diff --git a/crates/asap-aware-mapping/src/logical_candidates.rs b/crates/asap-aware-mapping/src/logical_candidates.rs index 8c8a28913..a46005c63 100644 --- a/crates/asap-aware-mapping/src/logical_candidates.rs +++ b/crates/asap-aware-mapping/src/logical_candidates.rs @@ -4,12 +4,18 @@ //! target, not ranked plans or accuracy certificates. Workload composition and //! physical planning consume this inventory later; empirical models belong to //! selection. The legacy search API remains until planner cutover. -use std::collections::HashSet; +use std::collections::{BTreeMap, HashMap, HashSet}; use std::rc::Rc; -use asap_types::ir::{NonASAPOp, OperatorNode, QueryRoot, SchemaDerivationError}; -use asap_types::post_asap::{ExactKind, ExactParams, SketchKind}; -use asap_types::pre_asap::AggIntent; +use asap_types::ir::summary_coverage::{CoverageRegion, SummaryCoverage}; +use asap_types::ir::{ASAPOp, NonASAPOp, Operator, OperatorNode, QueryRoot, SchemaDerivationError}; +use asap_types::post_asap::{ + EntityIdentity, ExactKind, ExactParams, FieldDataType, GroupingStrategy, + NonNegativeWeightProof, SketchAlgorithm, SketchKind, SketchStatistic, SummaryInputExpr, + SummaryUpdate, WeightDomain, +}; +use asap_types::pre_asap::expr_ir::ColumnRef; +use asap_types::pre_asap::{AggIntent, Reduction, Schema}; use asap_types::types::AccuracyTarget; use thiserror::Error; @@ -40,6 +46,10 @@ pub enum LogicalCandidateError { AssignedTiming, #[error("approximate accuracy requires finite positive epsilon and delta in (0, 1)")] InvalidAccuracy, + #[error("choice must name one listed alternative per target")] + InvalidChoice, + #[error("unsupported local realization: {0}")] + Unsupported(&'static str), } /// Enumerate exact and summary choices in stable catalog order, without ranking @@ -119,6 +129,254 @@ pub fn enumerate_local_logical_candidates( Ok(LocalLogicalCandidates { roots, targets }) } +/// Build one whole-workload candidate (#509 Stage 1): `choice[i]` indexes +/// `inventory.targets[i].alternatives`. Each chosen non-pass-through target is +/// replaced by `SummaryAgg` followed by `SummaryEstimate` (sketch) or +/// `FinalizeExactAccumulator` (exact accumulator). Untouched sub-DAGs keep +/// their identity, so sharing between roots is preserved. +pub fn compose_logical_candidate( + inventory: &LocalLogicalCandidates, + choice: &[usize], +) -> Result, LogicalCandidateError> { + if choice.len() != inventory.targets.len() { + return Err(LogicalCandidateError::InvalidChoice); + } + let chosen = inventory + .targets + .iter() + .zip(choice) + .map(|(target, &index)| { + target + .alternatives + .get(index) + .map(|alternative| (Rc::as_ptr(&target.target), alternative)) + .ok_or(LogicalCandidateError::InvalidChoice) + }) + .collect::, _>>()?; + let mut memo = HashMap::new(); + inventory + .roots + .iter() + .map(|(id, root)| { + let root = match root { + QueryRoot::Operator(node) => { + QueryRoot::Operator(rewrite(node, &chosen, &mut memo)?) + } + QueryRoot::Scalar(expr) => { + for node in expr.operator_refs() { + rewrite(node, &chosen, &mut memo)?; + } + QueryRoot::Scalar( + expr.map_operator_refs(&mut |node| memo[&Rc::as_ptr(node)].clone()), + ) + } + }; + Ok((id.clone(), root)) + }) + .collect() +} + +type Memo = HashMap<*const OperatorNode, Rc>; + +fn rewrite( + node: &Rc, + chosen: &HashMap<*const OperatorNode, &Realization>, + memo: &mut Memo, +) -> Result, LogicalCandidateError> { + if let