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Error when loading large file to local server #7

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michael-sky opened this issue Sep 5, 2019 · 16 comments
Open

Error when loading large file to local server #7

michael-sky opened this issue Sep 5, 2019 · 16 comments

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@michael-sky
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File size is 72MB and I get the following error in the java console. However, the loading is still "running".

"Failed to load resource: net::ERR_CONTENT_LENGTH_MISMATCH"

@dsaffo
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dsaffo commented Sep 5, 2019

Can you provide the line number and file the error is from.

@michael-sky
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As I recall, it said parse:1

@dsaffo
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dsaffo commented Sep 5, 2019

So it's coming from the backend and likely means Pyulog is failing to read the file somehow. I'm not sure I can debug this one without the log file. Could you share it?

@michael-sky
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Unfortunately I cannot share the particular log file. However, I might be able to find another one and test with that as well. I will also look into the parsing with python.

@dsaffo
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dsaffo commented Sep 5, 2019

I understand that no worries, if you can run the ulog2csv command it is most likely a network issue and not a issue with the log.

@michael-sky
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It is definitely not an issue with the log. It doesn’t fail every time. If I try multiple times, it will succeed at some point.

@dsaffo
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dsaffo commented Sep 5, 2019

I see, definitely a network issue then, I am working on a javascript parser which would solve these issue but if it seems like it will take a lot of time I will invest more time into better netcode.

@michael-sky
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The log is fine, if I try multiple times with the same log, eventually it will succeeed.

@dsaffo
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dsaffo commented Sep 5, 2019

With the larger logs i have noticed it can sometimes fail to send all the data to the python sever correctly. With a JavaScript parser that step is not necessary any more and there shouldn't be network failures since everything would happen on the client side.

@dsaffo
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dsaffo commented Sep 5, 2019

In the mean time, I could setup datacomets to accept pre-processed logs. This way for very large logs you can parse them separately with a quick python command and then load the log into data comets. This would also be faster for very large logs since you dont have to deal with the network. Less convenient but a stop gap for now, what do you think?

@michael-sky
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Sounds great. Please let me know if I can be of any assistance.

@michael-sky
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@dsaffo I missed the comment about preprocessed logs. How would I preprocess the logs then? It doesn't seem to be the "parsing" that fails, but the uploading. Which would still have to take place as the server is plotting?

Please correct me if I am wrong.

@michael-sky
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Keep in mind, that when I say "local server", it is a server I started using your suggestion with gunicorn.

@dsaffo
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dsaffo commented Sep 6, 2019 via email

@dsaffo
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dsaffo commented Sep 6, 2019

Actually after doing so more research I think I will try to implement this plugin instead https://github.com/blueimp/jQuery-File-Upload/blob/master/README.md#features. It features file chunking and progress bars so might get 2 for 1 solution here.

@michael-sky
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@dsaffo That would definitely be the preferred solution.

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