Arangodb version number4/8/2023 ![]() ![]() Build high performance applications using a. ![]() For certain queries, indexes are necessary to avoid high computational complexity (here: full collection scans 2,200,000,000,000 reads in the worst case?). ArangoDB is a native multi-model database with flexible data models for documents, graphs, and key-values. The different queries completed roughly within the same time, but showed different RAM usage characteristics. The performance appears to be reasonable with ArangoDB v3.0, although it may degrade if not enough RAM is available. FOR doc IN test2ĬOLLECT myid = doc.myid WITH COUNT INTO count I double-checked the query results above and everything checked out. RETURN, otherwise there are still duplicates. 187k records have a unique id, 60k myids exist twice, and 70k three times. In addition, every record has an attribute myid. I generated 2.2 million records with 5-20 random attributes and 160 chars of gibberish per attribute. This is especially a problem with spinning disks, not so much with fast flash storage devices. Following are the results for calling the route with wrk, comparing the stable ArangoDB version (2.6.3) with the current development version (head of devel branch as of today). If you're short of memory, performance will suffer because the operating system needs to swap data between memory and mass storage. Indexes require some memory, but compared to the needed memory during query execution for grouping the records, it is negligible. It does not take that long to de-duplicate the records and write them to another collection ( less than 60 seconds), at least on my desktop machine (Windows 10, Intel 6700K 4x4.0GHz, 32GB RAM, Evo 850 SSD).Ĭertain queries require proper indexing however, or they will last forever.
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