Refactor coordinator module and ensure cache invalidation on coordinator->worker stream drop

Author: gabotechs

src/coordinator/distributed.rs

@@ -1,10 +1,10 @@
 use crate::common::{require_one_child, serialize_uuid};
 use crate::coordinator::metrics_store::MetricsStore;
 use crate::coordinator::prepare_static_plan::prepare_static_plan;
+use crate::coordinator::query_coordinator::QueryCoordinator;
 use crate::distributed_planner::NetworkBoundaryExt;
 use crate::worker::generated::worker::TaskKey;
 use datafusion::common::internal_datafusion_err;
-use datafusion::common::runtime::JoinSet;
 use datafusion::common::tree_node::{TreeNode, TreeNodeRecursion};
 use datafusion::common::{Result, exec_err};
 use datafusion::execution::{SendableRecordBatchStream, TaskContext};
@@ -14,8 +14,7 @@ use datafusion::physical_plan::stream::RecordBatchReceiverStreamBuilder;
 use datafusion::physical_plan::{DisplayAs, DisplayFormatType, ExecutionPlan, PlanProperties};
 use futures::StreamExt;
 use std::fmt::Formatter;
-use std::sync::Arc;
-use std::sync::Mutex;
+use std::sync::{Arc, Mutex};
 
 /// [ExecutionPlan] that executes the inner plan in distributed mode.
 /// Before executing it, two modifications are lazily performed on the plan:
@@ -26,22 +25,39 @@ use std::sync::Mutex;
 ///    over the wire.
 #[derive(Debug)]
 pub struct DistributedExec {
-    plan: Arc<dyn ExecutionPlan>,
-    prepared_plan: Arc<Mutex<Option<Arc<dyn ExecutionPlan>>>>,
+    /// Initial [ExecutionPlan] present before execution.
+    /// - If the plan was distributed statically, this will be the final distributed plan with all
+    ///   the appropriate network boundaries in it.
+    /// - If the plan is going to be distributed dynamically during execution, this is the initial
+    ///   non-distributed plan.
+    base_plan: Arc<dyn ExecutionPlan>,
+    /// Resulting [ExecutionPlan] after execution ready for visualization purposes.
+    /// - If the plan was distributed statically, this is equal to the base plan.
+    /// - If the plan is going to be distributed dynamically during execution, this is the resulting
+    ///   plan re-calculated based on runtime statistics.
+    plan_for_viz: Arc<Mutex<Option<Arc<dyn ExecutionPlan>>>>,
+    /// The head stage meant to be executed locally on [DistributedExec::execute].
+    head_stage: Arc<Mutex<Option<Arc<dyn ExecutionPlan>>>>,
+    /// DataFusion metrics.
     metrics: ExecutionPlanMetricsSet,
+    /// Storage where metrics collected from workers at runtime will place their results as they
+    /// finish their respective remote tasks.
     pub(crate) metrics_store: Option<Arc<MetricsStore>>,
 }
 
 pub(super) struct PreparedPlan {
+    /// The head stage meant to be executed locally by the coordinator.
     pub(super) head_stage: Arc<dyn ExecutionPlan>,
-    pub(super) join_set: JoinSet<Result<()>>,
+    /// A final representation of the plan for visualization purposes.
+    pub(super) plan_for_viz: Arc<dyn ExecutionPlan>,
 }
 
