More efficient jsonencode for large data?
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So I am using matlabs jsonencode function to encode a structure array to a character array, and then write this to an output json text file. The structure array mat file equalls approximately 10GB. This takes both a long time, and alot of computer memory.
I then import the JSON text file into mongodb.
Is there a more efficient way to directly get the data into mongodb? Maybe the only option is the MatLab database toolbox...?
Thanks
Respuestas (3)
You can try following the example in this File Exchange function, which uses the MongoDB Java driver to insert a document:
The following Stackoverflow post also has some good suggestions:
With these approaches, you should be able to avoid writing text to disk, which may be more efficient. Note that this workflow has not been qualified, and it may or may not be more efficient than your current method.
Marco Rossi
el 28 de Jul. de 2021
1 voto
Is matlab development team planning to remove this limitation? I also noticed that, when the 32 bit limit is overtaken, no warnings/errors are returned.
1 comentario
Joris Brouwer
el 11 de Ag. de 2022
I second that. Running into what seems to be exponentionally / halting jsonencode performance as well. Trying the chunked solution mentioned above.
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Más información sobre JSON Format en Centro de ayuda y File Exchange.
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