avg:{client-id=consumer-perf-consumer-25533-1}                                           : NaN
    consumer-coordinator-metrics:partition-lost-latency-max:{client-id=consumer-perf-consumer-25533-1}                                           : NaN
    consumer-coordinator-metrics:partition-revoked-latency-avg:{client-id=consumer-perf-consumer-25533-1}                                        : 0.000
    consumer-coordinator-metrics:partition-revoked-latency-max:{client-id=consumer-perf-consumer-25533-1}                                        : 0.000
    consumer-coordinator-metrics:rebalance-latency-avg:{client-id=consumer-perf-consumer-25533-1}                                                : NaN
    consumer-coordinator-metrics:rebalance-latency-max:{client-id=consumer-perf-consumer-25533-1}                                                : NaN
    consumer-coordinator-metrics:rebalance-latency-total:{client-id=consumer-perf-consumer-25533-1}                                              : 83.000
    consumer-coordinator-metrics:rebalance-rate-per-hour:{client-id=consumer-perf-consumer-25533-1}                                              : 0.000
    consumer-coordinator-metrics:rebalance-total:{client-id=consumer-perf-consumer-25533-1}                                                      : 1.000
    consumer-coordinator-metrics:sync-rate:{client-id=consumer-perf-consumer-25533-1}                                                            : 0.000
    consumer-coordinator-metrics:sync-time-avg:{client-id=consumer-perf-consumer-25533-1}                                                        : NaN
    consumer-coordinator-metrics:sync-time-max:{client-id=consumer-perf-consumer-25533-1}                                                        : NaN
    consumer-coordinator-metrics:sync-total:{client-id=consumer-perf-consumer-25533-1}                                                           : 1.000
    consumer-fetch-manager-metrics:bytes-consumed-rate:{client-id=consumer-perf-consumer-25533-1, topic=topic_test8_cons_test1}                  : 434828205.989
    consumer-fetch-manager-metrics:bytes-consumed-rate:{client-id=consumer-perf-consumer-25533-1}                                                : 434828205.989
    consumer-fetch-manager-metrics:bytes-consumed-total:{client-id=consumer-perf-consumer-25533-1, topic=topic_test8_cons_test1}                 : 460817319851.000
    consumer-fetch-manager-metrics:bytes-consumed-total:{client-id=consumer-perf-consumer-25533-1}                                               : 460817319851.000
    consumer-fetch-manager-metrics:fetch-latency-avg:{client-id=consumer-perf-consumer-25533-1}                                                  : 58.870
    consumer-fetch-manager-metrics:fetch-latency-max:{client-id=consumer-perf-consumer-25533-1}                                                  : 503.000
    consumer-fetch-manager-metrics:fetch-rate:{client-id=consumer-perf-consumer-25533-1}                                                         : 48.670
    consumer-fetch-manager-metrics:fetch-size-avg:{client-id=consumer-perf-consumer-25533-1, topic=topic_test8_cons_test1}                       : 9543108.526
    consumer-fetch-manager-metrics:fetch-size-avg:{client-id=consumer-perf-consumer-25533-1}                                                     : 9543108.526
    consumer-fetch-manager-metrics:fetch-size-max:{client-id=consumer-perf-consumer-25533-1, topic=topic_test8_cons_test1}                       : 11412584.000
    consumer-fetch-manager-metrics:fetch-size-max:{client-id=consumer-perf-consumer-25533-1}                                                     : 11412584.000
    consumer-fetch-manager-metrics:fetch-throttle-time-avg:{client-id=consumer-perf-consumer-25533-1}                                            : 0.000
    consumer-fetch-manager-metrics:fetch-throttle-time-max:{client-id=consumer-perf-consumer-25533-1}                                            : 0.000
    consumer-fetch-manager-metrics:fetch-total:{client-id=consumer-perf-consumer-25533-1}                                                        : 44889.000
    Exception in thread "main" java.util.IllegalFormatConversionException: f != java.lang.Integer
    at java.base/java.util.Formatter$FormatSpecifier.failConversion(Formatter.java:4426)
            at java.base/java.util.Formatter$FormatSpecifier.printFloat(Formatter.java:2951)
            at java.base/java.util.Formatter$FormatSpecifier.print(Formatter.java:2898)
            at java.base/java.util.Formatter.format(Formatter.java:2673)
            at java.base/java.util.Formatter.format(Formatter.java:2609)
            at java.base/java.lang.String.format(String.java:2897)
            at scala.collection.immutable.StringLike.format(StringLike.scala:354)
            at scala.collection.immutable.StringLike.format$(StringLike.scala:353)
            at scala.collection.immutable.StringOps.format(StringOps.scala:33)
            at kafka.utils.ToolsUtils$.$anonfun$printMetrics$3(ToolsUtils.scala:60)
            at kafka.utils.ToolsUtils$.$anonfun$printMetrics$3$adapted(ToolsUtils.scala:58)
            at scala.collection.mutable.ResizableArray.foreach(ResizableArray.scala:62)
            at scala.collection.mutable.ResizableArray.foreach$(ResizableArray.scala:55)
            at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:49)
            at kafka.utils.ToolsUtils$.printMetrics(ToolsUtils.scala:58)
            at kafka.tools.ConsumerPerformance$.main(ConsumerPerformance.scala:82)
            at kafka.tools.ConsumerPerformance.main(ConsumerPerformance.scala)

Answer 1

1. https://medium.com/metrosystemsro/apache-kafka-how-to-test-performance-for-clients-configured-with-ssl-encryption-3356d3a0d52b这是我写的一篇关于此的帖子。

预期根据 this KIP用于rebalance.time.ms 和fetch.time.ms 以显示消费者组的总重新平衡时间和不包括重新平衡时间的总获取时间。据我所知，从 Apache Kafka 版本 2.6.0 开始，这项工作仍在进行中，目前输出是 Unix epoch time 中的时间戳。 .fetch.MB.sec 和 fetch.nMsg.sec 旨在显示每秒消耗的平均消息数量(以 MB 为单位并作为计数)

1. 参见 https://kafka.apache.org/documentation/#consumer_group_monitoring对于使用 --print-metrics 标记

   列出的消费者组指标

2. fetch-latency-avg(获取请求所花费的平均时间)会有所不同，但这在很大程度上取决于测试设置。