datafusion_session/

table.rs

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//
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use std::any::Any;
use std::borrow::Cow;
use std::fmt::Debug;
use std::sync::Arc;

use crate::session::Session;
use arrow_schema::SchemaRef;
use async_trait::async_trait;
use datafusion_common::{Constraints, Statistics, not_impl_err};
use datafusion_common::{DFSchemaRef, Result, internal_err};
use datafusion_expr::Expr;
use datafusion_expr::statistics::StatisticsRequest;

use datafusion_expr::dml::{InsertOp, MergeIntoClause};
use datafusion_expr::{
    CreateExternalTable, LogicalPlan, TableProviderFilterPushDown, TableType,
};
use datafusion_physical_plan::ExecutionPlan;

/// A table which can be queried and modified.
///
/// Please see [`CatalogProvider`] for details of implementing a custom catalog.
///
/// [`TableProvider`] represents a source of data which can provide data as
/// Apache Arrow [`RecordBatch`]es. Implementations of this trait provide
/// important information for planning such as:
///
/// 1. [`Self::schema`]: The schema (columns and their types) of the table
/// 2. [`Self::supports_filters_pushdown`]: Should filters be pushed into this scan
/// 2. [`Self::scan`]: An [`ExecutionPlan`] that can read data
///
/// [`RecordBatch`]: https://docs.rs/arrow/latest/arrow/record_batch/struct.RecordBatch.html
/// [`CatalogProvider`]: super::CatalogProvider
#[async_trait]
pub trait TableProvider: Any + Debug + Sync + Send {
    /// Get a reference to the schema for this table
    fn schema(&self) -> SchemaRef;

    /// Get a reference to the constraints of the table.
    /// Returns:
    /// - `None` for tables that do not support constraints.
    /// - `Some(&Constraints)` for tables supporting constraints.
    /// Therefore, a `Some(&Constraints::empty())` return value indicates that
    /// this table supports constraints, but there are no constraints.
    fn constraints(&self) -> Option<&Constraints> {
        None
    }

    /// Get the type of this table for metadata/catalog purposes.
    fn table_type(&self) -> TableType;

    /// Get the create statement used to create this table, if available.
    fn get_table_definition(&self) -> Option<&str> {
        None
    }

    /// Get the [`LogicalPlan`] of this table, if available.
    fn get_logical_plan(&'_ self) -> Option<Cow<'_, LogicalPlan>> {
        None
    }

    /// Get the default value for a column, if available.
    fn get_column_default(&self, _column: &str) -> Option<&Expr> {
        None
    }

