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EvaluationHandler

buoyant_kernel

Trait EvaluationHandler 

Source 
pub trait EvaluationHandler: AsAny {
    // Required methods
    fn new_expression_evaluator(
        &self,
        input_schema: SchemaRef,
        expression: ExpressionRef,
        output_type: DataType,
    ) -> DeltaResult<Arc<dyn ExpressionEvaluator>>;
    fn new_predicate_evaluator(
        &self,
        input_schema: SchemaRef,
        predicate: PredicateRef,
    ) -> DeltaResult<Arc<dyn PredicateEvaluator>>;
    fn null_row(
        &self,
        output_schema: SchemaRef,
    ) -> DeltaResult<Box<dyn EngineData>>;
    fn create_many(
        &self,
        schema: SchemaRef,
        rows: &[&[Scalar]],
    ) -> DeltaResult<Box<dyn EngineData>>;
}
Expand description

Provides expression evaluation capability to Delta Kernel.

Delta Kernel can use this handler to evaluate a predicate on partition filters, fill up partition column values, and any computation on data using Expressions.

Required Methods§

Source

fn new_expression_evaluator( &self, input_schema: SchemaRef, expression: ExpressionRef, output_type: DataType, ) -> DeltaResult<Arc<dyn ExpressionEvaluator>>

Create an ExpressionEvaluator that can evaluate the given Expression on columnar batches with the given Schema to produce data of DataType.

If the provided output type is a struct, its fields describe the columns of output produced by the evaluator. Otherwise, the output schema is a single column named “output” of the specified output_type. In all cases, the output schema is only used for its names (all field names will be updated to match) and nullability (non-nullable columns can be converted to nullable). Any mismatch in types (including number of columns) will produce an error.

§Parameters
  • input_schema: Schema of the input data.
  • expression: Expression to evaluate.
  • output_type: Expected result data type.
Source

fn new_predicate_evaluator( &self, input_schema: SchemaRef, predicate: PredicateRef, ) -> DeltaResult<Arc<dyn PredicateEvaluator>>

Create a PredicateEvaluator that can evaluate the given Predicate on columnar batches with the given Schema to produce a column of boolean results.

The output schema is a single nullable boolean column named “output”.

§Parameters
  • input_schema: Schema of the input data.
  • predicate: Predicate to evaluate.
Source

fn null_row(&self, output_schema: SchemaRef) -> DeltaResult<Box<dyn EngineData>>

Create a single-row all-null-value EngineData with the schema specified by output_schema.

Source

fn create_many( &self, schema: SchemaRef, rows: &[&[Scalar]], ) -> DeltaResult<Box<dyn EngineData>>

Create a multi-row EngineData by applying the given schema to multiple rows of values.

Each element in rows represents one row of data, where each row is a slice of structured scalar values (one scalar per top-level field in the schema).

§Parameters
  • schema: Schema describing the structure of each row.
  • rows: Slice of rows, where each row contains one structured scalar per top-level schema field.
§Returns

A multi-row EngineData containing all rows.

§Errors

Returns an error if any row has a number of scalars that does not match the number of top-level fields in schema, or if any scalar value cannot be appended to its corresponding field’s builder (e.g. due to a type mismatch).

§Example

For a schema with fields [add: Struct, remove: Struct], each row should contain exactly 2 scalars: one for the add field and one for the remove field.

Implementors§