一. Linux下ZooKeeper的安装及使用
1、创建工作目录，下载安装包
#创建安装目录
mkdir -p /opt/zookeeper
#移动到目录
cd /opt/zookeepe
#下载zookeeper安装包
wget https://mirrors.aliyun.com/apache/zookeeper/zookeeper-3.4.14/zookeeper-3.4.14.tar.gz
#解压缩
tar -zxvf zookeeper-3.4.14.tar.gz
2、配置文件
#移到配置目录
cd /opt/zookeeper/zookeeper-3.4.14/conf/
#复制配置文件
cp zoo_sample.cfg zoo.cfg
#修改及添加以下配置
tickTime=2000
initLimit=10
syncLimit=5
dataDir=/opt/zookeeper/zoodata
dataLogDir=/opt/zookeeper/zoodatalog
clientPort=2181
server.0=127.0.0.1:2888:3888
#多节点 集群
#server.1=127.0.0.1:4888:5888
#server.2=127.0.0.1:5888:6888
admin.serverPort=9099
#保存退出
#配置说明
tickTime：客户端会话超时时间，默认2000毫秒。
initLimit：配置客户端初始化可接受多少个心跳监测，默认10，即10*tickTime(默认2000)，表示20s没有连接上集群的配置则连接失败。
syncLimit：配置Leader和follwer之间，允许多少个请求应答长度，默认5，即5*tickTime(默认2000)，表示默认10sLeader和Follwer之间如果消息5次没有发送成功就不尝试了。
dataDir：配置存储快照文件的目录。
dataLogDir：配置事务日志存储的目录。
clientPort：服务默认端口，默认2181。
server.X=A:B:C 其中X是一个数字，表示这是第几号server，A是该server所在的IP地址，B配置该server和集群中的leader交换消息所使用的端口，C配置选举leader时所使用的端口。
3、创建节点的myid
#创建dataDir目录
mkdir -p /opt/zookeeper/zoodata
#移动到目录
cd /opt/zookeeper/zoodata
#把节点号写入myid文件(各个节点分别配置)
echo 0 > myid
#配置端口防火墙(各个节点分别配置)
firewall-cmd --zone=public --add-port=2181/tcp --permanent
firewall-cmd --reload
4、启动ZooKeeper
#重启
./zkServer.sh restart
#关闭
./zkServer.sh stop
#查看状态
./zkServer.sh staus
#启动的时候，查看后台信息
./zkServer.sh start-foreground &
没起来的可能报错
2023-10-27 14:15:16,975 [myid:0] - ERROR [main:ZooKeeperServerMain@85] - Unable to start AdminServer, exiting abnormally
原因： zk admin启动默认端口是8080，如果有其他服务在用8080，那启动时就报错了，端口已被绑定 配置文件中添加admin.serverPort=9099
5、客户端连接
#启动客户端
./zkCli.sh#创建节点
create /test test1
#获取节点数据
get /test
#更新节点
set /test test2
#删除节点
delete /test
#递归删除数据，将子目录的数据也删除掉
rmr /test
#查看节点
ls /
#查看输入过的命令
history
二. Linux下搭建Kafka服务
1、安装JDK 1.8
java -version 命令查看JDK版本，如图安装成功
[root@localhost kafka]# java -version
java version "1.8.0_201"
Java(TM) SE Runtime Environment (build 1.8.0_201-b09)
Java HotSpot(TM) 64-Bit Server VM (build 25.201-b09, mixed mode)
2、安装kafka
#创建安装目录
mkdir -p /opt/kafka
#移动到目录
cd /opt/kafka
#下载kafka安装包
wget https://mirrors.aliyun.com/apache/kafka/2.5.0/kafka_2.12-2.5.0.tgz
#解压缩
tar -zxvf kafka_2.12-2.5.0.tgz
3、配置文件
#进入配置目录
cd kafka_2.12-2.5.0/config/
#备份配置文件
cp server.properties server.properties.bak
#修改配置文件
vim server.properties
#修改及添加以下配置
broker.id=1
listeners=PLAINTEXT://127.0.0.1:9092
advertised.listeners=PLAINTEXT://127.0.0.1:9092
#其他自定义配置（根据实际修改）
zookeeper.connect=127.0.0.1:2181
zookeeper.connection.timeout.ms=18000
#保存退出
#配置说明
broker.id：当前机器在集群中的唯一标识。例如有三台Kafka主机，则分别配置为1,2,3。
listeners：服务监听端口。
