Consolidate udf examples (#18142) (#18493)

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- part of ##18142.

## Rationale for this change
This PR is for consolidating all the `udf` examples into a single
example binary. We are agreed on the pattern and we can apply it to the
remaining examples
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---------

Co-authored-by: Sergey Zhukov <[email protected]>

Author: cj-zhukov

datafusion-examples/README.md

@@ -46,11 +46,11 @@ cargo run --example dataframe
 
 ## Single Process
 
-- [`advanced_udaf.rs`](examples/advanced_udaf.rs): Define and invoke a more complicated User Defined Aggregate Function (UDAF)
-- [`advanced_udf.rs`](examples/advanced_udf.rs): Define and invoke a more complicated User Defined Scalar Function (UDF)
-- [`advanced_udwf.rs`](examples/advanced_udwf.rs): Define and invoke a more complicated User Defined Window Function (UDWF)
+- [`examples/udf/advanced_udaf.rs`](examples/udf/advanced_udaf.rs): Define and invoke a more complicated User Defined Aggregate Function (UDAF)
+- [`examples/udf/advanced_udf.rs`](examples/udf/advanced_udf.rs): Define and invoke a more complicated User Defined Scalar Function (UDF)
+- [`examples/udf/advanced_udwf.rs`](examples/udf/advanced_udwf.rs): Define and invoke a more complicated User Defined Window Function (UDWF)
 - [`advanced_parquet_index.rs`](examples/advanced_parquet_index.rs): Creates a detailed secondary index that covers the contents of several parquet files
-- [`async_udf.rs`](examples/async_udf.rs): Define and invoke an asynchronous User Defined Scalar Function (UDF)
+- [`examples/udf/async_udf.rs`](examples/udf/async_udf.rs): Define and invoke an asynchronous User Defined Scalar Function (UDF)
 - [`analyzer_rule.rs`](examples/analyzer_rule.rs): Use a custom AnalyzerRule to change a query's semantics (row level access control)
 - [`catalog.rs`](examples/catalog.rs): Register the table into a custom catalog
 - [`composed_extension_codec`](examples/composed_extension_codec.rs): Example of using multiple extension codecs for serialization / deserialization
@@ -83,9 +83,10 @@ cargo run --example dataframe
 - [`query-http-csv.rs`](examples/query-http-csv.rs): Configure `object_store` and run a query against files vi HTTP
 - [`regexp.rs`](examples/regexp.rs): Examples of using regular expression functions
 - [`remote_catalog.rs`](examples/regexp.rs): Examples of interfacing with a remote catalog (e.g. over a network)
-- [`simple_udaf.rs`](examples/simple_udaf.rs): Define and invoke a User Defined Aggregate Function (UDAF)
-- [`simple_udf.rs`](examples/simple_udf.rs): Define and invoke a User Defined Scalar Function (UDF)
-- [`simple_udfw.rs`](examples/simple_udwf.rs): Define and invoke a User Defined Window Function (UDWF)
+- [`examples/udf/simple_udaf.rs`](examples/udf/simple_udaf.rs): Define and invoke a User Defined Aggregate Function (UDAF)
+- [`examples/udf/simple_udf.rs`](examples/udf/simple_udf.rs): Define and invoke a User Defined Scalar Function (UDF)
+- [`examples/udf/simple_udtf.rs`](examples/udf/simple_udtf.rs): Define and invoke a User Defined Table Function (UDTF)
+- [`examples/udf/simple_udfw.rs`](examples/udf/simple_udwf.rs): Define and invoke a User Defined Window Function (UDWF)
 - [`sql_analysis.rs`](examples/sql_analysis.rs): Analyse SQL queries with DataFusion structures
 - [`sql_frontend.rs`](examples/sql_frontend.rs): Create LogicalPlans (only) from sql strings
 - [`sql_dialect.rs`](examples/sql_dialect.rs): Example of implementing a custom SQL dialect on top of `DFParser`

datafusion-examples/examples/advanced_udaf.rs renamed to datafusion-examples/examples/udf/advanced_udaf.rs

@@ -469,8 +469,9 @@ fn create_context() -> Result<SessionContext> {
     Ok(ctx)
 }
 
-#[tokio::main]
-async fn main() -> Result<()> {
+/// In this example we register `GeoMeanUdaf` and `SimplifiedGeoMeanUdaf`
+/// as user defined aggregate functions and invoke them via the DataFrame API and SQL
+pub async fn advanced_udaf() -> Result<()> {
     let ctx = create_context()?;
 
     let geo_mean_udf = AggregateUDF::from(GeoMeanUdaf::new());

datafusion-examples/examples/advanced_udf.rs renamed to datafusion-examples/examples/udf/advanced_udf.rs

@@ -245,10 +245,35 @@ fn maybe_pow_in_place(base: f64, exp_array: ArrayRef) -> Result<ArrayRef> {
     }
 }
 
