mirror of
https://github.com/GreptimeTeam/greptimedb.git
synced 2026-05-25 01:10:37 +00:00
feat: support distributed EXPLAIN ANALYZE (#3908)
* feat: fetch and pass per-plan metrics Signed-off-by: Ruihang Xia <waynestxia@gmail.com> * impl DistAnalyzeExec Signed-off-by: Ruihang Xia <waynestxia@gmail.com> * update sqlness results Signed-off-by: Ruihang Xia <waynestxia@gmail.com> * fix clippy Signed-off-by: Ruihang Xia <waynestxia@gmail.com> * fix typo Signed-off-by: Ruihang Xia <waynestxia@gmail.com> * fix typo again Signed-off-by: Ruihang Xia <waynestxia@gmail.com> * Update src/query/src/analyze.rs Co-authored-by: Jeremyhi <jiachun_feng@proton.me> --------- Signed-off-by: Ruihang Xia <waynestxia@gmail.com> Co-authored-by: Jeremyhi <jiachun_feng@proton.me>
This commit is contained in:
@@ -12,6 +12,14 @@
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// See the License for the specific language governing permissions and
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// limitations under the License.
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pub mod columnar_value;
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pub mod error;
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mod function;
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pub mod logical_plan;
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pub mod physical_plan;
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pub mod prelude;
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mod signature;
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use std::fmt::{Debug, Display, Formatter};
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use std::sync::Arc;
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@@ -20,14 +28,6 @@ use api::greptime_proto::v1::AddColumnLocation as Location;
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use common_recordbatch::{RecordBatches, SendableRecordBatchStream};
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use physical_plan::PhysicalPlan;
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use serde::{Deserialize, Serialize};
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pub mod columnar_value;
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pub mod error;
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mod function;
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pub mod logical_plan;
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pub mod physical_plan;
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pub mod prelude;
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mod signature;
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use sqlparser_derive::{Visit, VisitMut};
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/// new Output struct with output data(previously Output) and output meta
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@@ -12,6 +12,7 @@
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// See the License for the specific language governing permissions and
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// limitations under the License.
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use std::fmt::Display;
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use std::future::Future;
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use std::marker::PhantomData;
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use std::pin::Pin;
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@@ -22,7 +23,10 @@ use datafusion::arrow::compute::cast;
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use datafusion::arrow::datatypes::SchemaRef as DfSchemaRef;
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use datafusion::error::Result as DfResult;
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use datafusion::physical_plan::metrics::{BaselineMetrics, MetricValue};
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use datafusion::physical_plan::{ExecutionPlan, RecordBatchStream as DfRecordBatchStream};
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use datafusion::physical_plan::{
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accept, displayable, ExecutionPlan, ExecutionPlanVisitor,
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RecordBatchStream as DfRecordBatchStream,
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};
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use datafusion_common::arrow::error::ArrowError;
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use datafusion_common::DataFusionError;
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use datatypes::schema::{Schema, SchemaRef};
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@@ -228,7 +232,7 @@ impl RecordBatchStream for RecordBatchStreamAdapter {
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fn metrics(&self) -> Option<RecordBatchMetrics> {
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match &self.metrics_2 {
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Metrics::Resolved(metrics) => Some(*metrics),
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Metrics::Resolved(metrics) => Some(metrics.clone()),
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Metrics::Unavailable | Metrics::Unresolved(_) => None,
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}
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}
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@@ -259,11 +263,9 @@ impl Stream for RecordBatchStreamAdapter {
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}
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Poll::Ready(None) => {
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if let Metrics::Unresolved(df_plan) = &self.metrics_2 {
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let mut metrics_holder = RecordBatchMetrics::default();
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collect_metrics(df_plan, &mut metrics_holder);
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if metrics_holder.elapsed_compute != 0 || metrics_holder.memory_usage != 0 {
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self.metrics_2 = Metrics::Resolved(metrics_holder);
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}
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let mut metric_collector = MetricCollector::default();
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accept(df_plan.as_ref(), &mut metric_collector).unwrap();
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self.metrics_2 = Metrics::Resolved(metric_collector.record_batch_metrics);
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}
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Poll::Ready(None)
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}
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@@ -276,28 +278,110 @@ impl Stream for RecordBatchStreamAdapter {
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}
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}
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fn collect_metrics(df_plan: &Arc<dyn ExecutionPlan>, result: &mut RecordBatchMetrics) {
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if let Some(metrics) = df_plan.metrics() {
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metrics.iter().for_each(|m| match m.value() {
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MetricValue::ElapsedCompute(ec) => result.elapsed_compute += ec.value(),
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MetricValue::CurrentMemoryUsage(m) => result.memory_usage += m.value(),
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_ => {}
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});
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/// An [ExecutionPlanVisitor] to collect metrics from a [ExecutionPlan].
