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// Licensed to the Apache Software Foundation (ASF) under one
// or more contributor license agreements.  See the NOTICE file
// distributed with this work for additional information
// regarding copyright ownership.  The ASF licenses this file
// to you under the Apache License, Version 2.0 (the
// "License"); you may not use this file except in compliance
// with the License.  You may obtain a copy of the License at
//
//   http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing,
// software distributed under the License is distributed on an
// "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
// KIND, either express or implied.  See the License for the
// specific language governing permissions and limitations
// under the License.

//! [`ApplyFunctionRewrites`] to replace `Expr`s with function calls (e.g `||` to array_concat`)

use super::AnalyzerRule;
use datafusion_common::config::ConfigOptions;
use datafusion_common::tree_node::{Transformed, TreeNodeRewriter};
use datafusion_common::{DFSchema, Result};
use datafusion_expr::expr::{Exists, InSubquery};
use datafusion_expr::expr_rewriter::{rewrite_preserving_name, FunctionRewrite};
use datafusion_expr::utils::merge_schema;
use datafusion_expr::{Expr, LogicalPlan, Subquery};
use std::sync::Arc;

/// Analyzer rule that invokes [`FunctionRewrite`]s on expressions
#[derive(Default)]
pub struct ApplyFunctionRewrites {
    /// Expr --> Function writes to apply
    function_rewrites: Vec<Arc<dyn FunctionRewrite + Send + Sync>>,
}

impl ApplyFunctionRewrites {
    pub fn new(function_rewrites: Vec<Arc<dyn FunctionRewrite + Send + Sync>>) -> Self {
        Self { function_rewrites }
    }
}

impl AnalyzerRule for ApplyFunctionRewrites {
    fn name(&self) -> &str {
        "apply_function_rewrites"
    }

    fn analyze(&self, plan: LogicalPlan, options: &ConfigOptions) -> Result<LogicalPlan> {
        analyze_internal(&plan, &self.function_rewrites, options)
    }
}

fn analyze_internal(
    plan: &LogicalPlan,
    function_rewrites: &[Arc<dyn FunctionRewrite + Send + Sync>],
    options: &ConfigOptions,
) -> Result<LogicalPlan> {
    // optimize child plans first
    let new_inputs = plan
        .inputs()
        .iter()
        .map(|p| analyze_internal(p, function_rewrites, options))
        .collect::<Result<Vec<_>>>()?;

    // get schema representing all available input fields. This is used for data type
    // resolution only, so order does not matter here
    let mut schema = merge_schema(new_inputs.iter().collect());

    if let LogicalPlan::TableScan(ts) = plan {
        let source_schema = DFSchema::try_from_qualified_schema(
            ts.table_name.clone(),
            &ts.source.schema(),
        )?;
        schema.merge(&source_schema);
    }

    let mut expr_rewrite = OperatorToFunctionRewriter {
        function_rewrites,
        options,
        schema: &schema,
    };

    let new_expr = plan
        .expressions()
        .into_iter()
        .map(|expr| {
            // ensure names don't change:
            // https://github.com/apache/arrow-datafusion/issues/3555
            rewrite_preserving_name(expr, &mut expr_rewrite)
        })
        .collect::<Result<Vec<_>>>()?;

    plan.with_new_exprs(new_expr, new_inputs)
}

fn rewrite_subquery(
    mut subquery: Subquery,
    function_rewrites: &[Arc<dyn FunctionRewrite + Send + Sync>],
    options: &ConfigOptions,
) -> Result<Subquery> {
    subquery.subquery = Arc::new(analyze_internal(
        &subquery.subquery,
        function_rewrites,
        options,
    )?);
    Ok(subquery)
}

struct OperatorToFunctionRewriter<'a> {
    function_rewrites: &'a [Arc<dyn FunctionRewrite + Send + Sync>],
    options: &'a ConfigOptions,
    schema: &'a DFSchema,
}

impl<'a> TreeNodeRewriter for OperatorToFunctionRewriter<'a> {
    type Node = Expr;

    fn f_up(&mut self, mut expr: Expr) -> Result<Transformed<Expr>> {
        // apply transforms one by one
        let mut transformed = false;
        for rewriter in self.function_rewrites.iter() {
            let result = rewriter.rewrite(expr, self.schema, self.options)?;
            if result.transformed {
                transformed = true;
            }
            expr = result.data
        }

        // recurse into subqueries if needed
        let expr = match expr {
            Expr::ScalarSubquery(subquery) => Expr::ScalarSubquery(rewrite_subquery(
                subquery,
                self.function_rewrites,
                self.options,
            )?),

            Expr::Exists(Exists { subquery, negated }) => Expr::Exists(Exists {
                subquery: rewrite_subquery(
                    subquery,
                    self.function_rewrites,
                    self.options,
                )?,
                negated,
            }),

            Expr::InSubquery(InSubquery {
                expr,
                subquery,
                negated,
            }) => Expr::InSubquery(InSubquery {
                expr,
                subquery: rewrite_subquery(
                    subquery,
                    self.function_rewrites,
                    self.options,
                )?,
                negated,
            }),

            expr => expr,
        };

        Ok(if transformed {
            Transformed::yes(expr)
        } else {
            Transformed::no(expr)
        })
    }
}