一.kafka介紹
kafka是一個分布式、多副本、多訂閱者、分區的，基於zoopkeeper協調的分布式日志系統。其主要特點為：
1.以時間復雜度為O(1)的方式提供消息持久化能力，即使對TB級以上的數據也能保證常數時間的訪問性能。
2.高吞吐率。即使在非常廉價的商用機器上也能做到單機支持每秒100K消息的傳輸。
3.支持kafka server間的消息分區以及分布式消費，同時保證每個partition內的消息順序和傳輸。
4.同時支持離線數據處理和實時數據處理。
二.應用場景
1.日志收集
2.數據推送
3.作為大緩沖區使用
4.服務中間件
三.應用架構
如上圖所示，一個kafka集群包含若干個Producer(服務器日志、業務數據、Web前端產生的page view等)，若干個Broker(kafka支持水平擴展，一般broker數量越多，集群的吞吐量越大)，若干個consumer group，一個zookeeper集群(kafka通過zookeeper管理集群配置、選舉leader、consumer group等發生變化時進行rebalance)。
3.1 名詞解釋
-
broker
消息中間件處理節點(服務器)，一個節點就是一個broker，一個kafka集群由一個或多個broker組成 -
Topic
kafka對消息進行歸類，發送到集群的每一條消息都要指定一個topic -
Partition
物理上的概念，每個topic包含一個或多個partition，一個partition對應一個文件夾，這個文件夾下存儲partition的數據和索引文件，每個partition內部是有序的。 -
Producer
生產者，負責發布消息到broker -
Consumer
消費者，從broker讀取消息 -
ConsumerGroup
每個consumer屬於一個特定的consumer group，可為每個consumer指定group name，若不指定，則屬於默認的group，一條消息可以發送到不同的consumer group，但一個consumer group中只能有一個consumer能消費這條消息。
四.kubernetes集群部署kafka
4.1 部署前准備
- 創建好的至少三個節點的kubernetes集群(這里我們使用的版本1.13.10)
- 創建好的存儲類StorageClass(這里我們使用的是cephfs)
4.2 部署yaml文件
1.部署zookeeper的yaml文件
[root@k8s001 kafka]# cat zookeeper.yaml
apiVersion: v1
kind: Service
metadata:
name: zk-hs
namespace: kafka
labels:
app: zk
spec:
ports:
- port: 2888
name: server
- port: 3888
name: leader-election
clusterIP: None
selector:
app: zk
---
apiVersion: v1
kind: Service
metadata:
name: zk-cs
namespace: kafka
labels:
app: zk
spec:
ports:
- port: 2181
name: client
selector:
app: zk
---
apiVersion: policy/v1beta1
kind: PodDisruptionBudget
metadata:
name: zk-pdb
namespace: kafka
spec:
selector:
matchLabels:
app: zk
maxUnavailable: 1
---
apiVersion: apps/v1
kind: StatefulSet
metadata:
name: zk
namespace: kafka
spec:
selector:
matchLabels:
app: zk
serviceName: zk-hs
replicas: 3
updateStrategy:
type: RollingUpdate
podManagementPolicy: Parallel
template:
metadata:
labels:
app: zk
spec:
nodeSelector:
travis.io/schedule-only: "kafka"
tolerations:
- key: "travis.io/schedule-only"
operator: "Equal"
value: "kafka"
effect: "NoSchedule"
- key: "travis.io/schedule-only"
operator: "Equal"
value: "kafka"
effect: "NoExecute"
tolerationSeconds: 3600
- key: "travis.io/schedule-only"
operator: "Equal"
value: "kafka"
effect: "PreferNoSchedule"
affinity:
podAntiAffinity:
requiredDuringSchedulingIgnoredDuringExecution:
- labelSelector:
matchExpressions:
- key: "app"
operator: In
values:
- zk
topologyKey: "kubernetes.io/hostname"
containers:
- name: kubernetes-zookeeper
imagePullPolicy: IfNotPresent
image: fastop/zookeeper:3.4.10
resources:
requests:
memory: "200Mi"
cpu: "0.1"
ports:
- containerPort: 2181
name: client
- containerPort: 2888
name: server
- containerPort: 3888
name: leader-election
command:
- sh
- -c
- "start-zookeeper \
--servers=3 \
--data_dir=/var/lib/zookeeper/data \
--data_log_dir=/var/lib/zookeeper/data/log \
--conf_dir=/opt/zookeeper/conf \
--client_port=2181 \
--election_port=3888 \
--server_port=2888 \
--tick_time=2000 \
