Do you read from the file in the callback from kafka? I just implemented c++ bindings and in one of the tests i did I got the following results:
1000 messages per batch (fairly small messages ~150 bytes) and then wait for the network layer to ack the send (not server ack)'s before putting another message on the tcp socket. This seems to give me a average latency of 17 ms. Througput about 10MB/s . If you are serializing your requests and is reading data from disk between calls to kafka then that would easily explain some added milliseconds in each call and thus a reduced throughput. Partitioning will not reduce latency. /svante 2014-05-26 6:18 GMT+02:00 Zhujie (zhujie, Smartcare) < first.zhu...@huawei.com>: > Only one broker，and eight partitions, async mode. > > Increase the number of batch.num.messages is useless. > > We split the whole file into 1K per block. > > > -----邮件原件----- > 发件人: robairrob...@gmail.com [mailto:robairrob...@gmail.com] 代表 Robert > Turner > 发送时间: 2014年5月16日 13:45 > 收件人: users@kafka.apache.org > 主题: Re: kafka performance question > > A couple of thoughts spring to mind, are you sending the whole file as 1 > message? and is your producer code using sync or async mode? > > Cheers > Rob. > > > On 14 May 2014 15:49, Jun Rao <jun...@gmail.com> wrote: > > > How many brokers and partitions do you have? You may try increasing > > batch.num.messages. > > > > Thanks, > > > > Jun > > > > > > On Tue, May 13, 2014 at 5:56 PM, Zhujie (zhujie, Smartcare) < > > first.zhu...@huawei.com> wrote: > > > > > Dear all, > > > > > > We want to use kafka to collect and dispatch data file, but the > > > performance is maybe lower than we want. > > > > > > In our cluster,there is a provider and a broker. We use a one thread > > > read file from local disk of provider and send it to broker. The > > > average throughput is only 3 MB/S~4MB/S. > > > But if we just use java NIO API to send file ,the throughput can > > > exceed 200MB/S. > > > Why the kafka performance is so bad in our test, are we missing > > something?? > > > > > > > > > > > > Our server: > > > Cpu: Intel(R) Xeon(R) CPU E5-4650 0 @ 2.70GHz*4 Mem:300G Disk:600G > > > 15K RPM SAS*8 > > > > > > Configuration of provider: > > > props.put("serializer.class", "kafka.serializer.NullEncoder"); > > > props.put("metadata.broker.list", "169.10.35.57:9092"); > > > props.put("request.required.acks", "0"); props.put("producer.type", > > > "async");//异步 > > > props.put("queue.buffering.max.ms","500"); > > > props.put("queue.buffering.max.messages","1000000000"); > > > props.put("batch.num.messages", "1200"); > > > props.put("queue.enqueue.timeout.ms", "-1"); > > > props.put("send.buffer.bytes", "102400000"); > > > > > > Configuration of broker: > > > > > > # Licensed to the Apache Software Foundation (ASF) under one or more > > > # contributor license agreements. See the NOTICE file distributed > > > with # this work for additional information regarding copyright > ownership. > > > # The ASF licenses this file to You under the Apache License, > > > Version 2.0 # (the "License"); you may not use this file except in > > > compliance with # the License. You may obtain a copy of the License > > > at # > > > # http://www.apache.org/licenses/LICENSE-2.0 > > > # > > > # Unless required by applicable law or agreed to in writing, > > > software # distributed under the License is distributed on an "AS > > > IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either > > > express or > > implied. > > > # See the License for the specific language governing permissions > > > and # limitations under the License. > > > # see kafka.server.KafkaConfig for additional details and defaults > > > > > > ############################# Server Basics > > > ############################# > > > > > > # The id of the broker. This must be set to a unique integer for > > > each broker. > > > broker.id=0 > > > > > > ############################# Socket Server Settings > > > ############################# > > > > > > # The port the socket server listens on > > > port=9092 > > > > > > # Hostname the broker will bind to. If not set, the server will bind > > > to all interfaces #host.name=localhost > > > > > > # Hostname the broker will advertise to producers and consumers. If > > > not set, it uses the # value for "host.name" if configured. > > > Otherwise, it will use the value returned from # > > > java.net.InetAddress.getCanonicalHostName(). > > > #advertised.host.name=<hostname routable by clients> > > > > > > # The port to publish to ZooKeeper for clients to use. If this is > > > not > > set, > > > # it will publish the same port that the broker binds to. > > > #advertised.port=<port accessible by clients> > > > > > > # The number of threads handling network requests > > > #num.network.threads=2 > > > # The number of threads doing disk I/O > > > #num.io.threads=8 > > > > > > # The send buffer (SO_SNDBUF) used by the socket server > > > #socket.send.buffer.bytes=1048576 > > > > > > # The receive buffer (SO_RCVBUF) used by the socket server > > > #socket.receive.buffer.bytes=1048576 > > > > > > # The maximum size of a request that the socket server will accept > > > (protection against OOM) > > > #socket.request.max.bytes=104857600 > > > > > > > > > ############################# Log