    /// Create an [`ExecutionPlan`] for scanning the table with optional
    /// `projection`, `filter`, and `limit`, described below.
    ///
    /// The returned `ExecutionPlan` is responsible for scanning the datasource's
    /// partitions in a streaming, parallelized fashion.
    ///
    /// # Projection
    ///
    /// If specified, only a subset of columns should be returned, in the order
    /// specified. The projection is a set of indexes of the fields in
    /// [`Self::schema`].
    ///
    /// DataFusion provides the projection so the scan reads only the columns
    /// actually used in the query, an optimization called "Projection
    /// Pushdown". Some datasources, such as Parquet, can use this information
    /// to go significantly faster when only a subset of columns is required.
    ///
    /// # Filters
    ///
    /// A list of boolean filter [`Expr`]s to evaluate *during* the scan, in the
    /// manner specified by [`Self::supports_filters_pushdown`]. Only rows for
    /// which *all* of the `Expr`s evaluate to `true` must be returned (that is,
    /// the expressions are `AND`ed together).
    ///
    /// To enable filter pushdown, override
    /// [`Self::supports_filters_pushdown`]. The default implementation does not
    /// push down filters, and `filters` will be empty.
    ///
    /// DataFusion pushes filters into scans whenever possible ("Filter
    /// Pushdown"). Depending on the data format and implementation, evaluating
    /// predicates during the scan can significantly improve performance.
    ///
    /// ## Note: Some columns may appear *only* in Filters
    ///
    /// In some cases, a query may use a column only in a filter and the
    /// projection will not contain all columns referenced by the filter
    /// expressions.
    ///
    /// For example, given the query `SELECT t.a FROM t WHERE t.b > 5`,
    ///
    /// ```text
    /// ┌────────────────────┐
    /// │  Projection(t.a)   │
    /// └────────────────────┘
    ///            ▲
    ///            │
    ///            │
    /// ┌────────────────────┐     Filter     ┌────────────────────┐   Projection    ┌────────────────────┐
    /// │  Filter(t.b > 5)   │────Pushdown──▶ │  Projection(t.a)   │ ───Pushdown───▶ │  Projection(t.a)   │
    /// └────────────────────┘                └────────────────────┘                 └────────────────────┘
    ///            ▲                                     ▲                                      ▲
    ///            │                                     │                                      │
    ///            │                                     │                           ┌────────────────────┐
    /// ┌────────────────────┐                ┌────────────────────┐                 │        Scan        │
    /// │        Scan        │                │        Scan        │                 │  filter=(t.b > 5)  │
    /// └────────────────────┘                │  filter=(t.b > 5)  │                 │  projection=(t.a)  │
    ///                                       └────────────────────┘                 └────────────────────┘
    ///
    /// Initial Plan                  If `TableProviderFilterPushDown`           Projection pushdown notes that
    ///                               returns true, filter pushdown              the scan only needs t.a
    ///                               pushes the filter into the scan
    ///                                                                          BUT internally evaluating the
    ///                                                                          predicate still requires t.b
    /// ```
    ///
    /// # Limit
    ///
    /// If `limit` is specified, the scan must produce *at least* this many
    /// rows, though it may return more. Like Projection Pushdown and Filter
    /// Pushdown, DataFusion pushes `LIMIT`s as far down in the plan as
    /// possible. This is called "Limit Pushdown", and some sources can use the
    /// information to improve performance.
    ///
    /// Note: If any pushed-down filters are `Inexact`, the `LIMIT` cannot be
    /// pushed down. Inexact filters do not guarantee that every filtered row is
    /// removed, so applying the limit could leave too few rows to return in the
    /// final result.
    ///
    /// # Evaluation Order
    ///
    /// The logical evaluation order is `filters`, then `limit`, then
    /// `projection`.
    ///
    /// Note that `limit` applies to the filtered result, not to the unfiltered
    /// input, and `projection` affects only which columns are returned, not
    /// which rows qualify.
    ///
    /// For example, if a scan receives:
    ///
    /// - `projection = [a]`
    /// - `filters = [b > 5]`
    /// - `limit = Some(3)`
    ///
    /// It must logically produce results equivalent to:
    ///
    /// ```text
    /// PROJECTION a (LIMIT 3 (SCAN WHERE b > 5))
    /// ```
    ///
    /// As noted above, columns referenced only by pushed-down filters may be
    /// absent from `projection`.
    async fn scan(
        &self,
        state: &dyn Session,
        projection: Option<&Vec<usize>>,
        filters: &[Expr],
        limit: Option<usize>,
    ) -> Result<Arc<dyn ExecutionPlan>>;

    /// Create an [`ExecutionPlan`] for scanning the table using structured arguments.
    ///
    /// This method uses [`ScanArgs`] to pass scan parameters in a structured way
    /// and returns a [`ScanResult`] containing the execution plan.
    ///
    /// Table providers can override this method to take advantage of additional
    /// parameters like the upcoming `preferred_ordering` that may not be available through
    /// other scan methods.
    ///
    /// # Arguments
    /// * `state` - The session state containing configuration and context
    /// * `args` - Structured scan arguments including projection, filters, limit, and ordering preferences
    ///
    /// # Returns
    /// A [`ScanResult`] containing the [`ExecutionPlan`] for scanning the table
    ///
    /// See [`Self::scan`] for detailed documentation about projection, filters, and limits.
    async fn scan_with_args<'a>(
        &self,
        state: &dyn Session,
        args: ScanArgs<'a>,
    ) -> Result<ScanResult> {
        let filters = args.filters().unwrap_or(&[]);
        let projection = args.projection().map(|p| p.to_vec());
        let limit = args.limit();
        let plan = self
            .scan(state, projection.as_ref(), filters, limit)
            .await?;
        Ok(plan.into())
    }

