Struct JsonTuple 

pub struct JsonTuple { /* private fields */ }

Spark-compatible json_tuple expression

https://spark.apache.org/docs/latest/api/sql/index.html#json_tuple

Extracts top-level fields from a JSON string and returns them as a struct.

json_tuple(json_string, field1, field2, ...) -> Struct<c0: Utf8, c1: Utf8, ...>

Note: In Spark, json_tuple is a Generator that produces multiple columns directly. In DataFusion, a ScalarUDF can only return one value per row, so the result is wrapped in a Struct. The caller (e.g. Comet) is expected to destructure the struct fields.

• Returns NULL for each field that is missing from the JSON object
• Returns NULL for all fields if the input is NULL or not valid JSON
• Non-string JSON values are converted to their JSON string representation
• JSON null values are returned as NULL (not the string “null”)

Implementations

impl JsonTuple

pub fn new() -> Self

Trait Implementations

impl Debug for JsonTuple

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Default for JsonTuple

fn default() -> Self

Returns the “default value” for a type.

impl Hash for JsonTuple

fn hash<__H: Hasher>(&self, state: &mut __H)

Feeds this value into the given Hasher.

fn hash_slice<H>(data: &[Self], state: &mut H)

where H: Hasher, Self: Sized,

Feeds a slice of this type into the given Hasher.

impl PartialEq for JsonTuple

fn eq(&self, other: &JsonTuple) -> bool

Tests for self and other values to be equal, and is used by ==.

fn ne(&self, other: &Rhs) -> bool

Tests for !=. The default implementation is almost always sufficient, and should not be overridden without very good reason.

impl ScalarUDFImpl for JsonTuple

fn as_any(&self) -> &dyn Any

Returns this object as an Any trait object

fn name(&self) -> &str

Returns this function’s name

fn signature(&self) -> &Signature

Returns a Signature describing the argument types for which this function has an implementation, and the function’s Volatility.

fn return_type(&self, _arg_types: &[DataType]) -> Result<DataType>

DataType returned by this function, given the types of the arguments.

fn return_field_from_args(&self, args: ReturnFieldArgs<'_>) -> Result<FieldRef>

What type will be returned by this function, given the arguments?

fn invoke_with_args(&self, args: ScalarFunctionArgs) -> Result<ColumnarValue>

Invoke the function returning the appropriate result.

fn aliases(&self) -> &[String]

Returns any aliases (alternate names) for this function.

fn display_name(&self, args: &[Expr]) -> Result<String, DataFusionError>

👎Deprecated since 50.0.0:

This method is unused and will be removed in a future release

Returns the user-defined display name of function, given the arguments

fn schema_name(&self, args: &[Expr]) -> Result<String, DataFusionError>

Returns the name of the column this expression would create

fn with_updated_config(&self, _config: &ConfigOptions) -> Option<ScalarUDF>

Create a new instance of this function with updated configuration.

fn is_nullable(&self, _args: &[Expr], _schema: &dyn ExprSchema) -> bool

👎Deprecated since 45.0.0:

Use return_field_from_args instead. if you use is_nullable that returns non-nullable with return_type, you would need to switch to return_field_from_args, you might have error

fn simplify( &self, args: Vec<Expr>, _info: &SimplifyContext, ) -> Result<ExprSimplifyResult, DataFusionError>

Optionally apply per-UDF simplification / rewrite rules.

fn preimage( &self, _args: &[Expr], _lit_expr: &Expr, _info: &SimplifyContext, ) -> Result<PreimageResult, DataFusionError>

Returns a single contiguous preimage for this function and the specified scalar expression, if any.

fn short_circuits(&self) -> bool

Returns true if some of this exprs subexpressions may not be evaluated and thus any side effects (like divide by zero) may not be encountered.

fn conditional_arguments<'a>( &self, args: &'a [Expr], ) -> Option<(Vec<&'a Expr>, Vec<&'a Expr>)>

Determines which of the arguments passed to this function are evaluated eagerly and which may be evaluated lazily.

fn evaluate_bounds( &self, _input: &[&Interval], ) -> Result<Interval, DataFusionError>

Computes the output Interval for a ScalarUDFImpl, given the input intervals.

fn propagate_constraints( &self, _interval: &Interval, _inputs: &[&Interval], ) -> Result<Option<Vec<Interval>>, DataFusionError>

Updates bounds for child expressions, given a known Intervals for this function.

fn output_ordering( &self, inputs: &[ExprProperties], ) -> Result<SortProperties, DataFusionError>

Calculates the SortProperties of this function based on its children’s properties.

fn preserves_lex_ordering( &self, _inputs: &[ExprProperties], ) -> Result<bool, DataFusionError>

Returns true if the function preserves lexicographical ordering based on the input ordering.

fn coerce_types( &self, _arg_types: &[DataType], ) -> Result<Vec<DataType>, DataFusionError>

Coerce arguments of a function call to types that the function can evaluate.

fn documentation(&self) -> Option<&Documentation>

Returns the documentation for this Scalar UDF.

fn placement(&self, _args: &[ExpressionPlacement]) -> ExpressionPlacement

Returns placement information for this function.

impl Eq for JsonTuple

impl StructuralPartialEq for JsonTuple