diff --git a/datafusion-examples/README.md b/datafusion-examples/README.md
index 5f032c3e9cfff..75fcaddf8def3 100644
--- a/datafusion-examples/README.md
+++ b/datafusion-examples/README.md
@@ -61,7 +61,7 @@ cargo run --example dataframe
 - [`dataframe_in_memory.rs`](examples/dataframe_in_memory.rs): Run a query using a DataFrame against data in memory
 - [`dataframe_output.rs`](examples/dataframe_output.rs): Examples of methods which write data out from a DataFrame
 - [`deserialize_to_struct.rs`](examples/deserialize_to_struct.rs): Convert query results into rust structs using serde
-- [`expr_api.rs`](examples/expr_api.rs): Create, execute, simplify and analyze `Expr`s
+- [`expr_api.rs`](examples/expr_api.rs): Create, execute, simplify, analyze and coerce `Expr`s
 - [`file_stream_provider.rs`](examples/file_stream_provider.rs): Run a query on `FileStreamProvider` which implements `StreamProvider` for reading and writing to arbitrary stream sources / sinks.
 - [`flight_sql_server.rs`](examples/flight/flight_sql_server.rs): Run DataFusion as a standalone process and execute SQL queries from JDBC clients
 - [`function_factory.rs`](examples/function_factory.rs): Register `CREATE FUNCTION` handler to implement SQL macros
diff --git a/datafusion-examples/examples/expr_api.rs b/datafusion-examples/examples/expr_api.rs
index 0eb823302acf6..cb0796bdcf735 100644
--- a/datafusion-examples/examples/expr_api.rs
+++ b/datafusion-examples/examples/expr_api.rs
@@ -18,7 +18,7 @@
 use std::collections::HashMap;
 use std::sync::Arc;
 
-use arrow::array::{BooleanArray, Int32Array};
+use arrow::array::{BooleanArray, Int32Array, Int8Array};
 use arrow::record_batch::RecordBatch;
 
 use datafusion::arrow::datatypes::{DataType, Field, Schema, TimeUnit};
@@ -28,12 +28,14 @@ use datafusion::functions_aggregate::first_last::first_value_udaf;
 use datafusion::optimizer::simplify_expressions::ExprSimplifier;
 use datafusion::physical_expr::{analyze, AnalysisContext, ExprBoundaries};
 use datafusion::prelude::*;
+use datafusion_common::tree_node::{Transformed, TreeNode};
 use datafusion_common::{ScalarValue, ToDFSchema};
 use datafusion_expr::execution_props::ExecutionProps;
 use datafusion_expr::expr::BinaryExpr;
 use datafusion_expr::interval_arithmetic::Interval;
 use datafusion_expr::simplify::SimplifyContext;
 use datafusion_expr::{ColumnarValue, ExprFunctionExt, ExprSchemable, Operator};
+use datafusion_optimizer::analyzer::type_coercion::TypeCoercionRewriter;
 
 /// This example demonstrates the DataFusion [`Expr`] API.
 ///
@@ -51,6 +53,7 @@ use datafusion_expr::{ColumnarValue, ExprFunctionExt, ExprSchemable, Operator};
 /// 4. Simplify expressions: [`simplify_demo`]
 /// 5. Analyze predicates for boundary ranges: [`range_analysis_demo`]
 /// 6. Get the types of the expressions: [`expression_type_demo`]
+/// 7. Apply type cocercion to expressions: [`type_coercion_demo`]
 #[tokio::main]
 async fn main() -> Result<()> {
     // The easiest way to do create expressions is to use the
@@ -80,6 +83,9 @@ async fn main() -> Result<()> {
     // See how to determine the data types of expressions
     expression_type_demo()?;
 
+    // See how to type coerce expressions.
+    type_coercion_demo()?;
+
     Ok(())
 }
 
