risingwave_frontend/optimizer/plan_node/
convert.rs

1// Copyright 2025 RisingWave Labs
2//
3// Licensed under the Apache License, Version 2.0 (the "License");
4// you may not use this file except in compliance with the License.
5// You may obtain a copy of the License at
6//
7//     http://www.apache.org/licenses/LICENSE-2.0
8//
9// Unless required by applicable law or agreed to in writing, software
10// distributed under the License is distributed on an "AS IS" BASIS,
11// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
12// See the License for the specific language governing permissions and
13// limitations under the License.
14
15use std::collections::HashMap;
16
17use risingwave_common::catalog::FieldDisplay;
18use risingwave_pb::stream_plan::StreamScanType;
19
20use super::*;
21use crate::optimizer::property::RequiredDist;
22
23/// `ToStream` converts a logical plan node to streaming physical node
24/// with an optional required distribution.
25///
26/// when implement this trait you can choose the two ways
27/// - Implement `to_stream` and use the default implementation of `to_stream_with_dist_required`
28/// - Or, if the required distribution is given, there will be a better plan. For example a hash
29///   join with hash-key(a,b) and the plan is required hash-distributed by (a,b,c). you can
30///   implement `to_stream_with_dist_required`, and implement `to_stream` with
31///   `to_stream_with_dist_required(RequiredDist::Any)`. you can see [`LogicalProject`] as an
32///   example.
33pub trait ToStream {
34    /// `logical_rewrite_for_stream` will rewrite the logical node, and return (`new_plan_node`,
35    /// `col_mapping`), the `col_mapping` is for original columns have been changed into some other
36    /// position.
37    ///
38    /// Now it is used to:
39    /// 1. ensure every plan node's output having pk column
40    /// 2. add `row_count`() in every Agg
41    fn logical_rewrite_for_stream(
42        &self,
43        ctx: &mut RewriteStreamContext,
44    ) -> Result<(LogicalPlanRef, ColIndexMapping)>;
45
46    /// `to_stream` is equivalent to `to_stream_with_dist_required(RequiredDist::Any)`
47    fn to_stream(&self, ctx: &mut ToStreamContext) -> Result<StreamPlanRef>;
48
49    /// convert the plan to streaming physical plan and satisfy the required distribution
50    fn to_stream_with_dist_required(
51        &self,
52        required_dist: &RequiredDist,
53        ctx: &mut ToStreamContext,
54    ) -> Result<StreamPlanRef> {
55        let ret = self.to_stream(ctx)?;
56        required_dist.streaming_enforce_if_not_satisfies(ret)
57    }
58}
59
60pub fn stream_enforce_eowc_requirement(
61    ctx: OptimizerContextRef,
62    plan: StreamPlanRef,
63    emit_on_window_close: bool,
64) -> Result<StreamPlanRef> {
65    if emit_on_window_close && !plan.emit_on_window_close() {
66        let watermark_groups = plan.watermark_columns().grouped();
67        let n_watermark_groups = watermark_groups.len();
68        if n_watermark_groups == 0 {
69            Err(ErrorCode::NotSupported(
70                "The query cannot be executed in Emit-On-Window-Close mode.".to_owned(),
71                "Try define a watermark column in the source, or avoid aggregation without GROUP BY".to_owned(),
72            )
73            .into())
74        } else {
75            let first_watermark_group = watermark_groups.values().next().unwrap();
76            let watermark_col_idx = first_watermark_group.indices().next().unwrap();
77            if n_watermark_groups > 1 {
78                ctx.warn_to_user(format!(
79                    "There are multiple unrelated watermark columns in the query, the first one `{}` is used.",
80                    FieldDisplay(&plan.schema()[watermark_col_idx])
81                ));
82            }
83            Ok(StreamEowcSort::new(plan, watermark_col_idx).into())
84        }
85    } else {
86        Ok(plan)
87    }
88}
89
90#[derive(Debug, Clone, Default)]
91pub struct RewriteStreamContext {
92    share_rewrite_map: HashMap<PlanNodeId, (LogicalPlanRef, ColIndexMapping)>,
93}
94
95impl RewriteStreamContext {
96    pub fn add_rewrite_result(
97        &mut self,
98        plan_node_id: PlanNodeId,
99        plan_ref: LogicalPlanRef,
100        col_change: ColIndexMapping,
101    ) {
102        let prev = self
103            .share_rewrite_map
104            .insert(plan_node_id, (plan_ref, col_change));
105        assert!(prev.is_none());
106    }
107
108    pub fn get_rewrite_result(
109        &self,