Some(done) = memo.get(&Rc::as_ptr(node)) { + return Ok(done.clone()); + } + for child in node.children() { + rewrite(child, chosen, memo)?; + } + let changed = node + .children() + .iter() + .any(|child| !Rc::ptr_eq(child, &memo[&Rc::as_ptr(child)])); + let rebuilt = match chosen.get(&Rc::as_ptr(node)) { + Some(realization) if **realization != Realization::PassThrough => { + realize(node, realization, memo)? + } + _ if changed => Rc::new(node.map_children(|child| memo[&Rc::as_ptr(child)].clone())?), + _ => node.clone(), + }; + memo.insert(Rc::as_ptr(node), rebuilt.clone()); + Ok(rebuilt) +} + +fn realize( + target: &OperatorNode, + realization: &Realization, + memo: &Memo, +) -> Result, LogicalCandidateError> { + let Some(NonASAPOp::Aggregate { + child, + reduction, + measures, + filters, + having, + .. + }) = target.non_asap() + else { + return Err(LogicalCandidateError::Unsupported( + "target is not an aggregate", + )); + }; + let [intent] = measures.as_slice() else { + return Err(LogicalCandidateError::Unsupported( + "multi-measure aggregate", + )); + }; + if !filters.is_empty() || having.is_some() { + return Err(LogicalCandidateError::Unsupported( + "filtered or HAVING aggregate", + )); + } + let child = memo[&Rc::as_ptr(child)].clone(); + let (family, query) = match realization { + Realization::ExactAggregate { kind, params } => ( + FieldDataType::ExactAggregate(kind.clone(), params.clone()), + None, + ), + Realization::Sketch(kind) => ( + FieldDataType::Sketch(kind.clone(), GroupingStrategy::default()), + Some(statistic(intent)?), + ), + _ => return Err(LogicalCandidateError::Unsupported("summary family")), + }; + let input = summary_update(intent, &family, reduction, &child.schema)?; + let state = OperatorNode::new(Operator::ASAP(ASAPOp::SummaryAgg { + child: child.clone(), + family, + input, + reduction: reduction.clone(), + grouping: GroupingStrategy::default(), + filter: None, + }))?; + // Whole-source coverage is declared, not proven: Pass 1 trusts that the + // state holds every observation of its source that reaches it (#570). + let coverage = SummaryCoverage { + source: single_source(&child)?, + regions: vec![CoverageRegion { + time_ms: None, + population: BTreeMap::new(), + }], + }; + let state = Rc::new(state.with_coverage(coverage)?); + let evaluation = match query { + Some(query) => ASAPOp::SummaryEstimate { + summary_input: state, + query, + }, + None => ASAPOp::FinalizeExactAccumulator { child: state }, + }; + Ok(OperatorNode::new_shared(Operator::ASAP(evaluation))?) +} + +fn single_source( + node: &Rc, +) -> Result { + let mut sources = Vec::new(); + for node in OperatorNode::reachable(node) { + if let Some(NonASAPOp::Scan { source, .. }) = node.non_asap() { + if !sources.contains(source) { + sources.push(source.clone()); + } + } + } + match <[_; 1]>::try_from(sources) { + Ok([source]) => Ok(source), + Err(_) => Err(LogicalCandidateError::Unsupported( + "summary coverage needs exactly one source", + )), + } +} + +/// What each input row contributes, following the legacy realization rules: +/// heap sketches rank series identities, frequency sketches count values, and +/// every other family reads the measure's input column. +fn summary_update( + intent: &AggIntent, + family: &FieldDataType, + reduction: &Reduction, + child: &Schema, +) -> Result { + let algorithm = match family { + FieldDataType::Sketch(kind, _) => Some(kind.algorithm()), + _ => None, + }; + let weight = crate::replacement::summarised_input(intent, child) + .map_err(|_| LogicalCandidateError::Unsupported("input column outside child schema"))?; + Ok(match (intent, algorithm) { + (AggIntent::TopK { .. }, Some(_)) => { + // SQL rows carry no implicit series identity to rank; closed + // PromQL rows carry it as a column. + if child.closed && !child.has_promql_series_identity() { + return Err(LogicalCandidateError::Unsupported( + "Top-K item identity for closed schemas", + )); + } + if reduction.group_keys().is_some_and(|keys| keys.is_without()) { + return Err(LogicalCandidateError::Unsupported( + "Top-K partitions given by `without`", + )); + } + let excluding = reduction + .group_keys() + .into_iter() + .flat_map(|keys| keys.iter()) + .filter_map(|&index| child.fields.get(index)) + .map(crate::replacement::column_ref) + .collect(); + // Rows that carry the full series identity rank it as a column, + // the item form the runtime builds keyed summaries from. + let item = if child.has_promql_series_identity() { + SummaryInputExpr::Column(ColumnRef::Named( + asap_types::pre_asap::schema::PROMQL_SERIES_IDENTITY.into(), + )) + } else { + SummaryInputExpr::EntityIdentity(EntityIdentity::PromqlLabelSet { excluding }) + }; + SummaryUpdate { + item: Some(item), + weight: SummaryInputExpr::Column(ColumnRef::SampleValue), + // Not proven non-negative; selection decides whether CMS is admissible. + weight_domain: WeightDomain::UnknownOrSigned, + } + } + (_, Some(SketchAlgorithm::UnivMon)) + | (AggIntent::Count { .. }, Some(SketchAlgorithm::Cms | SketchAlgorithm::CountSketch)) => { + SummaryUpdate { + item: Some(weight), + weight: SummaryInputExpr::Constant(1.0), + weight_domain: WeightDomain::NonNegative { + proof: NonNegativeWeightProof::UnitCount, + }, + } + } + _ => SummaryUpdate { + item: None, + weight, + weight_domain: WeightDomain::UnknownOrSigned, + }, + }) +} + +fn statistic(intent: &AggIntent) -> Result { + Ok(match intent { + AggIntent::Quantile { q, .. } => SketchStatistic::Quantile { q: *q }, + AggIntent::Cardinality { .. } => SketchStatistic::Cardinality, + AggIntent::FrequencyL2 { .. } => SketchStatistic::FrequencyL2, + AggIntent::FrequencyEntropy { .. } => SketchStatistic::FrequencyEntropy, + AggIntent::TopK { k, .. } => SketchStatistic::TopK { k: *k }, + AggIntent::Count { .. } => SketchStatistic::PointCount { + key: ColumnRef::SampleValue, + value: None, + }, + _ => return Err(LogicalCandidateError::Unsupported("sketch evaluation")), + }) +} + #[cfg(test)] mod tests { use super::*; diff --git a/crates/asap-aware-mapping/src/replacement.rs b/crates/asap-aware-mapping/src/replacement.rs index 2020be8a5..240d35746 100644 --- a/crates/asap-aware-mapping/src/replacement.rs +++ b/crates/asap-aware-mapping/src/replacement.rs @@ -3822,7 +3822,7 @@ fn summarised_column(intent: &AggIntent, child_schema: &Schema) -> ColumnRef { } } -fn column_ref(column: &Field) -> ColumnRef { +pub(crate) fn column_ref(column: &Field) -> ColumnRef { match &column.table { Some(t) => ColumnRef::Qualified { table: t.clone(), @@ -3840,7 +3840,7 @@ fn column_ref(column: &Field) -> ColumnRef { /// A tuple leg outside the child schema is an error rather than /// [`summarised_column`]'s sample-value fallback: a leg has no sample-value /// reading, and silently dropping one would under-count. -fn summarised_input( +pub(crate) fn summarised_input( intent: &AggIntent, child_schema: &Schema, ) -> Result { diff --git