- Fluid(version >= 0.5.0)
请参考Fluid安装文档完成安
$ mkdir <any-path>/dataset_scale
$ cd <any-path>/dataset_scale
创建Dataset和AlluxioRuntime资源对象
$ cat << EOF > dataset.yaml
apiVersion: data.fluid.io/v1alpha1
kind: Dataset
metadata:
name: hbase
spec:
mounts:
- mountPoint: https://mirrors.tuna.tsinghua.edu.cn/apache/hbase/stable/
name: hbase
---
apiVersion: data.fluid.io/v1alpha1
kind: AlluxioRuntime
metadata:
name: hbase
spec:
replicas: 1
tieredstore:
levels:
- mediumtype: MEM
path: /dev/shm
quota: 2Gi
high: "0.95"
low: "0.7"
EOF
在上述示例中,我们设置AlluxioRuntime.spec.replicas
为1,这意味着我们将启动一个带有一个Worker的Alluxio集群来缓存数据集中的数据。
$ kubectl create -f dataset.yaml
dataset.data.fluid.io/hbase created
alluxioruntime.data.fluid.io/hbase created
待Alluxio集群正常启动后,可以看到此时创建出来的Dataset以及AlluxioRuntime处于如下状态:
Alluxio各组件运行状态:
$ kubectl get pod
NAME READY STATUS RESTARTS AGE
hbase-master-0 2/2 Running 0 3m50s
hbase-worker-0 2/2 Running 0 3m15s
Dataset状态:
$ kubectl get dataset hbase
NAME UFS TOTAL SIZE CACHED CACHE CAPACITY CACHED PERCENTAGE PHASE AGE
hbase 544.77MiB 0.00B 2.00GiB 0.0% Bound 3m28s
AlluxioRuntime状态:
$ kubectl get alluxioruntime hbase -o wide
NAME READY MASTERS DESIRED MASTERS MASTER PHASE READY WORKERS DESIRED WORKERS WORKER PHASE READY FUSES DESIRED FUSES FUSE PHASE AGE
hbase 1 1 Ready 1 1 Ready 0 0 Ready 4m55s
Cache Runtime扩容
$ kubectl scale alluxioruntime hbase --replicas=2
alluxioruntime.data.fluid.io/hbase scaled
直接使用kubectl scale
命令即可完成Cache Runtime的扩容操作。在成功执行上述命令并等待一段时间后可以看到Dataset以及AlluxioRuntime的状态均发生了变化:
一个新的Alluxio Worker以及对应的Alluxio Fuse组件成功启动:
$ kubectl get pod
NAME READY STATUS RESTARTS AGE
hbase-master-0 2/2 Running 0 13m
hbase-worker-1 2/2 Running 0 6m49s
hbase-worker-0 2/2 Running 0 13m
Dataset中的Cache Capacity
从原来的2.00GiB
变为4.00GiB
,表明该Dataset的可用缓存容量增加:
$ kubectl get dataset hbase
NAME UFS TOTAL SIZE CACHED CACHE CAPACITY CACHED PERCENTAGE PHASE AGE
hbase 544.77MiB 0.00B 4.00GiB 0.0% Bound 15m
AlluxioRuntime中的Ready Workers
以及Ready Fuses
属性均变为2:
$ kubectl get alluxioruntime hbase -o wide
NAME READY MASTERS DESIRED MASTERS MASTER PHASE READY WORKERS DESIRED WORKERS WORKER PHASE READY FUSES DESIRED FUSES FUSE PHASE AGE
hbase 1 1 Ready 2 2 Ready 0 0 Ready 17m
查看AlluxioRuntime的具体描述信息可以了解最新的扩缩容信息:
$ kubectl describe alluxioruntime hbase
...
Conditions:
...
Last Probe Time: 2021-04-23T07:54:03Z
Last Transition Time: 2021-04-23T07:54:03Z
Message: The workers are scale out.
Reason: Workers scaled out
Status: True
Type: WorkersScaledOut
...
Events:
Type Reason Age From Message
---- ------ ---- ---- -------
Normal Succeed 2m2s AlluxioRuntime Runtime scaled out. current replicas: 2, desired replicas: 2.
Cache Runtime缩容
与扩容类似,缩容时同样可以使用kubectl scale
对Cache Runtime的Worker数量进行调整:
$ kubectl scale alluxioruntime hbase --replicas=1
alluxioruntime.data.fluid.io/hbase scaled
成功执行上述命令后,如果目前环境中没有应用正在尝试访问该数据集,那么就会触发Runtime的缩容。
超出指定replicas
数量的Runtime Worker将会被停止:
NAME READY STATUS RESTARTS AGE
hbase-master-0 2/2 Running 0 22m
hbase-worker-1 2/2 Terminating 0 17m32s
hbase-worker-0 2/2 Running 0 21m
Dataset的缓存容量(Cache Capacity
)恢复到2.00GiB
:
$ kubectl get dataset hbase
NAME UFS TOTAL SIZE CACHED CACHE CAPACITY CACHED PERCENTAGE PHASE AGE
hbase 544.77MiB 0.00B 2.00GiB 0.0% Bound 30m
注意:在目前版本的Fluid中,缩容时Dataset中
Cache Capacity
属性字段的变化存在几分钟的延迟,因此您可能无法迅速观察到这一属性的变化
AlluxioRuntime中的Ready Workers
以及Ready Fuses
字段同样变为1
:
$ kubectl get alluxioruntime hbase -o wide
NAME READY MASTERS DESIRED MASTERS MASTER PHASE READY WORKERS DESIRED WORKERS WORKER PHASE READY FUSES DESIRED FUSES FUSE PHASE AGE
hbase 1 1 Ready 1 1 Ready 0 0 Ready 30m
查看AlluxioRuntime的具体描述信息可以了解最新的扩缩容信息:
$ kubectl describe alluxioruntime hbase
...
Conditions:
...
Last Probe Time: 2021-04-23T08:00:55Z
Last Transition Time: 2021-04-23T08:00:55Z
Message: The workers scaled in.
Reason: Workers scaled in
Status: True
Type: WorkersScaledIn
...
Events:
Type Reason Age From Message
---- ------ ---- ---- -------
Normal Succeed 6m56s AlluxioRuntime Alluxio runtime scaled out. current replicas: 2, desired replicas: 2.
Normal Succeed 4s AlluxioRuntime Alluxio runtime scaled in. current replicas: 1, desired replicas: 1.
Fluid提供的这种扩缩容能力能够帮助用户或是集群管理员适时地调整数据集缓存所占用的集群资源,减少某个不频繁使用的数据集的缓存容量(缩容),或者按需增加某数据集的缓存容量(扩容),以实现更加精细的资源分配,提高资源利用率。
$ kubectl delete -f dataset.yaml