 impl DistributedExec {
-    pub fn new(plan: Arc<dyn ExecutionPlan>) -> Self {
+    pub fn new(base_plan: Arc<dyn ExecutionPlan>) -> Self {
         Self {
-            plan,
-            prepared_plan: Arc::new(Mutex::new(None)),
+            base_plan,
+            plan_for_viz: Arc::new(Mutex::new(None)),
+            head_stage: Arc::new(Mutex::new(None)),
             metrics: ExecutionPlanMetricsSet::new(),
             metrics_store: None,
         }
@@ -68,7 +84,10 @@ impl DistributedExec {
         let Some(task_metrics) = &self.metrics_store else {
             return;
         };
-        let _ = self.plan.apply(|plan| {
+        let Some(plan) = self.plan_for_viz.lock().unwrap().as_ref().cloned() else {
+            return;
+        };
+        let _ = plan.apply(|plan| {
             if let Some(boundary) = plan.as_network_boundary() {
                 let stage = boundary.input_stage();
                 for i in 0..stage.task_count() {
@@ -93,15 +112,27 @@ impl DistributedExec {
     /// Returns the plan which is lazily prepared on `execute()` and actually gets executed.
     /// It is updated on every call to `execute()`. Returns an error if `.execute()` has not been
     /// called.
-    pub(crate) fn prepared_plan(&self) -> Result<Arc<dyn ExecutionPlan>> {
-        self.prepared_plan
+    pub(crate) fn plan_for_viz(&self) -> Result<Arc<dyn ExecutionPlan>> {
+        self.plan_for_viz
             .lock()
             .map_err(|e| internal_datafusion_err!("Failed to lock prepared plan: {}", e))?
             .clone()
             .ok_or_else(|| {
                 internal_datafusion_err!("No prepared plan found. Was execute() called?")
             })
     }
+
+    /// Returns the head stage that was actually executed. Unlike [`Self::plan_for_viz`] (which is
+    /// reconstructed for visualization, with `Stage::Local` boundaries and rebuilt ancestor
+    /// `Arc`s), this returns the original `Arc` instances whose metrics were populated during
+    /// execution.
+    pub(crate) fn head_stage(&self) -> Result<Arc<dyn ExecutionPlan>> {
+        self.head_stage
+            .lock()
+            .map_err(|e| internal_datafusion_err!("Failed to lock head stage: {}", e))?
+            .clone()
+            .ok_or_else(|| internal_datafusion_err!("No head stage found. Was execute() called?"))
+    }
 }
 
 impl DisplayAs for DistributedExec {
@@ -116,20 +147,21 @@ impl ExecutionPlan for DistributedExec {
     }
 
     fn properties(&self) -> &Arc<PlanProperties> {
-        self.plan.properties()
+        self.base_plan.properties()
     }
 
     fn children(&self) -> Vec<&Arc<dyn ExecutionPlan>> {
-        vec![&self.plan]
+        vec![&self.base_plan]
     }
 
     fn with_new_children(
         self: Arc<Self>,
         children: Vec<Arc<dyn ExecutionPlan>>,
     ) -> Result<Arc<dyn ExecutionPlan>> {
         Ok(Arc::new(DistributedExec {
-            plan: require_one_child(&children)?,
-            prepared_plan: self.prepared_plan.clone(),
+            base_plan: require_one_child(&children)?,
+            plan_for_viz: Arc::new(Mutex::new(None)),
+            head_stage: Arc::new(Mutex::new(None)),
             metrics: self.metrics.clone(),
             metrics_store: self.metrics_store.clone(),
         }))
@@ -150,36 +182,43 @@ impl ExecutionPlan for DistributedExec {
             );
         }
 
-        let PreparedPlan {
-            head_stage,
-            join_set,
-        } = prepare_static_plan(&self.plan, &self.metrics, &self.metrics_store, &context)?;
-        {
-            let mut guard = self
-                .prepared_plan
-                .lock()
-                .map_err(|e| internal_datafusion_err!("Failed to lock prepared plan: {e}"))?;
-            *guard = Some(head_stage.clone());
-        }
+        let base_plan = Arc::clone(&self.base_plan);
+        let plan_for_viz = Arc::clone(&self.plan_for_viz);
+        let head_stage = Arc::clone(&self.head_stage);
+
+        let query_coordinator = QueryCoordinator::new(
+            Arc::clone(&context),
+            &self.metrics,
+            self.metrics_store.clone(),
+        );
+
         let mut builder = RecordBatchReceiverStreamBuilder::new(self.schema(), 1);
         let tx = builder.tx();
-        // Spawn the task that pulls data from child...
+
         builder.spawn(async move {
-            let mut stream = head_stage.execute(partition, context)?;
+            let _guard = query_coordinator.end_query_guard();
+
+            let result = prepare_static_plan(&query_coordinator, &base_plan)?;
+
+            plan_for_viz
+                .lock()
+                .expect("poisoned lock")
+                .replace(result.plan_for_viz);
+            head_stage
+                .lock()
+                .expect("poisoned lock")
+                .replace(Arc::clone(&result.head_stage));
+            let mut stream = result.head_stage.execute(partition, context)?;
             while let Some(msg) = stream.next().await {
                 if tx.send(msg).await.is_err() {
                     break; // channel closed
                 }
             }
+            drop(tx);
+            query_coordinator.drain_pending_tasks().await?;
             Ok(())
         });
-        // ...in parallel to the one that feeds the plan to workers.
-        builder.spawn(async move {
-            for res in join_set.join_all().await {
-                res?;
-            }
-            Ok(())
-        });
+
         Ok(builder.build())
     }
 

