uforwarder/src/main/resources/application-uforwarder-controller.yaml [165:216]:
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    kafka:
      enabled: true
      # This determines how we will resolve the kafka brokers.
      resolverClass: com.uber.data.kafka.datatransfer.common.KafkaClusterResolver
      # This is the bootstrap server that is used if resovlerMode = STATIC.
      bootstrapServers: 127.0.0.1:9092
      # The acks setting that we pass to Apache Kafka Producer.
      acks: all
      # This metrics reporting interval for Kafka Producer metrics in ms.
      metricsInterval: 60000
      # The maximum size of a request in bytes. This setting will limit the number of record batches the producer
      # will send in a single request to avoid sending huge requests. This is also effectively a cap on the maximum
      # uncompressed record batch size. Note that the server has its own cap on the record batch size (after compression
      # if compression is enabled) which may be different from this.
      maxRequestSize: 31457280
      # This decides if KCP will have compression enabled when producing messages into the retry
      # queues and DLQs. It also specifies the compression algorithm
      compressionType: snappy
  # These are the configurations for the processors.
  processor:
    # The thread pool size for each processor
    # As those threads process message, its workload is usually high. If there are CPU
    # throttling problems, please (1) increase the # of CPU cores (2) increase this number
    threadPoolSize: 4
    # The max number of unprocessed inbound messages cached for each topic-partition.
    maxInboundCacheCount: 1000
    # The max number of unprocessed outbound messages cached for each topic-partition.
    # This number can be override by user-defined JobConfiguration.
    maxOutboundCacheCount: 400
    # The max difference between an ACKed offset and the largest committed offset for each
    # topic-partition.
    maxAckCommitSkew: 10000
    # This filters out messages that was not originally produced to the cluster that it is being read from.
    clusterFilterEnabled: false
  # These are the configurations for the fetchers.
  fetcher:
    # These are the configurations for the kafka fetcher.
    kafka:
      # Enable the kafka spring auto configuration.
      # Setting this to true will automatically inject the kafka fetcher into the spring container.
      enabled: true
      # This determines how we will resolve the kafka brokers.
      resolverClass: com.uber.data.kafka.datatransfer.common.KafkaClusterResolver
      # This is the bootstrap server that is used if resolverClass = STATIC.
      bootstrapServers: 127.0.0.1:9092
  # These are configurations for the pipeline
  pipeline:
    manager:
      # This is the interval for the pipeline manager to garbage collect unused pipelines
      gcInterval: 60000 # 1 min in ms
      # This is the interval for the pipeline manager to log and report metrics
      metricsInterval: 10000 # 10s
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uforwarder/src/main/resources/application-uforwarder-worker.yaml [81:132]:
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    kafka:
      enabled: true
      # This determines how we will resolve the kafka brokers.
      resolverClass: com.uber.data.kafka.datatransfer.common.KafkaClusterResolver
      # This is the bootstrap server that is used if resovlerMode = STATIC.
      bootstrapServers: 127.0.0.1:9092
      # The acks setting that we pass to Apache Kafka Producer.
      acks: all
      # This metrics reporting interval for Kafka Producer metrics in ms.
      metricsInterval: 60000
      # The maximum size of a request in bytes. This setting will limit the number of record batches the producer
      # will send in a single request to avoid sending huge requests. This is also effectively a cap on the maximum
      # uncompressed record batch size. Note that the server has its own cap on the record batch size (after compression
      # if compression is enabled) which may be different from this.
      maxRequestSize: 31457280
      # This decides if KCP will have compression enabled when producing messages into the retry
      # queues and DLQs. It also specifies the compression algorithm
      compressionType: snappy
  # These are the configurations for the processors.
  processor:
    # The thread pool size for each processor
    # As those threads process message, its workload is usually high. If there are CPU
    # throttling problems, please (1) increase the # of CPU cores (2) increase this number
    threadPoolSize: 4
    # The max number of unprocessed inbound messages cached for each topic-partition.
    maxInboundCacheCount: 1000
    # The max number of unprocessed outbound messages cached for each topic-partition.
    # This number can be override by user-defined JobConfiguration.
    maxOutboundCacheCount: 400
    # The max difference between an ACKed offset and the largest committed offset for each
    # topic-partition.
    maxAckCommitSkew: 10000
    # This filters out messages that was not originally produced to the cluster that it is being read from.
    clusterFilterEnabled: false
  # These are the configurations for the fetchers.
  fetcher:
    # These are the configurations for the kafka fetcher.
    kafka:
      # Enable the kafka spring auto configuration.
      # Setting this to true will automatically inject the kafka fetcher into the spring container.
      enabled: true
      # This determines how we will resolve the kafka brokers.
      resolverClass: com.uber.data.kafka.datatransfer.common.KafkaClusterResolver
      # This is the bootstrap server that is used if resolverClass = STATIC.
      bootstrapServers: 127.0.0.1:9092
  # These are configurations for the pipeline
  pipeline:
    manager:
      # This is the interval for the pipeline manager to garbage collect unused pipelines
      gcInterval: 60000 # 1 min in ms
      # This is the interval for the pipeline manager to log and report metrics
      metricsInterval: 10000 # 10s
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