@@ -316,3 +322,103 @@ fn expression_type_demo() -> Result<()> {
 
     Ok(())
 }
+
+/// This function demonstrates how to apply type coercion to expressions, such as binary expressions.
+///
+/// In most cases, manual type coercion is not required since DataFusion handles it implicitly.
+/// However, certain projects may construct `ExecutionPlan`s directly from DataFusion logical expressions,
+/// bypassing the construction of DataFusion logical plans.
+/// Since constructing `ExecutionPlan`s from logical expressions does not automatically apply type coercion,
+/// you may need to handle type coercion manually in these cases.
+///
+/// The codes in this function shows various ways to perform type coercion on expressions:
+/// 1. Using `SessionContext::create_physical_expr`
+/// 2. Using `ExprSimplifier::coerce`
+/// 3. Using `TreeNodeRewriter::rewrite` based on `TypeCoercionRewriter`
+/// 4. Using `TreeNode::transform`
+///
+/// Note, this list may not be complete and there may be other methods to apply type coercion to expressions.
+fn type_coercion_demo() -> Result<()> {
+    // Creates a record batch for demo.
+    let df_schema = DFSchema::from_unqualified_fields(
+        vec![Field::new("a", DataType::Int8, false)].into(),
+        HashMap::new(),
+    )?;
+    let i8_array = Int8Array::from_iter_values(vec![0, 1, 2]);
+    let batch = RecordBatch::try_new(
+        Arc::new(df_schema.as_arrow().to_owned()),
+        vec![Arc::new(i8_array) as _],
+    )?;
+
+    // Constructs a binary expression for demo.
+    // By default, the literal `1` is translated into the Int32 type and cannot be directly compared with the Int8 type.
+    let expr = col("a").gt(lit(1));
+
+    // Evaluation with an expression that has not been type coerced cannot succeed.
+    let props = ExecutionProps::default();
+    let physical_expr =
+        datafusion_physical_expr::create_physical_expr(&expr, &df_schema, &props)?;
+    let e = physical_expr.evaluate(&batch).unwrap_err();
+    assert!(e
+        .find_root()
+        .to_string()
+        .contains("Invalid comparison operation: Int8 > Int32"));
+
+    // 1. Type coercion with `SessionContext::create_physical_expr` which implicitly applies type coercion before constructing the physical expr.
+    let physical_expr =
+        SessionContext::new().create_physical_expr(expr.clone(), &df_schema)?;
+    assert!(physical_expr.evaluate(&batch).is_ok());
+
+    // 2. Type coercion with `ExprSimplifier::coerce`.
+    let context = SimplifyContext::new(&props).with_schema(Arc::new(df_schema.clone()));
+    let simplifier = ExprSimplifier::new(context);
+    let coerced_expr = simplifier.coerce(expr.clone(), &df_schema)?;
+    let physical_expr = datafusion_physical_expr::create_physical_expr(
+        &coerced_expr,
+        &df_schema,
+        &props,
+    )?;
+    assert!(physical_expr.evaluate(&batch).is_ok());
+
+    // 3. Type coercion with `TypeCoercionRewriter`.
+    let coerced_expr = expr
+        .clone()
+        .rewrite(&mut TypeCoercionRewriter::new(&df_schema))?
+        .data;
+    let physical_expr = datafusion_physical_expr::create_physical_expr(
+        &coerced_expr,
+        &df_schema,
+        &props,
+    )?;
+    assert!(physical_expr.evaluate(&batch).is_ok());
+
+    // 4. Apply explict type coercion by manually rewriting the expression
+    let coerced_expr = expr
+        .transform(|e| {
+            // Only type coerces binary expressions.
+            let Expr::BinaryExpr(e) = e else {
+                return Ok(Transformed::no(e));
+            };
+            if let Expr::Column(ref col_expr) = *e.left {
+                let field = df_schema.field_with_name(None, col_expr.name())?;
+                let cast_to_type = field.data_type();
+                let coerced_right = e.right.cast_to(cast_to_type, &df_schema)?;
+                Ok(Transformed::yes(Expr::BinaryExpr(BinaryExpr::new(
+                    e.left,
+                    e.op,
+                    Box::new(coerced_right),
+                ))))
+            } else {
+                Ok(Transformed::no(Expr::BinaryExpr(e)))
+            }
+        })?
+        .data;
+    let physical_expr = datafusion_physical_expr::create_physical_expr(
+        &coerced_expr,
+        &df_schema,
+        &props,
+    )?;
+    assert!(physical_expr.evaluate(&batch).is_ok());
+
+    Ok(())
+}
diff --git a/datafusion/optimizer/src/analyzer/type_coercion.rs b/datafusion/optimizer/src/analyzer/type_coercion.rs
index 9793c4c5490f3..b56c2dc604a9b 100644
--- a/datafusion/optimizer/src/analyzer/type_coercion.rs
+++ b/datafusion/optimizer/src/analyzer/type_coercion.rs
@@ -158,7 +158,7 @@ pub struct TypeCoercionRewriter<'a> {
 impl<'a> TypeCoercionRewriter<'a> {
     /// Create a new [`TypeCoercionRewriter`] with a provided schema
     /// representing both the inputs and output of the [`LogicalPlan`] node.
-    fn new(schema: &'a DFSchema) -> Self {
+    pub fn new(schema: &'a DFSchema) -> Self {
         Self { schema }
     }
 
diff --git a/datafusion/sql/README.md b/datafusion/sql/README.md
index 02ed1ae1f58be..98f3c4faa2ec0 100644
--- a/datafusion/sql/README.md
+++ b/datafusion/sql/README.md
@@ -52,8 +52,8 @@ fn main() {
     let statement = &ast[0];
 
     // create a logical query plan
-    let schema_provider = MySchemaProvider::new();
-    let sql_to_rel = SqlToRel::new(&schema_provider);
+    let context_provider = MyContextProvider::new();
+    let sql_to_rel = SqlToRel::new(&context_provider);
     let plan = sql_to_rel.sql_statement_to_plan(statement.clone()).unwrap();
 
     // show the plan