sql/stats: use nil *eval.Context as CompareContext when forecasting

When forecasting table statistics, we don't need a full *eval.Context.
We can simply use a nil *eval.Context as a tree.CompareContext. This
means we don't have to plumb an eval.Context into the stats cache.

Assists: cockroachdb#79872

Release note: None

pkg/sql/rowexec/sample_aggregator.go

@@ -616,6 +616,8 @@ func (s *sampleAggregator) generateHistogram(
 			prevCapacity, sr.Cap(),
 		)
 	}
+	// TODO(michae2): Instead of using the flowCtx's evalCtx, investigate
+	// whether this can use a nil *eval.Context.
 	h, _, err := stats.EquiDepthHistogram(evalCtx, colType, values, numRows, distinctCount, maxBuckets)
 	return h, err
 }

pkg/sql/sem/eval/context.go

@@ -562,6 +562,9 @@ func (ec *Context) SetStmtTimestamp(ts time.Time) {
 
 // GetLocation returns the session timezone.
 func (ec *Context) GetLocation() *time.Location {
+	if ec == nil {
+		return time.UTC
+	}
 	return ec.SessionData().GetLocation()
 }
 

pkg/sql/show_stats.go

@@ -179,7 +179,7 @@ func (p *planner) ShowTableStats(ctx context.Context, n *tree.ShowTableStats) (p
 					observed[i], observed[j] = observed[j], observed[i]
 				}
 
-				forecasts := stats.ForecastTableStatistics(ctx, p.EvalContext(), observed)
+				forecasts := stats.ForecastTableStatistics(ctx, observed)
 
 				// Iterate in reverse order to match the ORDER BY "columnIDs".
 				for i := len(forecasts) - 1; i >= 0; i-- {

pkg/sql/stats/forecast.go

@@ -17,6 +17,7 @@ import (
 
 	"github.com/cockroachdb/cockroach/pkg/jobs/jobspb"
 	"github.com/cockroachdb/cockroach/pkg/sql/opt/cat"
+	"github.com/cockroachdb/cockroach/pkg/sql/sem/eval"
 	"github.com/cockroachdb/cockroach/pkg/sql/sem/tree"
 	"github.com/cockroachdb/cockroach/pkg/sql/types"
 	"github.com/cockroachdb/cockroach/pkg/util/log"
@@ -57,12 +58,7 @@ const maxForecastDistance = time.Hour * 24 * 7
 //
 // ForecastTableStatistics is deterministic: given the same observations it will
 // return the same forecasts.
-//
-// TODO(michae2): Use nil *eval.Context or custom tree.CompareContext instead of
-// taking an evalCtx.
-func ForecastTableStatistics(
-	ctx context.Context, evalCtx tree.CompareContext, observed []*TableStatistic,
-) []*TableStatistic {
+func ForecastTableStatistics(ctx context.Context, observed []*TableStatistic) []*TableStatistic {
 	// Early sanity check. We'll check this again in forecastColumnStatistics.
 	if len(observed) < minObservationsForForecast {
 		return nil
@@ -102,9 +98,7 @@ func ForecastTableStatistics(
 
 	forecasts := make([]*TableStatistic, 0, len(forecastCols))
 	for _, colKey := range forecastCols {
-		forecast, err := forecastColumnStatistics(
-			ctx, evalCtx, observedByCols[colKey], at, minGoodnessOfFit,
-		)
+		forecast, err := forecastColumnStatistics(ctx, observedByCols[colKey], at, minGoodnessOfFit)
 		if err != nil {
 			log.VEventf(
 				ctx, 2, "could not forecast statistics for table %v columns %s: %v",
@@ -135,11 +129,7 @@ func ForecastTableStatistics(
 // forecastColumnStatistics is deterministic: given the same observations and
 // forecast time, it will return the same forecast.
 func forecastColumnStatistics(
-	ctx context.Context,
-	evalCtx tree.CompareContext,
-	observed []*TableStatistic,
-	at time.Time,
-	minRequiredFit float64,
+	ctx context.Context, observed []*TableStatistic, at time.Time, minRequiredFit float64,
 ) (forecast *TableStatistic, err error) {
 	if len(observed) < minObservationsForForecast {
 		return nil, errors.New("not enough observations to forecast statistics")
@@ -263,6 +253,8 @@ func forecastColumnStatistics(
 	// histogram. NOTE: If any of the observed histograms were for inverted
 	// indexes this will produce an incorrect histogram.
 	if observed[0].HistogramData != nil {
+		var evalCtx *eval.Context
+
 		hist, err := predictHistogram(
 			ctx, evalCtx, observed, forecastAt, minRequiredFit, nonNullRowCount,
 		)

pkg/sql/stats/forecast_test.go

@@ -18,10 +18,8 @@ import (
 	"time"
 