    /// Specify if DataFusion should provide filter expressions to the
    /// TableProvider to apply *during* the scan.
    ///
    /// Some TableProviders can evaluate filters more efficiently than the
    /// `Filter` operator in DataFusion, for example by using an index.
    ///
    /// # Parameters and Return Value
    ///
    /// The return `Vec` must have one element for each element of the `filters`
    /// argument. The value of each element indicates if the TableProvider can
    /// apply the corresponding filter during the scan. The position in the return
    /// value corresponds to the expression in the `filters` parameter.
    ///
    /// If the length of the resulting `Vec` does not match the `filters` input
    /// an error will be thrown.
    ///
    /// Each element in the resulting `Vec` is one of the following:
    /// * [`Exact`] or [`Inexact`]: The TableProvider can apply the filter
    /// during scan
    /// * [`Unsupported`]: The TableProvider cannot apply the filter during scan
    ///
    /// By default, this function returns [`Unsupported`] for all filters,
    /// meaning no filters will be provided to [`Self::scan`].
    ///
    /// [`Unsupported`]: TableProviderFilterPushDown::Unsupported
    /// [`Exact`]: TableProviderFilterPushDown::Exact
    /// [`Inexact`]: TableProviderFilterPushDown::Inexact
    /// # Example
    ///
    /// ```rust
    /// # use std::any::Any;
    /// # use std::sync::Arc;
    /// # use arrow_schema::SchemaRef;
    /// # use async_trait::async_trait;
    /// # use datafusion_session::{TableProvider, Session};
    /// # use datafusion_common::Result;
    /// # use datafusion_expr::{Expr, TableProviderFilterPushDown, TableType};
    /// # use datafusion_physical_plan::ExecutionPlan;
    /// // Define a struct that implements the TableProvider trait
    /// #[derive(Debug)]
    /// struct TestDataSource {}
    ///
    /// #[async_trait]
    /// impl TableProvider for TestDataSource {
    /// # fn schema(&self) -> SchemaRef { todo!() }
    /// # fn table_type(&self) -> TableType { todo!() }
    /// # async fn scan(&self, s: &dyn Session, p: Option<&Vec<usize>>, f: &[Expr], l: Option<usize>) -> Result<Arc<dyn ExecutionPlan>> {
    ///         todo!()
    /// # }
    ///     // Override the supports_filters_pushdown to evaluate which expressions
    ///     // to accept as pushdown predicates.
    ///     fn supports_filters_pushdown(&self, filters: &[&Expr]) -> Result<Vec<TableProviderFilterPushDown>> {
    ///         // Process each filter
    ///         let support: Vec<_> = filters.iter().map(|expr| {
    ///           match expr {
    ///             // This example only supports a between expr with a single column named "c1".
    ///             Expr::Between(between_expr) => {
    ///                 between_expr.expr
    ///                 .try_as_col()
    ///                 .map(|column| {
    ///                     if column.name == "c1" {
    ///                         TableProviderFilterPushDown::Exact
    ///                     } else {
    ///                         TableProviderFilterPushDown::Unsupported
    ///                     }
    ///                 })
    ///                 // If there is no column in the expr set the filter to unsupported.
    ///                 .unwrap_or(TableProviderFilterPushDown::Unsupported)
    ///             }
    ///             _ => {
    ///                 // For all other cases return Unsupported.
    ///                 TableProviderFilterPushDown::Unsupported
    ///             }
    ///         }
    ///     }).collect();
    ///     Ok(support)
    ///     }
    /// }
    /// ```
    fn supports_filters_pushdown(
        &self,
        filters: &[&Expr],
    ) -> Result<Vec<TableProviderFilterPushDown>> {
        Ok(vec![
            TableProviderFilterPushDown::Unsupported;
            filters.len()
        ])
    }

