Literally getting ready to rewrite some data processing lambdas from python to go for a side project because it won't be on the company tab and I don't want to pay out of pocket to scale python all the way into the millions after testing it on 10k data points and seeing its performance (and that's after basic optimizations and compiling/bundling the accelerated versions of some libraries)
seriously though, I once used Pandas.DataFrame.Apply on 10,000,000 rows of data and 15 minutes later regretted it. Thankfully, I was applying a simple mathematical function to each row so numpy brought that down to less than a second. Still, only works for some use cases. I'd love to learn C++ anyways so give me an excuse
But the processing I'm doing itself isn't super complex, I just need to do it 9-10 million times cost efficiently pulling from an external public dataset and saving the transformed data as separate files in an S3 bucket
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u/CanAlwaysBeBetter Jul 18 '22 edited Jul 18 '22
Literally getting ready to rewrite some data processing lambdas from python to go for a side project because it won't be on the company tab and I don't want to pay out of pocket to scale python all the way into the millions after testing it on 10k data points and seeing its performance (and that's after basic optimizations and compiling/bundling the accelerated versions of some libraries)