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#[derive(Default)]
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pub struct MetricCollector {
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current_level: usize,
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pub record_batch_metrics: RecordBatchMetrics,
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}
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impl ExecutionPlanVisitor for MetricCollector {
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type Error = !;
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fn pre_visit(&mut self, plan: &dyn ExecutionPlan) -> std::result::Result<bool, Self::Error> {
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// skip if no metric available
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let Some(metric) = plan.metrics() else {
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self.record_batch_metrics.plan_metrics.push(PlanMetrics {
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plan: plan.name().to_string(),
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level: self.current_level,
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metrics: vec![],
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});
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return Ok(true);
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};
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// scrape plan metrics
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let metric = metric
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.aggregate_by_name()
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.sorted_for_display()
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.timestamps_removed();
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let mut plan_metric = PlanMetrics {
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plan: displayable(plan).one_line().to_string(),
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level: self.current_level,
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metrics: Vec::with_capacity(metric.iter().size_hint().0),
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};
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for m in metric.iter() {
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plan_metric
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.metrics
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.push((m.value().name().to_string(), m.value().as_usize()));
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// aggregate high-level metrics
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match m.value() {
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MetricValue::ElapsedCompute(ec) => {
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self.record_batch_metrics.elapsed_compute += ec.value()
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}
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MetricValue::CurrentMemoryUsage(m) => {
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self.record_batch_metrics.memory_usage += m.value()
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}
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_ => {}
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}
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}
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self.record_batch_metrics.plan_metrics.push(plan_metric);
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self.current_level += 1;
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Ok(true)
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}
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for child in df_plan.children() {
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collect_metrics(&child, result);
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fn post_visit(&mut self, _plan: &dyn ExecutionPlan) -> std::result::Result<bool, Self::Error> {
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// the last minus will underflow
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self.current_level = self.current_level.wrapping_sub(1);
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Ok(true)
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}
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}
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/// [`RecordBatchMetrics`] carrys metrics value
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/// from datanode to frontend through gRPC
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#[derive(serde::Serialize, serde::Deserialize, Default, Debug, Clone, Copy)]
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#[derive(serde::Serialize, serde::Deserialize, Default, Debug, Clone)]
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pub struct RecordBatchMetrics {
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// cpu consumption in nanoseconds
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// High-level aggregated metrics
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/// CPU consumption in nanoseconds
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pub elapsed_compute: usize,
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// memory used by the plan in bytes
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/// Memory used by the plan in bytes
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pub memory_usage: usize,
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// Detailed per-plan metrics
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/// An ordered list of plan metrics, from top to bottom in post-order.
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pub plan_metrics: Vec<PlanMetrics>,
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}
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/// Only display `plan_metrics` with indent ` ` (2 spaces).
