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Noone here can tell you if any database works like this, but I am pretty sure in most cases this is quite simple: For any field or combination of fields where an index was created beforehand, this index is utilized whenever the ORDER_BY clause contains the related fields. That index could be implemented as a B-tree. For any other field (or combination of ...


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Normally it will create an index (for example a B tree) for the primary key automatically and allow the database administrator to create aditional indices for other columns, combinations of columns or expressions over column values. As you point out this trades some space (and insertion speed) for retrival speed. So to get the best performance add enough ...


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There are plenty of rules-based monitoring systems out there, nagios is very popular, for smaller projects the free version of PRTG is easier to learn.


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If you need to update the rules within a rule engine, you need to replace the code that expresses the rules. Dynamically load the rules class(es) from a jar. Have a endpoint in your app that would trigger re-reading and re-loading a new jar after you uploaded it to a server. The JVM has a built-in interpreter support for like 15 years. Pick any interpreter ...


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Ultimately, I think your question has roots in the common misuse of HTTP verbs. PUT It's common to equate a PUT to an UPDATE in an RDBMs but it's actually more like an 'UPSERT' (i.e. update or insert if not present). So as pointed out by Robert Harvey in comments on another answer, at first glance, it doesn't make sense to return a 404 not found in the ...


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I feel safe in saying that there is a large consensus amongst experts against using 404 to indicate that the object your API is looking for in its database was not found. The main issue is that you will also get 404 when your webserver or client is misconfigured, or you simply mistype the domain. The second is that you often don't want to throw an ...


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Excellent analysis. Writing an object graph is notoriously difficult because it can involve a lot of foreign key lookups and these are hard to implement without incurring a lot of waits. To make a dent in the performance, you need to widen your approach. Few ideas to consider: Blasting all the new data into a temporary table and reconcile with the main ...


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There's an app for that! https://stackoverflow.com/questions/6587007/what-is-meant-by-sparse-data-datastore-database The short version is, the cost of having a lot of null values varies by database product. Schemaless databases tend to be better at building or allowing custom indices that can speed up specific column combinations. But ACID databases have to ...


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