alamb commented on code in PR #15353:
URL: https://github.com/apache/datafusion/pull/15353#discussion_r2008792240
##########
docs/source/library-user-guide/adding-udfs.md:
##########
@@ -1160,6 +1160,89 @@ async fn main() -> Result<()> {
// +---+
```
+## Custom Expression Planning
+
+DataFusion provides native support for a limited set of SQL operators by
default. For operators not natively defined, developers can extend DataFusion's
functionality by implementing custom expression planning. This extensibility is
a core feature of DataFusion, allowing it to be customized for particular
workloads and requirements.
+
+### Implementing Custom Expression Planning
+
+To extend DataFusion with support for custom operators not natively available,
you need to:
+
+1. Implement the `ExprPlanner` trait: This allows you to define custom logic
for planning expressions that DataFusion doesn't natively recognize. The trait
provides the necessary interface to translate logical expressions into physical
execution plans.
+
+ For a detailed documentation please see: [Trait
ExprPlanner](https://docs.rs/datafusion/latest/datafusion/logical_expr/planner/trait.ExprPlanner.html)
+
+2. Register your custom planner: Integrate your implementation with
DataFusion's `SessionContext` to ensure your custom planning logic is invoked
during the query optimization and execution planning phase.
+
+ For a detailed documentation please see: [fn
register_expr_planner](https://docs.rs/datafusion/latest/datafusion/execution/trait.FunctionRegistry.html#method.register_expr_planner)
Review Comment:
```suggestion
For a detailed documentation see: [fn
register_expr_planner](https://docs.rs/datafusion/latest/datafusion/execution/trait.FunctionRegistry.html#method.register_expr_planner)
```
##########
docs/source/library-user-guide/adding-udfs.md:
##########
@@ -1160,6 +1160,89 @@ async fn main() -> Result<()> {
// +---+
```
+## Custom Expression Planning
+
+DataFusion provides native support for a limited set of SQL operators by
default. For operators not natively defined, developers can extend DataFusion's
functionality by implementing custom expression planning. This extensibility is
a core feature of DataFusion, allowing it to be customized for particular
workloads and requirements.
+
+### Implementing Custom Expression Planning
+
+To extend DataFusion with support for custom operators not natively available,
you need to:
+
+1. Implement the `ExprPlanner` trait: This allows you to define custom logic
for planning expressions that DataFusion doesn't natively recognize. The trait
provides the necessary interface to translate logical expressions into physical
execution plans.
+
+ For a detailed documentation please see: [Trait
ExprPlanner](https://docs.rs/datafusion/latest/datafusion/logical_expr/planner/trait.ExprPlanner.html)
+
+2. Register your custom planner: Integrate your implementation with
DataFusion's `SessionContext` to ensure your custom planning logic is invoked
during the query optimization and execution planning phase.
+
+ For a detailed documentation please see: [fn
register_expr_planner](https://docs.rs/datafusion/latest/datafusion/execution/trait.FunctionRegistry.html#method.register_expr_planner)
+
+See example below:
+
+```rust
+# use arrow::array::RecordBatch;
+# use std::sync::Arc;
+
+# use datafusion::common::{assert_batches_eq, DFSchema};
+# use datafusion::error::Result;
+# use datafusion::execution::FunctionRegistry;
+# use datafusion::logical_expr::Operator;
+# use datafusion::prelude::*;
+# use datafusion::sql::sqlparser::ast::BinaryOperator;
+# use datafusion_common::ScalarValue;
+# use datafusion_expr::expr::Alias;
+# use datafusion_expr::planner::{ExprPlanner, PlannerResult, RawBinaryExpr};
+# use datafusion_expr::BinaryExpr;
+
+# #[derive(Debug)]
+# // Define the custom planner
+# struct MyCustomPlanner;
+
+// Implement ExprPlanner for cutom operator logic
+impl ExprPlanner for MyCustomPlanner {
+ fn plan_binary_op(
+ &self,
+ expr: RawBinaryExpr,
+ _schema: &DFSchema,
+ ) -> Result<PlannerResult<RawBinaryExpr>> {
+ match &expr.op {
+ // Map `->` to string concatenation
+ BinaryOperator::Arrow => {
+ // Rewrite `->` as a string concatenation operation
+ // - `left` and `right` are the operands (e.g., 'hello' and
'world')
+ // - `Operator::StringConcat` tells DataFusion to concatenate
them
+ Ok(PlannerResult::Planned(Expr::BinaryExpr(BinaryExpr {
+ left: Box::new(expr.left.clone()),
+ right: Box::new(expr.right.clone()),
+ op: Operator::StringConcat,
+ })))
+ }
+ _ => Ok(PlannerResult::Original(expr)),
+ }
+ }
+}
+
+use datafusion::execution::context::SessionContext;
+use datafusion::arrow::util::pretty;
+
+#[tokio::main]
+async fn main() -> Result<()> {
+ let config = SessionConfig::new().set_str("datafusion.sql_parser.dialect",
"postgres");
+ let mut ctx = SessionContext::new_with_config(config);
+ ctx.register_expr_planner(Arc::new(MyCustomPlanner))?;
+ let results = ctx.sql("select 'foo'->'bar';").await?.collect().await?;
+
+ pretty::print_batches(&results)?;
Review Comment:
Could you please change this to use `assert_batches_eq! so the actual
output is in the test and it is tested in CI
##########
docs/source/library-user-guide/adding-udfs.md:
##########
@@ -1160,6 +1160,89 @@ async fn main() -> Result<()> {
// +---+
```
+## Custom Expression Planning
+
+DataFusion provides native support for a limited set of SQL operators by
default. For operators not natively defined, developers can extend DataFusion's
functionality by implementing custom expression planning. This extensibility is
a core feature of DataFusion, allowing it to be customized for particular
workloads and requirements.
