docker pull wurstmeister/zookeeper
docker pull wurstmeister/kafka
二、先啟動zookeeper
#單機方式
docker run -d --name zookeeper -p 2181:2181 -t wurstmeister/zookeeper
三、啟動kafka
#單機方式
docker run -d --name kafka \
-p 9092:9092 \
-e KAFKA_BROKER_ID=0 \
-e KAFKA_ZOOKEEPER_CONNECT=10.0.0.101:2181 \
-e KAFKA_ADVERTISED_LISTENERS=PLAINTEXT://10.0.0.101:9092 \
-e KAFKA_LISTENERS=PLAINTEXT://0.0.0.0:9092 wurstmeister/kafka
四、創建一個topic(使用代碼次步可省略)
#進入容器
docker exec -it ${CONTAINER ID} /bin/bash
cd opt/bin
#單機方式:創建一個主題
bin/kafka-topics.sh --create --zookeeper zookeeper:2181 --replication-factor 1 --partitions 1 --topic mykafka
#運行一個生產者
bin/kafka-console-producer.sh --broker-list localhost:9092 --topic mykafka
#運行一個消費者
bin/kafka-console-consumer.sh --zookeeper zookeeper:2181 --topic mykafka --from-beginning
五、kafka設置分區數量
#分區數量的作用:有多少分區就能負載多少個消費者,生產者會自動分配給分區數據,每個消費者只消費自己分區的數據,每個分區有自己獨立的offset
#進入kafka容器
vi opt/kafka/config/server.properties
修改run.partitions=2
#退出容器
ctrl+p+q
#重啟容器
docker restart kafka
#修改指定topic
./kafka-topics.sh --zookeeper localhost:2181 --alter --partitions 3 --topic topicname
六、python代碼
#生產者
from kafka import KafkaProducer
import json
import datetime
topic='test'
producer = KafkaProducer(bootstrap_servers='10.0.0.101:9092',value_serializer=lambda m:json.dumps(m).encode("utf-8")) # 連接kafka
# 參數bootstrap_servers:指定kafka連接地址
# 參數value_serializer:指定序列化的方式,我們定義json來序列化數據,當字典傳入kafka時自動轉換成bytes
# 用戶密碼登入參數
# security_protocol="SASL_PLAINTEXT"
# sasl_mechanism="PLAIN"
# sasl_plain_username="maple"
# sasl_plain_password="maple"
for i in range(1000):
data={"num":i,"ts":datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S")}
producer.send(topic,data)
producer.close()
#消費者
from kafka import KafkaConsumer
import time
topic = 'test'
consumer = KafkaConsumer(topic, bootstrap_servers=['10.0.0.101:9092'], group_id="test", auto_offset_reset="earliest")
# 參數bootstrap_servers:指定kafka連接地址
# 參數group_id:如果2個程序的topic和group_id相同,那么他們讀取的數據不會重復,2個程序的topic相同,group_id不同,那么他們各自消費相同的數據,互不影響
# 參數auto_offset_reset:默認為latest表示offset設置為當前程序啟動時的數據位置,earliest表示offset設置為0,在你的group_id第一次運行時,還沒有offset的時候,給你設定初始offset。一旦group_id有了offset,那么此參數就不起作用了
for msg in consumer:
recv = "%s:%d:%d: key=%s value=%s" % (msg.topic, msg.partition, msg.offset, msg.key, msg.value)
print(recv)
# time.sleep(1)
#運行3個消費者結果
test:0:3212: key=None value=b'{"num": 981, "ts": "2021-02-23 16:38:14"}'
test:0:3213: key=None value=b'{"num": 982, "ts": "2021-02-23 16:38:14"}'
test:0:3214: key=None value=b'{"num": 987, "ts": "2021-02-23 16:38:14"}'
test:0:3215: key=None value=b'{"num": 997, "ts": "2021-02-23 16:38:14"}'
test:0:3216: key=None value=b'{"num": 998, "ts": "2021-02-23 16:38:14"}'
test:0:3217: key=None value=b'{"num": 999, "ts": "2021-02-23 16:38:14"}'
test:1:353: key=None value=b'{"num": 970, "ts": "2021-02-23 16:38:14"}'
test:1:354: key=None value=b'{"num": 977, "ts": "2021-02-23 16:38:14"}'
test:1:355: key=None value=b'{"num": 978, "ts": "2021-02-23 16:38:14"}'
test:1:356: key=None value=b'{"num": 979, "ts": "2021-02-23 16:38:14"}'
test:1:357: key=None value=b'{"num": 984, "ts": "2021-02-23 16:38:14"}'
test:1:358: key=None value=b'{"num": 985, "ts": "2021-02-23 16:38:14"}'
test:1:359: key=None value=b'{"num": 994, "ts": "2021-02-23 16:38:14"}'
test:2:317: key=None value=b'{"num": 989, "ts": "2021-02-23 16:38:14"}'
test:2:318: key=None value=b'{"num": 990, "ts": "2021-02-23 16:38:14"}'
test:2:319: key=None value=b'{"num": 991, "ts": "2021-02-23 16:38:14"}'
test:2:320: key=None value=b'{"num": 992, "ts": "2021-02-23 16:38:14"}'
test:2:321: key=None value=b'{"num": 993, "ts": "2021-02-23 16:38:14"}'
test:2:322: key=None value=b'{"num": 995, "ts": "2021-02-23 16:38:14"}'
test:2:323: key=None value=b'{"num": 996, "ts": "2021-02-23 16:38:14"}'