这部分内容对了解系统和提高软件性能都有很大的帮助,kafka官网上也给出了比较详细的配置详单,但是我们还是直接从代码来看broker到底有哪些配置需要我们去了解的,配置都有英文注释,所以每一部分是干什么的就不翻译了,都能看懂:
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package kafka.server
import java.util.Properties
import kafka.utils.{Utils, ZKConfig}
import kafka.message.Message
/**
* Configuration settings for the kafka server
*/
class KafkaConfig(props: Properties) extends ZKConfig(props) {
/* the port to listen and accept connections on */
val port: Int = Utils.getInt(props, "port", 6667)
/* hostname of broker. If not set, will pick up from the value returned from getLocalHost. If there are multiple interfaces getLocalHost may not be what you want. */
val hostName: String = Utils.getString(props, "hostname", null)
/* the broker id for this server */
val brokerId: Int = Utils.getInt(props, "brokerid")
/* the SO_SNDBUFF buffer of the socket sever sockets */
val socketSendBuffer: Int = Utils.getInt(props, "socket.send.buffer", 100*1024)
/* the SO_RCVBUFF buffer of the socket sever sockets */
val socketReceiveBuffer: Int = Utils.getInt(props, "socket.receive.buffer", 100*1024)
/* the maximum number of bytes in a socket request */
val maxSocketRequestSize: Int = Utils.getIntInRange(props, "max.socket.request.bytes", 100*1024*1024, (1, Int.MaxValue))
/* the maximum size of message that the server can receive */
val maxMessageSize = Utils.getIntInRange(props, "max.message.size", 1000000, (0, Int.MaxValue))
/* the number of worker threads that the server uses for handling all client requests*/
val numThreads = Utils.getIntInRange(props, "num.threads", Runtime.getRuntime().availableProcessors, (1, Int.MaxValue))
/* the interval in which to measure performance statistics */
val monitoringPeriodSecs = Utils.getIntInRange(props, "monitoring.period.secs", 600, (1, Int.MaxValue))
/* the default number of log partitions per topic */
val numPartitions = Utils.getIntInRange(props, "num.partitions", 1, (1, Int.MaxValue))
/* the directory in which the log data is kept */
val logDir = Utils.getString(props, "log.dir")
/* the maximum size of a single log file */
val logFileSize = Utils.getIntInRange(props, "log.file.size", 1*1024*1024*1024, (Message.MinHeaderSize, Int.MaxValue))
/* the maximum size of a single log file for some specific topic */
val logFileSizeMap = Utils.getTopicFileSize(Utils.getString(props, "topic.log.file.size", ""))
/* the maximum time before a new log segment is rolled out */
val logRollHours = Utils.getIntInRange(props, "log.roll.hours", 24*7, (1, Int.MaxValue))
/* the number of hours before rolling out a new log segment for some specific topic */
val logRollHoursMap = Utils.getTopicRollHours(Utils.getString(props, "topic.log.roll.hours", ""))
/* the number of hours to keep a log file before deleting it */
val logRetentionHours = Utils.getIntInRange(props, "log.retention.hours", 24*7, (1, Int.MaxValue))
/* the number of hours to keep a log file before deleting it for some specific topic*/
val logRetentionHoursMap = Utils.getTopicRetentionHours(Utils.getString(props, "topic.log.retention.hours", ""))
/* the maximum size of the log before deleting it */
val logRetentionSize = Utils.getLong(props, "log.retention.size", -1)
/* the maximum size of the log for some specific topic before deleting it */
val logRetentionSizeMap = Utils.getTopicRetentionSize(Utils.getString(props, "topic.log.retention.size", ""))
