Merge pull request #31878 from mgree/track-column-names

[explain] propagate column name information

Author: ggevay

ci/nightly/pipeline.template.yml

@@ -1352,7 +1352,7 @@ steps:
         plugins:
           - ./ci/plugins/mzcompose:
               composition: sqlsmith
-              args: [--max-joins=15, --explain-only, --runtime=1500]
+              args: [--max-joins=12, --explain-only, --runtime=1500]
 
   - group: SQLancer
     key: sqlancer

doc/developer/testdrive.md

@@ -943,5 +943,21 @@ SELECT mz_version_num() < 2601;
 
 The `[version>=13000]` property allows running the action or query only when we are connected to a Materialize instance with a compatible version. The supported comparison operators are `>`, `>=`, `=`, `<=` and `<`. The version number is the same as returned from [`mz_version_num()`](https://materialize.com/docs/sql/functions/#system-information-func) and has the same format `XXXYYYZZ`, where `XX` is the major version, `YYY` is the minor version and `ZZ` is the patch version. So in the example we are only running the `SELECT 1` query if the Materialize instance is of version `v0.130.0` or higher. For lower versions no query is run and no comparison of results is performed subsequently.
 
+You can bound the version above and below using the following syntax:
+
+```
+?[13500<=version<14300] SELECT 1;
+1
+```
+
+You can use `<` or `<=` freely. The following are equivalent:
+
+```
+?[version>14300] SELECT 1;
+1
+?[14300<version] SELECT 1;
+1
+```
+
 [confluent-arm]: https://github.com/confluentinc/common-docker/issues/117#issuecomment-948789717
 [aws-creds]: https://github.com/MaterializeInc/i2/blob/main/doc/aws-access.md

misc/python/materialize/checks/all_checks/explain_catalog_item.py

@@ -74,7 +74,18 @@ def validate(self) -> Testdrive:
             Target cluster: quickstart
 
 
-            ?[version>=13500] EXPLAIN OPTIMIZED PLAN AS VERBOSE TEXT FOR MATERIALIZED VIEW explain_mv2;
+            ?[version>=14400] EXPLAIN OPTIMIZED PLAN AS VERBOSE TEXT FOR MATERIALIZED VIEW explain_mv2;
+            materialize.public.explain_mv2:
+              Filter (#1{y} = 7)
+                ReadStorage materialize.public.explain_item_t2
+
+            Source materialize.public.explain_item_t2
+              filter=((#1{y} = 7))
+
+            Target cluster: quickstart
+
+
+            ?[13500<=version<14400] EXPLAIN OPTIMIZED PLAN AS VERBOSE TEXT FOR MATERIALIZED VIEW explain_mv2;
             materialize.public.explain_mv2:
               Filter (#1 = 7)
                 ReadStorage materialize.public.explain_item_t2

src/adapter/src/catalog/apply.rs

@@ -1753,7 +1753,7 @@ impl CatalogState {
                 .variant
                 .index_by()
                 .into_iter()
-                .map(MirScalarExpr::Column)
+                .map(MirScalarExpr::column)
                 .collect(),
             create_sql: index_sql(
                 index_item_name,

src/adapter/src/catalog/builtin_table_updates.rs

@@ -1661,7 +1661,7 @@ impl CatalogState {
                 .expect("missing sql information for index key")
                 .to_ast_string_simple();
             let (field_number, expression) = match key {
-                MirScalarExpr::Column(col) => {
+                MirScalarExpr::Column(col, _) => {
                     (Datum::UInt64(u64::cast_from(*col + 1)), Datum::Null)
                 }
                 _ => (Datum::Null, Datum::String(&key_sql)),

src/adapter/src/coord/peek.rs

@@ -95,7 +95,7 @@ impl<T> PeekDataflowPlan<T> {
         let key = typ
             .default_key()
             .into_iter()
-            .map(MirScalarExpr::Column)
+            .map(MirScalarExpr::column)
             .collect::<Vec<_>>();
         let (permutation, thinning) = permutation_for_arrangement(&key, arity);
         Self {
@@ -397,7 +397,7 @@ pub fn create_fast_path_plan<T: Timestamp>(
                             if !preserves_order(&col.scalar_type) {
                                 break;
                             }
-                            let col_expr = MirScalarExpr::Column(idx);
+                            let col_expr = MirScalarExpr::column(idx);
 
                             let Some((literal, _)) = filters
                                 .iter()

src/adapter/src/optimize/peek.rs

@@ -244,7 +244,7 @@ impl<'s> Optimize<LocalMirPlan<Resolved<'s>>> for Optimizer {
         let key = typ
             .default_key()
             .iter()
-            .map(|k| MirScalarExpr::Column(*k))
+            .map(|k| MirScalarExpr::column(*k))
             .collect();
 
         // The assembled dataflow contains a view and an index of that view.

src/compute-types/src/plan/lowering.rs

@@ -575,7 +575,7 @@ impl Context {
                         // All columns of the constant input will be part of the arrangement key.
                         let source_arrangement = (
                             (0..key.len())
-                                .map(MirScalarExpr::Column)
+                                .map(MirScalarExpr::column)
                                 .collect::<Vec<_>>(),
                             (0..key.len()).collect::<Vec<_>>(),
                             Vec::<usize>::new(),

src/compute-types/src/plan/reduce.rs

@@ -807,7 +807,7 @@ impl ReducePlan {
     /// that key a single arrangement.
     pub fn keys(&self, key_arity: usize, arity: usize) -> AvailableCollections {
         let key = (0..key_arity)
-            .map(MirScalarExpr::Column)
+            .map(MirScalarExpr::column)
             .collect::<Vec<_>>();
         let (permutation, thinning) = permutation_for_arrangement(&key, arity);
         AvailableCollections::new_arranged(vec![(key, permutation, thinning)], None)

src/compute-types/src/plan/threshold.rs

@@ -126,7 +126,7 @@ impl ThresholdPlan {
         // Arrange the input by all columns in order.
         let mut all_columns = Vec::new();
         for column in 0..arity {
-            all_columns.push(mz_expr::MirScalarExpr::Column(column));
+            all_columns.push(mz_expr::MirScalarExpr::column(column));
         }
         let (permutation, thinning) = permutation_for_arrangement(&all_columns, arity);
         let ensure_arrangement = (all_columns, permutation, thinning);