Nested Loop Joins (fixes TPCH query 22) (#104)

* allow nested_loop_joins

* check if plan can be divided into tasks

* moving function to more logical location

Author: robtandy

src/common/ttl_map.rs

@@ -27,7 +27,6 @@ use dashmap::{DashMap, Entry};
 use datafusion::error::DataFusionError;
 use std::collections::HashSet;
 use std::hash::Hash;
-use std::mem;
 use std::sync::atomic::AtomicU64;
 #[cfg(test)]
 use std::sync::atomic::{AtomicUsize, Ordering::Relaxed};
@@ -94,7 +93,7 @@ where
                     shard.insert(key);
                 }
                 BucketOp::Clear => {
-                    let keys_to_delete = mem::replace(&mut shard, HashSet::new());
+                    let keys_to_delete = std::mem::replace(&mut shard, HashSet::new());
                     for key in keys_to_delete {
                         data.remove(&key);
                     }

src/common/util.rs

@@ -1,7 +1,9 @@
+use datafusion::common::tree_node::{TreeNode, TreeNodeRecursion};
 use datafusion::error::Result;
 use datafusion::physical_plan::{displayable, ExecutionPlan, ExecutionPlanProperties};
 
 use std::fmt::Write;
+use std::sync::Arc;
 
 pub fn display_plan_with_partition_in_out(plan: &dyn ExecutionPlan) -> Result<String> {
     let mut f = String::new();

src/physical_optimizer.rs

@@ -83,12 +83,14 @@ impl DistributedPhysicalOptimizerRule {
                     internal_datafusion_err!("Expected RepartitionExec to have a child"),
                 )?);
 
-                let maybe_isolated_plan = if let Some(ppt) = self.partitions_per_task {
-                    let isolated = Arc::new(PartitionIsolatorExec::new(child, ppt));
-                    plan.with_new_children(vec![isolated])?
-                } else {
-                    plan
-                };
+                let maybe_isolated_plan =
+                    if can_be_divided(&plan)? && self.partitions_per_task.is_some() {
+                        let ppt = self.partitions_per_task.unwrap();
+                        let isolated = Arc::new(PartitionIsolatorExec::new(child, ppt));
+                        plan.with_new_children(vec![isolated])?
+                    } else {
+                        plan
+                    };
 
                 return Ok(Transformed::yes(Arc::new(
                     ArrowFlightReadExec::new_pending(
@@ -120,7 +122,7 @@ impl DistributedPhysicalOptimizerRule {
     ) -> Result<ExecutionStage, DataFusionError> {
         let mut inputs = vec![];
 
-        let distributed = plan.transform_down(|plan| {
+        let distributed = plan.clone().transform_down(|plan| {
             let Some(node) = plan.as_any().downcast_ref::<ArrowFlightReadExec>() else {
                 return Ok(Transformed::no(plan));
             };
@@ -137,15 +139,45 @@ impl DistributedPhysicalOptimizerRule {
         let mut stage = ExecutionStage::new(query_id, *num, distributed.data, inputs);
         *num += 1;
 
-        if let Some(partitions_per_task) = self.partitions_per_task {
-            stage = stage.with_maximum_partitions_per_task(partitions_per_task);
-        }
+        stage = match (self.partitions_per_task, can_be_divided(&plan)?) {
+            (Some(partitions_per_task), true) => {
+                stage.with_maximum_partitions_per_task(partitions_per_task)
+            }
+            (_, _) => stage,
+        };
+
         stage.depth = depth;
 
         Ok(stage)
     }
 }
 
+/// Returns a boolean indicating if this stage can be divided into more than one task.
+///
+/// Some Plan nodes need to materialize all partitions inorder to execute such as
+/// NestedLoopJoinExec.   Rewriting the plan to accommodate dividing it into tasks
+/// would result in redundant work.
+///
+/// The plans we cannot split are:
+/// - NestedLoopJoinExec
+pub fn can_be_divided(plan: &Arc<dyn ExecutionPlan>) -> Result<bool> {
+    // recursively check to see if this stages plan contains a NestedLoopJoinExec
+    let mut has_unsplittable_plan = false;
+    let search = |f: &Arc<dyn ExecutionPlan>| {
+        if f.as_any()
+            .downcast_ref::<datafusion::physical_plan::joins::NestedLoopJoinExec>()
+            .is_some()
+        {
+            has_unsplittable_plan = true;
+            return Ok(TreeNodeRecursion::Stop);
+        }
+
+        Ok(TreeNodeRecursion::Continue)
+    };
+    plan.apply(search)?;
+    Ok(!has_unsplittable_plan)
+}
+
 #[cfg(test)]
 mod tests {
     use crate::assert_snapshot;