110        plan_node_id: PlanNodeId,
111    ) -> Option<&(LogicalPlanRef, ColIndexMapping)> {
112        self.share_rewrite_map.get(&plan_node_id)
113    }
114}
115
116#[derive(Debug, Clone)]
117pub struct ToStreamContext {
118    share_to_stream_map: HashMap<PlanNodeId, StreamPlanRef>,
119    emit_on_window_close: bool,
120    stream_scan_type: StreamScanType,
121}
122
123impl ToStreamContext {
124    pub fn new(emit_on_window_close: bool) -> Self {
125        Self::new_with_stream_scan_type(emit_on_window_close, StreamScanType::Backfill)
126    }
127
128    pub fn new_with_stream_scan_type(
129        emit_on_window_close: bool,
130        stream_scan_type: StreamScanType,
131    ) -> Self {
132        Self {
133            share_to_stream_map: HashMap::new(),
134            emit_on_window_close,
135            stream_scan_type,
136        }
137    }
138
139    pub fn stream_scan_type(&self) -> StreamScanType {
140        self.stream_scan_type
141    }
142
143    pub fn add_to_stream_result(&mut self, plan_node_id: PlanNodeId, plan_ref: StreamPlanRef) {
144        self.share_to_stream_map
145            .try_insert(plan_node_id, plan_ref)
146            .unwrap();
147    }
148
149    pub fn get_to_stream_result(&self, plan_node_id: PlanNodeId) -> Option<&StreamPlanRef> {
150        self.share_to_stream_map.get(&plan_node_id)
151    }
152
153    pub fn emit_on_window_close(&self) -> bool {
154        self.emit_on_window_close
155    }
156}
157
158/// `ToBatch` allows to convert a logical plan node to batch physical node
159/// with an optional required order.
160///
161/// The generated plan has single distribution and doesn't have any exchange nodes inserted.
162/// Use either [`ToLocalBatch`] or [`ToDistributedBatch`] after `ToBatch` to get a distributed plan.
163///
164/// To implement this trait you can choose one of the two ways:
165/// - Implement `to_batch` and use the default implementation of `to_batch_with_order_required`
166/// - Or, if a better plan can be generated when a required order is given, you can implement
167///   `to_batch_with_order_required`, and implement `to_batch` with
168///   `to_batch_with_order_required(&Order::any())`.
169pub trait ToBatch {
170    /// `to_batch` is equivalent to `to_batch_with_order_required(&Order::any())`
171    fn to_batch(&self) -> Result<BatchPlanRef>;
172    /// convert the plan to batch physical plan and satisfy the required Order
173    fn to_batch_with_order_required(&self, required_order: &Order) -> Result<BatchPlanRef> {
174        let ret = self.to_batch()?;
175        required_order.enforce_if_not_satisfies(ret)
176    }
177}
178
179/// Converts a batch physical plan to local plan for local execution.
180///
181/// This is quite similar to `ToBatch`, but different in several ways. For example it converts
182/// scan to exchange + scan.
183pub trait ToLocalBatch {
184    fn to_local(&self) -> Result<BatchPlanRef>;
185
186    /// Convert the plan to batch local physical plan and satisfy the required Order
187    fn to_local_with_order_required(&self, required_order: &Order) -> Result<BatchPlanRef> {
188        let ret = self.to_local()?;
189        required_order.enforce_if_not_satisfies(ret)
190    }
191}
192
193/// `ToDistributedBatch` allows to convert a batch physical plan to distributed batch plan, by
194/// insert exchange node, with an optional required order and distributed.
195///
196/// To implement this trait you can choose one of the two ways:
197/// - Implement `to_distributed` and use the default implementation of
198///   `to_distributed_with_required`
199/// - Or, if a better plan can be generated when a required order is given, you can implement
200///   `to_distributed_with_required`, and implement `to_distributed` with
201///   `to_distributed_with_required(&Order::any(), &RequiredDist::Any)`
202pub trait ToDistributedBatch {
203    /// `to_distributed` is equivalent to `to_distributed_with_required(&Order::any(),
204    /// &RequiredDist::Any)`
205    fn to_distributed(&self) -> Result<BatchPlanRef>;
206    /// insert the exchange in batch physical plan to satisfy the required Distribution and Order.
207    fn to_distributed_with_required(
208        &self,
209        required_order: &Order,
210        required_dist: &RequiredDist,
211    ) -> Result<BatchPlanRef> {
212        let ret = self.to_distributed()?;
213        let ret = required_order.enforce_if_not_satisfies(ret)?;
214        required_dist.batch_enforce_if_not_satisfies(ret, required_order)
215    }
216}