Storage Memory Usage Benchmark
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Two parts of etcd storage devour physical memory. The etcd process allocates an in-memory index to speed 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 index holds all the keys in a B-tree data construction, together with pointers to the on-disk knowledge (the values). Each key in the B-tree could include a number of pointers, pointing to totally different versions 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 isn't lined intimately in this doc. In this check, we solely benchmark the memory usage of the in-memory index. The objective is to search out c1 and c2 mentioned above and to know the hard restrict of memory consumption of the storage.
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We calculate the memory usage consumption through the Go runtime.ReadMemStats. We calculate the whole allocated bytes difference earlier than creating the index and after creating the index. It can't perfectly reflect the Memory Wave Workshop utilization of the in-memory index itself but can show the rough consumption sample. 30bytes. We only want two units of data to calculate c1 and c2, since they are the one unknown variable in the system. 30bytes are the common value of the four units of c1 and Memory Wave c2 we calculated. The important thing metadata overhead remains to be comparatively nontrivial (50%) for small key-value pairs. However, this is a big improvement over the previous store, which had no less than 1000% overhead. The overall memory usage captures how much RSS etcd consumes with the storage. The value dimension should have very little influence on the overall memory usage of etcd, Memory Wave since we keep values on disk and only retain hot values in memory, managed by the OS web page cache. Based on the result, we know the value dimension does not considerably affect the memory consumption. There is a few minor improve on account of extra information held in the OS web page cache. Was this web page useful? Glad to hear it! Please tell us how we are able to enhance. Sorry to listen to that. Please tell us how we will improve.


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