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perf: Apply DataFusion's projection pushdown rule #907

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perf: Apply DataFusion's projection pushdown rule #907

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8dff659
Use DataFusion's projection pushdown rule
andygrove Sep 3, 2024
f2dca63
call optimizer
andygrove Sep 3, 2024
c7fdb89
upmerge
andygrove Sep 3, 2024
913eb15
fix
andygrove Sep 4, 2024
a70cff6
add config
andygrove Sep 4, 2024
c51ced6
machete
andygrove Sep 4, 2024
bdc8144
revert a change
andygrove Sep 4, 2024
4c5a3ef
remove default features from session state
andygrove Sep 4, 2024
14c32c5
Revert "remove default features from session state"
andygrove Sep 4, 2024
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7 changes: 7 additions & 0 deletions common/src/main/scala/org/apache/comet/CometConf.scala
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Original file line number Diff line number Diff line change
Expand Up @@ -347,6 +347,13 @@ object CometConf extends ShimCometConf {
.booleanConf
.createWithDefault(false)

val COMET_NATIVE_OPTIMIZER_ENABLED: ConfigEntry[Boolean] =
conf("spark.comet.exec.optimizer.enabled")
.internal()
.doc("Enable DataFusion physical optimizer for native plans.")
.booleanConf
.createWithDefault(true)

val COMET_WORKER_THREADS: ConfigEntry[Int] =
conf("spark.comet.workerThreads")
.internal()
Expand Down
38 changes: 26 additions & 12 deletions native/core/src/execution/datafusion/planner.rs
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Expand Up @@ -58,6 +58,7 @@ use datafusion::functions_aggregate::sum::sum_udaf;
use datafusion::physical_expr_functions_aggregate::aggregate::AggregateExprBuilder;
use datafusion::physical_plan::windows::BoundedWindowAggExec;
use datafusion::physical_plan::InputOrderMode;
use datafusion::physical_planner::DefaultPhysicalPlanner;
use datafusion::{
arrow::{compute::SortOptions, datatypes::SchemaRef},
common::DataFusionError,
Expand Down Expand Up @@ -138,18 +139,6 @@ pub struct PhysicalPlanner {
session_ctx: Arc<SessionContext>,
}

impl Default for PhysicalPlanner {
fn default() -> Self {
let session_ctx = Arc::new(SessionContext::new());
let execution_props = ExecutionProps::new();
Self {
exec_context_id: TEST_EXEC_CONTEXT_ID,
execution_props,
session_ctx,
}
}
}
Comment on lines -141 to -151
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This code was only used in tests so I moved it into the test module


impl PhysicalPlanner {
pub fn new(session_ctx: Arc<SessionContext>) -> Self {
let execution_props = ExecutionProps::new();
Expand Down Expand Up @@ -1115,6 +1104,17 @@ impl PhysicalPlanner {
}
}

pub fn optimize_plan(
&self,
plan: Arc<dyn ExecutionPlan>,
) -> Result<Arc<dyn ExecutionPlan>, ExecutionError> {
// optimize the physical plan
let datafusion_planner = DefaultPhysicalPlanner::default();
datafusion_planner
.optimize_physical_plan(plan, &self.session_ctx.state(), |_, _| {})
.map_err(|e| e.into())
}

fn parse_join_parameters(
&self,
inputs: &mut Vec<Arc<GlobalRef>>,
Expand Down Expand Up @@ -1967,10 +1967,12 @@ mod tests {
use arrow_array::{DictionaryArray, Int32Array, StringArray};
use arrow_schema::DataType;
use datafusion::{physical_plan::common::collect, prelude::SessionContext};
use datafusion_expr::execution_props::ExecutionProps;
use tokio::sync::mpsc;

use crate::execution::{datafusion::planner::PhysicalPlanner, operators::InputBatch};

use crate::execution::datafusion::planner::TEST_EXEC_CONTEXT_ID;
use crate::execution::operators::ExecutionError;
use datafusion_comet_proto::{
spark_expression::expr::ExprStruct::*,
Expand All @@ -1979,6 +1981,18 @@ mod tests {
spark_operator::{operator::OpStruct, Operator},
};

impl Default for PhysicalPlanner {
fn default() -> Self {
let session_ctx = Arc::new(SessionContext::default());
let execution_props = ExecutionProps::new();
Self {
exec_context_id: TEST_EXEC_CONTEXT_ID,
execution_props,
session_ctx,
}
}
}

#[test]
fn test_unpack_dictionary_primitive() {
let op_scan = Operator {
Expand Down
27 changes: 21 additions & 6 deletions native/core/src/execution/jni_api.rs
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Original file line number Diff line number Diff line change
Expand Up @@ -17,11 +17,14 @@

//! Define JNI APIs which can be called from Java/Scala.

use super::{serde, utils::SparkArrowConvert, CometMemoryPool};
use arrow::{
datatypes::DataType as ArrowDataType,
ffi::{FFI_ArrowArray, FFI_ArrowSchema},
};
use arrow_array::RecordBatch;
use datafusion::execution::session_state::SessionStateBuilder;
use datafusion::physical_optimizer::projection_pushdown::ProjectionPushdown;
use datafusion::{
execution::{
disk_manager::DiskManagerConfig,
Expand All @@ -42,8 +45,6 @@ use jni::{
};
use std::{collections::HashMap, sync::Arc, task::Poll};

use super::{serde, utils::SparkArrowConvert, CometMemoryPool};

use crate::{
errors::{try_unwrap_or_throw, CometError, CometResult},
execution::{
Expand Down Expand Up @@ -92,6 +93,8 @@ struct ExecutionContext {
pub debug_native: bool,
/// Whether to write native plans with metrics to stdout
pub explain_native: bool,
/// Whether to enable physical optimizer
pub enable_optimizer: bool,
}