src/test_utils/tpch.rs

@@ -160,13 +160,18 @@ where
 
 macro_rules! must_generate_tpch_table {
     ($generator:ident, $arrow:ident, $name:literal, $data_dir:expr) => {
-        generate_table(
-            // TODO: Consider adjusting the partitions and batch sizes.
-            $arrow::new($generator::new(SCALE_FACTOR, 1, 1)).with_batch_size(1000),
-            $name,
-            $data_dir,
-        )
-        .expect(concat!("Failed to generate ", $name, " table"));
+        let data_dir = $data_dir.join(format!("{}.parquet", $name));
+        fs::create_dir_all(data_dir.clone()).expect("Failed to create data directory");
+        // create three partitions for the table
+        (1..=3).for_each(|part| {
+            generate_table(
+                // TODO: Consider adjusting the partitions and batch sizes.
+                $arrow::new($generator::new(SCALE_FACTOR, part, 3)).with_batch_size(1000),
+                &format!("{}.parquet", part),
+                &data_dir.clone().into_boxed_path(),
+            )
+            .expect(concat!("Failed to generate ", $name, " table"));
+        });
     };
 }
 

tests/non_distributed_consistency_test.rs renamed to tests/tpch_validation_test.rs

@@ -6,6 +6,7 @@ mod tests {
     use async_trait::async_trait;
     use datafusion::error::DataFusionError;
     use datafusion::execution::SessionStateBuilder;
+
     use datafusion::prelude::{SessionConfig, SessionContext};
     use datafusion_distributed::test_utils::localhost::start_localhost_context;
     use datafusion_distributed::{DistributedPhysicalOptimizerRule, SessionBuilder};
@@ -119,8 +120,6 @@ mod tests {
     }
 
     #[tokio::test]
-    // TODO: Add support for NestedLoopJoinExec to support query 22.
-    #[ignore]
     async fn test_tpch_22() -> Result<(), Box<dyn Error>> {
         test_tpch_query(22).await
     }
@@ -155,7 +154,6 @@ mod tests {
 
             config.options_mut().optimizer.prefer_hash_join = true;
             // end critical options section
-
             let rule = DistributedPhysicalOptimizerRule::new().with_maximum_partitions_per_task(2);
             Ok(builder
                 .with_config(config)
@@ -174,7 +172,6 @@ mod tests {
     // and once in a non-distributed manner. For each query, it asserts that the results are identical.
     async fn run_tpch_query(ctx2: SessionContext, query_id: u8) -> Result<(), Box<dyn Error>> {
         ensure_tpch_data().await;
-
         let sql = get_test_tpch_query(query_id);
 
         // Context 1: Non-distributed execution.
@@ -205,19 +202,21 @@ mod tests {
             .await?;
         }
 
+        // Query 15 has three queries in it, one creating the view, the second
+        // executing, which we want to capture the output of, and the third
+        // tearing down the view
         let (stream1, stream2) = if query_id == 15 {
             let queries: Vec<&str> = sql
                 .split(';')
                 .map(str::trim)
                 .filter(|s| !s.is_empty())
                 .collect();
 
-            println!("queryies: {:?}", queries);
-
             ctx1.sql(queries[0]).await?.collect().await?;
             ctx2.sql(queries[0]).await?.collect().await?;
             let df1 = ctx1.sql(queries[1]).await?;
             let df2 = ctx2.sql(queries[1]).await?;
+
             let stream1 = df1.execute_stream().await?;
             let stream2 = df2.execute_stream().await?;
 
@@ -227,6 +226,7 @@ mod tests {
         } else {
             let stream1 = ctx1.sql(&sql).await?.execute_stream().await?;
             let stream2 = ctx2.sql(&sql).await?.execute_stream().await?;
+
             (stream1, stream2)
         };