+/// create local execution context with an in-memory table:
+///
+/// ```text
+/// +-----+-----+
+/// | a   | b   |
+/// +-----+-----+
+/// | 2.1 | 1.0 |
+/// | 3.1 | 2.0 |
+/// | 4.1 | 3.0 |
+/// | 5.1 | 4.0 |
+/// +-----+-----+
+/// ```
+fn create_context() -> Result<SessionContext> {
+    // define data.
+    let a: ArrayRef = Arc::new(Float32Array::from(vec![2.1, 3.1, 4.1, 5.1]));
+    let b: ArrayRef = Arc::new(Float64Array::from(vec![1.0, 2.0, 3.0, 4.0]));
+    let batch = RecordBatch::try_from_iter(vec![("a", a), ("b", b)])?;
+
+    // declare a new context. In Spark API, this corresponds to a new SparkSession
+    let ctx = SessionContext::new();
+
+    // declare a table in memory. In Spark API, this corresponds to createDataFrame(...).
+    ctx.register_batch("t", batch)?;
+    Ok(ctx)
+}
+
 /// In this example we register `PowUdf` as a user defined function
 /// and invoke it via the DataFrame API and SQL
-#[tokio::main]
-async fn main() -> Result<()> {
+pub async fn advanced_udf() -> Result<()> {
     let ctx = create_context()?;
 
     // create the UDF
@@ -295,29 +320,3 @@ async fn main() -> Result<()> {
 
     Ok(())
 }
-
-/// create local execution context with an in-memory table:
-///
-/// ```text
-/// +-----+-----+
-/// | a   | b   |
-/// +-----+-----+
-/// | 2.1 | 1.0 |
-/// | 3.1 | 2.0 |
-/// | 4.1 | 3.0 |
-/// | 5.1 | 4.0 |
-/// +-----+-----+
-/// ```
-fn create_context() -> Result<SessionContext> {
-    // define data.
-    let a: ArrayRef = Arc::new(Float32Array::from(vec![2.1, 3.1, 4.1, 5.1]));
-    let b: ArrayRef = Arc::new(Float64Array::from(vec![1.0, 2.0, 3.0, 4.0]));
-    let batch = RecordBatch::try_from_iter(vec![("a", a), ("b", b)])?;
-
-    // declare a new context. In Spark API, this corresponds to a new SparkSession
-    let ctx = SessionContext::new();
-
-    // declare a table in memory. In Spark API, this corresponds to createDataFrame(...).
-    ctx.register_batch("t", batch)?;
-    Ok(ctx)
-}

datafusion-examples/examples/advanced_udwf.rs renamed to datafusion-examples/examples/udf/advanced_udwf.rs

@@ -236,8 +236,9 @@ async fn create_context() -> Result<SessionContext> {
     Ok(ctx)
 }
 
-#[tokio::main]
-async fn main() -> Result<()> {
+/// In this example we register `SmoothItUdf` as user defined window function
+/// and invoke it via the DataFrame API and SQL
+pub async fn advanced_udwf() -> Result<()> {
     let ctx = create_context().await?;
     let smooth_it = WindowUDF::from(SmoothItUdf::new());
     ctx.register_udwf(smooth_it.clone());

datafusion-examples/examples/async_udf.rs renamed to datafusion-examples/examples/udf/async_udf.rs

@@ -38,8 +38,9 @@ use datafusion::prelude::{SessionConfig, SessionContext};
 use std::any::Any;
 use std::sync::Arc;
 
-#[tokio::main]
-async fn main() -> Result<()> {
+/// In this example we register `AskLLM` as an asynchronous user defined function
+/// and invoke it via the DataFrame API and SQL
+pub async fn async_udf() -> Result<()> {
     // Use a hard coded parallelism level of 4 so the explain plan
     // is consistent across machines.
     let config = SessionConfig::new().with_target_partitions(4);