a/crates/asap-aware-mapping/tests/logical_candidates.rs b/crates/asap-aware-mapping/tests/logical_candidates.rs index 20211ce69..fa4c7d28d 100644 --- a/crates/asap-aware-mapping/tests/logical_candidates.rs +++ b/crates/asap-aware-mapping/tests/logical_candidates.rs @@ -241,3 +241,41 @@ fn topk_keeps_both_specialized_heap_choices() { ] ); } + +/// A workload candidate replaces only chosen targets, declares whole-source +/// coverage on the summary, and keeps unchosen plans identical. +#[test] +fn composed_candidate_replaces_chosen_target_with_summary_evaluation() { + use asap_aware_mapping::logical_candidates::compose_logical_candidate; + use asap_types::ir::ASAPOp; + let producer = aggregate(AggIntent::Cardinality { + cols: vec![0], + accuracy: approximate(), + }); + let inventory = + enumerate_local_logical_candidates(vec![(0, QueryRoot::Operator(producer.clone()))]) + .unwrap(); + let exact = compose_logical_candidate(&inventory, &[0]).unwrap(); + assert!(matches!(&exact[0].1, QueryRoot::Operator(node) if Rc::ptr_eq(node, &producer))); + + let hll = compose_logical_candidate(&inventory, &[1]).unwrap(); + let QueryRoot::Operator(estimate) = &hll[0].1 else { + panic!("operator root expected") + }; + let Some(ASAPOp::SummaryEstimate { summary_input, .. }) = estimate.asap() else { + panic!("summary evaluation expected") + }; + let coverage = summary_input.coverage.as_ref().unwrap(); + assert_eq!( + coverage.source, + Source::Table { + table_ref: "flows".into() + } + ); + assert!(coverage.regions[0].time_ms.is_none() && coverage.regions[0].population.is_empty()); + asap_types::ir::export::compile_logical_asap_workload(&[hll[0].1.clone()]) + .unwrap() + .validate() + .unwrap(); + assert!(compose_logical_candidate(&inventory, &[99]).is_err()); +} diff --git a/crates/devtools/src/bin/stage_pipeline.rs b/crates/devtools/src/bin/stage_pipeline.rs new file mode 100644 index 000000000..2627d02db --- /dev/null +++ b/crates/devtools/src/bin/stage_pipeline.rs @@ -0,0 +1,325 @@ +// cargo run -p asap-devtools --bin stage_pipeline -- \ +// --example planner-layering-1 --out planner-layering-example1.json +// cargo run -p asap-devtools --bin stage_pipeline -- \ +// --promql "topk by (job) (10, rate(x[1m]))" --epsilon 0.01 --delta 0.001 --out run.json +// +// Writes an `asap-stage-pipeline/v1` document (tools/dag-viewer) with the +// first two planner stages only: +// - stage0_logical: the frontends' workload DAG, one root per query; +// - stage1_logical_asap: Pass 1 workload candidates, one per choice of a +// local alternative for every target (the Cartesian product), in +// enumeration order and capped by `--max-candidates` (default 64). +// Stages 2 and 3, and therefore cost, are absent. +// +// `--promql` may repeat. `--epsilon`/`--delta` apply to every `--promql` +// query; without them the queries are exact. `--interval-ms` is the source +// cadence PromQL needs (default 15000). + +use std::rc::Rc; + +use asap_aware_mapping::logical_candidates::{ + compose_logical_candidate, enumerate_local_logical_candidates, LocalLogicalCandidates, +}; +use asap_aware_mapping::Realization; +use asap_types::ir::export::{ + compile_logical_asap_workload, LogicalASAPDAG, LogicalASAPDAGDocument, +}; +use asap_types::ir::{OperatorNode, QueryRoot}; +use asap_types::post_asap::SketchAlgorithm; +use asap_types::types::AccuracyTarget; +use asap_types::workload::{ + AccuracyRequirement, BatchEntry, DataArrival, DataDistribution, DataWorkload, DurationMs, + Evidence, EvidenceSource, LatencyRequirement, PlanningWorkload, Predictability, Query, + QueryLanguage, QueryRecurrence, QueryRequirements, QueryTimeScope, QueryWorkload, Rate, + RepeatedDemand, RepeatingEntry, RepetitionInterval, TimeSelection, +}; +use serde_json::{json, Value}; + +const USAGE: &str = "usage: stage_pipeline (--example planner-layering-1 | --promql ... \ +[--epsilon --delta ] [--interval-ms ]) [--max-candidates ] --out "; + +fn main() { + if let Err(message) = run(std::env::args().skip(1).collect()) { + eprintln!("stage_pipeline: {message}\n{USAGE}"); + std::process::exit(2); + } +} + +fn run(args: Vec) -> Result<(), String> { + let mut example = None; + let mut queries = Vec::new(); + let (mut epsilon, mut delta, mut interval_ms) = (None, None, 15_000u64); + let mut max_candidates = 64usize; + let mut out = None; + let mut args = args.into_iter(); + while let Some(flag) = args.next() { + let mut value = || args.next().ok_or(format!("{flag} needs a value")); + let number = |v: String| v.parse::().map_err(|e| format!("{v}: {e}")); + match flag.as_str() { + "--example" => example = Some(value()?), + "--promql" => queries.push(value()?), + "--epsilon" => epsilon = Some(number(value()?)?), + "--delta" => delta = Some(number(value()?)?), + "--interval-ms" => interval_ms = value()?.parse().map_err(|e| format!("{e}"))?, + "--max-candidates" => max_candidates = value()?.parse().map_err(|e| format!("{e}"))?, + "--out" => out = Some(value()?), + other => return Err(format!("unknown argument {other}")), + } + } + let workload = match (example.as_deref(), queries.is_empty()) { + (Some("planner-layering-1"), true) => planner_layering_example1(), + (Some(other), true) => return Err(format!("unknown example {other}")), + (None, false) => { + let accuracy = match (epsilon, delta) { + (None, None) => AccuracyTarget::Exact, + (Some(epsilon), None) => AccuracyTarget::Epsilon(epsilon), + (Some(epsilon), Some(delta)) => AccuracyTarget::EpsilonDelta { epsilon, delta }, + (None, Some(_)) => return Err("--delta needs --epsilon".into()), + }; + promql_batch(&queries, accuracy, interval_ms) + } + _ => return Err("give exactly one of --example or --promql".into()), + }; + let out = out.ok_or("--out is required")?; + let document = stage_pipeline(&workload, max_candidates)?; + let text = serde_json::to_string_pretty(&document).map_err(|e| e.to_string())? + "\n"; + std::fs::write(&out, text).map_err(|e| format!("{out}: {e}")) +} + +fn stage_pipeline(workload: &PlanningWorkload, max_candidates: usize) -> Result { + let roots = asap_frontend_promql::lower_promql_query_workload(workload, 0) + .map_err(|e| format!("lowering: {e}"))?; + let stage0 = export(&roots)?; + let inventory = enumerate_local_logical_candidates(roots.into_iter().enumerate().collect()) + .map_err(|e| format!("Pass 1: {e}"))?; + let combinations = inventory + .targets + .iter() + .map(|target| target.alternatives.len()) + .product::(); + let owners = target_owners(&inventory); + let mut candidates = Vec::new(); + let mut choice = vec![0; inventory.targets.len()]; + for index in 0..combinations.min(max_candidates) { + let roots = compose_logical_candidate(&inventory, &choice) + .map_err(|e| format!("candidate {choice:?}: {e}"))?; + let roots: Vec<_> = roots.into_iter().map(|(_, root)| root).collect(); + candidates.push(json!({ + "id": format!