I have a dataset with a size of about 100000. The dataset is rarely added or updated, mainly because of frequent query operations, efficient query, and regardless of memory footprint and preload time. Which solution is better to use SQL or JSON+LINQ?
which is more efficient, native SQL or packaged SQL?
frequent queries and few updates, use cache
Big Brother dei,redis memcache to learn about it.
100000 is not stressful for mysql. If you query frequently, you can consider caching. Redis is a good choice, or you can use ES, that is, elasticsearch, to store some frequently queried data. Responses of tens of millions of levels are also at the millisecond level
cache . (regardless of memory footprint, Then load it all into head )
if this requirement is put forward, considering the data size, the first consideration is memory storage.
using Mongodb can automatically cache data into memory to a certain extent.
if you pursue extreme efficiency, you can read it into memory and build your own search tree.
just do mysql casually. 10 weeks is too little and it doesn't make much difference. The sentence is reasonable when the index is built, it takes more than 0.0 seconds
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I have a dataset with a size of about 100000. The dataset is rarely added or updated, mainly because of frequent query operations, efficient query, and regardless of memory footprint and preload time. Which solution is better to use SQL or JSON+LINQ? ...
I have a dataset with a size of about 100000. The dataset is rarely added or updated, mainly because of frequent query operations, efficient query, and regardless of memory footprint and preload time. Which solution is better to use SQL or JSON+LINQ? ...