--init_limit=10 \
--sync_limit=5 \
--heap=512M \
--max_client_cnxns=60 \
--snap_retain_count=3 \
--purge_interval=12 \
--max_session_timeout=40000 \
--min_session_timeout=4000 \
--log_level=INFO"
readinessProbe:
exec:
command:
- sh
- -c
- "zookeeper-ready 2181"
initialDelaySeconds: 10
timeoutSeconds: 5
livenessProbe:
exec:
command:
- sh
- -c
- "zookeeper-ready 2181"
initialDelaySeconds: 10
timeoutSeconds: 5
volumeMounts:
- name: datadir
mountPath: /var/lib/zookeeper
# 這里我們需要將runAsuser和fsGroup用戶調整為0，也就是管理員用戶允許，否則會提示權限的報錯
securityContext:
runAsUser: 0
fsGroup: 0
volumeClaimTemplates:
- metadata:
name: datadir
spec:
accessModes: [ "ReadWriteMany" ]
storageClassName: cephfs
resources:
requests:
storage: 20Gi
2.部署kafka的yaml文件
[root@k8s001 kafka]# cat kafka.yaml
---
apiVersion: v1
kind: Service
metadata:
name: kafka-svc
namespace: kafka
labels:
app: kafka
spec:
ports:
- port: 9092
name: server
clusterIP: None
selector:
app: kafka
---
apiVersion: policy/v1beta1
kind: PodDisruptionBudget
metadata:
name: kafka-pdb
namespace: kafka
spec:
selector:
matchLabels:
app: kafka
minAvailable: 2
---
apiVersion: apps/v1
kind: StatefulSet
metadata:
name: kafka
namespace: kafka
spec:
selector:
matchLabels:
app: kafka
serviceName: kafka-svc
replicas: 3
template:
metadata:
labels:
app: kafka
spec:
nodeSelector:
travis.io/schedule-only: "kafka"
tolerations:
- key: "travis.io/schedule-only"
operator: "Equal"
value: "kafka"
effect: "NoSchedule"
- key: "travis.io/schedule-only"
operator: "Equal"
value: "kafka"
effect: "NoExecute"
tolerationSeconds: 3600
- key: "travis.io/schedule-only"
operator: "Equal"
value: "kafka"
effect: "PreferNoSchedule"
affinity:
podAntiAffinity:
requiredDuringSchedulingIgnoredDuringExecution:
- labelSelector:
matchExpressions:
- key: "app"
operator: In
values:
- kafka
topologyKey: "kubernetes.io/hostname"
podAffinity:
preferredDuringSchedulingIgnoredDuringExecution:
- weight: 1
podAffinityTerm:
labelSelector:
matchExpressions:
- key: "app"
operator: In
values:
- zk
topologyKey: "kubernetes.io/hostname"
terminationGracePeriodSeconds: 300
containers:
- name: k8s-kafka
imagePullPolicy: IfNotPresent
image: fastop/kafka:2.2.0
resources:
requests:
memory: "600Mi"
cpu: 500m
ports:
- containerPort: 9092
name: server
command:
- sh
- -c
- "exec kafka-server-start.sh /opt/kafka/config/server.properties --override broker.id=${HOSTNAME##*-} \
--override listeners=PLAINTEXT://:9092 \
--override zookeeper.connect=zk-0.zk-hs.kafka.svc.cluster.local:2181,zk-1.zk-hs.kafka.svc.cluster.local:2181,zk-2.zk-hs.kafka.svc.cluster.local:2181 \
--override log.dir=/var/lib/kafka \
--override auto.create.topics.enable=true \
--override auto.leader.rebalance.enable=true \
--override background.threads=10 \
--override compression.type=producer \
--override delete.topic.enable=false \
--override leader.imbalance.check.interval.seconds=300 \
--override leader.imbalance.per.broker.percentage=10 \
