[GitHub] [arrow-datafusion] alamb commented on a diff in pull request #5961: add an example of using DataFrame to create a subquery

["alamb (via GitHub)" <gi...@apache.org>]

alamb commented on code in PR #5961:
URL: https://github.com/apache/arrow-datafusion/pull/5961#discussion_r1163337939


##########
datafusion-examples/examples/dataframe_subquery.rs:
##########
@@ -0,0 +1,129 @@
+// 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 std::sync::Arc;
+
+use datafusion::error::Result;
+use datafusion::prelude::*;
+use datafusion::test_util::arrow_test_data;
+use datafusion_common::ScalarValue;
+use datafusion_expr::Subquery;
+
+/// This example demonstrates how to use the DataFrame API to create a subquery.
+#[tokio::main]
+async fn main() -> Result<()> {
+    let ctx = SessionContext::new();
+    register_aggregate_test_data("t1", &ctx).await?;
+    register_aggregate_test_data("t2", &ctx).await?;
+
+    where_scalar_subquery(&ctx).await?;
+
+    where_in_subquery(&ctx).await?;
+
+    where_exist_subquery(&ctx).await?;
+
+    Ok(())
+}
+
+//select c1,c2 from t1 where (select avg(t2.c2) from t2 where t1.c1 = t2.c1)>0 limit 10;
+async fn where_scalar_subquery(ctx: &SessionContext) -> Result<()> {
+    ctx.table("t1")
+        .await?
+        .filter(
+            Expr::ScalarSubquery(datafusion_expr::Subquery {

Review Comment:
   I agree this is 🤮  -- let me see if I can come up with some way to make this easier to construct



##########
datafusion-examples/examples/dataframe_subquery.rs:
##########
@@ -0,0 +1,129 @@
+// 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 std::sync::Arc;
+
+use datafusion::error::Result;
+use datafusion::prelude::*;
+use datafusion::test_util::arrow_test_data;
+use datafusion_common::ScalarValue;
+use datafusion_expr::Subquery;
+
+/// This example demonstrates how to use the DataFrame API to create a subquery.
+#[tokio::main]
+async fn main() -> Result<()> {
+    let ctx = SessionContext::new();
+    register_aggregate_test_data("t1", &ctx).await?;
+    register_aggregate_test_data("t2", &ctx).await?;
+
+    where_scalar_subquery(&ctx).await?;
+
+    where_in_subquery(&ctx).await?;
+
+    where_exist_subquery(&ctx).await?;
+
+    Ok(())
+}
+
+//select c1,c2 from t1 where (select avg(t2.c2) from t2 where t1.c1 = t2.c1)>0 limit 10;
+async fn where_scalar_subquery(ctx: &SessionContext) -> Result<()> {
+    ctx.table("t1")
+        .await?
+        .filter(
+            Expr::ScalarSubquery(datafusion_expr::Subquery {
+                subquery: Arc::new(
+                    ctx.table("t2")
+                        .await?
+                        .filter(col("t1.c1").eq(col("t2.c1")))?
+                        .aggregate(vec![], vec![avg(col("t2.c2"))])?
+                        .select(vec![avg(col("t2.c2"))])?
+                        .into_unoptimized_plan(),
+                ),
+                outer_ref_columns: vec![],
+            })
+            .gt(lit(ScalarValue::UInt8(Some(0)))),

Review Comment:
   ```suggestion
               .gt(lit(0u8)),
   ```



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