+
+### Implementing Custom Expression Planning
+
+To extend DataFusion with support for custom operators not natively available,
you need to:
+
+1. Implement the `ExprPlanner` trait: This allows you to define custom logic
for planning expressions that DataFusion doesn't natively recognize. The trait
provides the necessary interface to translate logical expressions into physical
execution plans.
+
+ For a detailed documentation please see: [Trait
ExprPlanner](https://docs.rs/datafusion/latest/datafusion/logical_expr/planner/trait.ExprPlanner.html)
Review Comment:
```suggestion
For detailed documentation please see: [Trait
ExprPlanner](https://docs.rs/datafusion/latest/datafusion/logical_expr/planner/trait.ExprPlanner.html)
```
##########
docs/source/library-user-guide/adding-udfs.md:
##########
@@ -1160,6 +1160,89 @@ async fn main() -> Result<()> {
// +---+
```
+## Custom Expression Planning
+
+DataFusion provides native support for a limited set of SQL operators by
default. For operators not natively defined, developers can extend DataFusion's
functionality by implementing custom expression planning. This extensibility is
a core feature of DataFusion, allowing it to be customized for particular
workloads and requirements.
Review Comment:
Here are some wordsmithing suggestions:
```suggestion
DataFusion provides native support for common SQL operators by default such
as `+`, `-`, `||`. However it does not provide support for other operators such
as `@>`. To override DataFusion's default handling or support unsupported
operators, developers can extend DataFusion by implementing custom expression
planning, a core feature of DataFusion
```
##########
docs/source/library-user-guide/adding-udfs.md:
##########
@@ -1160,6 +1160,89 @@ async fn main() -> Result<()> {
// +---+
```
+## Custom Expression Planning
+
+DataFusion provides native support for a limited set of SQL operators by
default. For operators not natively defined, developers can extend DataFusion's
functionality by implementing custom expression planning. This extensibility is
a core feature of DataFusion, allowing it to be customized for particular
workloads and requirements.
+
+### Implementing Custom Expression Planning
+
+To extend DataFusion with support for custom operators not natively available,
you need to:
+
+1. Implement the `ExprPlanner` trait: This allows you to define custom logic
for planning expressions that DataFusion doesn't natively recognize. The trait
provides the necessary interface to translate logical expressions into physical
execution plans.
Review Comment:
I think ExprPlanner actually converts the SQL AST to `Expr`s:
```suggestion
1. Implement the `ExprPlanner` trait: This allows you to define custom logic
for planning expressions that DataFusion doesn't natively recognize. The trait
provides the necessary interface to translate SQL AST nodes into logical `Expr`.
```
##########
docs/source/library-user-guide/adding-udfs.md:
##########
@@ -1160,6 +1160,89 @@ async fn main() -> Result<()> {
// +---+
```
+## Custom Expression Planning
+
+DataFusion provides native support for a limited set of SQL operators by
default. For operators not natively defined, developers can extend DataFusion's
functionality by implementing custom expression planning. This extensibility is
a core feature of DataFusion, allowing it to be customized for particular
workloads and requirements.
+
+### Implementing Custom Expression Planning
+
+To extend DataFusion with support for custom operators not natively available,
you need to:
+
+1. Implement the `ExprPlanner` trait: This allows you to define custom logic
for planning expressions that DataFusion doesn't natively recognize. The trait
provides the necessary interface to translate logical expressions into physical
execution plans.
+
+ For a detailed documentation please see: [Trait
ExprPlanner](https://docs.rs/datafusion/latest/datafusion/logical_expr/planner/trait.ExprPlanner.html)
+
+2. Register your custom planner: Integrate your implementation with
DataFusion's `SessionContext` to ensure your custom planning logic is invoked
during the query optimization and execution planning phase.
+
+ For a detailed documentation please see: [fn
register_expr_planner](https://docs.rs/datafusion/latest/datafusion/execution/trait.FunctionRegistry.html#method.register_expr_planner)
+
+See example below:
+
+```rust
+# use arrow::array::RecordBatch;
+# use std::sync::Arc;
+
+# use datafusion::common::{assert_batches_eq, DFSchema};
+# use datafusion::error::Result;
+# use datafusion::execution::FunctionRegistry;
+# use datafusion::logical_expr::Operator;
+# use datafusion::prelude::*;
+# use datafusion::sql::sqlparser::ast::BinaryOperator;
+# use datafusion_common::ScalarValue;
+# use datafusion_expr::expr::Alias;
+# use datafusion_expr::planner::{ExprPlanner, PlannerResult, RawBinaryExpr};
+# use datafusion_expr::BinaryExpr;
+
+# #[derive(Debug)]
+# // Define the custom planner
+# struct MyCustomPlanner;
+
+// Implement ExprPlanner for cutom operator logic
Review Comment:
```suggestion
// Implement ExprPlanner to add support for the `->` custom operator
```
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