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impl Display for RecordBatchMetrics {
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fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
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for metric in &self.plan_metrics {
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write!(
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f,
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"{:indent$}{} metrics=[",
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" ",
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metric.plan.trim_end(),
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indent = metric.level * 2,
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)?;
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for (label, value) in &metric.metrics {
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write!(f, "{}: {}, ", label, value)?;
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}
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writeln!(f, "]")?;
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}
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Ok(())
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}
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}
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#[derive(serde::Serialize, serde::Deserialize, Default, Debug, Clone)]
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pub struct PlanMetrics {
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/// The plan name
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pub plan: String,
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/// The level of the plan, starts from 0
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pub level: usize,
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/// An ordered key-value list of metrics.
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/// Key is metric label and value is metric value.
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pub metrics: Vec<(String, usize)>,
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}
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enum AsyncRecordBatchStreamAdapterState {
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@@ -12,6 +12,8 @@
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// See the License for the specific language governing permissions and
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// limitations under the License.
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#![feature(never_type)]
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pub mod adapter;
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pub mod error;
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pub mod filter;
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@@ -260,7 +262,7 @@ impl<S: Stream<Item = Result<RecordBatch>> + Unpin> RecordBatchStream
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}
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fn metrics(&self) -> Option<RecordBatchMetrics> {
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self.metrics.load().as_ref().map(|s| *s.as_ref())
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self.metrics.load().as_ref().map(|s| s.as_ref().clone())
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}
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}
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229
src/query/src/analyze.rs
Normal file
229
src/query/src/analyze.rs
Normal file
@@ -0,0 +1,229 @@
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// Copyright 2023 Greptime Team
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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//! Customized `ANALYZE` plan that aware of [MergeScanExec].
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//!
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//! The code skeleton is taken from `datafusion/physical-plan/src/analyze.rs`
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use std::any::Any;
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use std::sync::Arc;
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use arrow::array::{StringBuilder, UInt32Builder};
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use arrow_schema::{DataType, Field, Schema, SchemaRef};
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use common_query::{DfPhysicalPlan, DfPhysicalPlanRef};
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use common_recordbatch::adapter::{MetricCollector, RecordBatchMetrics};
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use common_recordbatch::{DfRecordBatch, DfSendableRecordBatchStream};
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use datafusion::error::Result as DfResult;
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use datafusion::execution::TaskContext;
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use datafusion::physical_plan::coalesce_partitions::CoalescePartitionsExec;
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use datafusion::physical_plan::stream::RecordBatchStreamAdapter;
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use datafusion::physical_plan::{
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accept, DisplayAs, DisplayFormatType, ExecutionPlanProperties, PlanProperties,
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};
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use datafusion_common::tree_node::{TreeNode, TreeNodeRecursion};
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use datafusion_common::{internal_err, DataFusionError};
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use datafusion_physical_expr::{Distribution, EquivalenceProperties, Partitioning};
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use futures::StreamExt;
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use crate::dist_plan::MergeScanExec;
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const STAGE: &str = "stage";
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const NODE: &str = "node";
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const PLAN: &str = "plan";
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#[derive(Debug)]
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pub struct DistAnalyzeExec {
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input: DfPhysicalPlanRef,
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schema: SchemaRef,
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properties: PlanProperties,
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}
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impl DistAnalyzeExec {
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/// Create a new DistAnalyzeExec
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pub fn new(input: DfPhysicalPlanRef) -> Self {
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let schema = SchemaRef::new(Schema::new(vec![
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Field::new(STAGE, DataType::UInt32, true),
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Field::new(NODE, DataType::UInt32, true),
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Field::new(PLAN, DataType::Utf8, true),
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]));
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let properties = Self::compute_properties(&input, schema.clone());
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Self {
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input,
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schema,
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properties,
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}
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}
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/// This function creates the cache object that stores the plan properties such as schema, equivalence properties, ordering, partitioning, etc.
