refactor(execution): NativeExecutor refactor

daft/daft/__init__.pyi

@@ -1695,10 +1695,7 @@ class LogicalPlanBuilder:
     def repr_mermaid(self, options: MermaidOptions) -> str: ...
 
 class NativeExecutor:
-    @staticmethod
-    def from_logical_plan_builder(
-        logical_plan_builder: LogicalPlanBuilder,
-    ) -> NativeExecutor: ...
+    def __init__(self) -> None: ...
     def run(
         self, psets: dict[str, list[PartitionT]], cfg: PyDaftExecutionConfig, results_buffer_size: int | None
     ) -> Iterator[PyMicroPartition]: ...

daft/execution/native_executor.py

@@ -5,10 +5,10 @@
 from daft.daft import (
     NativeExecutor as _NativeExecutor,
 )
-from daft.daft import PyDaftExecutionConfig
 from daft.table import MicroPartition
 
 if TYPE_CHECKING:
+    from daft.daft import PyDaftExecutionConfig
     from daft.logical.builder import LogicalPlanBuilder
     from daft.runners.partitioning import (
         LocalMaterializedResult,
@@ -18,16 +18,12 @@
 
 
 class NativeExecutor:
-    def __init__(self, executor: _NativeExecutor):
-        self._executor = executor
-
-    @classmethod
-    def from_logical_plan_builder(cls, builder: LogicalPlanBuilder) -> NativeExecutor:
-        executor = _NativeExecutor.from_logical_plan_builder(builder._builder)
-        return cls(executor)
+    def __init__(self):
+        self._executor = _NativeExecutor()
 
     def run(
         self,
+        builder: LogicalPlanBuilder,
         psets: dict[str, list[MaterializedResult[PartitionT]]],
         daft_execution_config: PyDaftExecutionConfig,
         results_buffer_size: int | None,
@@ -39,5 +35,5 @@
         }
         return (
             LocalMaterializedResult(MicroPartition._from_pymicropartition(part))
-            for part in self._executor.run(psets_mp, daft_execution_config, results_buffer_size)
+            for part in self._executor.run(builder._builder, psets_mp, daft_execution_config, results_buffer_size)
         )

daft/runners/native_runner.py

@@ -75,8 +75,9 @@ def run_iter(
 
         # Optimize the logical plan.
         builder = builder.optimize()
-        executor = NativeExecutor.from_logical_plan_builder(builder)
+        executor = NativeExecutor()
         results_gen = executor.run(
+            builder,
             {k: v.values() for k, v in self._part_set_cache.get_all_partition_sets().items()},
             daft_execution_config,
             results_buffer_size,

daft/runners/pyrunner.py

@@ -380,8 +380,9 @@
             if daft_execution_config.enable_native_executor:
                 logger.info("Using native executor")
 
-                executor = NativeExecutor.from_logical_plan_builder(builder)
+                executor = NativeExecutor()
                 results_gen = executor.run(
+                    builder,
                     {k: v.values() for k, v in self._part_set_cache.get_all_partition_sets().items()},
                     daft_execution_config,
                     results_buffer_size,

src/common/runtime/src/lib.rs

@@ -69,13 +69,16 @@ impl<T: Send + 'static> Future for RuntimeTask<T> {
 }
 
 pub struct Runtime {
-    runtime: tokio::runtime::Runtime,
+    pub runtime: Arc<tokio::runtime::Runtime>,
     pool_type: PoolType,
 }
 
 impl Runtime {
     pub(crate) fn new(runtime: tokio::runtime::Runtime, pool_type: PoolType) -> RuntimeRef {
-        Arc::new(Self { runtime, pool_type })
+        Arc::new(Self {
+            runtime: Arc::new(runtime),
+            pool_type,
+        })
     }
 
     async fn execute_task<F>(future: F, pool_type: PoolType) -> DaftResult<F::Output>

src/daft-connect/Cargo.toml

@@ -1,7 +1,6 @@
 [dependencies]
 arrow2 = {workspace = true, features = ["io_json_integration"]}
 async-stream = "0.3.6"
-common-daft-config = {workspace = true, optional = true, features = ["python"]}
 common-error = {workspace = true, optional = true, features = ["python"]}
 common-file-formats = {workspace = true, optional = true, features = ["python"]}
 daft-catalog = {path = "../daft-catalog", optional = true, features = ["python"]}
@@ -27,12 +26,12 @@ tokio = {version = "1.40.0", features = ["full"]}
 tonic = "0.12.3"
 tracing = {workspace = true}
 uuid = {version = "1.10.0", features = ["v4"]}
+common-runtime.workspace = true
 
 [features]
 default = ["python"]
 python = [
   "dep:pyo3",
-  "dep:common-daft-config",
   "dep:common-error",
   "dep:common-file-formats",
   "dep:daft-core",

src/daft-connect/src/execute.rs

@@ -1,20 +1,17 @@
 use std::{future::ready, sync::Arc};
 