src/coordinator/latency_metric.rs

@@ -0,0 +1,62 @@
+use datafusion::common::instant::Instant;
+use datafusion::physical_expr_common::metrics::{
+    ExecutionPlanMetricsSet, MetricBuilder, MetricValue, Time,
+};
+use std::fmt::Display;
+use std::sync::atomic::{AtomicU64, Ordering};
+use std::time::Duration;
+
+/// DataFusion metrics system is pretty limited from an API standpoint. This intermediate struct
+/// bridges the gaps that are not satisfied by upstream API for measuring latency.
+pub(super) struct LatencyMetric {
+    max: Time,
+    avg: Time,
+    max_latency_micros: AtomicU64,
+    sum_latency_micros: AtomicU64,
+    count_latency_micros: AtomicU64,
+}
+
+impl Drop for LatencyMetric {
+    fn drop(&mut self) {
+        self.max.add_duration(Duration::from_micros(
+            self.max_latency_micros.load(Ordering::Relaxed),
+        ));
+        self.avg.add_duration(Duration::from_micros(
+            self.sum_latency_micros.load(Ordering::Relaxed)
+                / self.count_latency_micros.load(Ordering::Relaxed).max(1),
+        ));
+    }
+}
+
+impl LatencyMetric {
+    pub(super) fn new(
+        name: impl Display,
+        builder: impl Fn(MetricBuilder) -> MetricBuilder,
+        metrics: &ExecutionPlanMetricsSet,
+    ) -> Self {
+        let max = Time::new();
+        builder(MetricBuilder::new(metrics)).build(MetricValue::Time {
+            name: format!("{name}_max").into(),
+            time: max.clone(),
+        });
+        let avg = Time::new();
+        builder(MetricBuilder::new(metrics)).build(MetricValue::Time {
+            name: format!("{name}_avg").into(),
+            time: avg.clone(),
+        });
+        Self {
+            max,
+            avg,
+            max_latency_micros: AtomicU64::new(0),
+            sum_latency_micros: AtomicU64::new(0),
+            count_latency_micros: AtomicU64::new(0),
+        }
+    }
+
+    pub(super) fn record(&self, start: &Instant) {
+        let micros = start.elapsed().as_micros() as u64;
+        self.max_latency_micros.fetch_max(micros, Ordering::Relaxed);
+        self.sum_latency_micros.fetch_add(micros, Ordering::Relaxed);
+        self.count_latency_micros.fetch_add(1, Ordering::Relaxed);
+    }
+}

src/coordinator/mod.rs

@@ -1,7 +1,8 @@
 mod distributed;
+mod latency_metric;
 mod metrics_store;
 mod prepare_static_plan;
-mod task_spawner;
+mod query_coordinator;
 
 pub use distributed::DistributedExec;
 pub(crate) use metrics_store::MetricsStore;

src/coordinator/prepare_static_plan.rs

@@ -1,20 +1,10 @@
-use crate::coordinator::MetricsStore;
 use crate::coordinator::distributed::PreparedPlan;
-use crate::coordinator::task_spawner::{
-    CoordinatorToWorkerMetrics, CoordinatorToWorkerTaskSpawner,
-};
+use crate::coordinator::query_coordinator::QueryCoordinator;
 use crate::stage::RemoteStage;
-use crate::{
-    DistributedConfig, NetworkBoundaryExt, Stage, TaskEstimator, TaskRoutingContext,
-    get_distributed_worker_resolver,
-};
-use datafusion::common::runtime::JoinSet;
+use crate::{NetworkBoundaryExt, Stage};
 use datafusion::common::tree_node::{Transformed, TreeNode};
 use datafusion::common::{Result, exec_err};
-use datafusion::execution::TaskContext;
 use datafusion::physical_plan::ExecutionPlan;
-use datafusion::physical_plan::metrics::ExecutionPlanMetricsSet;
-use rand::Rng;
 use std::sync::Arc;
 
