我想根据存储类获取存储桶的大小。我已在存储桶中添加了规则,以根据文件的使用期限更改文件的存储类。 我使用了以下命令
gsutil du -sh gs://[bucket-name]
To get Meta-data :
gsutil ls -L gs://[bucket-name]
To set ACL to bucket
gsutil lifecycle set life-cycle.json gs://[bucket-name]
请对此提供任何帮助以解决我的问题
答案 0 :(得分:2)
编辑:
我已经在Public Issue Tracker上为此提交了功能请求。同时,可以使用下面的代码。
我相信没有gsutil
命令可以按存储类别显示GCS存储桶的总大小。
但是,我使用Cloud Storage Client Libraries for Python,编写了一个脚本,该脚本可以满足您的要求:
from google.cloud import storage
import math
### SET THESE VARIABLES ###
PROJECT_ID = ""
CLOUD_STORAGE_BUCKET = ""
###########################
def _get_storage_client():
return storage.Client(
project=PROJECT_ID)
def convert_size(size_bytes):
if size_bytes == 0:
return "0 B"
size_name = ("B", "KB", "MB", "GB", "TB", "PB", "EB", "ZB", "YB")
i = int(math.floor(math.log(size_bytes, 1024)))
p = math.pow(1024, i)
s = round(size_bytes / p, 2)
return "%s %s" % (s, size_name[i])
def size_by_class():
client = _get_storage_client()
bucket = client.bucket(CLOUD_STORAGE_BUCKET)
blobs = bucket.list_blobs()
size_multi_regional = size_regional = size_nearline = size_coldline = 0
for blob in blobs:
if blob.storage_class == "MULTI_REGIONAL":
size_multi_regional = size_multi_regional + blob.size
if blob.storage_class == "REGIONAL":
size_regional = size_regional + blob.size
if blob.storage_class == "NEARLINE":
size_nearline = size_nearline + blob.size
if blob.storage_class == "COLDLINE":
size_coldline = size_coldline + blob.size
print("MULTI_REGIONAL: "+str(convert_size(size_multi_regional))+"\n"+
"REGIONAL: "+str(convert_size(size_regional)+"\n"+
"NEARLINE: "+str(convert_size(size_nearline))+"\n"+
"COLDLINE: "+str(convert_size(size_coldline))
))
if __name__ == '__main__':
size_by_class()
要从Google Cloud Shell运行此程序,请确保以前安装了Client Library for Python并带有:
pip install --upgrade google-cloud-storage
并且为了向应用程序代码提供身份验证凭据,您必须将环境变量GOOGLE_APPLICATION_CREDENTIALS
指向包含service account密钥的JSON文件的位置:
export `GOOGLE_APPLICATION_CREDENTIALS`="/home/user/Downloads/[FILE_NAME].json"
在运行脚本之前,将PROJECT_ID
设置为项目的ID,并将CLOUD_STORAGE_BUCKET
设置为GCS Bucket的名称。
使用python main.py
运行脚本。输出应类似于:
MULTI_REGIONAL: 1.0 GB
REGIONAL: 300 MB
NEARLINE: 200 MB
COLDLINE: 10 MB