    /// Get statistics for this table, if available
    /// Although not presently used in mainline DataFusion, this allows implementation specific
    /// behavior for downstream repositories, in conjunction with specialized optimizer rules to
    /// perform operations such as re-ordering of joins.
    fn statistics(&self) -> Option<Statistics> {
        None
    }

    /// Return an [`ExecutionPlan`] to insert data into this table, if
    /// supported.
    ///
    /// The returned plan should return a single row in a UInt64
    /// column called "count" such as the following
    ///
    /// ```text
    /// +-------+,
    /// | count |,
    /// +-------+,
    /// | 6     |,
    /// +-------+,
    /// ```
    ///
    /// # See Also
    ///
    /// See [`DataSinkExec`] for the common pattern of inserting a
    /// streams of `RecordBatch`es as files to an ObjectStore.
    ///
    /// [`DataSinkExec`]: https://docs.rs/datafusion-datasource/latest/datafusion_datasource/sink/struct.DataSinkExec.html
    async fn insert_into(
        &self,
        _state: &dyn Session,
        _input: Arc<dyn ExecutionPlan>,
        _insert_op: InsertOp,
    ) -> Result<Arc<dyn ExecutionPlan>> {
        not_impl_err!("Insert into not implemented for this table")
    }

    /// Delete rows matching the filter predicates.
    ///
    /// Returns an [`ExecutionPlan`] producing a single row with `count` (UInt64).
    /// Empty `filters` deletes all rows.
    async fn delete_from(
        &self,
        _state: &dyn Session,
        _filters: Vec<Expr>,
    ) -> Result<Arc<dyn ExecutionPlan>> {
        not_impl_err!("DELETE not supported for {} table", self.table_type())
    }

    /// Update rows matching the filter predicates.
    ///
    /// Returns an [`ExecutionPlan`] producing a single row with `count` (UInt64).
    /// Empty `filters` updates all rows.
    async fn update(
        &self,
        _state: &dyn Session,
        _assignments: Vec<(String, Expr)>,
        _filters: Vec<Expr>,
    ) -> Result<Arc<dyn ExecutionPlan>> {
        not_impl_err!("UPDATE not supported for {} table", self.table_type())
    }

    /// Remove all rows from the table.
    ///
    /// Should return an [ExecutionPlan] producing a single row with count (UInt64),
    /// representing the number of rows removed.
    async fn truncate(&self, _state: &dyn Session) -> Result<Arc<dyn ExecutionPlan>> {
        not_impl_err!("TRUNCATE not supported for {} table", self.table_type())
    }

    /// Merge rows from a source into this table.
    ///
    /// The `source` is an [`ExecutionPlan`] representing the USING clause.
    /// The `merge_schema` contains the target columns followed by the source
    /// columns, preserving their logical qualifiers. Providers can use this
    /// schema to resolve the logical expressions against the combined rows
    /// they construct while executing the merge.
    /// The `on` condition is the join predicate from the ON clause.
    /// The `clauses` describe the WHEN MATCHED / WHEN NOT MATCHED actions.
    ///
    /// Returns an [`ExecutionPlan`] producing a single row with `count` (UInt64).
    async fn merge_into(
        &self,
        _state: &dyn Session,
        _source: Arc<dyn ExecutionPlan>,
        _merge_schema: DFSchemaRef,
        _on: Expr,
        _clauses: Vec<MergeIntoClause>,
    ) -> Result<Arc<dyn ExecutionPlan>> {
        not_impl_err!("MERGE INTO not supported for {} table", self.table_type())
    }
}

impl dyn TableProvider {
    /// Returns `true` if the table provider is of type `T`.
    ///
    /// Prefer this over `downcast_ref::<T>().is_some()`. Works correctly when
    /// called on `Arc<dyn TableProvider>` via auto-deref.
    pub fn is<T: TableProvider>(&self) -> bool {
        (self as &dyn Any).is::<T>()
    }

