datafusion-catalog 48.0.1

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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::datatypes::SchemaRef;
use async_trait::async_trait;
use datafusion_common::Result;
use datafusion_common::{not_impl_err, Constraints, Statistics};
use datafusion_expr::Expr;

use datafusion_expr::dml::InsertOp;
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: Debug + Sync + Send {
    /// Returns the table provider as [`Any`](std::any::Any) so that it can be
    /// downcast to a specific implementation.
    fn as_any(&self) -> &dyn Any;

    /// 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 optionally
    /// specified `projection`, `filter` and `limit`, described below.
    ///
    /// The `ExecutionPlan` is responsible 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 to scan only the columns actually
    /// used in the query to improve performance, 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 (aka the
    /// expressions are `AND`ed together).
    ///
    /// To enable filter pushdown you must override
    /// [`Self::supports_filters_pushdown`] as the default implementation does
    /// not and `filters` will be empty.
    ///
    /// DataFusion pushes filtering into the scans whenever possible
    /// ("Filter Pushdown"), and depending on the format and the
    /// implementation of the format, evaluating the predicate during the scan
    /// can increase performance significantly.
    ///
    /// ## Note: Some columns may appear *only* in Filters
    ///
    /// In certain cases, a query may only use a certain column in a Filter that
    /// has been completely pushed down to the scan. In this case, the
    /// projection will not contain all the columns found in 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,  must only 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, called "Limit Pushdown" as some sources can use this
    /// information to improve their performance. Note that if there are any
    /// Inexact filters pushed down, the LIMIT cannot be pushed down. This is
    /// because inexact filters do not guarantee that every filtered row is
    /// removed, so applying the limit could lead to too few rows being available
    /// to return as a final result.
    async fn scan(
        &self,
        state: &dyn Session,
        projection: Option<&Vec<usize>>,
        filters: &[Expr],
        limit: Option<usize>,
    ) -> Result<Arc<dyn ExecutionPlan>>;

    /// 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::datatypes::SchemaRef;
    /// # use async_trait::async_trait;
    /// # use datafusion_catalog::{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 as_any(&self) -> &dyn Any { todo!() }
    /// # 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`]: datafusion_datasource::sink::DataSinkExec
    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")
    }
}

/// 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>>;
}

/// A trait for table function implementations
pub trait TableFunctionImpl: Debug + Sync + Send {
    /// Create a table provider
    fn call(&self, args: &[Expr]) -> Result<Arc<dyn TableProvider>>;
}

/// A table that uses a function to generate data
#[derive(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
    pub fn create_table_provider(&self, args: &[Expr]) -> Result<Arc<dyn TableProvider>> {
        self.fun.call(args)
    }
}