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fn compute_properties(input: &DfPhysicalPlanRef, schema: SchemaRef) -> PlanProperties {
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let eq_properties = EquivalenceProperties::new(schema);
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let output_partitioning = Partitioning::UnknownPartitioning(1);
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let exec_mode = input.execution_mode();
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PlanProperties::new(eq_properties, output_partitioning, exec_mode)
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}
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}
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impl DisplayAs for DistAnalyzeExec {
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fn fmt_as(&self, t: DisplayFormatType, f: &mut std::fmt::Formatter) -> std::fmt::Result {
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match t {
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DisplayFormatType::Default | DisplayFormatType::Verbose => {
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write!(f, "DistAnalyzeExec",)
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}
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}
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}
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}
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impl DfPhysicalPlan for DistAnalyzeExec {
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fn name(&self) -> &'static str {
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"DistAnalyzeExec"
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}
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/// Return a reference to Any that can be used for downcasting
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fn as_any(&self) -> &dyn Any {
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self
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}
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fn properties(&self) -> &PlanProperties {
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&self.properties
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}
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fn children(&self) -> Vec<DfPhysicalPlanRef> {
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vec![self.input.clone()]
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}
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/// AnalyzeExec is handled specially so this value is ignored
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fn required_input_distribution(&self) -> Vec<Distribution> {
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vec![]
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}
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fn with_new_children(
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self: Arc<Self>,
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mut children: Vec<DfPhysicalPlanRef>,
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) -> DfResult<DfPhysicalPlanRef> {
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Ok(Arc::new(Self::new(children.pop().unwrap())))
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}
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fn execute(
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&self,
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partition: usize,
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context: Arc<TaskContext>,
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) -> DfResult<DfSendableRecordBatchStream> {
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if 0 != partition {
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return internal_err!("AnalyzeExec invalid partition. Expected 0, got {partition}");
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}
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// Wrap the input plan using `CoalescePartitionsExec` to poll multiple
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// partitions in parallel
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let coalesce_partition_plan = CoalescePartitionsExec::new(self.input.clone());
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// Create future that computes thefinal output
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let captured_input = self.input.clone();
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let captured_schema = self.schema.clone();
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// Finish the input stream and create the output
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let mut input_stream = coalesce_partition_plan.execute(0, context)?;
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let output = async move {
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let mut total_rows = 0;
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while let Some(batch) = input_stream.next().await.transpose()? {
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total_rows += batch.num_rows();
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}
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create_output_batch(total_rows, captured_input, captured_schema)
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};
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Ok(Box::pin(RecordBatchStreamAdapter::new(
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self.schema.clone(),
