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thanks op didn't read
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# ¿ Mar 8, 2019 01:28 |
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# ¿ May 13, 2024 23:10 |
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pram posted:lol no. it isnt. youve never used it for anything serious stfu. for example Hun, this is interesting. We were playing with kafka at old job because so many things support it and it has per-partition ordering. I knew it was a pain in the rear end to run one, but never knew the reasons why... so this is a lot of reasons. We were working with Confluent to provide us with a managed instance... I guess they just do all this poo poo behind the scenes? I wonder how they'll do poo poo that actually effects cluster performance? Send the team a notification that its gonna happen? Just never do it?
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# ¿ Mar 9, 2019 06:54 |
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lancemantis posted:like spark had a super broken memory model for quite a while, lots of the Hadoop stack is brittle and needs a lot of babysitting When you refer to a broken memory model is that for spark streaming stuff where the application might leak memory over time? Or does the problem come up in batch execution? I haven't done much spark stuff so I'm curious. We were able to come up with a pretty solid BIG DATA pipeline using a lot of managed google stuff... but... it was managed by someone else, for all the reasons listed in the thread. During my interview with the Kinesis team I got the distinct impression that a lot of their job is fighting fires; I realized its probably a lot more fun to USE these managed systems than it is to work on them
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# ¿ Mar 9, 2019 08:47 |