Reading large CSV files

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Sanchit Sharma
Sanchit Sharma 2022-4-2
回答： Esha Chakraborty 2022-4-5
Hello,
I have a 28GB Large .csv file that I am trying to read. I have tried readmatrix() and readtable(). Both functions are giving me below error:
Caught "std::exception" Exception message is:
Failed to convert character code.
Could you please provide me a solution.
Thanks
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Sanchit Sharma
Sanchit Sharma 2022-4-2
编辑：Sanchit Sharma 2022-4-2
yes i have 512GB ram
per isakson
per isakson 2022-4-2
编辑：per isakson 2022-4-2
Propably, your file contains some strange characters, e.g. to indicate missing data. The error message indicates that. One way to spot the position in the file that causes the error is
textscan( __________ , 'ReturnOnError',false )
It produces a better error message.

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Esha Chakraborty
Esha Chakraborty 2022-4-5
Hi Sanchit,
I understand that you are receiving the message - 'Failed to convert character code' when you are attempting to read large CSV files. Possible reason can be that the read buffer is too large and too much data is being read at once. It is suggested to reduce the amount of data being loaded and see if the situation still exists.
Here are a few ways to import large CSV array:
  1. You can try to split the file into smaller sections using any reliable third-party file splitting software, before importing to MATLAB.
  2. You can explore if the Datastore feature suits your use case. A Datastore is an object for reading a single file or a collection of files or data. The Datastore acts as a repository for data that has the same structure and formatting. You can refer to the following documentation page for more details on Datastore here.
  3. You can also explore if MapReduce is an option in your use case. MapReduce is a programming technique for analyzing data sets that do not fit in memory. You can refer to the following documentation page for more details on Mapreduce here.

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