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futures::stream::once(output),
|
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)))
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}
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}
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/// Build the result [`DfRecordBatch`] of `ANALYZE`
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struct AnalyzeOutputBuilder {
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stage_builder: UInt32Builder,
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node_builder: UInt32Builder,
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plan_builder: StringBuilder,
|
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schema: SchemaRef,
|
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}
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|
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impl AnalyzeOutputBuilder {
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fn new(schema: SchemaRef) -> Self {
|
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Self {
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stage_builder: UInt32Builder::with_capacity(4),
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node_builder: UInt32Builder::with_capacity(4),
|
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plan_builder: StringBuilder::with_capacity(1, 1024),
|
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schema,
|
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}
|
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}
|
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|
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fn append_metric(&mut self, stage: u32, node: u32, metric: RecordBatchMetrics) {
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self.stage_builder.append_value(stage);
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self.node_builder.append_value(node);
|
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self.plan_builder.append_value(metric.to_string());
|
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}
|
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|
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fn append_total_rows(&mut self, total_rows: usize) {
|
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self.stage_builder.append_null();
|
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self.node_builder.append_null();
|
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self.plan_builder
|
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.append_value(format!("Total rows: {}", total_rows));
|
||||
}
|
||||
|
||||
fn finish(mut self) -> DfResult<DfRecordBatch> {
|
||||
DfRecordBatch::try_new(
|
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self.schema,
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vec![
|
||||
Arc::new(self.stage_builder.finish()),
|
||||
Arc::new(self.node_builder.finish()),
|
||||
Arc::new(self.plan_builder.finish()),
|
||||
],
|
||||
)
|
||||
.map_err(DataFusionError::from)
|
||||
}
|
||||
}
|
||||
|
||||
/// Creates the output of AnalyzeExec as a RecordBatch
|
||||
fn create_output_batch(
|
||||
total_rows: usize,
|
||||
input: DfPhysicalPlanRef,
|
||||
schema: SchemaRef,
|
||||
) -> DfResult<DfRecordBatch> {
|
||||
let mut builder = AnalyzeOutputBuilder::new(schema);
|
||||
|
||||
// Treat the current stage as stage 0. Fetch its metrics
|
||||
let mut collector = MetricCollector::default();
|
||||
// Safety: metric collector won't return error
|
||||
accept(input.as_ref(), &mut collector).unwrap();
|
||||
let stage_0_metrics = collector.record_batch_metrics;
|
||||
|
||||
// Append the metrics of the current stage
|
||||
builder.append_metric(0, 0, stage_0_metrics);
|
||||
|
||||
// Find merge scan and append its sub_stage_metrics
|
||||
input.apply(&mut |plan| {
|
||||
if let Some(merge_scan) = plan.as_any().downcast_ref::<MergeScanExec>() {
|
||||
let sub_stage_metrics = merge_scan.sub_stage_metrics();
|
||||
for (node, metric) in sub_stage_metrics.into_iter().enumerate() {
|
||||
builder.append_metric(1, node as _, metric);
|
||||
}
|
||||
return Ok(TreeNodeRecursion::Stop);
|
||||
}
|
||||
Ok(TreeNodeRecursion::Continue)
|
||||
})?;
|
||||
|
||||
// Write total rows
|
||||
builder.append_total_rows(total_rows);
|
||||
|
||||
builder.finish()
|
||||
}
|
||||
@@ -44,6 +44,7 @@ use snafu::{ensure, OptionExt, ResultExt};
|
||||
use table::requests::{DeleteRequest, InsertRequest};
|
||||
use table::TableRef;
|
||||
|
||||
use crate::analyze::DistAnalyzeExec;
|
||||
use crate::dataframe::DataFrame;
|
||||
pub use crate::datafusion::planner::DfContextProviderAdapter;
|
||||
use crate::error::{
|
||||
@@ -407,9 +408,7 @@ impl PhysicalOptimizer for DatafusionQueryEngine {
|
||||
.optimize(new_plan, config)
|
||||
.context(DataFusionSnafu)?;
|
||||
}
|
||||
Arc::new(analyze_plan.clone())
|
||||
.with_new_children(vec![new_plan])
|
||||
.unwrap()
|
||||
Arc::new(DistAnalyzeExec::new(new_plan))
|
||||
} else {
|
||||
let mut new_plan = df_plan;
|
||||
for optimizer in state.physical_optimizers() {
|
||||
|
||||
@@ -18,5 +18,5 @@ mod merge_scan;
|
||||
mod planner;
|
||||
|
||||
pub use analyzer::DistPlannerAnalyzer;
|
||||
pub use merge_scan::MergeScanLogicalPlan;
|
||||
pub use merge_scan::{MergeScanExec, MergeScanLogicalPlan};
|
||||
pub use planner::DistExtensionPlanner;
|
||||
|
||||
@@ -13,7 +13,7 @@
|
||||
// limitations under the License.
