h = my_hash(value1, value2, value3)
select ... from Table T where T.hash = h and T.attr1 = value1 and T.attr2 = value2 and T.attr3 = value3

class BitmapCube : ICube {..... classic bitmap cube bla-bla-bla..... }

class AdvancedBloomCube : ICube {

   // Probabilistic data structure. 
   BloomFilter bloom;
   // Table contains false-positive values that should be avoided during check callback
   HashTable exceptions;
   
   public AdvancedBloomCube(double bloomFalsePositiveProbability) {
      .....

   }

   bool check(String jsonTuple) {
       if (bloom.contains(jsonTuple) and not (exceptionList.contains(jsonTuple))) return true;
       else return false;
   }
  
   // Initialize. Works a lot of time :). But needed :)
   void bulkLoadFromBitmapCube(ICube bitmapCube) {

       forAll(String json : bitmapCube.getIterator()) bloom.set(json);

       // Route over all combinations of original cube. Looks like for(...) for (...) for (...) {...}
       forAll(String json : bitmapCube.getDimensionsPermutations()) {
            if (bloom.contains(json) and not(bitmapCube.contains(json)) exceptions.add(json,true);
       }
   }

621883*16818*77*116*68*11 = 69 876 854 232 861 984 bit ~7 944 Tb

Id|OrderId|ProductId|UnitPrice|Quantity|Discount
10248/11|10248|11|14|12|0.0
10248/42|10248|42|9.8|10|0.0
10248/72|10248|72|34.8|5|0.0
10249/14|10249|14|18.6|9|0.0
10249/51|10249|51|42.4|40|0.0
10250/41|10250|41|7.7|10|0.0
10250/51|10250|51|42.4|35|0.15
10250/65|10250|65|16.8|15|0.15
10251/22|10251|22|16.8|6|0.05
10251/57|10251|57|15.6|15|0.05
10251/65|10251|65|16.8|20|0.0
10252/20|10252|20|64.8|40|0.05
10252/33|10252|33|2|25|0.05
10252/60|10252|60|27.2|40|0.0
10253/31|10253|31|10|20|0.0
10253/39|10253|39|14.4|42|0.0
10253/49|10253|49|16|40|0.0

bool check(String jsonTuple) 

Id|OrderId|ProductId|UnitPrice|Quantity|Discount
10248/11|10248|11|14|12|0.0

jsonTuple=" { Id : 10248/11 , OrderId : 10248,  ProductId : 11, UnitPrice : 14, Quantity : 12, Discount : 0.0 } "