advertised.listeners：提供给生产者，消费者的端口号，即外部访问地址。默认为listeners的值。
zookeeper.connect：zookeeper连接地址。如有集群配置，每台Kafka主机都需要连接全部zookeeper服务，实例如下：
zookeeper.connect=192.168.1.41:2181,192.168.1.42:2181,192.168.1.47:2181
zookeeper.connection.timeout.ms：zookeeper连接超时时间。
4、启动Kafka
#移到工作目录
cd /opt/kafka/kafka_2.12-2.5.0/bin/
#启动kafka
./kafka-server-start.sh -daemon ../config/server.properties
#关闭kafka服务
./kafka-server-stop.sh
查看端口已被监听，启动成功:
[root@localhost kafka]# netstat -antlp | grep 9092
tcp 0 0 127.0.0.1:34162 127.0.0.1:9092 ESTABLISHED 19313/./my_producer
tcp6 0 0 127.0.0.1:9092 :::* LISTEN 10101/java
tcp6 1 0 127.0.0.1:34142 127.0.0.1:9092 CLOSE_WAIT 10101/java
tcp6 0 0 127.0.0.1:9092 127.0.0.1:34162 ESTABLISHED 10101/java
5、测试创建一个topic
#移到工作目录
cd /opt/kafka/kafka_2.12-2.5.0/bin/
#创建topic
./kafka-topics.sh --create --zookeeper 127.0.0.1:2181 --replication-factor 1 --partitions 1 --topic topic1
#查看topic信息
./kafka-topics.sh --describe --zookeeper 127.0.0.1:2181 --topic topic1
测试
#启动生产者控制台
[root@localhost bin]# ./kafka-console-producer.sh --broker-list 127.0.0.1:9092 --topic t1
>test
>123456
#启动消费者控制台（新开一个窗口）
[root@localhost bin]# ./kafka-console-consumer.sh --bootstrap-server 127.0.0.1:9092 --topic t1 --from-beginning
test
123456
[root@localhost bin]# ./kafka-topics.sh --create --zookeeper 127.0.0.1:2181 --replication-factor 1 --partitions 1 --topic t1
Created topic t1.
[root@localhost bin]#
[root@localhost bin]# ./kafka-topics.sh --describe --zookeeper 127.0.0.1:2181 --topic t1
Topic: t1 PartitionCount: 1 ReplicationFactor: 1 Configs:Topic: t1 Partition: 0 Leader: 0 Replicas: 0 Isr: 0
[root@localhost bin]#
三. c语言使用librdkafka库实现kafka的生产和消费实例
1. 生产者常用接口
1、创建kafka配置
rd_kafka_conf_t *rd_kafka_conf_new (void)
2、配置kafka各项参数
rd_kafka_conf_res_t rd_kafka_conf_set (rd_kafka_conf_t *conf,const char *name,const char *value,char *errstr, size_t errstr_size)
3、设置发送回调函数
void rd_kafka_conf_set_dr_msg_cb (rd_kafka_conf_t *conf,void (*dr_msg_cb) (rd_kafka_t *rk,const rd_kafka_message_t *rkmessage,void *opaque))
4、创建producer实例
rd_kafka_t *rd_kafka_new (rd_kafka_type_t type, rd_kafka_conf_t *conf,char *errstr, size_t errstr_size)
5、实例化topic
rd_kafka_topic_t *rd_kafka_topic_new (rd_kafka_t *rk, const char *topic, rd_kafka_topic_conf_t *conf)
6、异步调用将消息发送到指定的topic
int rd_kafka_produce (rd_kafka_topic_t *rkt, int32_t partition,int msgflags,void *payload, size_t len,const void *key, size_t keylen,void *msg_opaque)
7、阻塞等待消息发送完成
int rd_kafka_poll (rd_kafka_t *rk, int timeout_ms)
8、等待完成producer请求完成
rd_kafka_resp_err_t rd_kafka_flush (rd_kafka_t *rk, int timeout_ms)
9、销毁topic
void rd_kafka_topic_destroy (rd_kafka_topic_t *app_rkt)