--override log.flush.interval.messages=9223372036854775807 \
--override log.flush.offset.checkpoint.interval.ms=60000 \
--override log.flush.scheduler.interval.ms=9223372036854775807 \
--override log.retention.bytes=-1 \
--override log.retention.hours=168 \
--override log.roll.hours=168 \
--override log.roll.jitter.hours=0 \
--override log.segment.bytes=1073741824 \
--override log.segment.delete.delay.ms=60000 \
--override message.max.bytes=1000012 \
--override min.insync.replicas=1 \
--override num.io.threads=8 \
--override num.network.threads=3 \
--override num.recovery.threads.per.data.dir=1 \
--override num.replica.fetchers=1 \
--override offset.metadata.max.bytes=4096 \
--override offsets.commit.required.acks=-1 \
--override offsets.commit.timeout.ms=5000 \
--override offsets.load.buffer.size=5242880 \
--override offsets.retention.check.interval.ms=600000 \
--override offsets.retention.minutes=1440 \
--override offsets.topic.compression.codec=0 \
--override offsets.topic.num.partitions=50 \
--override offsets.topic.replication.factor=3 \
--override offsets.topic.segment.bytes=104857600 \
--override queued.max.requests=500 \
--override quota.consumer.default=9223372036854775807 \
--override quota.producer.default=9223372036854775807 \
--override replica.fetch.min.bytes=1 \
--override replica.fetch.wait.max.ms=500 \
--override replica.high.watermark.checkpoint.interval.ms=5000 \
--override replica.lag.time.max.ms=10000 \
--override replica.socket.receive.buffer.bytes=65536 \
--override replica.socket.timeout.ms=30000 \
--override request.timeout.ms=30000 \
--override socket.receive.buffer.bytes=102400 \
--override socket.request.max.bytes=104857600 \
--override socket.send.buffer.bytes=102400 \
--override unclean.leader.election.enable=true \
--override zookeeper.session.timeout.ms=6000 \
--override zookeeper.set.acl=false \
--override broker.id.generation.enable=true \
--override connections.max.idle.ms=600000 \
--override controlled.shutdown.enable=true \
--override controlled.shutdown.max.retries=3 \
--override controlled.shutdown.retry.backoff.ms=5000 \
--override controller.socket.timeout.ms=30000 \
--override default.replication.factor=1 \
--override fetch.purgatory.purge.interval.requests=1000 \
--override group.max.session.timeout.ms=300000 \
--override group.min.session.timeout.ms=6000 \
--override inter.broker.protocol.version=2.2.0 \
--override log.cleaner.backoff.ms=15000 \
--override log.cleaner.dedupe.buffer.size=134217728 \
--override log.cleaner.delete.retention.ms=86400000 \
--override log.cleaner.enable=true \
--override log.cleaner.io.buffer.load.factor=0.9 \
--override log.cleaner.io.buffer.size=524288 \
--override log.cleaner.io.max.bytes.per.second=1.7976931348623157E308 \
--override log.cleaner.min.cleanable.ratio=0.5 \
--override log.cleaner.min.compaction.lag.ms=0 \
--override log.cleaner.threads=1 \
--override log.cleanup.policy=delete \
