Trait PhysicalExpr

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pub trait PhysicalExpr:
    Send
    + Sync
    + Display
    + Debug
    + DynEq
    + DynHash {
Show 14 methods    // Required methods
    fn as_any(&self) -> &(dyn Any + 'static);
    fn data_type(
        &self,
        input_schema: &Schema,
    ) -> Result<DataType, DataFusionError>;
    fn nullable(&self, input_schema: &Schema) -> Result<bool, DataFusionError>;
    fn evaluate(
        &self,
        batch: &RecordBatch,
    ) -> Result<ColumnarValue, DataFusionError>;
    fn children(&self) -> Vec<&Arc<dyn PhysicalExpr>>;
    fn with_new_children(
        self: Arc<Self>,
        children: Vec<Arc<dyn PhysicalExpr>>,
    ) -> Result<Arc<dyn PhysicalExpr>, DataFusionError>;
    fn fmt_sql(&self, f: &mut Formatter<'_>) -> Result<(), Error>;

    // Provided methods
    fn evaluate_selection(
        &self,
        batch: &RecordBatch,
        selection: &BooleanArray,
    ) -> Result<ColumnarValue, DataFusionError> { ... }
    fn evaluate_bounds(
        &self,
        _children: &[&Interval],
    ) -> Result<Interval, DataFusionError> { ... }
    fn propagate_constraints(
        &self,
        _interval: &Interval,
        _children: &[&Interval],
    ) -> Result<Option<Vec<Interval>>, DataFusionError> { ... }
    fn evaluate_statistics(
        &self,
        children: &[&Distribution],
    ) -> Result<Distribution, DataFusionError> { ... }
    fn propagate_statistics(
        &self,
        parent: &Distribution,
        children: &[&Distribution],
    ) -> Result<Option<Vec<Distribution>>, DataFusionError> { ... }
    fn get_properties(
        &self,
        _children: &[ExprProperties],
    ) -> Result<ExprProperties, DataFusionError> { ... }
    fn snapshot(&self) -> Result<Option<Arc<dyn PhysicalExpr>>, DataFusionError> { ... }
}

Expand description

PhysicalExprs represent expressions such as A + 1 or CAST(c1 AS int).

PhysicalExpr knows its type, nullability and can be evaluated directly on a RecordBatch (see Self::evaluate).

PhysicalExpr are the physical counterpart to Expr used in logical planning. They are typically created from Expr by a PhysicalPlanner invoked from a higher level API

Some important examples of PhysicalExpr are:

Column: Represents a column at a given index in a RecordBatch

To create PhysicalExpr from Expr, see

SessionContext::create_physical_expr: A high level API
create_physical_expr: A low level API

§Formatting `PhysicalExpr` as strings

There are three ways to format PhysicalExpr as a string:

Debug: Standard Rust debugging format (e.g. Constant { value: ... })
Display: Detailed SQL-like format that shows expression structure (e.g. (Utf8 ("foobar")). This is often used for debugging and tests
Self::fmt_sql: SQL-like human readable format (e.g. (‘foobar’)), See also [sql_fmt`]

Required Methods§

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fn as_any(&self) -> &(dyn Any + 'static)

Returns the physical expression as Any so that it can be downcast to a specific implementation.

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fn data_type(&self, input_schema: &Schema) -> Result<DataType, DataFusionError>

Get the data type of this expression, given the schema of the input

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fn nullable(&self, input_schema: &Schema) -> Result<bool, DataFusionError>

Determine whether this expression is nullable, given the schema of the input

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fn evaluate( &self, batch: &RecordBatch, ) -> Result<ColumnarValue, DataFusionError>

Evaluate an expression against a RecordBatch

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fn children(&self) -> Vec<&Arc<dyn PhysicalExpr>>

Get a list of child PhysicalExpr that provide the input for this expr.

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fn with_new_children( self: Arc<Self>, children: Vec<Arc<dyn PhysicalExpr>>, ) -> Result<Arc<dyn PhysicalExpr>, DataFusionError>

Returns a new PhysicalExpr where all children were replaced by new exprs.

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

Format this PhysicalExpr in nice human readable “SQL” format

Specifically, this format is designed to be readable by humans, at the expense of details. Use Display or Debug for more detailed representation.

See the fmt_sql function for an example of printing PhysicalExprs as SQL.

Provided Methods§

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fn evaluate_selection( &self, batch: &RecordBatch, selection: &BooleanArray, ) -> Result<ColumnarValue, DataFusionError>

Evaluate an expression against a RecordBatch after first applying a validity array

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

Computes the output interval for the expression, given the input intervals.

§Parameters

children are the intervals for the children (inputs) of this expression.