10、销毁producer实例
void rd_kafka_destroy (rd_kafka_t *rk)
生产者实例实现：
#include <stdio.h>
#include <signal.h>
#include <string.h>
#include "librdkafka/rdkafka.h"
// gcc produce.c -o my_producer -lrdkafka -lz -lpthread -lrt
static int run = 1;
static void stop(int sig){run = 0;fclose(stdin);
}
/*每条消息调用一次该回调函数，说明消息是传递成功(rkmessage->err == RD_KAFKA_RESP_ERR_NO_ERROR)还是传递失败(rkmessage->err != RD_KAFKA_RESP_ERR_NO_ERROR)该回调函数由rd_kafka_poll()触发，在应用程序的线程上执行
*/
static void dr_msg_cb(rd_kafka_t *rk,const rd_kafka_message_t *rkmessage, void *opaque){if(rkmessage->err)fprintf(stderr, "%% Message delivery failed: %s\n",rd_kafka_err2str(rkmessage->err));elsefprintf(stderr,"%% Message delivered (%zd bytes, ""partition %"PRId32")\n",rkmessage->len, rkmessage->partition);/* rkmessage被librdkafka自动销毁*/
}
int main(int argc, char **argv){rd_kafka_t *rk; /*Producer instance handle*/rd_kafka_topic_t *rkt; /*topic对象*/rd_kafka_conf_t *conf; /*临时配置对象*/char errstr[512]; char buf[512]; const char *brokers; const char *topic; if(argc != 3){fprintf(stderr, "%% Usage: %s <broker> <topic>\n", argv[0]);return 1;}brokers = argv[1];topic = argv[2];/* 创建一个kafka配置占位 */conf = rd_kafka_conf_new();/*创建broker集群*/if (rd_kafka_conf_set(conf, "bootstrap.servers", brokers, errstr,sizeof(errstr)) != RD_KAFKA_CONF_OK){fprintf(stderr, "%s\n", errstr);return 1;}/*设置发送报告回调函数，rd_kafka_produce()接收的每条消息都会调用一次该回调函数*应用程序需要定期调用rd_kafka_poll()来服务排队的发送报告回调函数*/rd_kafka_conf_set_dr_msg_cb(conf, dr_msg_cb);/*创建producer实例rd_kafka_new()获取conf对象的所有权,应用程序在此调用之后不得再次引用它*/rk = rd_kafka_new(RD_KAFKA_PRODUCER, conf, errstr, sizeof(errstr));if(!rk){fprintf(stderr, "%% Failed to create new producer:%s\n", errstr);return 1;}/*实例化一个或多个topics(`rd_kafka_topic_t`)来提供生产或消费，topic对象保存topic特定的配置，并在内部填充所有可用分区和leader brokers，*/rkt = rd_kafka_topic_new(rk, topic, NULL);if (!rkt){fprintf(stderr, "%% Failed to create topic object: %s\n",rd_kafka_err2str(rd_kafka_last_error()));rd_kafka_destroy(rk);return 1;}/*用于中断的信号*/signal(SIGINT, stop);fprintf(stderr,"%% Type some text and hit enter to produce message\n""%% Or just hit enter to only serve delivery reports\n""%% Press Ctrl-C or Ctrl-D to exit\n");while(run && fgets(buf, sizeof(buf), stdin)){size_t len = strlen(buf);if(buf[len-1] == '\n')buf[--len] = '\0';if(len == 0){/*轮询用于事件的kafka handle，事件将导致应用程序提供的回调函数被调用第二个参数是最大阻塞时间，如果设为0，将会是非阻塞的调用*/rd_kafka_poll(rk, 0);continue;}retry:/*Send/Produce message.