scrapy-culster集群搭建之kafka安装
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环境同上次zookeeper的安装环境一致就不累赘了。我们来下载kafka,这里我下载的是Scala 2.10 - kafka_2.10-0.10.2.0.tgz (asc, md5)版本的
wget https://www.apache.org/dyn/closer.cgi?path=/kafka/0.10.2.0/kafka_2.11-0.10.2.0.tgz
完成后解压:
[root@shulaibao4 ~]# tar zxf kafka_2.11-0.10.2.0.tgz[root@shulaibao4 ~]# mv kafka_2.11-0.10.2.0 /usr/lib[root@shulaibao4 ~]# cd /usr/lib/kafka_2.11-0.10.2.0
现在这个单台机器的集群是可以启动起来的,但是我们的目的是搭建三台机器的集群,那我们来开始配置,打开conf文件下的server.properties
[root@shulaibao4 kafka_2.11-0.10.2.0]# vim config/server.properties # 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=2 # kafka的机器编号,host.name = 172.*.*.13 # 绑定ipport=9092 # 默认端口9092,# Switch to enable topic deletion or not, default value is falsedelete.topic.enable=true############################# Socket Server Settings ############################## The address the socket server listens on. It will get the value returned from # java.net.InetAddress.getCanonicalHostName() if not configured.# FORMAT:# listeners = listener_name://host_name:port# EXAMPLE:# listeners = PLAINTEXT://your.host.name:9092#listeners=PLAINTEXT://:9092# Hostname and port the broker will advertise to producers and consumers. If not set, # it uses the value for "listeners" if configured. Otherwise, it will use the value# returned from java.net.InetAddress.getCanonicalHostName().#advertised.listeners=PLAINTEXT://your.host.name:9092# Maps listener names to security protocols, the default is for them to be the same. See the config documentation for more details#listener.security.protocol.map=PLAINTEXT:PLAINTEXT,SSL:SSL,SASL_PLAINTEXT:SASL_PLAINTEXT,SASL_SSL:SASL_SSL# The number of threads handling network requestsnum.network.threads=3# The number of threads doing disk I/Onum.io.threads=8# The send buffer (SO_SNDBUF) used by the socket serversocket.send.buffer.bytes=102400# The receive buffer (SO_RCVBUF) used by the socket serversocket.receive.buffer.bytes=102400# 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 fileslog.dirs=/tmp/kafka-logs # kafka的日志目录,话题,偏移量等也存于此处# 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=3 # 设置复制数量,默认是1# The number of threads per data directory to be used for log recovery at startup and flushing at shutdown.# This value is recommended to be increased for installations with data dirs located in RAID array.num.recovery.threads.per.data.dir=1############################# 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 ############################## 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 due to agelog.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. Functions independently of log.retention.hours.#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=1073741824# The interval at which log segments are checked to see if they can be deleted according# to the retention policieslog.retention.check.interval.ms=300000############################# 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#zookeeper.connect=workstation1:2181zookeeper.connect=172.*.*.12:2181,172.*.*.13:2181,172.*.*.14:2181 # 连接zookeeper集群,# Timeout in ms for connecting to zookeeperzookeeper.connection.timeout.ms=6000
此配置文件配置好后把kafka文件scp到其他机器上,
[root@shulaibao4 kafka_2.11-0.10.2.0]# cd ..[root@shulaibao4 lib]# scp -r kafka_2.11-0.10.2.0/ root@172.*.*.14: /usr/lib......[root@shulaibao4 lib]# scp -r kafka_2.11-0.10.2.0/ root@172.*.*.12: /usr/lib......
在这两台机器上只需要修改conf目录下的server.properties文件即可,
第一, 修改 broker.id且互相不可重复,
第二, 修改 host.name,改为各自机器绑定的IP
每台机器做完这两步,这个小小的集群就搭建起来了,接下来我们让它运行起来
首先启动每台机器的zookeeper,(上篇文章已介绍,这里不在累赘)
然后启动我们的kafka集群,命令如下:
[root@shulaibao4 kafka_2.11-0.10.2.0]# bin/kafka-server-start.sh config/server.properties &[1] 12608[root@shulaibao4 kafka_2.11-0.10.2.0]# [2017-08-10 11:56:48,766] INFO KafkaConfig values: … … … … … …
当我们看到如下输出则证明单台机器启动成功:
… …[2017-08-10 11:56:49,930] INFO Kafka version : 0.10.2.0 (org.apache.kafka.common.utils.AppInfoParser)[2017-08-10 11:56:49,931] INFO Kafka commitId : 576d93a8dc0cf421 (org.apache.kafka.common.utils.AppInfoParser)[2017-08-10 11:56:49,931] INFO [Kafka Server 2], started (kafka.server.KafkaServer)
接下来我们验证下我们的集群是否可用, 首先创建一个 test“topic”,
[root@shulaibao4 kafka_2.11-0.10.2.0]# bin/kafka-topics.sh --create --zookeeper shulaibao3:2181 --replication-factor 1 --partitions 1 --topic testCreated topic "test".[root@shulaibao4 kafka_2.11-0.10.2.0]#
然后在另一台机器上查看我们刚创建的 topic的详细信息
[root@shulaibao4 kafka_2.11-0.10.2.0]# bin/kafka-topics.sh --describe --zookeeper shulaibao4:2181 --topic testTopic:test PartitionCount:1 ReplicationFactor:1 Configs: Topic: test Partition: 0 Leader: 3 Replicas: 3 Isr: 3
查看集群中所有的 topic 列表
[root@shulaibao5 kafka_2.11-0.10.2.0]# bin/kafka-topics.sh --list --zookeeper shulaibao4:2181test[root@shulaibao5 kafka_2.11-0.10.2.0]#
可以看到这个 topic已经在集群中, 接下来我们利用此 topic 来生产和消费,这里输入完成后敲回车键就可以了,当然也可以读取文件或者数据库将内容发送出去
[root@shulaibao5 kafka_2.11-0.10.2.0]# bin/kafka-console-producer.sh --broker-list shulaibao4:9092 --topic test This is a scrapy cluster
接着我们来消费刚才发送的消息:
[root@shulaibao3 kafka_2.11-0.10.2.0]# bin/kafka-console-consumer.sh --zookeeper shulaibao4:2181 --topic test --from-beginningUsing the ConsoleConsumer with old consumer is deprecated and will be removed in a future major release. Consider using the new consumer by passing [bootstrap-server] instead of [zookeeper].This is a scrapy cluster
这里可以看到消息被消费了,只要这个消费窗口不关,有test的消息被生产,此窗口就会消费。
至此我们的kafka集群已经搭建完成并且可以正常工作了。
接下来我们看看scrapy-cluster集群的搭建。
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