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之前在 PR444 中的算法原理为,找出当前app中partition流量的最小值为 qps_min,此时partition热点数值为 当前partition_qps/max(1,qps_min) 实验结果如图所示: 可见在开头和结尾时,有两个异常的凸起。 造成凸起的原因是:当读写刚刚进行时,某个partition没有流量,导致该app中 qps_min直接取到1,而分子是正常的流量,所以导致整体数值偏大。而当各个partition都有正常的流量后,分母qps_min变大,虽然分子中热点paritition的数值也相应较大,但是算下来热点数值并不如初期异常的大,所以会出现开始和结束时的异常凸起。 为了避免这种情况的产生,我调研了新的算法:三倍标准差 算法流程如下:
qps_min
当前partition_qps/max(1,qps_min)
The text was updated successfully, but these errors were encountered:
之前在 PR444 中的算法原理为
github的地址可以自动转换为超链接,像下面这样: #444
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fix: fix memory leak in asio_udp_provider (#477)
965f32a
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之前在 PR444 中的算法原理为,找出当前app中partition流量的最小值为
qps_min
,此时partition热点数值为当前partition_qps/max(1,qps_min)
实验结果如图所示:
可见在开头和结尾时,有两个异常的凸起。
造成凸起的原因是:当读写刚刚进行时,某个partition没有流量,导致该app中
qps_min
直接取到1,而分子是正常的流量,所以导致整体数值偏大。而当各个partition都有正常的流量后,分母qps_min
变大,虽然分子中热点paritition的数值也相应较大,但是算下来热点数值并不如初期异常的大,所以会出现开始和结束时的异常凸起。为了避免这种情况的产生,我调研了新的算法:三倍标准差
算法流程如下:
The text was updated successfully, but these errors were encountered: