Hi Zeno GH,
Thanks for reaching out to Microsoft Q&A.
I want to know is there any more efficient way to check the MD5 mismatch at memory level as the download is happening and then immediately re-try(re-download) that file which has failed the MD5 check?
To efficiently check for MD5 mismatches during a file download, you can use a streaming approach where the data is hashed as it’s being received. Libraries like hashlib in Python allow you to update the hash with chunks of data as they come in. If a mismatch is detected, you can use exception handling to trigger an immediate retry of the download. This process can be automated using a script or within a data pipeline in Azure Data Factory by incorporating custom activities or Azure Functions for the hashing and retry logic.
import hashlib
import requests
def download_file(url, expected_md5):
response = requests.get(url, stream=True)
md5_hash = hashlib.md5()
for chunk in response.iter_content(chunk_size=4096):
md5_hash.update(chunk)
if md5_hash.hexdigest() == expected_md5:
print("MD5 matched.")
# Save the file content if needed
else:
print("MD5 mismatch, retrying download...")
download_file(url, expected_md5)
# Example usage
url = 'https://example.com/file'
expected_md5 = 'expected_md5_hash_here'
download_file(url, expected_md5)
This function recursively retries the download until the MD5 matches the expected value. You can try integrating this logic into an azure Function and trigger it within adf for automated retries.
Azcopy.log option - will MD5 mismatch be logged in DOWNLOADSFAILED section with the file path? So I can fetch the file location and re-try to download that file instead of downloading the whole folder again
Yes, azcopy will log an MD5 mismatch under the DOWNLOADS FAILED section in the azcopy.log file, including the file path. This allows you to identify the specific files that failed the MD5 check so you can retry downloading just those files instead of the entire folder.
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