这是一个异步调用，在成功的情况下，只会将消息排入内部producer队列，对broker的实际传递尝试由后台线程处理，之前注册的传递回调函数(dr_msg_cb)用于在消息传递成功或失败时向应用程序发回信号*/if (rd_kafka_produce(/* Topic object */rkt,/*使用内置的分区来选择分区*/RD_KAFKA_PARTITION_UA,/*生成payload的副本*/RD_KAFKA_MSG_F_COPY,/*消息体和长度*/buf, len,/*可选键及其长度*/NULL, 0,NULL) == -1){fprintf(stderr,"%% Failed to produce to topic %s: %s\n",rd_kafka_topic_name(rkt),rd_kafka_err2str(rd_kafka_last_error()));if (rd_kafka_last_error() == RD_KAFKA_RESP_ERR__QUEUE_FULL){/*如果内部队列满，等待消息传输完成并retry,内部队列表示要发送的消息和已发送或失败的消息，内部队列受限于queue.buffering.max.messages配置项*/rd_kafka_poll(rk, 1000);goto retry;} }else{fprintf(stderr, "%% Enqueued message (%zd bytes) for topic %s\n",len, rd_kafka_topic_name(rkt));}/*producer应用程序应不断地通过以频繁的间隔调用rd_kafka_poll()来为传送报告队列提供服务。在没有生成消息以确定先前生成的消息已发送了其发送报告回调函数(和其他注册过的回调函数)期间，要确保rd_kafka_poll()仍然被调用*/rd_kafka_poll(rk, 0);}fprintf(stderr, "%% Flushing final message.. \n");/*rd_kafka_flush是rd_kafka_poll()的抽象化，等待所有未完成的produce请求完成，通常在销毁producer实例前完成以确保所有排列中和正在传输的produce请求在销毁前完成*/rd_kafka_flush(rk, 10*1000);/* Destroy topic object */rd_kafka_topic_destroy(rkt);/* Destroy the producer instance */rd_kafka_destroy(rk);return 0;
}
**2. 消费者常用接口 **
1、创建kafka配置
rd_kafka_conf_t *rd_kafka_conf_new (void)
2、创建kafka topic的配置
rd_kafka_topic_conf_t *rd_kafka_topic_conf_new (void)
3、配置kafka各项参数
rd_kafka_conf_res_t rd_kafka_conf_set (rd_kafka_conf_t *conf,const char *name,const char *value,char *errstr, size_t errstr_size)
4、配置kafka topic各项参数
rd_kafka_conf_res_t rd_kafka_topic_conf_set (rd_kafka_topic_conf_t *conf,const char *name,const char *value,char *errstr, size_t errstr_size)
5、创建consumer实例
rd_kafka_t *rd_kafka_new (rd_kafka_type_t type, rd_kafka_conf_t *conf, char *errstr, size_t errstr_size)
6、为consumer实例添加brokerlist
int rd_kafka_brokers_add (rd_kafka_t *rk, const char *brokerlist)
7、开启consumer订阅
rd_kafka_subscribe (rd_kafka_t *rk, const rd_kafka_topic_partition_list_t *topics)
8、轮询消息或事件，并调用回调函数
rd_kafka_message_t *rd_kafka_consumer_poll (rd_kafka_t *rk,int timeout_ms)
9、关闭consumer实例
rd_kafka_resp_err_t rd_kafka_consumer_close (rd_kafka_t *rk)
10、释放topic list资源
rd_kafka_topic_partition_list_destroy (rd_kafka_topic_partition_list_t *rktparlist)
11、销毁consumer实例
void rd_kafka_destroy (rd_kafka_t *rk)
12、等待consumer对象的销毁
int rd_kafka_wait_destroyed (int timeout_ms)
消费者实例实现
#include <string.h>
#include <stdlib.h>
#include <syslog.h>
#include <signal.h>
#include <error.h>
#include <getopt.h>
#include "librdkafka/rdkafka.h"// gcc consume.c -o my_consumer -lrdkafka -lz -lpthread -lrtstatic int run = 1;
//`rd_kafka_t`自带一个可选的配置API，如果没有调用API，Librdkafka将会使用CONFIGURATION.md中的默认配置。
static rd_kafka_t *rk;
static rd_kafka_topic_partition_list_t *topics;
static void stop (int sig) {if (!run)exit(1);run = 0;fclose(stdin); /* abort fgets() */
