Too many fields in an index

[Jurrien]

We have an index with the following structure (see below)

So basically, we have our index business_objects with a link and no. We add objects to this index (doc_type1, doc_type2, ....). These objects are linked via no 5793328-03-01 for example.

The problem is that we have many doc_types (doc_type1, doc_type2, …., doc_type100).

Each doc_type has some common fields like date, id, mime_type but there are also some doc_type specific fields like business_number,…
So at the moment this increases the fields in the index if we add a new doc_type eg doc_type101.
We are well over 1000 fields now.

How could we redesign this index so we stay below the recommended 1000 fields?

We were thinking of only having one doc_type and rely on the doc_type.type to determine the type of the doc_type.
This 'generic' doc_type would contain the sum of all fields in (doc_type1, doc_type2, …., doc_type100).
The problem is that we cannot use source filtering and security filtering like this anymore if we do that:

"except": [
"link.doc_type_1.*”,  

Are there any other solutions for this type of index design?

"_index" : "business_objects",
        "_type" : "_doc",
        "_id" : "8579338-3",
        "_score" : 1.0,
        "_source" : {
          "business_object_no" : "8579338-3",
          "company" : {
            "id" : "148",
            "call_sign" : “NAME”
          },
          "link" : [
            {
              "no" : "5793328-03-01",
              "doc_type_1" : [
                {
                  "date" : "20220301000000",
                  "filename" : "test1.pdf",
                  "official_number" : "2022000000013",
                  "mime_type" : "application/pdf",
                  "id" : "5009467F-0000-C91C-B281-BBBBZA",
                  "type" : "doc_type_1",
                  "business_number" : "22000766"
                }
              ],
              "doc_type_2" : [
                {
                  "date" : "20220301000000",
                  "filename" : "test2.pdf",
                  "official_number" : "RE02022000000013",
                  "mime_type" : "text/xml",
                  "id" : "800D467F-0000-C314-88D3-AAAAZE",
                  "type" : "doc_type_2"
                }
              ]
        }
}