Add example of dataframe API aggregations

datafusion-examples/examples/csv_compressed.rs

@@ -0,0 +1,56 @@
+// 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.
+
+use datafusion::datasource::file_format::file_compression_type::FileCompressionType;
+use datafusion::error::Result;
+use datafusion::prelude::*;
+
+/// This example demonstrates executing a simple query against a compressed CSV file
+#[tokio::main]
+async fn main() -> Result<()> {
+    // create local execution context
+    let ctx = SessionContext::new();
+
+    let testdata = datafusion::test_util::arrow_test_data();
+
+    // register csv file with the execution context
+    ctx.register_csv(
+        "aggregate_test_100",
+        &format!("{testdata}/csv/aggregate_test_100.csv"),
+        CsvReadOptions::new(),
+    )
+    .await?;
+
+    // query compressed CSV with specific options
+    let csv_options = CsvReadOptions::default()
+        .has_header(true)
+        .file_compression_type(FileCompressionType::GZIP)
+        .file_extension("csv.gz");
+    let df = ctx
+        .read_csv(
+            &format!("{testdata}/csv/aggregate_test_100.csv.gz"),
+            csv_options,
+        )
+        .await?;
+    let df = df
+        .filter(col("c1").eq(lit("a")))?
+        .select_columns(&["c2", "c3"])?;
+
+    df.show().await?;
+
+    Ok(())
+}

datafusion-examples/examples/csv_dataframe.rs

@@ -0,0 +1,48 @@
+// 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.
+
+use datafusion::error::Result;
+use datafusion::functions_aggregate::count::count;
+use datafusion::prelude::*;
+
+/// This example demonstrates executing a DataFrame operation against an Arrow data source (CSV) and
+/// fetching results. See `csv_sql.rs` for a SQL version of this example.
+#[tokio::main]
+async fn main() -> Result<()> {
+    // create local execution context
+    let ctx = SessionContext::new();
+
+    let testdata = datafusion::test_util::arrow_test_data();
+
+    // execute the query
+    let df = ctx
+        .read_csv(
+            &format!("{testdata}/csv/aggregate_test_100.csv"),
+            CsvReadOptions::new(),
+        )
+        .await?
+        .filter(col("c11").gt(lit(0.1)).and(col("c11").lt(lit(0.9))))?
+        .aggregate(
+            vec![col("c1")],
+            vec![min(col("c12")), max(col("c12")), count(wildcard())],
+        )?;
+
+    // print the results
+    df.show().await?;
+
+    Ok(())
+}

datafusion-examples/examples/csv_sql.rs

@@ -15,12 +15,11 @@
 // specific language governing permissions and limitations
 // under the License.
 
-use datafusion::datasource::file_format::file_compression_type::FileCompressionType;
 use datafusion::error::Result;
 use datafusion::prelude::*;
 
 /// This example demonstrates executing a simple query against an Arrow data source (CSV) and
-/// fetching results
+/// fetching results. See `csv_dataframe.rs` for a DataFrame version of this example.
 #[tokio::main]
 async fn main() -> Result<()> {
     // create local execution context
@@ -39,7 +38,7 @@ async fn main() -> Result<()> {
     // execute the query
     let df = ctx
         .sql(
-            "SELECT c1, MIN(c12), MAX(c12) \
+            "SELECT c1, MIN(c12), MAX(c12), COUNT(*) \
         FROM aggregate_test_100 \
         WHERE c11 > 0.1 AND c11 < 0.9 \
         GROUP BY c1",
@@ -49,22 +48,5 @@ async fn main() -> Result<()> {
     // print the results
     df.show().await?;
 
-    // query compressed CSV with specific options
-    let csv_options = CsvReadOptions::default()
-        .has_header(true)
-        .file_compression_type(FileCompressionType::GZIP)
-        .file_extension("csv.gz");
-    let df = ctx
-        .read_csv(
-            &format!("{testdata}/csv/aggregate_test_100.csv.gz"),
-            csv_options,
-        )
-        .await?;
-    let df = df
-        .filter(col("c1").eq(lit("a")))?
-        .select_columns(&["c2", "c3"])?;
-
-    df.show().await?;
-
     Ok(())
 }