kafka安装并测试
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)= RD_KAFKA_RESP_ERR_NO_ERROR)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。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()rd_kafka_flu
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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));
else
fprintf(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 -lrt
static 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));
else
fprintf(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 termination
snprintf(tmp, sizeof(tmp), "%i", SIGIO);
rd_kafka_conf_set(conf, "internal.termination.signal", tmp, NULL, 0);
//topic configuration
topic_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list
if (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list
rd_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 handle
rd_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-1
while(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
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