How to implement properly multiple inequality filters on Google App Engine Datastore? -

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according app engine restriction on inequality filters, there suggestions implement advanced searches (filtering results limiting ranges on many properties) filtering properties manually in ram:

how run 2 inequality filters on queries in app engine

so, feasible amount of sorting , filtering in ram large datasets? there java sample code demonstrates proper implementation? idea stick traditional rdbms in order avoid drawback?

as andrei has mentioned, there isn't general solution problem of needing multiple inequality filter conditions. depends on data, queries , application requirements.

here possible solutions use:

perform filtering in application. if have 2 inequality conditions, , b, , know majority (e.g. > 80%) of entities meet condition meet condition b, query without condition b against datastore, , filter returned results in application code. lets continue use datastore, , efficiency hit shouldn't bad, since know > 80% match.

however, extending solution more inequalities, or cases overlap between condition , condition b not great, result in inefficient data retrieval.

secondary search index. it's possible if have complicated filtering / sorting logic, have more akin search problem, google app engine search might more suitable. search allows run flexible queries on documents in search index, including multiple inequality queries.

i point out search offers eventual consistency, , indexes limited 10gb (but can extended 200gb on request).


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