 	"github.com/cockroachdb/cockroach/pkg/jobs/jobspb"
-	"github.com/cockroachdb/cockroach/pkg/settings/cluster"
 	"github.com/cockroachdb/cockroach/pkg/sql/catalog/descpb"
 	"github.com/cockroachdb/cockroach/pkg/sql/sem/catid"
-	"github.com/cockroachdb/cockroach/pkg/sql/sem/eval"
 	"github.com/cockroachdb/cockroach/pkg/sql/types"
 	"github.com/cockroachdb/cockroach/pkg/util/timeutil"
 )
@@ -581,7 +579,6 @@ func TestForecastColumnStatistics(t *testing.T) {
 		},
 	}
 	ctx := context.Background()
-	evalCtx := eval.NewTestingEvalContext(cluster.MakeTestingClusterSettings())
 	for i, tc := range testCases {
 		t.Run(strconv.Itoa(i), func(t *testing.T) {
 
@@ -593,7 +590,7 @@ func TestForecastColumnStatistics(t *testing.T) {
 			expected := tc.forecast.toTableStatistic(jobspb.ForecastStatsName, i)
 			at := testStatTime(tc.at)
 
-			forecast, err := forecastColumnStatistics(ctx, evalCtx, observed, at, 1)
+			forecast, err := forecastColumnStatistics(ctx, observed, at, 1)
 			if err != nil {
 				if !tc.err {
 					t.Errorf("test case %d unexpected forecastColumnStatistics err: %v", i, err)

pkg/sql/stats/quantile_test.go

@@ -20,7 +20,6 @@ import (
 	"strconv"
 	"testing"
 
-	"github.com/cockroachdb/cockroach/pkg/settings/cluster"
 	"github.com/cockroachdb/cockroach/pkg/sql/opt/cat"
 	"github.com/cockroachdb/cockroach/pkg/sql/sem/eval"
 	"github.com/cockroachdb/cockroach/pkg/sql/sem/tree"
@@ -41,7 +40,7 @@ func TestRandomQuantileRoundTrip(t *testing.T) {
 		types.Float4,
 	}
 	colTypes = append(colTypes, types.Scalar...)
-	evalCtx := eval.NewTestingEvalContext(cluster.MakeTestingClusterSettings())
+	var evalCtx *eval.Context
 	rng, seed := randutil.NewTestRand()
 	for _, colType := range colTypes {
 		if canMakeQuantile(histVersion, colType) {
@@ -566,7 +565,7 @@ func TestQuantileToHistogram(t *testing.T) {
 			err:  true,
 		},
 	}
-	evalCtx := eval.NewTestingEvalContext(cluster.MakeTestingClusterSettings())
+	var evalCtx *eval.Context
 	for i, tc := range testCases {
 		t.Run(strconv.Itoa(i), func(t *testing.T) {
 			hist, err := tc.qfun.toHistogram(evalCtx, types.Float, tc.rows)
@@ -843,7 +842,7 @@ func TestQuantileValueRoundTrip(t *testing.T) {
 			err: true,
 		},
 	}
-	evalCtx := eval.NewTestingEvalContext(cluster.MakeTestingClusterSettings())
+	var evalCtx *eval.Context
 	for i, tc := range testCases {
 		t.Run(strconv.Itoa(i), func(t *testing.T) {
 			val, err := toQuantileValue(tc.dat)
@@ -1120,7 +1119,7 @@ func TestQuantileValueRoundTripOverflow(t *testing.T) {
 			res: quantileMaxTimestampSec,
 		},
 	}
-	evalCtx := eval.NewTestingEvalContext(cluster.MakeTestingClusterSettings())
+	var evalCtx *eval.Context
 	for i, tc := range testCases {
 		t.Run(strconv.Itoa(i), func(t *testing.T) {
 			d, err := fromQuantileValue(tc.typ, tc.val)