I am having an issue with aggregation framework in one particular aspect - its not handling _missing values and _other values as they were handled in facets (_other was not handled even in any stats facets just in terms) traditional OLAP would slice/roll-up the same data set by various dimensions so roll up counts/totals would come out the same even if we are grouping on a field which may be null for some records
With aggregation framework there is no way to do it except for an exceedingly convoluted use of "missing" aggregation (just try to have missing values aggregated as part of the overall bucket-set when doing multi-level aggregation) you can find lot more details, example and my proposal here https://github.com/elasticsearch/elasticsearch/issues/5324 Unfortunately it did not get any reply from the development team so I can only assume they are not convinced or did not read it (would be nice if they at least said so may be they missed it all together) I do not want to replace null values with some fake values representing null and have it bleed all over the applications consuming JSON data from elastic. So if Elastic is not going to handle missing, what are my options (apart from the option described in my proposal on github)? Could I use "null_value" in my index mapping for nullable fields? Will they be used for aggregation rather than _source. Even if they are will it work when null value is one of objects and I am aggregating on that object properties? (i.e. case type is {caseNumber:123, caseType:{id:10, name:'Civil'}} and I am aggregating on caseType.id and caseType could be null) -- You received this message because you are subscribed to the Google Groups "elasticsearch" group. To unsubscribe from this group and stop receiving emails from it, send an email to [email protected]. To view this discussion on the web visit https://groups.google.com/d/msgid/elasticsearch/6ad26233-59f4-4464-a380-2832685e528b%40googlegroups.com. For more options, visit https://groups.google.com/d/optout.
