feat: support nested aggregate subqueries

influxdb_iox/tests/query_tests/cases/in/issue_6112.influxql.expected

@@ -2821,3 +2821,25 @@ tags: cpu=cpu1
 | 2022-10-31T02:00:00 | 1.98       |
 | 2022-10-31T02:00:10 | 1.99       |
 +---------------------+------------+
+-- InfluxQL: SELECT * FROM (SELECT MAX(value) FROM (SELECT DISTINCT(usage_idle) AS value FROM cpu)) GROUP BY cpu;
+name: cpu
+tags: cpu=cpu-total
++---------------------+------+
+| time                | max  |
++---------------------+------+
+| 1970-01-01T00:00:00 | 2.99 |
++---------------------+------+
+name: cpu
+tags: cpu=cpu0
++---------------------+------+
+| time                | max  |
++---------------------+------+
+| 1970-01-01T00:00:00 | 0.99 |
++---------------------+------+
+name: cpu
+tags: cpu=cpu1
++---------------------+------+
+| time                | max  |
++---------------------+------+
+| 1970-01-01T00:00:00 | 1.99 |
++---------------------+------+

iox_query_influxql/src/plan/planner.rs

@@ -2,7 +2,7 @@ mod select;
 
 use crate::plan::ir::{DataSource, Field, Select, SelectQuery};
 use crate::plan::planner::select::{
-    check_exprs_satisfy_columns, fields_to_exprs_no_nulls, make_tag_key_column_meta, plan_with_sort,
+    fields_to_exprs_no_nulls, make_tag_key_column_meta, plan_with_sort,
 };
 use crate::plan::planner_time_range_expression::{
     duration_expr_to_nanoseconds, expr_to_df_interval_dt, time_range_to_df_expr,
@@ -21,7 +21,7 @@ use datafusion::datasource::{provider_as_source, MemTable};
 use datafusion::logical_expr::expr_rewriter::normalize_col;
 use datafusion::logical_expr::logical_plan::builder::project;
 use datafusion::logical_expr::logical_plan::Analyze;
-use datafusion::logical_expr::utils::{expr_as_column_expr, find_aggregate_exprs};
+use datafusion::logical_expr::utils::find_aggregate_exprs;
 use datafusion::logical_expr::{
     binary_expr, col, date_bin, expr, expr::WindowFunction, lit, lit_timestamp_nano, now,
     window_function, Aggregate, AggregateFunction, AggregateUDF, Between, BuiltInWindowFunction,
@@ -754,7 +754,7 @@ impl<'a> InfluxQLToLogicalPlan<'a> {
 
             let schema = ds.schema(self.s)?;
             group_by_exprs.extend(group_by_tag_set.iter().filter_map(|name| {
-                if let Some(InfluxColumnType::Tag) = schema.field_type_by_name(name) {
+                if schema.is_tag_field(name) {
                     Some(name.as_expr())
                 } else {
                     None
@@ -818,13 +818,6 @@ impl<'a> InfluxQLToLogicalPlan<'a> {
         // the final projection from the aggregate operator.
         let aggr_projection_exprs = [aggr_group_by_exprs, aggr_exprs].concat();
 
-        // Replace any expressions that are not a column with a column referencing
-        // an output column from the aggregate schema.
-        let column_exprs_post_aggr = aggr_projection_exprs
-            .iter()
-            .map(|expr| expr_as_column_expr(expr, &plan))
-            .collect::<Result<Vec<Expr>>>()?;
-
         // Create a literal expression for `value` if the strategy
         // is `FILL(<value>)`
         let fill_if_null = match fill_option {
@@ -850,29 +843,6 @@ impl<'a> InfluxQLToLogicalPlan<'a> {
             })
             .collect::<Result<Vec<Expr>>>()?;
 
-        // Strip the NULL columns, which are tags that do not exist in the aggregate
-        // table schema. The NULL columns are projected as scalar values in the final
-        // projection.
-        let select_exprs_post_aggr_no_nulls = select_exprs_post_aggr
-            .iter()
-            .filter(|expr| match expr {
-                Expr::Alias(expr, _) => !matches!(**expr, Expr::Literal(ScalarValue::Null)),
-                _ => true,
-            })
-            .cloned()
-            .collect::<Vec<_>>();
-
-        // Finally, we ensure that the re-written projection can be resolved
-        // from the aggregate output columns and that there are no
-        // column references that are not aggregates.
-        //
-        // This will identify issues such as:
-        //
-        // SELECT COUNT(field), field FROM foo
-        //
-        // where the field without the aggregate is not valid.
-        check_exprs_satisfy_columns(&column_exprs_post_aggr, &select_exprs_post_aggr_no_nulls)?;
-
         Ok((plan, select_exprs_post_aggr))
     }
 

iox_query_influxql/src/plan/planner/select.rs

@@ -1,8 +1,6 @@
-use crate::plan::error;
 use crate::plan::ir::Field;
 use arrow::datatypes::DataType;
 use datafusion::common::{DFSchemaRef, Result};
-use datafusion::logical_expr::utils::find_column_exprs;
 use datafusion::logical_expr::{Expr, LogicalPlan, LogicalPlanBuilder};
 use datafusion_util::AsExpr;
 use generated_types::influxdata::iox::querier::v1::influx_ql_metadata::TagKeyColumn;
@@ -11,19 +9,6 @@ use schema::INFLUXQL_MEASUREMENT_COLUMN_NAME;
 use std::collections::HashMap;
 use std::ops::Deref;
 
-/// Determines that all [`Expr::Column`] references in `exprs` refer to a
-/// column in `columns`.
-pub(crate) fn check_exprs_satisfy_columns(columns: &[Expr], exprs: &[Expr]) -> Result<()> {
-    if !columns.iter().all(|c| matches!(c, Expr::Column(_))) {
-        return error::internal("expected Expr::Column");
-    }
-    let column_exprs = find_column_exprs(exprs);
-    if column_exprs.iter().any(|expr| !columns.contains(expr)) {
-        return error::query("mixing aggregate and non-aggregate columns is not supported");
-    }
-    Ok(())
-}
-
 pub(super) fn make_tag_key_column_meta(
     fields: &[Field],
     tag_set: &[&str],