/// Accept serialized query plan and return the address of the native query plan.
Expand Down Expand Up @@ -132,6 +135,7 @@ pub unsafe extern "system" fn Java_org_apache_comet_Native_createPlan(
// Whether we've enabled additional debugging on the native side
let debug_native = parse_bool(&configs, "debug_native")?;
let explain_native = parse_bool(&configs, "explain_native")?;
let enable_optimizer = parse_bool(&configs, "native_optimizer")?;

let worker_threads = configs
.get("worker_threads")
Expand Down Expand Up @@ -184,6 +188,7 @@ pub unsafe extern "system" fn Java_org_apache_comet_Native_createPlan(
session_ctx: Arc::new(session),
debug_native,
explain_native,
enable_optimizer,
});

Ok(Box::into_raw(exec_context) as i64)
Expand Down Expand Up @@ -249,11 +254,14 @@ fn prepare_datafusion_session_context(

let runtime = RuntimeEnv::new(rt_config).unwrap();

let mut session_ctx = SessionContext::new_with_config_rt(session_config, Arc::new(runtime));
let state = SessionStateBuilder::new()
.with_config(session_config)
.with_runtime_env(Arc::new(runtime))
.with_default_features()
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default features needed to use the planner?

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Let me see if I can remove that

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Removing this causes test failures. We were previously calling the following method to create the context and this also enabled default features.

    pub fn new_with_config_rt(config: SessionConfig, runtime: Arc<RuntimeEnv>) -> Self {
        let state = SessionStateBuilder::new()
            .with_config(config)
            .with_runtime_env(runtime)
            .with_default_features()
            .build();
        Self::new_with_state(state)
    }

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since we using a planner only perhaps this should be enough

.with_query_planner(SessionStateDefaults::default_expr_planners())

?

.with_physical_optimizer_rules(vec![Arc::new(ProjectionPushdown::new())])
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I wonder if other rules can be considered?

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Possibly. We are starting out with a physical plan that is already optimized by Spark though, so many optimizations have already been applied. We also are running queries in single partitions within a distributed cluster so we cannot leverage anything that uses RepartitionExec.

.build();

datafusion_functions_nested::register_all(&mut session_ctx)?;

Ok(session_ctx)
Ok(SessionContext::new_with_state(state))
}

fn parse_bool(conf: &HashMap<String, String>, name: &str) -> CometResult<bool> {
Expand Down Expand Up @@ -355,6 +363,13 @@ pub unsafe extern "system" fn Java_org_apache_comet_Native_executePlan(
&mut exec_context.input_sources.clone(),
)?;

// optimize the physical plan
let root_op = if exec_context.enable_optimizer {
planner.optimize_plan(root_op)?
} else {
root_op
};

exec_context.root_op = Some(Arc::clone(&root_op));
exec_context.scans = scans;

Expand Down
5 changes: 2 additions & 3 deletions native/core/src/execution/operators/copy.rs
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Expand Up @@ -116,10 +116,9 @@ impl ExecutionPlan for CopyExec {
self: Arc<Self>,
children: Vec<Arc<dyn ExecutionPlan>>,
) -> DataFusionResult<Arc<dyn ExecutionPlan>> {
let input = Arc::clone(&self.input);
let new_input = input.with_new_children(children)?;
assert!(children.len() == 1);
Ok(Arc::new(CopyExec {
input: new_input,
input: Arc::clone(&children[0]),
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Adding the optimizer highlighted that the previous implementation of CopyExec::with_new_children was incorrect.

schema: Arc::clone(&self.schema),
cache: self.cache.clone(),
metrics: self.metrics.clone(),
Expand Down
3 changes: 2 additions & 1 deletion spark/src/main/scala/org/apache/comet/CometExecIterator.scala
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Expand Up @@ -23,7 +23,7 @@ import org.apache.spark._
import org.apache.spark.sql.comet.CometMetricNode
import org.apache.spark.sql.vectorized._

import org.apache.comet.CometConf.{COMET_BATCH_SIZE, COMET_BLOCKING_THREADS, COMET_DEBUG_ENABLED, COMET_EXEC_MEMORY_FRACTION, COMET_EXPLAIN_NATIVE_ENABLED, COMET_WORKER_THREADS}
import org.apache.comet.CometConf.{COMET_BATCH_SIZE, COMET_BLOCKING_THREADS, COMET_DEBUG_ENABLED, COMET_EXEC_MEMORY_FRACTION, COMET_EXPLAIN_NATIVE_ENABLED, COMET_NATIVE_OPTIMIZER_ENABLED, COMET_WORKER_THREADS}
import org.apache.comet.vector.NativeUtil

/**
Expand Down Expand Up @@ -86,6 +86,7 @@ class CometExecIterator(
result.put("batch_size", String.valueOf(COMET_BATCH_SIZE.get()))
result.put("debug_native", String.valueOf(COMET_DEBUG_ENABLED.get()))
result.put("explain_native", String.valueOf(COMET_EXPLAIN_NATIVE_ENABLED.get()))
result.put("native_optimizer", String.valueOf(COMET_NATIVE_OPTIMIZER_ENABLED.get()))
result.put("worker_threads", String.valueOf(COMET_WORKER_THREADS.get()))
result.put("blocking_threads", String.valueOf(COMET_BLOCKING_THREADS.get()))

Expand Down
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