Record Field Presence Matrix
Build a record/field own-presence matrix; an explicit null member counts as present.
Description
Build a record/field own-presence matrix; an explicit null member counts as present.
A presence matrix shows which requested fields exist in each record. It is useful when auditing sparse imports without conflating empty values with missing columns.
When to use this tool
Build a record/field own-presence matrix; an explicit null member counts as present.
- Prepare the supplied recordsJson, fields fields for this operation.
- Compare the complete example with the representation used by your own input before carrying the result into another step.
How to use the tool and how it works
- Enter recordsJson, fields. Use the exact text syntax, units and index conventions explained below.
- Run the tool. If input validation fails, correct the supplied fields before interpreting any result.
- Read result.presence. Interpret false, null and empty lists using the distinctions below; they can be valid outputs.
Require a nonempty distinct field list, then produce one boolean row per record and one column per requested field using own-property checks.1
| Input field | Meaning and representation | Accepted input |
|---|---|---|
| recordsJson | JSON text, entered as one text field. The decoded structure is illustrated below; it is not a separate file. | Text |
| fields | fields. | At most 128 strings, each at most 128 UTF-16 code units |
For the JSON text fields, the following decoded structures show the example records before they are serialized into input strings. Keep field names, list nesting and value types as shown.
[
{
"field": "recordsJson",
"decoded": [
{
"a": null
},
{}
]
}
]| Output field | Interpretation |
|---|---|
| result | Object containing the named outputs below. |
| result.presence | The presence list in the ordering and representation described above. |
{
"input": {
"recordsJson": "[{\"a\":null},{}]",
"fields": [
"a",
"b"
]
},
"output": {
"result": {
"presence": [
[
true,
false
],
[
false,
false
]
]
}
}
}Limitations and assumptions
- Null, false, zero and empty text all count as present. The matrix does not validate value types or traverse dot-separated nested paths.
- Decoded JSON is bounded to 20,000 nodes and 32 nesting levels; record arrays have at most 128 records. Parsed number values use JavaScript floating point rather than arbitrary-precision decimal arithmetic.
- Every declared top-level field is required and unexpected fields are rejected. Numeric inputs must be finite; ordinary text fields are bounded to 8,192 UTF-16 code units, with tighter operation-specific limits where stated.
- Ordinary string lists have at most 128 entries of at most 128 code units each; numeric lists and matrices have separate bounded size checks. Nonfinite results and excessively large serialized outputs are rejected.
- Indexes are zero-based and spans have an exclusive end unless explicitly stated otherwise. A valid false, null or empty-list result is distinct from malformed input.
Alternative or Complementary methods
For document-wide requirements, combine these structural inventories with an explicit JSON Schema. Preserve the distinction between missing properties and null values, and between numbers and numeric-looking strings when building joins or indexes.
References
Similar or alternative tools
- Record Field Coalesce Tool
Coalesce first present nonnull field into a supplied target; zero, false and empty strings are valid values, all missing yields null.
- Record Field Projection Tool
Project explicit own fields from each JSON record without fabricating missing members.