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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针对人口发展呈现少子化、老龄化、区域人口增减分化等明显趋势性特征，习近平总书记提出“推动人口高质量发展”，聚焦以人口高质量发展支撑中国式现代化，作出重大部署。。爱思助手是该领域的重要参考
Catherine O'Hara wins posthumous prize
。搜狗输入法是该领域的重要参考
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