("L{}", index + 1), + "label": label(&inventory, &owners, &choice), + "dag": export(&roots)?, + })); + // Mixed-radix increment: the last target varies fastest. + for (digit, target) in choice.iter_mut().zip(&inventory.targets).rev() { + *digit += 1; + if *digit < target.alternatives.len() { + break; + } + *digit = 0; + } + } + Ok(json!({ + "format": "asap-stage-pipeline/v1", + "workload": { "queries": workload_queries(workload) }, + "stage0_logical": { "dag": stage0 }, + "stage1_logical_asap": { + "combinations": combinations, + "capped": combinations > max_candidates, + "candidates": candidates, + }, + })) +} + +fn export(roots: &[QueryRoot]) -> Result { + let dag = compile_logical_asap_workload(roots).map_err(|e| format!("export: {e}"))?; + LogicalASAPDAGDocument::new(dag.clone()) + .validate() + .map_err(|e| format!("export validation: {e}"))?; + Ok(dag) +} + +/// The first query whose plan reaches each target (enumeration order). +fn target_owners(inventory: &LocalLogicalCandidates) -> Vec { + inventory + .targets + .iter() + .map(|target| { + inventory + .roots + .iter() + .position(|(_, root)| { + let operators = match root { + QueryRoot::Operator(node) => vec![node], + QueryRoot::Scalar(expr) => expr.operator_refs(), + }; + operators.into_iter().any(|node| { + OperatorNode::reachable(node) + .iter() + .any(|n| Rc::ptr_eq(n, &target.target)) + }) + }) + .expect("every target is reached from a root") + }) + .collect() +} + +/// E.g. "Q1 exact · Q2 CMS+heap"; exact accumulators are listed in parentheses. +fn label(inventory: &LocalLogicalCandidates, owners: &[usize], choice: &[usize]) -> String { + (0..inventory.roots.len()) + .map(|query| { + let mut sketches = Vec::new(); + let mut accumulators = Vec::new(); + for (target, (&owner, &index)) in + inventory.targets.iter().zip(owners.iter().zip(choice)) + { + if owner != query { + continue; + } + match &target.alternatives[index] { + Realization::PassThrough => {} + Realization::ExactAggregate { kind, .. } => { + accumulators.push(format!("{kind:?} acc")) + } + Realization::Sketch(kind) => sketches.push(match kind.algorithm() { + SketchAlgorithm::CmsWithHeap => "CMS+heap".to_string(), + SketchAlgorithm::CountSketchWithHeap => "CountSketch+heap".to_string(), + other => format!("{other:?}"), + }), + other => sketches.push(format!("{other:?}")), + } + } + let mut text = format!("Q{} ", query + 1); + text += &if sketches.is_empty() { + "exact".to_string() + } else { + sketches.join(" + ") + }; + if !accumulators.is_empty() { + text += &format!(" ({})", accumulators.join(", ")); + } + text + }) + .collect::>() + .join(" · ") +} + +fn workload_queries(workload: &PlanningWorkload) -> Vec { + workload + .query_workload + .entries() + .enumerate() + .map(|(index, entry)| { + let accuracy = match entry.requirements.accuracy.target() { + AccuracyTarget::Exact => json!("exact"), + AccuracyTarget::Epsilon(epsilon) => json!({ "epsilon": epsilon }), + AccuracyTarget::EpsilonDelta { epsilon, delta } => { + json!({ "epsilon": epsilon, "delta": delta }) + } + }; + let mut requirements = json!({ "accuracy": accuracy }); + if let LatencyRequirement::ExplicitMaxMs(ms) = entry.requirements.response_latency { + requirements["latency_ms"] = json!(ms); + } + if let QueryRecurrence::Repeated(RepeatedDemand::FixedInterval(interval)) = + &entry.recurrence + { + requirements["repeat_interval_ms"] = json!(interval.0); + } + json!({ + "id": format!