-use common_daft_config::DaftExecutionConfig;
-use common_error::{DaftError, DaftResult};
+use common_error::DaftResult;
 use common_file_formats::FileFormat;
 use daft_dsl::LiteralValue;
-use daft_local_execution::NativeExecutor;
 use daft_logical_plan::LogicalPlanBuilder;
 use daft_micropartition::MicroPartition;
 use daft_ray_execution::RayEngine;
 use daft_table::Table;
 use eyre::{bail, Context};
 use futures::{
     stream::{self, BoxStream},
-    StreamExt, TryFutureExt, TryStreamExt,
+    StreamExt, TryStreamExt,
 };
-use itertools::Itertools;
 use pyo3::Python;
 use spark_connect::{
     relation::RelType,
@@ -63,17 +60,13 @@
 
             Runner::Native => {
                 let this = self.clone();
-                let result_stream = tokio::task::spawn_blocking(move || {
-                    let plan = lp.optimize()?;
-                    let cfg = Arc::new(DaftExecutionConfig::default());
-                    let native_executor = NativeExecutor::from_logical_plan_builder(&plan)?;
-                    let results = native_executor.run(&*this.psets, cfg, None)?;
-                    let it = results.into_iter();
-                    Ok::<_, DaftError>(it.collect_vec())
-                })
-                .await??;
 
-                Ok(Box::pin(stream::iter(result_stream)))
+                let plan = lp.optimize_async().await?;
+
+                let results = this
+                    .engine
+                    .run(&plan, &*this.psets, Default::default(), None)?;
+                Ok(results.into_stream().boxed())
             }
         }
     }
@@ -85,14 +78,12 @@
     ) -> Result<ExecuteStream, Status> {
         use futures::{StreamExt, TryStreamExt};
 
-        // fallback response
         let result_complete = res.result_complete_response();
 
         let (tx, rx) = tokio::sync::mpsc::channel::<eyre::Result<ExecutePlanResponse>>(1);
 
         let this = self.clone();
-
-        tokio::spawn(async move {
+        self.compute_runtime.runtime.spawn(async move {
             let execution_fut = async {
                 let translator = SparkAnalyzer::new(&this);
                 match command.rel_type {
@@ -144,7 +135,7 @@
     pub async fn execute_write_operation(
         &self,
         operation: WriteOperation,
-        response_builder: ResponseBuilder<ExecutePlanResponse>,
+        res: ResponseBuilder<ExecutePlanResponse>,
     ) -> Result<ExecuteStream, Status> {
         fn check_write_operation(write_op: &WriteOperation) -> Result<(), Status> {
             if !write_op.sort_column_names.is_empty() {
@@ -179,60 +170,70 @@
             }
         }
 
-        let finished = response_builder.result_complete_response();
+        let finished = res.result_complete_response();
+
+        let (tx, rx) = tokio::sync::mpsc::channel::<eyre::Result<ExecutePlanResponse>>(1);
 
         let this = self.clone();
 
-        let result = async move {
-            check_write_operation(&operation)?;
+        self.compute_runtime.runtime.spawn(async move {
+            let result = async {
+                check_write_operation(&operation)?;
 
-            let WriteOperation {
-                input,
-                source,
-                save_type,
-                ..
-            } = operation;
+                let WriteOperation {
+                    input,
+                    source,
+                    save_type,
+                    ..
+                } = operation;
 
-            let input = input.required("input")?;
-            let source = source.required("source")?;
+                let input = input.required("input")?;
+                let source = source.required("source")?;
 
-            let file_format: FileFormat = source.parse()?;
+                let file_format: FileFormat = source.parse()?;
 
-            let Some(save_type) = save_type else {
-                bail!("Save type is required");
-            };
+                let Some(save_type) = save_type else {
+                    bail!("Save type is required");
+                };
 
-            let path = match save_type {
-                SaveType::Path(path) => path,
-                SaveType::Table(_) => {
-                    return not_yet_implemented!("write to table").map_err(|e| e.into())
-                }
-            };
+                let path = match save_type {
+                    SaveType::Path(path) => path,
+                    SaveType::Table(_) => {
+                        return not_yet_implemented!("write to table").map_err(|e| e.into())
+                    }
+                };
 
-            let translator = SparkAnalyzer::new(&this);
+                let translator = SparkAnalyzer::new(&this);
 
-            let plan = translator.to_logical_plan(input).await?;
+                let plan = translator.to_logical_plan(input).await?;
 
-            let plan = plan.table_write(&path, file_format, None, None, None)?;
+                let plan = plan.table_write(&path, file_format, None, None, None)?;
 
-            let mut result_stream = this.run_query(plan).await?;
+                let mut result_stream = this.run_query(plan).await?;
 
-            // this is so we make sure the operation is actually done
-            // before we return
-            //
-            // an example where this is important is if we write to a parquet file
-            // and then read immediately after, we need to wait for the write to finish
-            while let Some(_result) = result_stream.next().await {}
+                // this is so we make sure the operation is actually done
+                // before we return
+                //
+                // an example where this is important is if we write to a parquet file
+                // and then read immediately after, we need to wait for the write to finish
+                while let Some(_result) = result_stream.next().await {}
 
-            Ok(())
-        };
+                Ok(())
+            };
 
-        let result = result.map_err(|e| {
-            Status::internal(textwrap::wrap(&format!("Error in Daft server: {e}"), 120).join("\n"))
+            if let Err(e) = result.await {
+                let _ = tx.send(Err(e)).await;
+            }
         });
+        let stream = ReceiverStream::new(rx);
 
-        let future = result.and_then(|()| ready(Ok(finished)));
-        let stream = futures::stream::once(future);
+        let stream = stream
+            .map_err(|e| {
+                Status::internal(
+                    textwrap::wrap(&format!("Error in Daft server: {e}"), 120).join("\n"),
+                )
+            })
+            .chain(stream::once(ready(Ok(finished))));
 
         Ok(Box::pin(stream))
     }

src/daft-connect/src/lib.rs

@@ -84,10 +84,10 @@ pub fn start(addr: &str) -> eyre::Result<ConnectionHandle> {
         shutdown_signal: Some(shutdown_signal),
         port,
     };
+    let runtime = common_runtime::get_io_runtime(true);
 
     std::thread::spawn(move || {
-        let runtime = tokio::runtime::Runtime::new().unwrap();
-        let result = runtime.block_on(async {
+        let result = runtime.block_on_current_thread(async {
             let incoming = {
                 let listener = tokio::net::TcpListener::from_std(listener)
                     .wrap_err("Failed to create TcpListener from std::net::TcpListener")?;

src/daft-connect/src/session.rs

@@ -3,7 +3,9 @@ use std::{
     sync::{Arc, RwLock},
 };
 
+use common_runtime::RuntimeRef;
 use daft_catalog::DaftCatalog;
+use daft_local_execution::NativeExecutor;
 use daft_micropartition::partitioning::InMemoryPartitionSetCache;
 use uuid::Uuid;
 
@@ -19,6 +21,8 @@ pub struct Session {
     /// MicroPartitionSet associated with this session
     /// this will be filled up as the user runs queries
     pub(crate) psets: Arc<InMemoryPartitionSetCache>,
+    pub(crate) compute_runtime: RuntimeRef,
+    pub(crate) engine: Arc<NativeExecutor>,
     pub(crate) catalog: Arc<RwLock<DaftCatalog>>,
 }
 
@@ -34,11 +38,15 @@ impl Session {
     pub fn new(id: String) -> Self {
         let server_side_session_id = Uuid::new_v4();
         let server_side_session_id = server_side_session_id.to_string();
+        let rt = common_runtime::get_compute_runtime();
+
         Self {
             config_values: Default::default(),
             id,
             server_side_session_id,
             psets: Arc::new(InMemoryPartitionSetCache::empty()),
+            compute_runtime: rt.clone(),
+            engine: Arc::new(NativeExecutor::default().with_runtime(rt.runtime.clone())),
             catalog: Arc::new(RwLock::new(DaftCatalog::default())),
         }
     }

src/daft-local-execution/src/lib.rs

@@ -26,7 +26,7 @@ use common_runtime::{RuntimeRef, RuntimeTask};
 use lazy_static::lazy_static;
 use progress_bar::{OperatorProgressBar, ProgressBarColor, ProgressBarManager};
 use resource_manager::MemoryManager;
-pub use run::{run_local, ExecutionEngineResult, NativeExecutor};
+pub use run::{ExecutionEngineResult, NativeExecutor};
 use runtime_stats::{RuntimeStatsContext, TimedFuture};
 use snafu::{futures::TryFutureExt, ResultExt, Snafu};
 use tracing::Instrument;
@@ -124,15 +124,15 @@ pub(crate) struct ExecutionRuntimeContext {
     worker_set: TaskSet<crate::Result<()>>,
     default_morsel_size: usize,
     memory_manager: Arc<MemoryManager>,
-    progress_bar_manager: Option<Box<dyn ProgressBarManager>>,
+    progress_bar_manager: Option<Arc<dyn ProgressBarManager>>,
 }
 
 impl ExecutionRuntimeContext {
     #[must_use]
     pub fn new(
         default_morsel_size: usize,
         memory_manager: Arc<MemoryManager>,
-        progress_bar_manager: Option<Box<dyn ProgressBarManager>>,
+        progress_bar_manager: Option<Arc<dyn ProgressBarManager>>,
     ) -> Self {
         Self {
             worker_set: TaskSet::new(),