I have a big gremlin query that is basically to filter results, is made of many has() and where() steps that can be written in any order and gives the same result, some of them are expensive and some of them are cheaper.
If i call the cheaper steps first I guess the expensive ones are going to be executed with less iterations because many vertices were filtered, this is true when coding in any language but in a database implementation I don't know if the Gremlin steps are executed in the order that are written.
I know this kind of things usually depends on the Gremlin database implementation but maybe you can give me some kind of general answer. Also I've tried to make some benchmarks but to build good ones in my specific case is too time consuming, so maybe you can help me with your knowledge of how databases are implemented internally.
As you mention, it really does depend on the query engine and the way optimized query plans are developed. Some engines will try to reorder parts of queries based on the estimated cardinality of elements being tested. Amazon Neptune works that way for example. In general it is best to filter out as much as possible as soon as possible. So in a social network you would not want to start with something like g.V().hasLabel(‘person’) unless you are confident the query engine is able to reorder such queries.