§Returns

A Result containing the output interval for the expression in case of success, or an error object in case of failure.

§Example

If the expression is a + b, and the input intervals are a: [1, 2] and b: [3, 4], then the output interval would be [4, 6].

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

Updates bounds for child expressions, given a known interval for this expression.

This is used to propagate constraints down through an expression tree.

§Parameters

interval is the currently known interval for this expression.
children are the current intervals for the children of this expression.

§Returns

A Result containing a Vec of new intervals for the children (in order) in case of success, or an error object in case of failure.

If constraint propagation reveals an infeasibility for any child, returns None. If none of the children intervals change as a result of propagation, may return an empty vector instead of cloning children. This is the default (and conservative) return value.

§Example

If the expression is a + b, the current interval is [4, 5] and the inputs a and b are respectively given as [0, 2] and [-∞, 4], then propagation would return [0, 2] and [2, 4] as b must be at least 2 to make the output at least 4.

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fn evaluate_statistics( &self, children: &[&Distribution], ) -> Result<Distribution, DataFusionError>

Computes the output statistics for the expression, given the input statistics.

§Parameters

children are the statistics for the children (inputs) of this expression.

§Returns

A Result containing the output statistics for the expression in case of success, or an error object in case of failure.

Expressions (should) implement this function and utilize the independence assumption, match on children distribution types and compute the output statistics accordingly. The default implementation simply creates an unknown output distribution by combining input ranges. This logic loses distribution information, but is a safe default.

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fn propagate_statistics( &self, parent: &Distribution, children: &[&Distribution], ) -> Result<Option<Vec<Distribution>>, DataFusionError>

Updates children statistics using the given parent statistic for this expression.

This is used to propagate statistics down through an expression tree.

§Parameters

parent is the currently known statistics for this expression.
children are the current statistics for the children of this expression.

§Returns

A Result containing a Vec of new statistics for the children (in order) in case of success, or an error object in case of failure.

If statistics propagation reveals an infeasibility for any child, returns None. If none of the children statistics change as a result of propagation, may return an empty vector instead of cloning children. This is the default (and conservative) return value.

Expressions (should) implement this function and apply Bayes rule to reconcile and update parent/children statistics. This involves utilizing the independence assumption, and matching on distribution types. The default implementation simply creates an unknown distribution if it can narrow the range by propagating ranges. This logic loses distribution information, but is a safe default.

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fn get_properties( &self, _children: &[ExprProperties], ) -> Result<ExprProperties, DataFusionError>

Calculates the properties of this PhysicalExpr based on its children’s properties (i.e. order and range), recursively aggregating the information from its children. In cases where the PhysicalExpr has no children (e.g., Literal or Column), these properties should be specified externally, as the function defaults to unknown properties.

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fn snapshot(&self) -> Result<Option<Arc<dyn PhysicalExpr>>, DataFusionError>

Take a snapshot of this PhysicalExpr, if it is dynamic.

“Dynamic” in this case means containing references to structures that may change during plan execution, such as hash tables.

This method is used to capture the current state of PhysicalExprs that may contain dynamic references to other operators in order to serialize it over the wire or treat it via downcast matching.

You should not call this method directly as it does not handle recursion. Instead use snapshot_physical_expr to handle recursion and capture the full state of the PhysicalExpr.

This is expected to return “simple” expressions that do not have mutable state and are composed of DataFusion’s built-in PhysicalExpr implementations. Callers however should not assume anything about the returned expressions since callers and implementers may not agree on what “simple” or “built-in” means. In other words, if you need to serialize a PhysicalExpr across the wire you should call this method and then try to serialize the result, but you should handle unknown or unexpected PhysicalExpr implementations gracefully just as if you had not called this method at all.

In particular, consider:

A PhysicalExpr that references the current state of a datafusion::physical_plan::TopK that is involved in a query with SELECT * FROM t1 ORDER BY a LIMIT 10. This function may return something like a >= 12.
A PhysicalExpr that references the current state of a datafusion::physical_plan::joins::HashJoinExec from a query such as SELECT * FROM t1 JOIN t2 ON t1.a = t2.b. This function may return something like t2.b IN (1, 5, 7).

A system or function that can only deal with a hardcoded set of PhysicalExpr implementations or needs to serialize this state to bytes may not be able to handle these dynamic references. In such cases, we should return a simplified version of the PhysicalExpr that does not contain these dynamic references.

Systems that implement remote execution of plans, e.g. serialize a portion of the query plan and send it across the wire to a remote executor may want to call this method after every batch on the source side and brodcast / update the current snaphot to the remote executor.

Note for implementers: this method should not handle recursion. Recursion is handled in snapshot_physical_expr.