 /// Prepares the distributed plan for execution, which implies:
@@ -28,18 +18,9 @@ use std::sync::Arc;
 /// 4. Spawn a background task per worker that waits for the worker to finish and collects
 ///    its metrics into [DistributedExec::task_metrics] via the coordinator channel.
 pub(super) fn prepare_static_plan(
+    query_coordinator: &QueryCoordinator,
     base_plan: &Arc<dyn ExecutionPlan>,
-    metrics: &ExecutionPlanMetricsSet,
-    task_metrics: &Option<Arc<MetricsStore>>,
-    ctx: &Arc<TaskContext>,
 ) -> Result<PreparedPlan> {
-    let worker_resolver = get_distributed_worker_resolver(ctx.session_config())?;
-
-    let available_urls = worker_resolver.get_urls()?;
-
-    let metrics = CoordinatorToWorkerMetrics::new(metrics);
-
-    let mut join_set = JoinSet::new();
     let prepared = Arc::clone(base_plan).transform_up(|plan| {
         // The following logic is just applied on network boundaries.
         let Some(plan) = plan.as_network_boundary() else {
@@ -50,46 +31,18 @@ pub(super) fn prepare_static_plan(
             return exec_err!("Input stage from network boundary was not in Local state");
         };
 
-        let d_cfg = DistributedConfig::from_config_options(ctx.session_config().options())?;
-        let task_estimator = &d_cfg.__private_task_estimator;
-
-        let mut spawner =
-            CoordinatorToWorkerTaskSpawner::new(stage, &metrics, task_metrics, ctx, &mut join_set)?;
+        let mut stage_coordinator = query_coordinator.stage_coordinator(stage);
 
-        let routed_urls = match task_estimator.route_tasks(&TaskRoutingContext {
-            task_ctx: Arc::clone(ctx),
-            plan: &stage.plan,
-            task_count: stage.tasks,
-            available_urls: &available_urls,
-        }) {
-            Ok(Some(routed_urls)) => routed_urls,
-            // If the user has not defined custom routing with a `route_tasks` implementation, we
-            // default to round-robin task assignation from a randomized starting point.
-            Ok(None) => {
-                let start_idx = rand::rng().random_range(0..available_urls.len());
-                (0..stage.tasks)
-                    .map(|i| available_urls[(start_idx + i) % available_urls.len()].clone())
-                    .collect()
-            }
-            Err(e) => return exec_err!("error routing tasks to workers: {e}"),
-        };
-
-        if routed_urls.len() != stage.tasks {
-            return exec_err!(
-                "number of tasks ({}) was not equal to number of urls ({}) at execution time",
-                stage.tasks,
-                routed_urls.len()
-            );
-        }
+        let routed_urls = stage_coordinator.routed_urls()?;
 
         let mut workers = Vec::with_capacity(stage.tasks);
         for (i, routed_url) in routed_urls.into_iter().enumerate() {
             workers.push(routed_url.clone());
             // Spawn a task that sends the subplan to the chosen URL.
             // There will be as many spawned tasks as workers.
-            let (tx, worker_rx) = spawner.send_plan_task(Arc::clone(ctx), i, routed_url)?;
-            spawner.metrics_collection_task(i, worker_rx);
-            spawner.work_unit_feed_task(Arc::clone(ctx), i, tx)?;
+            let (worker_tx, worker_rx) = stage_coordinator.send_plan_task(i, routed_url)?;
+            stage_coordinator.worker_to_coordinator_task(i, worker_rx);
+            stage_coordinator.coordinator_to_worker_task(i, worker_tx)?;
         }
 
         Ok(Transformed::yes(plan.with_input_stage(Stage::Remote(
@@ -102,6 +55,8 @@ pub(super) fn prepare_static_plan(
     })?;
     Ok(PreparedPlan {
         head_stage: prepared.data,
-        join_set,
+        // If the plan was statically planned, the base plan is the same one that will be used for
+        // visualization.
+        plan_for_viz: Arc::clone(base_plan),
     })
 }