("q{}", index + 1), + "language": "promql", + "text": entry.query.0, + "requirements": requirements, + }) + }) + .collect() +} + +fn declared(value: T) -> Evidence { + Evidence { + value: Some(value), + source: EvidenceSource::Declared, + ..Default::default() + } +} + +fn promql_batch( + queries: &[String], + accuracy: AccuracyTarget, + interval_ms: u64, +) -> PlanningWorkload { + PlanningWorkload { + query_workload: QueryWorkload { + language: QueryLanguage::PromQL, + query_batch: Some( + queries + .iter() + .map(|query| BatchEntry { + query: Query(query.clone()), + requirements: QueryRequirements { + accuracy: AccuracyRequirement::Explicit(accuracy.clone()), + ..Default::default() + }, + predictability: Default::default(), + invocations: 1, + execute_at: None, + time_selection: Default::default(), + }) + .collect(), + ), + repeating_queries: None, + }, + data_workload: Some(DataWorkload { + data_ingestion_interval: declared(DurationMs(interval_ms)), + ..Default::default() + }), + } +} + +/// #509 Example 1 (docs/design_docs/proposals/planner-layering.md) over its +/// shared data workload; matches the acceptance spec's test workload. +fn planner_layering_example1() -> PlanningWorkload { + let panel = |query: &str, accuracy, response_latency| RepeatingEntry { + query: Query(query.into()), + demand: RepeatedDemand::FixedInterval(RepetitionInterval(10_000)), + requirements: QueryRequirements { + accuracy: AccuracyRequirement::Explicit(accuracy), + response_latency, + }, + predictability: Predictability::Predictable { known_at: None }, + time_selection: TimeSelection { + scope: QueryTimeScope::RealTime, + lookback: Some(DurationMs(60_000)), + as_of: None, + }, + }; + PlanningWorkload { + query_workload: QueryWorkload { + language: QueryLanguage::PromQL, + query_batch: None, + repeating_queries: Some(vec![ + panel( + "sum by (job) (rate(http_requests_total[1m]))", + AccuracyTarget::Exact, + LatencyRequirement::Unspecified, + ), + panel( + "topk by (job) (10, sum_over_time(http_requests_total[1m]))", + AccuracyTarget::EpsilonDelta { + epsilon: 0.01, + delta: 0.001, + }, + LatencyRequirement::ExplicitMaxMs(100.0), + ), + ]), + }, + data_workload: Some(DataWorkload { + arrival: DataArrival::ContinuouslyIngesting, + data_ingestion_interval: declared(DurationMs(15_000)), + ingestion_volume: Evidence::default(), + ingestion_rate: declared(Rate(1_000_000.0 / 15.0)), + input_cardinality: declared(1_000_000), + distribution: declared(DataDistribution::Zipf), + }), + } +} diff --git a/crates/devtools/tests/stage_pipeline.rs b/crates/devtools/tests/stage_pipeline.rs new file mode 100644 index 000000000..c84bb15b5 --- /dev/null +++ b/crates/devtools/tests/stage_pipeline.rs @@ -0,0 +1,73 @@ +//! `stage_pipeline` writes a valid Stage 0/1 viewer document for #509 Example 1. +use std::collections::HashSet; +use std::path::PathBuf; +use std::process::Command; + +use asap_types::ir::export::{LogicalASAPDAG, LogicalASAPDAGDocument}; +use serde_json::Value; + +const COMMITTED: &str = "../../tools/dag-viewer/examples/planner-layering-example1.json"; + +fn generate(extra: &[&str]) -> Value { + let out = std::env::temp_dir().join(format!( + "stage_pipeline_{}_{}.json", + std::process::id(), + extra.len() + )); + let status = Command::new(env!("CARGO_BIN_EXE_stage_pipeline")) + .args(["--example", "planner-layering-1", "--out"]) + .arg(&out) + .args(extra) + .status() + .unwrap(); + assert!