}
static void sig_usr1 (int sig) {rd_kafka_dump(stdout, rk);
}
/**
* 处理并打印已消费的消息
*/
static void msg_consume (rd_kafka_message_t *rkmessage,void *opaque) {if (rkmessage->err) {if (rkmessage->err == RD_KAFKA_RESP_ERR__PARTITION_EOF) {fprintf(stderr,"%% Consumer reached end of %s [%"PRId32"] ""message queue at offset %"PRId64"\n",rd_kafka_topic_name(rkmessage->rkt),rkmessage->partition, rkmessage->offset);return;}if (rkmessage->rkt)fprintf(stderr, "%% Consume error for ""topic \"%s\" [%"PRId32"] ""offset %"PRId64": %s\n",rd_kafka_topic_name(rkmessage->rkt),rkmessage->partition,rkmessage->offset,rd_kafka_message_errstr(rkmessage));elsefprintf(stderr, "%% Consumer error: %s: %s\n",rd_kafka_err2str(rkmessage->err),rd_kafka_message_errstr(rkmessage));if (rkmessage->err == RD_KAFKA_RESP_ERR__UNKNOWN_PARTITION ||rkmessage->err == RD_KAFKA_RESP_ERR__UNKNOWN_TOPIC)run = 0;return;}fprintf(stdout, "%% Message (topic %s [%"PRId32"], ""offset %"PRId64", %zd bytes):\n",rd_kafka_topic_name(rkmessage->rkt),rkmessage->partition,rkmessage->offset, rkmessage->len);if (rkmessage->key_len) {printf("Key: %.*s\n",(int)rkmessage->key_len, (char *)rkmessage->key);}printf("%.*s\n",(int)rkmessage->len, (char *)rkmessage->payload);}
/*init all configuration of kafka
*/
int initKafka(char *brokers, char *group,char *topic){rd_kafka_conf_t *conf;rd_kafka_topic_conf_t *topic_conf;rd_kafka_resp_err_t err;char tmp[16];char errstr[512];/* Kafka configuration */conf = rd_kafka_conf_new();//quick terminationsnprintf(tmp, sizeof(tmp), "%i", SIGIO);rd_kafka_conf_set(conf, "internal.termination.signal", tmp, NULL, 0);//topic configurationtopic_conf = rd_kafka_topic_conf_new();/* Consumer groups require a group id */if (!group)group = "rdkafka_consumer_example";if (rd_kafka_conf_set(conf, "group.id", group,errstr, sizeof(errstr)) !=RD_KAFKA_CONF_OK) {fprintf(stderr, "%% %s\n", errstr);return -1;}/* Consumer groups always use broker based offset storage */if (rd_kafka_topic_conf_set(topic_conf, "offset.store.method","broker",errstr, sizeof(errstr)) !=RD_KAFKA_CONF_OK) {fprintf(stderr, "%% %s\n", errstr);return -1;}/* Set default topic config for pattern-matched topics. */rd_kafka_conf_set_default_topic_conf(conf, topic_conf);//实例化一个顶级对象rd_kafka_t作为基础容器，提供全局配置和共享状态rk = rd_kafka_new(RD_KAFKA_CONSUMER, conf, errstr, sizeof(errstr));if(!rk){fprintf(stderr, "%% Failed to create new consumer:%s\n", errstr);return -1;}//Librdkafka需要至少一个brokers的初始化listif (rd_kafka_brokers_add(rk, brokers) == 0){fprintf(stderr, "%% No valid brokers specified\n");return -1;}//重定向 