Logging 如何使用log4j在日志中打印spring kafka配置

Logging 如何使用log4j在日志中打印spring kafka配置,logging,properties,apache-kafka,spring-kafka,Logging,Properties,Apache Kafka,Spring Kafka,有没有办法使用log4j在日志中记录所有spring kafka配置?我尝试在我的应用程序log4j2.yml中使用以下记录器配置,我可以看到所有信息和调试日志,但看不到配置。 -名称:org.springframework.kafka 可加性:false 级别:信息/调试 附录REF: -参考:一些附录 提前感谢您的帮助。我认为您只需要担心应用于Apache Kafka客户端的属性。这也将涵盖Spring Kafka配置。为此,您只需为org.apache.kafka.clients类别配置I

有没有办法使用log4j在日志中记录所有spring kafka配置?我尝试在我的应用程序log4j2.yml中使用以下记录器配置,我可以看到所有信息和调试日志,但看不到配置。 -名称:org.springframework.kafka 可加性:false 级别:信息/调试 附录REF: -参考:一些附录
提前感谢您的帮助。

我认为您只需要担心应用于Apache Kafka客户端的属性。这也将涵盖Spring Kafka配置。为此,您只需为
org.apache.kafka.clients
类别配置
INFO

这是我一次测试的日志:

16:55:20.616 INFO  [main][org.apache.kafka.clients.consumer.ConsumerConfig] ConsumerConfig values: 
    auto.commit.interval.ms = 10
    auto.offset.reset = earliest
    bootstrap.servers = [127.0.0.1:56505]
    check.crcs = true
    client.id = 
    connections.max.idle.ms = 540000
    enable.auto.commit = false
    exclude.internal.topics = true
    fetch.max.bytes = 52428800
    fetch.max.wait.ms = 500
    fetch.min.bytes = 1
    group.id = blc
    heartbeat.interval.ms = 3000
    interceptor.classes = null
    internal.leave.group.on.close = true
    isolation.level = read_uncommitted
    key.deserializer = class org.apache.kafka.common.serialization.IntegerDeserializer
    max.partition.fetch.bytes = 1048576
    max.poll.interval.ms = 300000
    max.poll.records = 500
    metadata.max.age.ms = 300000
    metric.reporters = []
    metrics.num.samples = 2
    metrics.recording.level = INFO
    metrics.sample.window.ms = 30000
    partition.assignment.strategy = [class org.apache.kafka.clients.consumer.RangeAssignor]
    receive.buffer.bytes = 65536
    reconnect.backoff.max.ms = 1000
    reconnect.backoff.ms = 50
    request.timeout.ms = 305000
    retry.backoff.ms = 100
    sasl.jaas.config = null
    sasl.kerberos.kinit.cmd = /usr/bin/kinit
    sasl.kerberos.min.time.before.relogin = 60000
    sasl.kerberos.service.name = null
    sasl.kerberos.ticket.renew.jitter = 0.05
    sasl.kerberos.ticket.renew.window.factor = 0.8
    sasl.mechanism = GSSAPI
    security.protocol = PLAINTEXT
    send.buffer.bytes = 131072
    session.timeout.ms = 60000
    ssl.cipher.suites = null
    ssl.enabled.protocols = [TLSv1.2, TLSv1.1, TLSv1]
    ssl.endpoint.identification.algorithm = null
    ssl.key.password = null
    ssl.keymanager.algorithm = SunX509
    ssl.keystore.location = null
    ssl.keystore.password = null
    ssl.keystore.type = JKS
    ssl.protocol = TLS
    ssl.provider = null
    ssl.secure.random.implementation = null
    ssl.trustmanager.algorithm = PKIX
    ssl.truststore.location = null
    ssl.truststore.password = null
    ssl.truststore.type = JKS
    value.deserializer = class org.apache.kafka.common.serialization.StringDeserializer

这对我来说很好

Configutation:
  name: Default

  Properties:
    Property:
      name: log-path
      value: "logs"

  Appenders:

    Console:
      name: Console_Appender
      target: SYSTEM_OUT
      PatternLayout:
        pattern: "[%-5level] %d{yyyy-MM-dd HH:mm:ss.SSS} [%t] %c{1} - %msg%n"

  Loggers:

      Root:
        level: warn
        AppenderRef:
          - ref: Console_Appender

      Logger:
        - name: org.apache.kafka
          level: info
          AppenderRef:
            - ref: Console_Appender


我知道org.apache.kafka会记录所有kafka客户端属性,但我想记录Spring kafka属性。示例如果我使用以下Spring Kafka道具配置应用程序,我应该能够在日志中看到这些配置,但这些道具不会显示为“org.apache.Kafka”的一部分Spring:Kafka:consumer:enable auto commit:false listener:ack mode:record某些Spring引导属性(特别是
消费者
生产者
)设置卡夫卡属性;例如,代码>启用自动提交< /COD>在卡夫卡属性中设置<代码>启用.Auto.Prime<代码>属性。我们目前不提供一种内置机制来记录Spring特定属性,如“代码> ACK模式< /代码>,但您可以添加自己的。请随意打开A,我们将考虑将其添加到未来。release.Contributions是受欢迎的。感谢Gary确认日志中没有打印Spring Kafka属性的默认方法。一个选项将是..感谢我更改package
org.apache.Kafka.clients的日志级别
有助于避免服务启动时日志混乱。正如Hoxton.SR1中使用Spring Cloud Stream的Kafka消费者所做的那样具有信息日志级别的大量配置日志。
[INFO ] 2017-12-20 17:00:08.591 [main] ProducerConfig - ProducerConfig values: 
    acks = 1
    batch.size = 16384
    bootstrap.servers = [localhost:9092]
    buffer.memory = 33554432
    ...