/* the frequency in minutes that the log cleaner checks whether any log is eligible for deletion */
val logCleanupIntervalMinutes = Utils.getIntInRange(props, "log.cleanup.interval.mins", 10, (1, Int.MaxValue))
/* enable zookeeper registration in the server */
val enableZookeeper = Utils.getBoolean(props, "enable.zookeeper", true)
/* the number of messages accumulated on a log partition before messages are flushed to disk */
val flushInterval = Utils.getIntInRange(props, "log.flush.interval", 500, (1, Int.MaxValue))
/* the maximum time in ms that a message in selected topics is kept in memory before flushed to disk, e.g., topic1:3000,topic2: 6000 */
val flushIntervalMap = Utils.getTopicFlushIntervals(Utils.getString(props, "topic.flush.intervals.ms", ""))
/* the frequency in ms that the log flusher checks whether any log needs to be flushed to disk */
val flushSchedulerThreadRate = Utils.getInt(props, "log.default.flush.scheduler.interval.ms", 3000)
/* the maximum time in ms that a message in any topic is kept in memory before flushed to disk */
val defaultFlushIntervalMs = Utils.getInt(props, "log.default.flush.interval.ms", flushSchedulerThreadRate)
/* the number of partitions for selected topics, e.g., topic1:8,topic2:16 */
val topicPartitionsMap = Utils.getTopicPartitions(Utils.getString(props, "topic.partition.count.map", ""))
/* the maximum length of topic name*/
val maxTopicNameLength = Utils.getIntInRange(props, "max.topic.name.length", 255, (1, Int.MaxValue))
}
上面这段代码来自kafka.server包下的KafkaConfig类,之前我们就说过,broker就是kafka中的server,所以讲配置放在这个包中也不奇怪。这里我们顺着代码往下读,也顺便看看scala的语法。和java一样也要import相关的包,kafka将同一包内的两个类写在大括号中:
import kafka.utils.{Utils, ZKConfig}
然后我们看类的写法:
class KafkaConfig(props: Properties) extends ZKConfig(props)
我们看到在加载kafkaConfig的时候会加载一个properties对象,同时也会加载有关zookeeper的properties,这个时候我们可以回忆一下,之前我们启动kafka broker的命令:
启动zookeeper server :bin/zookeeper-server-start.sh ../config/zookeeper.properties & (用&是为了能退出命令行)
启动kafka server: bin/kafka-server-start.sh ../config/server.properties &
所以你能明白,初始化kafka broker的时候程序一定是去加载位于config文件夹下的properties,这个和java都一样没有区别。当然properties我们也可以通过程序来给出,这个我们后面再说,继续看我们的代码。既然找到了对应的properties文件,我们就结合代码和properties一起来看。
Kafka broker的properties中,将配置分为以下六类:
l Server Basics:关于brokerid,hostname等配置
l Socket Server Settings:关于传输的配置,端口、buffer的区间等。
l Log Basics:配置log的位置和partition的数量。
l Log Flush Policy:这部分是kafka配置中最重要的部分,决定了数据flush到disk的策略。
l Log Retention Policy:这部分主要配置日志处理时的策略。
l Zookeeper:配置zookeeper的相关信息。
在文件properties中的配置均出现在kafkaConfig这个类中,我们再看看kafkaConfig中的代码:
/* the broker id for this server */
val brokerId: Int = Utils.getInt(props, "brokerid")
/* the SO_SNDBUFF buffer of the socket sever sockets */
val socketSendBuffer: Int = Utils.getInt(props, "socket.send.buffer", 100*1024)
凡是参数中有三个的,最后一个是default,而参数只有两个的则要求你一定要配置,否则的话则报错。当然在这么多参数中肯定是有一些经验参数的,至于这些参数怎么配置我确实没有一个特别的推荐,需要在不断的测试中才能磨合出来。
当然你也可以将配置写在程序里,然后通过程序去启动broker,这样kafka的配置就可以像下面一样写:
Properties props = new Properties();
props.setProperty("port","9093");
props.setProperty("log.dir","/home/kafka/data1");
我倒是觉得配置还是直接写在配置文件中比较好,如果需要修改也不会影响正在运行的服务,写在内存中,总是会有些不方便的地方。所以还是建议大家都写配置好了,后面讲到的producer和consumer都一样。
这里再提两个参数一个是brokerid,每个broker的id必须要区分;第二个参数是hostname,这个是broker和producer、consumer联系的关键,这里记住一定要改成你的地址和端口,否则永远连得都是localhost。
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下一篇将写producer和consumer的配置了,涉及到这部分就要开始编程了,写着写着又往源码里看进去了,下篇会先讲如何搭建开发环境,然后再写两个简单那的例子去熟悉配置。