There are a couple ways mitigate this drawback, both of which are outside the scope of this article. One is “garbage collection”: pruning tombstones from CRDTs, which prevents you from merging states with any changes made before the tombstones were removed. Another is creating an efficient format to encode the data. You can also combine these methods. Research suggests that this can result in as little as 50% overhead compared to the “plain” data CRDTs: The Hard Parts A talk on the latest research on CRDTs, originally given at the Hydra distributed computing conference on 6 July 2020.References: https://martin.kleppmann.co... youtu.be/x7drE24geUw?t=3587 . If you’d like to skip ahead and see some of this optimization in action, check out the final part in this series: Making CRDTs 98% More Efficient Making CRDTs 98% More Efficient | jakelazaroff.com State-based CRDTs grow monotonically, but that doesn't mean they can't be efficient. We'll learn how to compress the pixel editor state by 98%. jakelazaroff.com/words/making-crdts-98-percent-more-efficient/ . ↩
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당시 서울경찰청에서 근무한 A 씨는 2023년 12월부터 2024년 3월까지 수사 대상자들에게 현금 5000만 원과 유흥대금 7000만 원 등 약 1억2000만 원의 뇌물을 수수한 혐의로 재판에 넘겨졌다. 그는 2023년 7월부터 2024년 6월까지 총 80회에 걸쳐 실제 근무하지 않은 내용을 초과근무로 제출해 근무수당 788만 원을 챙긴 혐의도 받았다.