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Storage-Memory-Usage-Benchmark.md 100644

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<br>Two elements of etcd storage consume physical memory. The etcd course of allocates an in-memory index to hurry key lookup. The process’s web page cache, managed by the operating system, shops recently-accessed data from disk for quick re-use. The [in-memory](https://openclipart.org/search/?query=in-memory) index holds all of the keys in a B-tree data structure, together with pointers to the on-disk knowledge (the values). Every key within the B-tree may include a number of pointers, pointing to completely different variations of its values. 1 is the key metadata overhead and c2 is the model metadata overhead. The graph shows the detailed structure of the in-memory index B-tree. Web page cache memory is managed by the operating system and is not covered intimately in this doc. In this test, we solely benchmark the memory usage of the in-memory index. The aim is to seek out c1 and c2 mentioned above and to understand the arduous limit of memory consumption of the storage.<br>
<br>We calculate the memory usage consumption via the Go runtime.ReadMemStats. We calculate the total allocated bytes distinction before creating the index and after creating the index. It can't completely mirror the memory usage of the in-memory index itself but can present the tough consumption sample. 30bytes. We solely want two units of information to calculate c1 and c2, since they are the only unknown variable in the system. 30bytes are the average value of the four sets of c1 and c2 we calculated. The key metadata overhead remains to be comparatively nontrivial (50%) for small key-worth pairs. Nonetheless, that is a major improvement over the old store, which had no less than 1000% overhead. The overall [Memory Wave](http://medik.co.kr/bbs/board.php?bo_table=free&wr_id=1623075) usage captures how much RSS etcd consumes with the storage. The worth dimension should have very little influence on the overall memory usage of etcd, since we keep values on disk and only retain hot values in memory, managed by the OS web page cache. Based mostly on the end result, we all know the worth dimension does not significantly impact the memory consumption. There is some minor enhance on account of more information held in the OS page cache. Was this page helpful? Glad to listen to it! Please tell us how we can improve. Sorry to hear that. Please tell us how we can improve.<br>[tilro.mn](http://tilro.mn/dihnolu)
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