    /// Attempts to downcast this table provider to a concrete type `T`,
    /// returning `None` if the provider is not of that type.
    ///
    /// Works correctly when called on `Arc<dyn TableProvider>` via auto-deref,
    /// unlike `(&arc as &dyn Any).downcast_ref::<T>()` which would attempt to
    /// downcast the `Arc` itself.
    pub fn downcast_ref<T: TableProvider>(&self) -> Option<&T> {
        (self as &dyn Any).downcast_ref()
    }
}

/// Arguments for scanning a table with [`TableProvider::scan_with_args`].
#[derive(Debug, Clone, Default)]
pub struct ScanArgs<'a> {
    filters: Option<&'a [Expr]>,
    projection: Option<&'a [usize]>,
    limit: Option<usize>,
    statistics_requests: &'a [StatisticsRequest],
}

impl<'a> ScanArgs<'a> {
    /// Set the column projection for the scan.
    ///
    /// The projection is a list of column indices from [`TableProvider::schema`]
    /// that should be included in the scan results. If `None`, all columns are included.
    ///
    /// # Arguments
    /// * `projection` - Optional slice of column indices to project
    pub fn with_projection(mut self, projection: Option<&'a [usize]>) -> Self {
        self.projection = projection;
        self
    }

    /// Get the column projection for the scan.
    ///
    /// Returns a reference to the projection column indices, or `None` if
    /// no projection was specified (meaning all columns should be included).
    pub fn projection(&self) -> Option<&'a [usize]> {
        self.projection
    }

    /// Set the filter expressions for the scan.
    ///
    /// Filters are boolean expressions that should be evaluated during the scan
    /// to reduce the number of rows returned. All expressions are combined with AND logic.
    /// Whether filters are actually pushed down depends on [`TableProvider::supports_filters_pushdown`].
    ///
    /// # Arguments
    /// * `filters` - Optional slice of filter expressions
    pub fn with_filters(mut self, filters: Option<&'a [Expr]>) -> Self {
        self.filters = filters;
        self
    }

    /// Get the filter expressions for the scan.
    ///
    /// Returns a reference to the filter expressions, or `None` if no filters were specified.
    pub fn filters(&self) -> Option<&'a [Expr]> {
        self.filters
    }

    /// Set the maximum number of rows to return from the scan.
    ///
    /// If specified, the scan should return at most this many rows. This is typically
    /// used to optimize queries with `LIMIT` clauses.
    ///
    /// # Arguments
    /// * `limit` - Optional maximum number of rows to return
    pub fn with_limit(mut self, limit: Option<usize>) -> Self {
        self.limit = limit;
        self
    }

    /// Get the maximum number of rows to return from the scan.
    ///
    /// Returns the row limit, or `None` if no limit was specified.
    pub fn limit(&self) -> Option<usize> {
        self.limit
    }

    /// Specifies the statistics the caller may use when optimizing the query.
    ///
    /// This is intended to allow the `TableProvider` to cheaply provide
    /// statistics that may help, such as those it has in an in-memory catalog
    /// or from some other metadata source.
    ///
    /// `TableProvider`s read these via [`Self::statistics_requests()`]; anything
    /// a `TableProvider` cannot answer cheaply it simply ignores. DataFusion's
    /// own `TableProvider`s ignore this field — it exists so a request can be
    /// threaded from a custom optimizer rule (which annotates
    /// `TableScan::statistics_requests`) through to a custom `TableProvider`.
    pub fn with_statistics_requests(
        mut self,
        statistics_requests: &'a [StatisticsRequest],
    ) -> Self {
        self.statistics_requests = statistics_requests;
        self
    }

    /// Get the statistics requests for the scan. Empty if none were set.
    ///
    /// See [`Self::with_statistics_requests`] for more details
    pub fn statistics_requests(&self) -> &'a [StatisticsRequest] {
        self.statistics_requests
    }
}

/// Result of a table scan operation from [`TableProvider::scan_with_args`].
#[derive(Debug, Clone)]
pub struct ScanResult {
    /// The ExecutionPlan to run.
    plan: Arc<dyn ExecutionPlan>,
}

impl ScanResult {
    /// Create a new `ScanResult` with the given execution plan.
    ///
    /// # Arguments
    /// * `plan` - The execution plan that will perform the table scan
    pub fn new(plan: Arc<dyn ExecutionPlan>) -> Self {
        Self { plan }
    }

