I have a smart contract which contains some article data stored inside a struct, which is mapped with an id which uniquely identifies it with a mapping, like this:

struct Foo {
    string a;
    string b;

mapping (uint64 => Foo) public articles;

(Obviously the above code is simplied, but the structure is the same, although the real struct has 7 variables instead of 2).

Now I have to be able to search using any of the 7 attributes. The blockchain is going to be private, so gas usage is not a concern.

My first solution was to add a search method to the smart contract and, within it, traverse the entire mapping and check which items satisfy the condition. Obviously this is O(n) and it was taking around 8 seconds for 2000 elements, which although isn't bad, I hope for a better solution.

Then I thought about having 7 more mappings which would act as search indexes, mapping each attribute value to the index of the article that satisfies it, such as:

mapping (string => uint64) public searchIndex;

(Note that right now it isn't required to check substrings, only equality)

And finally, I was thinking about if it would be good to do keep these indexes on Elastic Search rather than on the blockchain itself, although I would prefer a pure blockchain-based solution if possible.

So, what of these options (of any other better you know) do you think is more adequate?

Thank you.


It is clear you can't directly get the object you want without knowing it's key. The idea of the 7 mappings is actually the most obvious and the least complicated one and it works in most cases not only yours.

The most useful idea I can come up with is that you look for patterns in your struct attributes, patterns that help you organize a search schema in case you have 10 or 20 thousand elements. e.g. ; if string a values are linked to a known timeline like a == "X12" for today and the next day another entry would havea == "X13". So when you want to search for structs with a == X32 you will have better understanding of where could that struct be and what are the search index limits.

Thus making searching in 20 thousand elements a search in only 2 thousand.

hope it was clear.

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