Diffing Two Documents in AQL: ArangoDB Data Comparison

2 Comments

1. CoDEmanX on May 26, 2015 at 6:21 pm

   I wonder if a custom AQL function written in JS for document diffing would be slower than your pure AQL query… BTW: there’s a json-patch format https://tools.ietf.org/html/rfc6902 and a diff format used here: https://github.com/benjamine/jsondiffpatch

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   • jsteemann on May 26, 2015 at 6:59 pm

     I was aware of JSON-patch, but I wasn’t sure what the intention of the to-be-generated diffs was. For simply detecting whether or not two documents differ and to what extent, a simple solution as demonstrated may already be sufficient. If the goal however is to create patches that can be sent somewhere via HTTP PATCH, JSON-patch will be the natural choice.
     I wasn’t aware of jsondiffpatch yet, and after looking into it, I still prefer JSON-patch.

     But which way to go really depends on what is to be achieved with the generated diffs.

     Performance-wise a custom AQL function may be faster if the documents
     are small. For example, the following custom function was about twice as
     fast as the AQL-only solution for the two example documents I used in the post:

     require(“org/arangodb/aql/functions”).register(“my::diff”, function (doc1, doc2) {
     var result = {
     missing: { },
     changed: { },
     added: { }
     };
     Object.keys(doc1).forEach(function(key) {
     if (! doc2.hasOwnProperty(key)) {
     result.missing[key] = doc1[key];
     }
     else if (JSON.stringify(doc1[key]) !== JSON.stringify(doc2[key])) {
     result.changed[key] = { old: doc1[key], ‘new’: doc2[key] };
     }
     });
     Object.keys(doc2).forEach(function(key) {
     if (! doc1.hasOwnProperty(key)) {
     result.added[key] = doc2[key];
     }
     });
     return result;
     };

     The JavaScript solution can save one iteration over all attributes because it can use if/then/else, which AQL does not provide.
     It may look different for other types of documents (especially bigger ones) and if new types of AQL optimizations are added.

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