    /// Get a reference to the execution plan for this scan result.
    ///
    /// Returns a reference to the [`ExecutionPlan`] that will perform
    /// the actual table scanning and data retrieval.
    pub fn plan(&self) -> &Arc<dyn ExecutionPlan> {
        &self.plan
    }

    /// Consume this ScanResult and return the execution plan.
    ///
    /// Returns the owned [`ExecutionPlan`] that will perform
    /// the actual table scanning and data retrieval.
    pub fn into_inner(self) -> Arc<dyn ExecutionPlan> {
        self.plan
    }
}

impl From<Arc<dyn ExecutionPlan>> for ScanResult {
    fn from(plan: Arc<dyn ExecutionPlan>) -> Self {
        Self::new(plan)
    }
}

/// A factory which creates [`TableProvider`]s at runtime given a URL.
///
/// For example, this can be used to create a table "on the fly"
/// from a directory of files only when that name is referenced.
#[async_trait]
pub trait TableProviderFactory: Debug + Sync + Send {
    /// Create a TableProvider with the given url
    async fn create(
        &self,
        state: &dyn Session,
        cmd: &CreateExternalTable,
    ) -> Result<Arc<dyn TableProvider>>;
}

/// Describes arguments provided to the table function call.
pub struct TableFunctionArgs<'e, 's> {
    /// Call arguments.
    exprs: &'e [Expr],
    /// Session within which the function is called.
    session: &'s dyn Session,
}

impl<'e, 's> TableFunctionArgs<'e, 's> {
    /// Make a new [`TableFunctionArgs`].
    pub fn new(exprs: &'e [Expr], session: &'s dyn Session) -> Self {
        Self { exprs, session }
    }

    /// Get expressions passed as the called function arguments.
    pub fn exprs(&self) -> &'e [Expr] {
        self.exprs
    }

    /// Get a session where the table function is called.
    pub fn session(&self) -> &'s dyn Session {
        self.session
    }
}

/// A trait for table function implementations
pub trait TableFunctionImpl: Debug + Sync + Send + Any {
    /// Create a table provider
    #[deprecated(
        since = "53.0.0",
        note = "Implement `TableFunctionImpl::call_with_args` instead"
    )]
    fn call(&self, _exprs: &[Expr]) -> Result<Arc<dyn TableProvider>> {
        internal_err!(
            "TableFunctionImpl::call is not implemented. Implement TableFunctionImpl::call_with_args instead."
        )
    }

    /// Create a table provider
    fn call_with_args(&self, args: TableFunctionArgs) -> Result<Arc<dyn TableProvider>> {
        #[expect(deprecated)]
        self.call(args.exprs)
    }
}

/// A table that uses a function to generate data
#[derive(Clone, Debug)]
pub struct TableFunction {
    /// Name of the table function
    name: String,
    /// Function implementation
    fun: Arc<dyn TableFunctionImpl>,
}

impl TableFunction {
    /// Create a new table function
    pub fn new(name: String, fun: Arc<dyn TableFunctionImpl>) -> Self {
        Self { name, fun }
    }

    /// Get the name of the table function
    pub fn name(&self) -> &str {
        &self.name
    }

    /// Get the implementation of the table function
    pub fn function(&self) -> &Arc<dyn TableFunctionImpl> {
        &self.fun
    }

    /// Get the function implementation and generate a table
    #[deprecated(
        since = "53.0.0",
        note = "Use `TableFunction::create_table_provider_with_args` instead"
    )]
    pub fn create_table_provider(&self, args: &[Expr]) -> Result<Arc<dyn TableProvider>> {
        #[expect(deprecated)]
        self.fun.call(args)
    }

    /// Get the function implementation and generate a table
    pub fn create_table_provider_with_args(
        &self,
        args: TableFunctionArgs,
    ) -> Result<Arc<dyn TableProvider>> {
        self.fun.call_with_args(args)
    }
}