rd_kafka_poll()队列到consumer_poll()队列rd_kafka_poll_set_consumer(rk);//创建一个Topic+Partition的存储空间(list/vector)topics = rd_kafka_topic_partition_list_new(1);//把Topic+Partition加入listrd_kafka_topic_partition_list_add(topics, topic, -1);//开启consumer订阅，匹配的topic将被添加到订阅列表中if((err = rd_kafka_subscribe(rk, topics))){fprintf(stderr, "%% Failed to start consuming topics: %s\n", rd_kafka_err2str(err));return -1;}return 1;
}
int main(int argc, char **argv){char *brokers = "localhost:9092";char *group = NULL;char *topic = NULL;int opt;rd_kafka_resp_err_t err;while ((opt = getopt(argc, argv, "g:b:t:qd:eX:As:DO")) != -1){switch (opt) {case 'b':brokers = optarg;break;case 'g':group = optarg;break;case 't':topic = optarg;break;default:break;}}signal(SIGINT, stop);signal(SIGUSR1, sig_usr1);if(!initKafka(brokers, group, topic)){fprintf(stderr, "kafka server initialize error\n");}else{while(run){rd_kafka_message_t *rkmessage;/*-轮询消费者的消息或事件，最多阻塞timeout_ms-应用程序应该定期调用consumer_poll()，即使没有预期的消息，以服务所有排队等待的回调函数，当注册过rebalance_cb，该操作尤为重要，因为它需要被正确地调用和处理以同步内部消费者状态 */rkmessage = rd_kafka_consumer_poll(rk, 1000);if(rkmessage){msg_consume(rkmessage, NULL);/*释放rkmessage的资源，并把所有权还给rdkafka*/rd_kafka_message_destroy(rkmessage);}}}
done:/*此调用将会阻塞，直到consumer撤销其分配，调用rebalance_cb(如果已设置)，commit offset到broker,并离开consumer group最大阻塞时间被设置为session.timeout.ms*/err = rd_kafka_consumer_close(rk);if(err){fprintf(stderr, "%% Failed to close consumer: %s\n", rd_kafka_err2str(err));}else{fprintf(stderr, "%% Consumer closed\n");}//释放topics list使用的所有资源和它自己rd_kafka_topic_partition_list_destroy(topics);//destroy kafka handlerd_kafka_destroy(rk);run = 5;//等待所有rd_kafka_t对象销毁，所有kafka对象被销毁，返回0，超时返回-1while(run-- > 0 && rd_kafka_wait_destroyed(1000) == -1){printf("Waiting for librdkafka to decommission\n");}if(run <= 0){//dump rdkafka内部状态到stdout流rd_kafka_dump(stdout, rk);}return 0;
}
运行：
[root@localhost kafka]# ./my_consumer -b localhost:9092 -t t1
%4|1592810248.073|CONFWARN|rdkafka#consumer-1| [thrd:app]: Configuration property offset.store.method is deprecated: Offset commit store method: 'file' - DEPRECATED: local file store (offset.store.path, et.al), 'broker' - broker commit store (requires "group.id" to be configured and Apache Kafka 0.8.2 or later on the broker.).
% Message (topic t1 [0], offset 5, 6 bytes):
hellpo
% Message (topic t1 [0], offset 6, 6 bytes):
123456[root@localhost kafka]# ./my_producer localhost:9092 t1
% Type some text and hit enter to produce message
% Or just hit enter to only serve delivery reports
% Press Ctrl-C or Ctrl-D to exit
hellpo
% Enqueued message (6 bytes) for topic t1
123456
)
EM算法的推导)