--override log.index.interval.bytes=4096 \
--override log.index.size.max.bytes=10485760 \
--override log.message.timestamp.difference.max.ms=9223372036854775807 \
--override log.message.timestamp.type=CreateTime \
--override log.preallocate=false \
--override log.retention.check.interval.ms=300000 \
--override max.connections.per.ip=2147483647 \
--override num.partitions=4 \
--override producer.purgatory.purge.interval.requests=1000 \
--override replica.fetch.backoff.ms=1000 \
--override replica.fetch.max.bytes=1048576 \
--override replica.fetch.response.max.bytes=10485760 \
--override reserved.broker.max.id=1000 "
env:
- name: KAFKA_HEAP_OPTS
value : "-Xmx512M -Xms512M"
- name: KAFKA_OPTS
value: "-Dlogging.level=INFO"
volumeMounts:
- name: datadir
mountPath: /var/lib/kafka
readinessProbe:
tcpSocket:
port: 9092
timeoutSeconds: 1
initialDelaySeconds: 5
securityContext:
runAsUser: 1000
fsGroup: 1000
volumeClaimTemplates:
- metadata:
name: datadir
spec:
accessModes: [ "ReadWriteMany" ]
storageClassName: cephfs
resources:
requests:
storage: 20Gi
4.3 部署
這里zookeeper和kafka都是有狀態的服務，不能使用deployment和rc這種控制器來部署，這里我們使用statefulset來部署zookeeper和kafka服務。
4.3.1 給節點打標簽
這里我們想在哪幾台機器上來運行kafka，需要對節點進行打標簽。
kubectl label node [node-name] travis.io/schedule-only=kafka
當然，如果我們如果不想在哪些節點運行kafka，可以通過配置污點來進行。
kubectl taint node [node-name] travis.io/schedule-only=kafka:NoSchedule
4.3.2 創建命名空間
[root@k8s001 kafka]# kubectl create ns kafka
4.3.3 創建zookeeper服務
# 創建zookeeper服務
[root@k8s001 kafka]# kubectl apply -f zookeeper.yaml
# 查看zookeeper服務運行狀態
[root@k8s001 kafka]# kubectl get pod -n kafka
NAME READY STATUS RESTARTS AGE
zk-0 1/1 Running 0 7m8s
zk-1 1/1 Running 0 7m8s
zk-2 1/1 Running 0 7m8s
4.3.4 創建kafka服務
[root@k8s001 kafka]# kubectl apply -f kafka.yaml
[root@k8s001 kafka]# kubectl get pod -n kafka
NAME READY STATUS RESTARTS AGE
kafka-0 1/1 Running 0 11m
kafka-1 1/1 Running 0 11m
kafka-2 1/1 Running 0 10m
zk-0 1/1 Running 0 6m44s
zk-1 1/1 Running 0 6m44s
zk-2 1/1 Running 0 6m44s
4.3.5 測試
測試zookeeper：
kubectl exec -it zk-0 -n kafka -- zkServer.sh status
kubectl exec -it zk-0 -n kafka -- zkCli.sh create /hello world
kubectl delete -f zookeeper.yaml
kubectl apply -f zookeeper.yaml
kubectl exec -it zk-0 -n kafka -- zkCli.sh get /hello
測試kafka:
kubectl exec -it kafka-0 -n kafka -- bash
>kafka-topics.sh --create \
--topic test \
--zookeeper zk-0.zk-hs.kafka.svc.cluster.local:2181,zk-1.zk-hs.kafka.svc.cluster.local:2181,zk-2.zk-hs.kafka.svc.cluster.local:2181 \
--partitions 3 \
--replication-factor 2
kafka-topics.sh --list --zookeeper zk-0.zk-hs.kafka.svc.cluster.local:2181,zk-1.zk-hs.kafka.svc.cluster.local:2181,zk-2.zk-hs.kafka.svc.cluster.local:2181
kafka-console-consumer.sh --topic test --bootstrap-server localhost:9092
# 另起一個窗口，進入kafka-1容器
kubectl exec -it kafka-1 -n kafka -- bash
>kafka-console-producer.sh --topic test --broker-list localhost:9092
隨便輸入內容，觀察kafka-0啟動的kafka-console-consumer.sh的輸出。