[英]how to invoke the same cloud run from a cloud run to run requests parallely?
I am running an ETL process using cloud run.我正在使用云运行运行 ETL 流程。
I have 2000 files.我有2000个文件。 Only 1200 files are getting preprocessed and loaded in BIG Query.
只有 1200 个文件在 BIG Query 中得到预处理和加载。 Because the cloud run is getting timed out.
因为云运行正在超时。 So, I thought of dividing the load.
所以,我想到了分配负载。
I am dividing 2000 files into set of 4 as 500 each and authenticating and using requests.post to call the same cloud run.我将 2000 个文件分成 4 个,每个 500 个,并验证和使用 requests.post 来调用相同的云运行。 However it executes one set after another with the same instance of cloud run.
但是,它使用相同的云运行实例依次执行一组。 And it again times out
它再次超时
How can I make it run parallely?我怎样才能让它并行运行?
As of now, max instances: 20. Concurrency: 1, CPU:2, Memory: 8GB.截至目前,最大实例数:20。并发数:1,CPU:2,Memory:8GB。
Well, I have worked on something like this.好吧,我做过这样的事情。 I am not sure if it'd help you since you haven't shared a single block of code.
我不确定它是否对您有帮助,因为您没有共享一个代码块。 Here's a sample code of 2k JSON files I'd download.
这是我要下载的 2k JSON 文件的示例代码。
You have 2000 files and 1200 of this is getting processed/loaded in GBQ before the cloud run timing out.您有 2000 个文件,其中 1200 个在云运行超时之前在 GBQ 中得到处理/加载。 What you can do is:
你可以做的是:
total_files = len(file_list)//1000 #let file list be 2000, total files will be 2.
#divide the files into sets of 1000 and loop over them one by one
for file_set in range(1,(total_files+1)):
auth_and_trigger(file_list[(file_set-1)*1000:(file_set*1000)])
#for files left after 1000*i , we finally trigger it.
auth_and_trigger(file_list[(total_files)*1000:len(file_list)])
Now this is how you can call the cloud run with auth and trigger function for every 1000 files.现在,您可以使用 auth 调用云运行并为每 1000 个文件触发 function。
def auth_and_trigger(self, rest_of_files):
#your cloud run url
receiving_service_url = 'https://cloudrun-url-uc.a.run.app/download'
# Set up metadata server request
# See https://cloud.google.com/compute/docs/instances/verifying-instance-identity#request_signature
metadata_server_token_url = 'http://metadata/computeMetadata/v1/instance/service-accounts/default/identity?audience='
token_request_url = metadata_server_token_url + receiving_service_url
token_request_headers = {'Metadata-Flavor': 'Google'}
# Fetch the token
token_response = requests.get(token_request_url, headers=token_request_headers)
jwt = token_response.content.decode("utf-8")
# Provide the token in the request to the receiving service
receiving_service_headers = {'Authorization': f'bearer {jwt}'}
try:
threading.Thread(target=self.trigger_ingest,
args=(receiving_service_url,
{"files": rest_of_files},
receiving_service_headers
)).start()
except Exception as error:
logging.error(error)
Each thread will call a function trigger_ingest that will call the cloud run.每个线程都会调用一个 function trigger_ingest 来调用云运行。 The code for it is below:
它的代码如下:
def trigger_ingest(url, json, headers=""):
service_response = requests.post(url=url,
json=json,
headers=headers
)
logging.info(service_response.content)
Now since you want a parallel execution, make sure no code gets repeated in the thread as you have it in the trigger for the cloud run.现在,由于您想要并行执行,因此请确保线程中没有代码重复,因为您在云运行的触发器中拥有它。
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