influxdata/influxdb · error

Error computing AND

Error message

Error computing AND

What it means

This panic fires when the DataFusion boolean AND kernel returns an error while reducing per-row boolean arrays into a single mask inside the test helper. Since all inputs are BooleanArrays produced by expression evaluation, the AND kernel is expected to always succeed; an error signals an unexpected array type or internal state.

Solutions

1. Confirm every expression being reduced evaluates to a Boolean array (cast or assert result type before reducing)
2. Check that as_boolean_array succeeded on both accumulator and next array
3. Verify the predicate rewrite only produces boolean predicates (comparison/logical expressions)
4. Test against the pinned DataFusion version; kernel error behavior can differ between releases

Example fix

// before
let bool_array = kernels::boolean::and(as_boolean_array(&acc), as_boolean_array(&arr)).expect("Error computing AND");
// after
let bool_array = kernels::boolean::and(as_boolean_array(&acc), as_boolean_array(&arr))
    .unwrap_or_else(|e| panic!("AND kernel failed; check expressions are boolean: {e}"));

// Rust: confirm arrays are boolean before AND reduction
fn all_boolean(arrs: &[ArrayRef]) -> bool {
    arrs.iter().all(|a| a.data_type() == &DataType::Boolean)
}

fn as_bool(arr: &ArrayRef) -> Option<&BooleanArray> { arr.as_any().downcast_ref::<BooleanArray>() }

let bool_array = kernels::boolean::and(as_boolean_array(&acc), as_boolean_array(&arr))
    .unwrap_or_else(|e| panic!("AND kernel error: {e} - verify all predicates are boolean"));

When it happens

Trigger: add_to_predicate's reduce step calls kernels::boolean::and on arrays that are not actually boolean (as_boolean_array failed earlier or an expression evaluated to a non-boolean type), producing an Err from the kernel.

Common situations: A rewrite rule lets a non-boolean expression (numeric/string comparison result) through to the AND reduction; a DataFusion version change alters and()'s behavior on nulls or chunked arrays.

Understand the failure class

Background: "This is a bug, please report it": internal invariant violations, unreachable panics, and SNH errors explained — this error's family across 47 libraries.

Related errors

• Expected scalar value
• Unexpected err evaluating
• datafusion error
• error while executing plan
• Expected array value

AI-assisted analysis of influxdata/influxdb@06200ef96b (2026-09-19). Data as JSON: /api/errors/91c57e2dc3ab9887. Report an issue: GitHub.

Appendix: source

Thrown at core/predicate/src/rpc_predicate/field_rewrite.rs:186

                Ok(ColumnarValue::Scalar(s)) => {
                    s.to_array_of_size(batch.num_rows()).unwrap_or_else(|e| {
                        panic!("Unexpected err converting scalar result from evaluating {expr:?} against {batch:?}: {e}")
                    })
                }
                Err(e) => panic!("Unexpected err evaluating {expr:?} against {batch:?}: {e}"),
            })
            // Now combine the arrays using AND to get a single output
            // boolean array. For the example above, we would get
            // ┌─────────┐
            // │  true   │
            // │  false  │
            // │  false  │
            // └─────────┘
            .reduce(|acc, arr| {
                // apply boolean AND
                let bool_array =
                    kernels::boolean::and(as_boolean_array(&acc), as_boolean_array(&arr))
                        .expect("Error computing AND");
                Arc::new(bool_array) as ArrayRef
            })
            .unwrap();

        assert_eq!(matching.len(), field_names.len());

        // now find all field names with a 'true' entry in the
        // corresponding row. From our example above:
        // ┌──────┐
        // │_field│
        // │ ---- ├─────────┐
        // │ "f1" │  true ◀─┼─────f1 matches
        // │ "f2" │  false  │
        // │ "f3" │  false  │
        // └──────┴─────────┘
        let new_fields = as_boolean_array(&matching)
            .iter()
            .zip(as_string_array(&field_names).iter())

View on GitHub (pinned to 06200ef96b)