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Re:Packet Capturing MySQL with Rust on Friday June 03, 2016 @07:23PM (#11833961)
Thank you for the suggestion. Spyglass went from concept to a working product which met the project goals, in a little over 5 weeks.

And, you're correct it won't save you from all programming errors. It does, however, make it far more difficult to accidentally encounter whole classes of them which constitute, on average, quite a high percentage of debug time in other systems languages.

Re:Packet Capturing MySQL with Rust on Friday June 03, 2016 @07:19PM (#11833941)
I have no doubt that there are some cases which won't match. This particular utility does not need to be 100% on for every possible corner case, to produce the desired result. That said, all improvements, whether pull request or posted suggestions, are much appreciated.

My comments regarding the regex was the very high number of cases that are correctly handled, with such a small amount of code.

Thank you for your comments. I appreciate it.

Re:Packet Capturing MySQL with Rust on Friday June 03, 2016 @07:16PM (#11833921)
Both good suggestions for improvement, Andrew. I saw the performance notes, and admit I was a little torn. Quite simply, the regex! macro was interesting for the reason stated, and I left it in there for the purpose of showcasing something (a little bit) unique in Rust.

Regarding the asterisk for versioning in Cargo.toml, I also agree. When quickly putting things together, I usually start with it just to see if the default version pulled works. The great utility of Cargo.lock, effectively storing the working versions of all the crates, allows scraping the versions out of there at any time, and putting them into the .toml.

I hope you noticed the extensive links in the post, as one of the goals was to bring more people into the Rust ecosystem. The Spyglass utility does work quite well. None of us claimed it has reached a state of absolute perfection, so your comments are appreciated (and pull requests will be as well)!

Thank you.

Re:Apache Spark: RDD, DataFrame or Dataset? on Tuesday January 26, 2016 @01:24PM (#10974925)
Great summary to provide to those new to Spark.

I'm looking forward to your future blog posts on the DataSet API.