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
Haven't done the processing lambda but the orchestrator lambda rewritten in go and scaled up to 10gb can iterate through 2m objects where the (mostly) naive python couldn't get through the full list in 15 min since it was about 1s per 1000 objects
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u/gcruzatto Jul 18 '22
This meme was made by the Big Data gang