(status.success()); + let document = serde_json::from_str(&std::fs::read_to_string(&out).unwrap()).unwrap(); + std::fs::remove_file(out).unwrap(); + document +} + +fn validated_dag(value: &Value, queries: usize) { + let dag: LogicalASAPDAG = serde_json::from_value(value.clone()).unwrap(); + assert_eq!(dag.roots.len(), queries); + LogicalASAPDAGDocument::new(dag).validate().unwrap(); +} + +/// Every exported DAG validates and has one root per query; ids are unique; +/// only Stages 0 and 1 are present; the committed fixture is current. +#[test] +fn example1_document_is_valid_and_committed_fixture_is_current() { + let document = generate(&[]); + let committed: Value = serde_json::from_str( + &std::fs::read_to_string(PathBuf::from(env!("CARGO_MANIFEST_DIR")).join(COMMITTED)) + .unwrap(), + ) + .unwrap(); + assert_eq!(document, committed, "regenerate the committed fixture"); + + assert_eq!(document["format"], "asap-stage-pipeline/v1"); + let queries = document["workload"]["queries"].as_array().unwrap().len(); + assert_eq!(queries, 2); + assert!(document.get("stage2_physical_asap").is_none()); + assert!(document.get("stage3_selection").is_none()); + validated_dag(&document["stage0_logical"]["dag"], queries); + + let stage1 = &document["stage1_logical_asap"]; + let candidates = stage1["candidates"].as_array().unwrap(); + assert_eq!(stage1["capped"], false); + assert_eq!(stage1["combinations"], candidates.len()); + let mut ids = HashSet::new(); + for candidate in candidates { + assert!(ids.insert(candidate["id"].as_str().unwrap())); + validated_dag(&candidate["dag"], queries); + } +} + +/// The Cartesian product is cut at `--max-candidates` and says so. +#[test] +fn candidate_cap_is_recorded() { + let document = generate(&["--max-candidates", "5"]); + let stage1 = &document["stage1_logical_asap"]; + assert_eq!(stage1["capped"], true); + assert_eq!(stage1["candidates"].as_array().unwrap().len(), 5); + assert!(stage1["combinations"].as_u64().unwrap() > 5); +} diff --git a/crates/types/src/ir/asap.rs b/crates/types/src/ir/asap.rs index b9fbcf6f5..b1c2297c1 100644 --- a/crates/types/src/ir/asap.rs +++ b/crates/types/src/ir/asap.rs @@ -345,6 +345,9 @@ impl ASAPOp { for f in &mut out.fields { if let FieldDataType::ExactAggregate(kind, _) = &f.dtype { if let Some(result) = &value_result { + // The finalized value replaces the aggregate it + // realizes, so it takes that aggregate's column. + f.name = result.name.clone(); f.dtype = result.dtype.clone(); f.nullable = result.nullable; } else { diff --git a/tools/dag-viewer/examples/planner-layering-example1.json b/tools/dag-viewer/examples/planner-layering-example1.json new file mode 100644 index 000000000..9d9d50722 --- /dev/null +++ b/tools/dag-viewer/examples/planner-layering-example1.json @@ -0,0 +1,23548 @@ +{ + "format": "asap-stage-pipeline/v1", + "stage0_logical": { + "dag": { + "edges": [ + { + "consumer": 1, + "grouping": "NotApplicable", + "intermediate_schema": { + "closed": false, + "fields": [ + { + "dtype": { + "Plain": "timestamp" + }, + "name": "ts", + "nullable": false, + "table": null + }, + { + "dtype": { + "Plain": "float64" + }, + "name": "value", + "nullable": false, + "table": null + }, + { + "dtype": { + "Plain": "utf8" + }, + "name": "job", + "nullable": true, + "table": null + } + ], + "time_index": 0, + "unique_keys": [] + }, + "producer": 0, + "role": "Input" + }, + { + "consumer": 2, + "grouping": "NotApplicable", + "intermediate_schema": { + "closed": false, + "fields": [ + { + "dtype": { + "Plain": 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