|
||||
|
||||
use std::any::Any;
|
||||
use std::sync::Arc;
|
||||
use std::sync::{Arc, Mutex};
|
||||
use std::time::Duration;
|
||||
|
||||
use arrow_schema::{Schema as ArrowSchema, SchemaRef as ArrowSchemaRef};
|
||||
@@ -24,7 +24,7 @@ use common_error::ext::BoxedError;
|
||||
use common_meta::table_name::TableName;
|
||||
use common_plugins::GREPTIME_EXEC_READ_COST;
|
||||
use common_query::physical_plan::TaskContext;
|
||||
use common_recordbatch::adapter::DfRecordBatchStreamAdapter;
|
||||
use common_recordbatch::adapter::{DfRecordBatchStreamAdapter, RecordBatchMetrics};
|
||||
use common_recordbatch::error::ExternalSnafu;
|
||||
use common_recordbatch::{
|
||||
DfSendableRecordBatchStream, RecordBatch, RecordBatchStreamWrapper, SendableRecordBatchStream,
|
||||
@@ -128,6 +128,8 @@ pub struct MergeScanExec {
|
||||
region_query_handler: RegionQueryHandlerRef,
|
||||
metric: ExecutionPlanMetricsSet,
|
||||
properties: PlanProperties,
|
||||
/// Metrics from sub stages
|
||||
sub_stage_metrics: Arc<Mutex<Vec<RecordBatchMetrics>>>,
|
||||
query_ctx: QueryContextRef,
|
||||
}
|
||||
|
||||
@@ -166,6 +168,7 @@ impl MergeScanExec {
|
||||
arrow_schema: arrow_schema_without_metadata,
|
||||
region_query_handler,
|
||||
metric: ExecutionPlanMetricsSet::new(),
|
||||
sub_stage_metrics: Arc::default(),
|
||||
properties,
|
||||
query_ctx,
|
||||
})
|
||||
@@ -185,6 +188,7 @@ impl MergeScanExec {
|
||||
let timezone = self.query_ctx.timezone().to_string();
|
||||
let extensions = self.query_ctx.extensions();
|
||||
|
||||
let sub_sgate_metrics_moved = self.sub_stage_metrics.clone();
|
||||
let stream = Box::pin(stream!({
|
||||
MERGE_SCAN_REGIONS.observe(regions.len() as f64);
|
||||
let _finish_timer = metric.finish_time().timer();
|
||||
@@ -236,6 +240,8 @@ impl MergeScanExec {
|
||||
// reset poll timer
|
||||
poll_timer = Instant::now();
|
||||
}
|
||||
|
||||
// process metrics after all data is drained.
|
||||
if let Some(metrics) = stream.metrics() {
|
||||
let (c, s) = parse_catalog_and_schema_from_db_string(&dbname);
|
||||
let value = read_meter!(
|
||||
@@ -247,6 +253,9 @@ impl MergeScanExec {
|
||||
}
|
||||
);
|
||||
metric.record_greptime_exec_cost(value as usize);
|
||||
|
||||
// record metrics from sub sgates
|
||||
sub_sgate_metrics_moved.lock().unwrap().push(metrics);
|
||||
}
|
||||
|
||||
MERGE_SCAN_POLL_ELAPSED.observe(poll_duration.as_secs_f64());
|
||||
@@ -279,6 +288,10 @@ impl MergeScanExec {
|
||||
let schema = Schema::try_from(arrow_schema).context(ConvertSchemaSnafu)?;
|
||||
Ok(Arc::new(schema))
|
||||
}
|
||||
|
||||
pub fn sub_stage_metrics(&self) -> Vec<RecordBatchMetrics> {
|
||||
self.sub_stage_metrics.lock().unwrap().clone()
|
||||
}
|
||||
}
|
||||
|
||||
impl ExecutionPlan for MergeScanExec {
|
||||
|
||||
@@ -15,6 +15,7 @@
|
||||
#![feature(let_chains)]
|
||||
#![feature(int_roundings)]
|
||||
|
||||
mod analyze;
|
||||
pub mod dataframe;
|
||||
pub mod datafusion;
|
||||
pub mod dist_plan;
|
||||
|
||||
@@ -49,7 +49,6 @@ impl Debug for StreamScanAdapter {
|
||||
fn fmt(&self, f: &mut Formatter<'_>) -> std::fmt::Result {
|
||||
f.debug_struct("StreamScanAdapter")
|
||||
.field("stream", &"<SendableRecordBatchStream>")
|
||||
.field("schema", &self.schema.arrow_schema().fields)
|
||||
.finish()
|
||||
}
|
||||
}
|
||||
|
||||
Reference in New Issue
Block a user