Basics > > > ############################# > > > > > > # A comma seperated list of directories under which to store log > > > files log.dirs=/data/kafka-logs > > > > > > # The default number of log partitions per topic. More partitions > > > allow greater # parallelism for consumption, but this will also > > > result in more files across # the brokers. > > > #num.partitions=2 > > > > > > ############################# Log Flush Policy > > > ############################# > > > > > > # Messages are immediately written to the filesystem but by default > > > we only fsync() to sync # the OS cache lazily. The following > > > configurations control the flush of data to disk. > > > # There are a few important trade-offs here: > > > # 1. Durability: Unflushed data may be lost if you are not using > > > replication. > > > # 2. Latency: Very large flush intervals may lead to latency spikes > > > when the flush does occur as there will be a lot of data to flush. > > > # 3. Throughput: The flush is generally the most expensive > operation, > > > and a small flush interval may lead to exceessive seeks. > > > # The settings below allow one to configure the flush policy to > > > flush > > data > > > after a period of time or > > > # every N messages (or both). This can be done globally and > > > overridden on a per-topic basis. > > > > > > # The number of messages to accept before forcing a flush of data to > > > disk > > > #log.flush.interval.messages=10000 > > > > > > # The maximum amount of time a message can sit in a log before we > > > force a flush > > > #log.flush.interval.ms=1000 > > > > > > ############################# Log Retention Policy > > > ############################# > > > > > > # The following configurations control the disposal of log segments. > > > The policy can # be set to delete segments after a period of time, > > > or after a given size has accumulated. > > > # A segment will be deleted whenever *either* of these criteria are > met. > > > Deletion always happens > > > # from the end of the log. > > > > > > # The minimum age of a log file to be eligible for deletion > > > #log.retention.hours=168 > > > > > > # A size-based retention policy for logs. Segments are pruned from > > > the > > log > > > as long as the remaining > > > # segments don't drop below log.retention.bytes. > > > #log.retention.bytes=1073741824 > > > > > > # The maximum size of a log segment file. When this size is reached > > > a new log segment will be created. > > > #log.segment.bytes=536870912 > > > > > > # The interval at which log segments are checked to see if they can > > > be deleted according # to the retention policies > > > log.retention.check.interval.ms=60000 > > > > > > # By default the log cleaner is disabled and the log retention > > > policy > > will > > > default to just delete segments after their retention expires. > > > # If log.cleaner.enable=true is set the cleaner will be enabled and > > > individual logs can then be marked for log compaction. > > > log.cleaner.enable=false > > > > > > ############################# Zookeeper > > > ############################# > > > > > > # Zookeeper connection string (see zookeeper docs for details). > > > # This is a comma separated host:port pairs, each corresponding to a > > > zk # server. e.g. "127.0.0.1:3000,127.0.0.1:3001,127.0.0.1:3002". > > > # You can also append an optional chroot string to the urls to > > > specify > > the > > > # root directory for all kafka znodes. > > > zookeeper.connect=localhost:2181 > > > > > > # Timeout in ms for connecting to zookeeper > > > zookeeper.connection.timeout.ms=1000000 > > > > > > # Replication configurations > > > num.replica.fetchers=0 > > > replica.fetch.max.bytes=104857600 > > > #replica.fetch.wait.max.ms=500 > > > #replica.high.watermark.checkpoint.interval.ms=5000 > > > #replica.socket.timeout.ms=30000 > > > #replica.socket.receive.buffer.bytes=65536 > > > #replica.lag.time.max.ms=10000 > > > #replica.lag.max.messages=4000 > > > > > > #controller.socket.timeout.ms=30000 > > > #controller.message.queue.size=10 > > > > > > # Log configuration > > > num.partitions=8 > > > message.max.bytes=104857600 > > > auto.create.topics.enable=true > > > log.index.interval.bytes=4096 > > > log.index.size.max.bytes=10485760 > > > log.retention.hours=168 > > > log.flush.interval.ms=10000 > > > log.flush.interval.messages=20000 > > > log.flush.scheduler.interval.ms=2000 > > > log.roll.hours=168 > > > log.cleanup.interval.mins=30 > > > log.segment.bytes=1073741824 > > > > > > # ZK configuration > > > zk.connection.timeout.ms=1000000 > > > zk.sync.time.ms=20000 > > > > > > # Socket server configuration > > > num.io.threads=8 > > > num.network.threads=20 > > > socket.request.max.bytes=104857600 > > > socket.receive.buffer.bytes=1048576 > > > socket.send.buffer.bytes=1048576 > > > queued.max.requests=5000 > > > fetch.purgatory.purge.interval.requests=10000 > > > producer.purgatory.purge.interval.requests=10000 > > > > > > > > > kafka.metrics.polling.interval.secs=5 > > > kafka.metrics.reporters=kafka.metrics.KafkaCSVMetricsReporter > > > kafka.csv.metrics.dir=/data/kafka_metrics > > > kafka.csv.metrics.reporter.enabled=false > > > > > > > > > > > > > > > -- > Cheers > Rob. >