datafusion-examples/examples/udf/main.rs

@@ -0,0 +1,133 @@
+// 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.
+
+//! # User-Defined Functions Examples
+//!
+//! These examples demonstrate user-defined functions in DataFusion.
+//!
+//! Each subcommand runs a corresponding example:
+//! - `adv_udaf` — user defined aggregate function example
+//! - `adv_udf` — user defined scalar function example
+//! - `adv_udwf` — user defined window function example
+//! - `async_udf` — asynchronous user defined function example
+//! - `udaf` — simple user defined aggregate function example
+//! - `udf` — simple user defined scalar function example
+//! - `udtf` — simple user defined table function example
+//! - `udwf` — simple user defined window function example
+
+mod advanced_udaf;
+mod advanced_udf;
+mod advanced_udwf;
+mod async_udf;
+mod simple_udaf;
+mod simple_udf;
+mod simple_udtf;
+mod simple_udwf;
+
+use std::str::FromStr;
+
+use datafusion::error::{DataFusionError, Result};
+
+enum ExampleKind {
+    AdvUdaf,
+    AdvUdf,
+    AdvUdwf,
+    AsyncUdf,
+    Udf,
+    Udaf,
+    Udwf,
+    Udtf,
+}
+
+impl AsRef<str> for ExampleKind {
+    fn as_ref(&self) -> &str {
+        match self {
+            Self::AdvUdaf => "adv_udaf",
+            Self::AdvUdf => "adv_udf",
+            Self::AdvUdwf => "adv_udwf",
+            Self::AsyncUdf => "async_udf",
+            Self::Udf => "udf",
+            Self::Udaf => "udaf",
+            Self::Udwf => "udwt",
+            Self::Udtf => "udtf",
+        }
+    }
+}
+
+impl FromStr for ExampleKind {
+    type Err = DataFusionError;
+
+    fn from_str(s: &str) -> Result<Self> {
+        match s {
+            "adv_udaf" => Ok(Self::AdvUdaf),
+            "adv_udf" => Ok(Self::AdvUdf),
+            "adv_udwf" => Ok(Self::AdvUdwf),
+            "async_udf" => Ok(Self::AsyncUdf),
+            "udaf" => Ok(Self::Udaf),
+            "udf" => Ok(Self::Udf),
+            "udtf" => Ok(Self::Udtf),
+            "udwf" => Ok(Self::Udwf),
+            _ => Err(DataFusionError::Execution(format!("Unknown example: {s}"))),
+        }
+    }
+}
+
+impl ExampleKind {
+    const ALL: [Self; 8] = [
+        Self::AdvUdaf,
+        Self::AdvUdf,
+        Self::AdvUdwf,
+        Self::AsyncUdf,
+        Self::Udaf,
+        Self::Udf,
+        Self::Udtf,
+        Self::Udwf,
+    ];
+
+    const EXAMPLE_NAME: &str = "udf";
+
+    fn variants() -> Vec<&'static str> {
+        Self::ALL.iter().map(|x| x.as_ref()).collect()
+    }
+}
+
+#[tokio::main]
+async fn main() -> Result<()> {
+    let usage = format!(
+        "Usage: cargo run --example {} -- [{}]",
+        ExampleKind::EXAMPLE_NAME,
+        ExampleKind::variants().join("|")
+    );
+
+    let arg = std::env::args().nth(1).ok_or_else(|| {
+        eprintln!("{usage}");
+        DataFusionError::Execution("Missing argument".to_string())
+    })?;
+
+    match arg.parse::<ExampleKind>()? {
+        ExampleKind::AdvUdaf => advanced_udaf::advanced_udaf().await?,
+        ExampleKind::AdvUdf => advanced_udf::advanced_udf().await?,
+        ExampleKind::AdvUdwf => advanced_udwf::advanced_udwf().await?,
+        ExampleKind::AsyncUdf => async_udf::async_udf().await?,
+        ExampleKind::Udaf => simple_udaf::simple_udaf().await?,
+        ExampleKind::Udf => simple_udf::simple_udf().await?,
+        ExampleKind::Udtf => simple_udtf::simple_udtf().await?,
+        ExampleKind::Udwf => simple_udwf::simple_udwf().await?,
+    }
+
+    Ok(())
+}

datafusion-examples/examples/simple_udaf.rs renamed to datafusion-examples/examples/udf/simple_udaf.rs

@@ -135,8 +135,9 @@ impl Accumulator for GeometricMean {
     }
 }
 
-#[tokio::main]
-async fn main() -> Result<()> {
+/// In this example we register `GeometricMean`
+/// as user defined aggregate function and invoke it via the DataFrame API and SQL
+pub async fn simple_udaf() -> Result<()> {
     let ctx = create_context()?;
 
     // here is where we define the UDAF. We also declare its signature:

datafusion-examples/examples/simple_udf.rs renamed to datafusion-examples/examples/udf/simple_udf.rs

@@ -57,8 +57,7 @@ fn create_context() -> Result<SessionContext> {
 }
 
 /// In this example we will declare a single-type, single return type UDF that exponentiates f64, a^b
-#[tokio::main]
-async fn main() -> Result<()> {
+pub async fn simple_udf() -> Result<()> {
     let ctx = create_context()?;
 
     // First, declare the actual implementation of the calculation

datafusion-examples/examples/simple_udtf.rs renamed to datafusion-examples/examples/udf/simple_udtf.rs

@@ -42,8 +42,7 @@ use std::sync::Arc;
 // 3. Register the function using [`SessionContext::register_udtf`]
 
 /// This example demonstrates how to register a TableFunction
-#[tokio::main]
-async fn main() -> Result<()> {
+pub async fn simple_udtf() -> Result<()> {
     // create local execution context
     let ctx = SessionContext::new();
 

datafusion-examples/examples/simple_udwf.rs renamed to datafusion-examples/examples/udf/simple_udwf.rs

@@ -42,8 +42,7 @@ async fn create_context() -> Result<SessionContext> {
 }
 
 /// In this example we will declare a user defined window function that computes a moving average and then run it using SQL
-#[tokio::main]
-async fn main() -> Result<()> {
+pub async fn simple_udwf() -> Result<()> {
     let ctx = create_context().await?;
 
     // here is where we define the UDWF. We also declare its signature: