fix: update rate/increase query and address several issues in builder queries

* feat: added option to copy legend text

* chore: added test for legend copy action

* chore: updated legend styles

* chore: added check icon when legend copied

* chore: added copytoclipboard hook

* chore: removed copytoclipboard options

conf/example.yaml

@@ -285,7 +285,6 @@ flagger:
   config:
     boolean:
       use_span_metrics: true
-      interpolation_enabled: false
       kafka_span_eval: false
     string:
     float:

frontend/src/hooks/useCopyToClipboard.ts

@@ -0,0 +1,61 @@
+import { useCallback, useEffect, useRef, useState } from 'react';
+
+const DEFAULT_COPIED_RESET_MS = 2000;
+
+export interface UseCopyToClipboardOptions {
+	/** How long (ms) to keep "copied" state before resetting. Default 2000. */
+	copiedResetMs?: number;
+}
+
+export type ID = number | string | null;
+
+export interface UseCopyToClipboardReturn {
+	/** Copy text to clipboard. Pass an optional id to track which item was copied (e.g. seriesIndex). */
+	copyToClipboard: (text: string, id?: ID) => void;
+	/** True when something was just copied and still within the reset threshold. */
+	isCopied: boolean;
+	/** The id passed to the last successful copy, or null after reset. Use to show "copied" state for a specific item (e.g. copiedId === item.seriesIndex). */
+	id: ID;
+}
+
+export function useCopyToClipboard(
+	options: UseCopyToClipboardOptions = {},
+): UseCopyToClipboardReturn {
+	const { copiedResetMs = DEFAULT_COPIED_RESET_MS } = options;
+	const [state, setState] = useState<{ isCopied: boolean; id: ID }>({
+		isCopied: false,
+		id: null,
+	});
+	const timeoutRef = useRef<ReturnType<typeof setTimeout> | null>(null);
+
+	useEffect(() => {
+		return (): void => {
+			if (timeoutRef.current) {
+				clearTimeout(timeoutRef.current);
+				timeoutRef.current = null;
+			}
+		};
+	}, []);
+
+	const copyToClipboard = useCallback(
+		(text: string, id?: ID): void => {
+			navigator.clipboard.writeText(text).then(() => {
+				if (timeoutRef.current) {
+					clearTimeout(timeoutRef.current);
+				}
+				setState({ isCopied: true, id: id ?? null });
+				timeoutRef.current = setTimeout(() => {
+					setState({ isCopied: false, id: null });
+					timeoutRef.current = null;
+				}, copiedResetMs);
+			});
+		},
+		[copiedResetMs],
+	);
+
+	return {
+		copyToClipboard,
+		isCopied: state.isCopied,
+		id: state.id,
+	};
+}

frontend/src/lib/uPlotV2/components/Legend/Legend.styles.scss

@@ -128,6 +128,15 @@
 		opacity: 1;
 	}
 
+	.legend-item-label-trigger {
+		display: flex;
+		align-items: center;
+		gap: 6px;
+		flex: 1;
+		min-width: 0;
+		cursor: pointer;
+	}
+
 	.legend-marker {
 		border-width: 2px;
 		border-radius: 50%;
@@ -157,10 +166,34 @@
 		text-overflow: ellipsis;
 		white-space: nowrap;
 		min-width: 0;
+		user-select: none;
+	}
+
+	.legend-copy-button {
+		display: none;
+		align-items: center;
+		justify-content: center;
+		flex-shrink: 0;
+		padding: 2px;
+		margin: 0;
+		border: none;
+		color: var(--bg-vanilla-400);
+		cursor: pointer;
+		border-radius: 4px;
+		opacity: 1;
+		transition: opacity 0.15s ease, color 0.15s ease;
+
+		&:hover {
+			color: var(--bg-vanilla-100);
+		}
 	}
 
 	&:hover {
 		background: rgba(255, 255, 255, 0.05);
+		.legend-copy-button {
+			display: flex;
+			opacity: 1;
+		}
 	}
 }
 
@@ -172,4 +205,17 @@
 			}
 		}
 	}
+
+	.legend-item {
+		&:hover {
+			background: rgba(0, 0, 0, 0.05);
+		}
+		.legend-copy-button {
+			color: var(--bg-ink-400);
+
+			&:hover {
+				color: var(--bg-ink-500);
+			}
+		}
+	}
 }

frontend/src/lib/uPlotV2/components/Legend/Legend.tsx

@@ -2,8 +2,10 @@ import { useCallback, useMemo, useRef, useState } from 'react';
 import { VirtuosoGrid } from 'react-virtuoso';
 import { Input, Tooltip as AntdTooltip } from 'antd';
 import cx from 'classnames';
+import { useCopyToClipboard } from 'hooks/useCopyToClipboard';
 import { LegendItem } from 'lib/uPlotV2/config/types';
 import useLegendsSync from 'lib/uPlotV2/hooks/useLegendsSync';
+import { Check, Copy } from 'lucide-react';
 
 import { useLegendActions } from '../../hooks/useLegendActions';
 import { LegendPosition, LegendProps } from '../types';
@@ -32,6 +34,7 @@ export default function Legend({
 	});
 	const legendContainerRef = useRef<HTMLDivElement | null>(null);
 	const [legendSearchQuery, setLegendSearchQuery] = useState('');
+	const { copyToClipboard, id: copiedId } = useCopyToClipboard();
 
 	const legendItems = useMemo(() => Object.values(legendItemsMap), [
 		legendItemsMap,
@@ -59,26 +62,53 @@ export default function Legend({
 		);
 	}, [position, legendSearchQuery, legendItems]);
 
+	const handleCopyLegendItem = useCallback(
+		(e: React.MouseEvent, seriesIndex: number, label: string): void => {
+			e.stopPropagation();
+			copyToClipboard(label, seriesIndex);
+		},
+		[copyToClipboard],
+	);
+
 	const renderLegendItem = useCallback(
-		(item: LegendItem): JSX.Element => (
-			<AntdTooltip key={item.seriesIndex} title={item.label}>
+		(item: LegendItem): JSX.Element => {
+			const isCopied = copiedId === item.seriesIndex;
+			return (
 				<div
+					key={item.seriesIndex}
 					data-legend-item-id={item.seriesIndex}
 					className={cx('legend-item', `legend-item-${position.toLowerCase()}`, {
 						'legend-item-off': !item.show,
 						'legend-item-focused': focusedSeriesIndex === item.seriesIndex,
 					})}
 				>
-					<div
-						className="legend-marker"
-						style={{ borderColor: String(item.color) }}
-						data-is-legend-marker={true}
-					/>
-					<span className="legend-label">{item.label}</span>
+					<AntdTooltip title={item.label}>
+						<div className="legend-item-label-trigger">
+							<div
+								className="legend-marker"
+								style={{ borderColor: String(item.color) }}
+								data-is-legend-marker={true}
+							/>
+							<span className="legend-label">{item.label}</span>
+						</div>
+					</AntdTooltip>
+					<AntdTooltip title={isCopied ? 'Copied' : 'Copy'}>
+						<button
+							type="button"
+							className="legend-copy-button"
+							onClick={(e): void =>
+								handleCopyLegendItem(e, item.seriesIndex, item.label ?? '')
+							}
+							aria-label={`Copy ${item.label}`}
+							data-testid="legend-copy"
+						>
+							{isCopied ? <Check size={12} /> : <Copy size={12} />}
+						</button>
+					</AntdTooltip>
 				</div>
-			</AntdTooltip>
-		),
-		[focusedSeriesIndex, position],
+			);
+		},
+		[copiedId, focusedSeriesIndex, handleCopyLegendItem, position],
 	);
 
 	const isEmptyState = useMemo(() => {

frontend/src/lib/uPlotV2/components/__tests__/Legend.test.tsx

@@ -1,5 +1,11 @@
 import React from 'react';
-import { render, RenderResult, screen } from '@testing-library/react';
+import {
+	fireEvent,
+	render,
+	RenderResult,
+	screen,
+	within,
+} from '@testing-library/react';
 import userEvent from '@testing-library/user-event';
 import { LegendItem } from 'lib/uPlotV2/config/types';
 import useLegendsSync from 'lib/uPlotV2/hooks/useLegendsSync';
@@ -8,6 +14,9 @@ import { useLegendActions } from '../../hooks/useLegendActions';
 import Legend from '../Legend/Legend';
 import { LegendPosition } from '../types';
 
+const mockWriteText = jest.fn().mockResolvedValue(undefined);
+let clipboardSpy: jest.SpyInstance | undefined;
+
 jest.mock('react-virtuoso', () => ({
 	VirtuosoGrid: ({
 		data,
@@ -39,6 +48,15 @@ const mockUseLegendActions = useLegendActions as jest.MockedFunction<
 >;
 
 describe('Legend', () => {
+	beforeAll(() => {
+		// JSDOM does not define navigator.clipboard; add it so we can spy on writeText
+		Object.defineProperty(navigator, 'clipboard', {
+			value: { writeText: () => Promise.resolve() },
+			writable: true,
+			configurable: true,
+		});
+	});
+
 	const baseLegendItemsMap = {
 		0: {
 			seriesIndex: 0,
@@ -70,6 +88,11 @@ describe('Legend', () => {
 		onLegendMouseMove = jest.fn();
 		onLegendMouseLeave = jest.fn();
 		onFocusSeries = jest.fn();
+		mockWriteText.mockClear();
+
+		clipboardSpy = jest
+			.spyOn(navigator.clipboard, 'writeText')
+			.mockImplementation(mockWriteText);
 
 		mockUseLegendsSync.mockReturnValue({
 			legendItemsMap: baseLegendItemsMap,
@@ -86,6 +109,7 @@ describe('Legend', () => {
 	});
 
 	afterEach(() => {
+		clipboardSpy?.mockRestore();
 		jest.clearAllMocks();
 	});
 
@@ -210,4 +234,47 @@ describe('Legend', () => {
 			expect(onLegendMouseLeave).toHaveBeenCalledTimes(1);
 		});
 	});
+
+	describe('copy action', () => {
+		it('copies the legend label to clipboard when copy button is clicked', () => {
+			renderLegend(LegendPosition.RIGHT);
+
+			const firstLegendItem = document.querySelector(
+				'[data-legend-item-id="0"]',
+			) as HTMLElement;
+			const copyButton = within(firstLegendItem).getByTestId('legend-copy');
+
+			fireEvent.click(copyButton);
+
+			expect(mockWriteText).toHaveBeenCalledTimes(1);
+			expect(mockWriteText).toHaveBeenCalledWith('A');
+		});
+
+		it('copies the correct label when copy is clicked on a different legend item', () => {
+			renderLegend(LegendPosition.RIGHT);
+
+			const thirdLegendItem = document.querySelector(
+				'[data-legend-item-id="2"]',
+			) as HTMLElement;
+			const copyButton = within(thirdLegendItem).getByTestId('legend-copy');
+
+			fireEvent.click(copyButton);
+
+			expect(mockWriteText).toHaveBeenCalledTimes(1);
+			expect(mockWriteText).toHaveBeenCalledWith('C');
+		});
+
+		it('does not call onLegendClick when copy button is clicked', () => {
+			renderLegend(LegendPosition.RIGHT);
+
+			const firstLegendItem = document.querySelector(
+				'[data-legend-item-id="0"]',
+			) as HTMLElement;
+			const copyButton = within(firstLegendItem).getByTestId('legend-copy');
+
+			fireEvent.click(copyButton);
+
+			expect(onLegendClick).not.toHaveBeenCalled();
+		});
+	});
 });

pkg/flagger/registry.go

@@ -3,9 +3,8 @@ package flagger
 import "github.com/SigNoz/signoz/pkg/types/featuretypes"
 
 var (
-	FeatureUseSpanMetrics       = featuretypes.MustNewName("use_span_metrics")
-	FeatureInterpolationEnabled = featuretypes.MustNewName("interpolation_enabled")
-	FeatureKafkaSpanEval        = featuretypes.MustNewName("kafka_span_eval")
+	FeatureUseSpanMetrics = featuretypes.MustNewName("use_span_metrics")
+	FeatureKafkaSpanEval  = featuretypes.MustNewName("kafka_span_eval")
 )
 
 func MustNewRegistry() featuretypes.Registry {
@@ -18,14 +17,6 @@ func MustNewRegistry() featuretypes.Registry {
 			DefaultVariant: featuretypes.MustNewName("disabled"),
 			Variants:       featuretypes.NewBooleanVariants(),
 		},
-		&featuretypes.Feature{
-			Name:           FeatureInterpolationEnabled,
-			Kind:           featuretypes.KindBoolean,
-			Stage:          featuretypes.StageExperimental,
-			Description:    "Controls whether to enable interpolation",
-			DefaultVariant: featuretypes.MustNewName("disabled"),
-			Variants:       featuretypes.NewBooleanVariants(),
-		},
 		&featuretypes.Feature{
 			Name:           FeatureKafkaSpanEval,
 			Kind:           featuretypes.KindBoolean,

pkg/querybuilder/where_clause_visitor.go

@@ -483,6 +483,22 @@ func (v *filterExpressionVisitor) VisitComparison(ctx *grammar.ComparisonContext
 		value1 := v.Visit(values[0])
 		value2 := v.Visit(values[1])
 
+		switch value1.(type) {
+		case float64:
+			if _, ok := value2.(float64); !ok {
+				v.errors = append(v.errors, fmt.Sprintf("value type mismatch for key %s: expected number for both operands", keys[0].Name))
+				return ""
+			}
+		case string:
+			if _, ok := value2.(string); !ok {
+				v.errors = append(v.errors, fmt.Sprintf("value type mismatch for key %s: expected string for both operands", keys[0].Name))
+				return ""
+			}
+		default:
+			v.errors = append(v.errors, fmt.Sprintf("value type mismatch for key %s: operands must be number or string", keys[0].Name))
+			return ""
+		}
+
 		var conds []string
 		for _, key := range keys {
 			condition, err := v.conditionBuilder.ConditionFor(context.Background(), key, op, []any{value1, value2}, v.builder, v.startNs, v.endNs)
@@ -855,7 +871,7 @@ func (v *filterExpressionVisitor) VisitKey(ctx *grammar.KeyContext) any {
 	// 1. either user meant key ( this is already handled above in fieldKeysForName )
 	// 2. or user meant `attribute.key` we look up in the map for all possible field keys with name 'attribute.key'
 
-	// Note: 
+	// Note:
 	// If user only wants to search `attribute.key`, then they have to use `attribute.attribute.key`
 	// If user only wants to search `key`, then they have to use `key`
 	// If user wants to search both, they can use `attribute.key` and we will resolve the ambiguity

pkg/signoz/config.go

@@ -375,13 +375,6 @@ func mergeAndEnsureBackwardCompatibility(ctx context.Context, logger *slog.Logge
 		config.Flagger.Config.Boolean[flagger.FeatureKafkaSpanEval.String()] = os.Getenv("KAFKA_SPAN_EVAL") == "true"
 	}
 
-	if os.Getenv("INTERPOLATION_ENABLED") != "" {
-		logger.WarnContext(ctx, "[Deprecated] env INTERPOLATION_ENABLED is deprecated and scheduled for removal. Please use SIGNOZ_FLAGGER_CONFIG_BOOLEAN_INTERPOLATION__ENABLED instead.")
-		if config.Flagger.Config.Boolean == nil {
-			config.Flagger.Config.Boolean = make(map[string]bool)
-		}
-		config.Flagger.Config.Boolean[flagger.FeatureInterpolationEnabled.String()] = os.Getenv("INTERPOLATION_ENABLED") == "true"
-	}
 }
 
 func (config Config) Collect(_ context.Context, _ valuer.UUID) (map[string]any, error) {

pkg/telemetrymeter/statement_builder.go

@@ -5,6 +5,7 @@ import (
 	"fmt"
 	"log/slog"
 
+	"github.com/SigNoz/signoz/pkg/errors"
 	"github.com/SigNoz/signoz/pkg/factory"
 	"github.com/SigNoz/signoz/pkg/querybuilder"
 	"github.com/SigNoz/signoz/pkg/telemetrymetrics"
@@ -91,8 +92,9 @@ func (b *meterQueryStatementBuilder) buildPipelineStatement(
 		}
 
 		// spatial_aggregation_cte
-		frag, args := b.buildSpatialAggregationCTE(ctx, start, end, query, keys)
-		if frag != "" {
+		if frag, args, err := b.buildSpatialAggregationCTE(ctx, start, end, query, keys); err != nil {
+			return nil, err
+		} else if frag != "" {
 			cteFragments = append(cteFragments, frag)
 			cteArgs = append(cteArgs, args)
 		}
@@ -128,7 +130,10 @@ func (b *meterQueryStatementBuilder) buildTemporalAggDeltaFastPath(
 	}
 
 	tbl := WhichSamplesTableToUse(start, end, query.Aggregations[0].Type, query.Aggregations[0].TimeAggregation, query.Aggregations[0].TableHints)
-	aggCol := AggregationColumnForSamplesTable(start, end, query.Aggregations[0].Type, query.Aggregations[0].Temporality, query.Aggregations[0].TimeAggregation, query.Aggregations[0].TableHints)
+	aggCol, err := AggregationColumnForSamplesTable(start, end, query.Aggregations[0].Type, query.Aggregations[0].Temporality, query.Aggregations[0].TimeAggregation, query.Aggregations[0].TableHints)
+	if err != nil {
+		return "", []any{}, err
+	}
 	if query.Aggregations[0].TimeAggregation == metrictypes.TimeAggregationRate {
 		aggCol = fmt.Sprintf("%s/%d", aggCol, stepSec)
 	}
@@ -208,8 +213,11 @@ func (b *meterQueryStatementBuilder) buildTemporalAggDelta(
 	}
 
 	tbl := WhichSamplesTableToUse(start, end, query.Aggregations[0].Type, query.Aggregations[0].TimeAggregation, query.Aggregations[0].TableHints)
-	aggCol := AggregationColumnForSamplesTable(start, end, query.Aggregations[0].Type, query.Aggregations[0].Temporality,
+	aggCol, err := AggregationColumnForSamplesTable(start, end, query.Aggregations[0].Type, query.Aggregations[0].Temporality,
 		query.Aggregations[0].TimeAggregation, query.Aggregations[0].TableHints)
+	if err != nil {
+		return "", nil, err
+	}
 	if query.Aggregations[0].TimeAggregation == metrictypes.TimeAggregationRate {
 		aggCol = fmt.Sprintf("%s/%d", aggCol, stepSec)
 	}
@@ -278,7 +286,10 @@ func (b *meterQueryStatementBuilder) buildTemporalAggCumulativeOrUnspecified(
 	}
 
 	tbl := WhichSamplesTableToUse(start, end, query.Aggregations[0].Type, query.Aggregations[0].TimeAggregation, query.Aggregations[0].TableHints)
-	aggCol := AggregationColumnForSamplesTable(start, end, query.Aggregations[0].Type, query.Aggregations[0].Temporality, query.Aggregations[0].TimeAggregation, query.Aggregations[0].TableHints)
+	aggCol, err := AggregationColumnForSamplesTable(start, end, query.Aggregations[0].Type, query.Aggregations[0].Temporality, query.Aggregations[0].TimeAggregation, query.Aggregations[0].TableHints)
+	if err != nil {
+		return "", nil, err
+	}
 	baseSb.SelectMore(fmt.Sprintf("%s AS per_series_value", aggCol))
 
 	baseSb.From(fmt.Sprintf("%s.%s AS points", DBName, tbl))
@@ -315,25 +326,23 @@ func (b *meterQueryStatementBuilder) buildTemporalAggCumulativeOrUnspecified(
 
 	switch query.Aggregations[0].TimeAggregation {
 	case metrictypes.TimeAggregationRate:
-		rateExpr := fmt.Sprintf(telemetrymetrics.RateWithoutNegative, start, start)
 		wrapped := sqlbuilder.NewSelectBuilder()
 		wrapped.Select("ts")
 		for _, g := range query.GroupBy {
 			wrapped.SelectMore(fmt.Sprintf("`%s`", g.TelemetryFieldKey.Name))
 		}
-		wrapped.SelectMore(fmt.Sprintf("%s AS per_series_value", rateExpr))
+		wrapped.SelectMore(fmt.Sprintf("%s AS per_series_value", telemetrymetrics.RateTmpl))
 		wrapped.From(fmt.Sprintf("(%s) WINDOW rate_window AS (PARTITION BY fingerprint ORDER BY fingerprint, ts)", innerQuery))
 		q, args := wrapped.BuildWithFlavor(sqlbuilder.ClickHouse, innerArgs...)
 		return fmt.Sprintf("__temporal_aggregation_cte AS (%s)", q), args, nil
 
 	case metrictypes.TimeAggregationIncrease:
-		incExpr := fmt.Sprintf(telemetrymetrics.IncreaseWithoutNegative, start, start)
 		wrapped := sqlbuilder.NewSelectBuilder()
 		wrapped.Select("ts")
 		for _, g := range query.GroupBy {
 			wrapped.SelectMore(fmt.Sprintf("`%s`", g.TelemetryFieldKey.Name))
 		}
-		wrapped.SelectMore(fmt.Sprintf("%s AS per_series_value", incExpr))
+		wrapped.SelectMore(fmt.Sprintf("%s AS per_series_value", telemetrymetrics.IncreaseTmpl))
 		wrapped.From(fmt.Sprintf("(%s) WINDOW rate_window AS (PARTITION BY fingerprint ORDER BY fingerprint, ts)", innerQuery))
 		q, args := wrapped.BuildWithFlavor(sqlbuilder.ClickHouse, innerArgs...)
 		return fmt.Sprintf("__temporal_aggregation_cte AS (%s)", q), args, nil
@@ -348,7 +357,15 @@ func (b *meterQueryStatementBuilder) buildSpatialAggregationCTE(
 	_ uint64,
 	query qbtypes.QueryBuilderQuery[qbtypes.MetricAggregation],
 	_ map[string][]*telemetrytypes.TelemetryFieldKey,
-) (string, []any) {
+) (string, []any, error) {
+
+	if query.Aggregations[0].SpaceAggregation.IsZero() {
+		return "", []any{}, errors.Newf(
+			errors.TypeInvalidInput,
+			errors.CodeInvalidInput,
+			"invalid space aggregation, should be one of the following: [`sum`, `avg`, `min`, `max`, `count`]",
+		)
+	}
 	sb := sqlbuilder.NewSelectBuilder()
 
 	sb.Select("ts")
@@ -365,5 +382,5 @@ func (b *meterQueryStatementBuilder) buildSpatialAggregationCTE(
 	sb.GroupBy(querybuilder.GroupByKeys(query.GroupBy)...)
 
 	q, args := sb.BuildWithFlavor(sqlbuilder.ClickHouse)
-	return fmt.Sprintf("__spatial_aggregation_cte AS (%s)", q), args
+	return fmt.Sprintf("__spatial_aggregation_cte AS (%s)", q), args, nil
 }

pkg/telemetrymeter/tables.go

@@ -3,6 +3,7 @@ package telemetrymeter
 import (
 	"time"
 
+	"github.com/SigNoz/signoz/pkg/errors"
 	"github.com/SigNoz/signoz/pkg/types/metrictypes"
 )
 
@@ -63,7 +64,7 @@ func AggregationColumnForSamplesTable(
 	temporality metrictypes.Temporality,
 	timeAggregation metrictypes.TimeAggregation,
 	tableHints *metrictypes.MetricTableHints,
-) string {
+) (string, error) {
 	tableName := WhichSamplesTableToUse(start, end, metricType, timeAggregation, tableHints)
 	var aggregationColumn string
 	switch temporality {
@@ -190,5 +191,13 @@ func AggregationColumnForSamplesTable(
 		}
 
 	}
-	return aggregationColumn
+
+	if aggregationColumn == "" {
+		return "", errors.Newf(
+			errors.TypeInvalidInput,
+			errors.CodeInvalidInput,
+			"invalid time aggregation, should be one of the following: [`latest`, `sum`, `avg`, `min`, `max`, `count`, `rate`, `increase`]",
+		)
+	}
+	return aggregationColumn, nil
 }

pkg/telemetrymetrics/condition_builder.go

@@ -29,13 +29,7 @@ func (c *conditionBuilder) conditionFor(
 	sb *sqlbuilder.SelectBuilder,
 ) (string, error) {
 
-	switch operator {
-	case qbtypes.FilterOperatorContains,
-		qbtypes.FilterOperatorNotContains,
-		qbtypes.FilterOperatorILike,
-		qbtypes.FilterOperatorNotILike,
-		qbtypes.FilterOperatorLike,
-		qbtypes.FilterOperatorNotLike:
+	if operator.IsStringSearchOperator() {
 		value = querybuilder.FormatValueForContains(value)
 	}
 
@@ -44,6 +38,18 @@ func (c *conditionBuilder) conditionFor(
 		return "", err
 	}
 
+	// todo(srikanthccv): use the same data type collision handling when metrics schemas are updated
+	switch v := value.(type) {
+	case float64:
+		tblFieldName = fmt.Sprintf("toFloat64OrNull(%s)", tblFieldName)
+	case []any:
+		if len(v) > 0 && (operator == qbtypes.FilterOperatorBetween || operator == qbtypes.FilterOperatorNotBetween) {
+			if _, ok := v[0].(float64); ok {
+				tblFieldName = fmt.Sprintf("toFloat64OrNull(%s)", tblFieldName)
+			}
+		}
+	}
+
 	switch operator {
 	case qbtypes.FilterOperatorEqual:
 		return sb.E(tblFieldName, value), nil

pkg/telemetrymetrics/statement_builder.go

@@ -5,67 +5,27 @@ import (
 	"fmt"
 	"log/slog"
 
+	"github.com/SigNoz/signoz/pkg/errors"
 	"github.com/SigNoz/signoz/pkg/factory"
 	"github.com/SigNoz/signoz/pkg/flagger"
 	"github.com/SigNoz/signoz/pkg/querybuilder"
-	"github.com/SigNoz/signoz/pkg/types/featuretypes"
 	"github.com/SigNoz/signoz/pkg/types/metrictypes"
 	qbtypes "github.com/SigNoz/signoz/pkg/types/querybuildertypes/querybuildertypesv5"
 	"github.com/SigNoz/signoz/pkg/types/telemetrytypes"
-	"github.com/SigNoz/signoz/pkg/valuer"
 	"github.com/huandu/go-sqlbuilder"
 	"golang.org/x/exp/slices"
 )
 
 const (
-	RateWithoutNegative     = `If((per_series_value - lagInFrame(per_series_value, 1, 0) OVER rate_window) < 0, per_series_value / (ts - lagInFrame(ts, 1, toDateTime(fromUnixTimestamp64Milli(%d))) OVER rate_window), (per_series_value - lagInFrame(per_series_value, 1, 0) OVER rate_window) / (ts - lagInFrame(ts, 1, toDateTime(fromUnixTimestamp64Milli(%d))) OVER rate_window))`
-	IncreaseWithoutNegative = `If((per_series_value - lagInFrame(per_series_value, 1, 0) OVER rate_window) < 0, per_series_value, ((per_series_value - lagInFrame(per_series_value, 1, 0) OVER rate_window) / (ts - lagInFrame(ts, 1, toDateTime(fromUnixTimestamp64Milli(%d))) OVER rate_window)) * (ts - lagInFrame(ts, 1, toDateTime(fromUnixTimestamp64Milli(%d))) OVER rate_window))`
+	RateTmpl = `multiIf(row_number() OVER rate_window = 1, nan, (per_series_value - lagInFrame(per_series_value, 1) OVER rate_window) < 0, per_series_value / (ts - lagInFrame(ts, 1) OVER rate_window), (per_series_value - lagInFrame(per_series_value, 1) OVER rate_window) / (ts - lagInFrame(ts, 1) OVER rate_window))`
 
-	RateWithoutNegativeMultiTemporality     = `IF(LOWER(temporality) LIKE LOWER('delta'), %s, IF((%s - lagInFrame(%s, 1, 0) OVER rate_window) < 0, %s / (ts - lagInFrame(ts, 1, toDateTime(fromUnixTimestamp64Milli(%d))) OVER rate_window), (%s - lagInFrame(%s, 1, 0) OVER rate_window) / (ts - lagInFrame(ts, 1, toDateTime(fromUnixTimestamp64Milli(%d))) OVER rate_window))) AS per_series_value`
-	IncreaseWithoutNegativeMultiTemporality = `IF(LOWER(temporality) LIKE LOWER('delta'), %s, IF((%s - lagInFrame(%s, 1, 0) OVER rate_window) < 0, %s, ((%s - lagInFrame(%s, 1, 0) OVER rate_window) / (ts - lagInFrame(ts, 1, toDateTime(fromUnixTimestamp64Milli(%d))) OVER rate_window)) * (ts - lagInFrame(ts, 1, toDateTime(fromUnixTimestamp64Milli(%d))) OVER rate_window))) AS per_series_value`
-	OthersMultiTemporality                  = `IF(LOWER(temporality) LIKE LOWER('delta'), %s, %s) AS per_series_value`
+	IncreaseTmpl = `multiIf(row_number() OVER rate_window = 1, nan, (per_series_value - lagInFrame(per_series_value, 1) OVER rate_window) < 0, per_series_value, per_series_value - lagInFrame(per_series_value, 1) OVER rate_window)`
 
-	RateWithInterpolation = `
-		CASE 
-			WHEN row_number() OVER rate_window = 1 THEN 
-				-- First row: try to interpolate using next value
-				CASE 
-					WHEN leadInFrame(per_series_value, 1) OVER rate_window IS NOT NULL THEN
-						-- Assume linear growth to next point
-						(leadInFrame(per_series_value, 1) OVER rate_window - per_series_value) / 
-						(leadInFrame(ts, 1) OVER rate_window - ts)
-					ELSE 
-						0  -- No next value either, can't interpolate
-				END
-			WHEN (per_series_value - lagInFrame(per_series_value, 1) OVER rate_window) < 0 THEN
-				-- Counter reset detected
-				per_series_value / (ts - lagInFrame(ts, 1) OVER rate_window)
-			ELSE 
-				-- Normal case: calculate rate
-				(per_series_value - lagInFrame(per_series_value, 1) OVER rate_window) / 
-				(ts - lagInFrame(ts, 1) OVER rate_window)
-		END`
+	RateWithoutNegativeMultiTemporality = `IF(LOWER(temporality) LIKE LOWER('delta'), %s, multiIf(row_number() OVER rate_window = 1, nan, (%s - lagInFrame(%s, 1) OVER rate_window) < 0, %s / (ts - lagInFrame(ts, 1) OVER rate_window), (%s - lagInFrame(%s, 1) OVER rate_window) / (ts - lagInFrame(ts, 1) OVER rate_window))) AS per_series_value`
 
-	IncreaseWithInterpolation = `
-		CASE 
-			WHEN row_number() OVER rate_window = 1 THEN 
-				-- First row: try to interpolate using next value
-				CASE 
-					WHEN leadInFrame(per_series_value, 1) OVER rate_window IS NOT NULL THEN
-						-- Calculate the interpolated increase for this interval
-						((leadInFrame(per_series_value, 1) OVER rate_window - per_series_value) / 
-						 (leadInFrame(ts, 1) OVER rate_window - ts)) * 
-						(leadInFrame(ts, 1) OVER rate_window - ts)
-					ELSE 
-						0  -- No next value either, can't interpolate
-				END
-			WHEN (per_series_value - lagInFrame(per_series_value, 1) OVER rate_window) < 0 THEN
-				-- Counter reset detected: the increase is the current value
-				per_series_value
-			ELSE 
-				-- Normal case: calculate increase
-				(per_series_value - lagInFrame(per_series_value, 1) OVER rate_window)
-		END`
+	IncreaseWithoutNegativeMultiTemporality = `IF(LOWER(temporality) LIKE LOWER('delta'), %s, multiIf(row_number() OVER rate_window = 1, nan, (%s - lagInFrame(%s, 1) OVER rate_window) < 0, %s, (%s - lagInFrame(%s, 1) OVER rate_window))) AS per_series_value`
+
+	OthersMultiTemporality = `IF(LOWER(temporality) LIKE LOWER('delta'), %s, %s) AS per_series_value`
 )
 
 type MetricQueryStatementBuilder struct {
@@ -258,8 +218,9 @@ func (b *MetricQueryStatementBuilder) buildPipelineStatement(
 
 	if b.CanShortCircuitDelta(query) {
 		// spatial_aggregation_cte directly for certain delta queries
-		frag, args := b.buildTemporalAggDeltaFastPath(start, end, query, timeSeriesCTE, timeSeriesCTEArgs)
-		if frag != "" {
+		if frag, args, err := b.buildTemporalAggDeltaFastPath(start, end, query, timeSeriesCTE, timeSeriesCTEArgs); err != nil {
+			return nil, err
+		} else if frag != "" {
 			cteFragments = append(cteFragments, frag)
 			cteArgs = append(cteArgs, args)
 		}
@@ -273,8 +234,9 @@ func (b *MetricQueryStatementBuilder) buildPipelineStatement(
 		}
 
 		// spatial_aggregation_cte
-		frag, args := b.buildSpatialAggregationCTE(ctx, start, end, query, keys)
-		if frag != "" {
+		if frag, args, err := b.buildSpatialAggregationCTE(ctx, start, end, query, keys); err != nil {
+			return nil, err
+		} else if frag != "" {
 			cteFragments = append(cteFragments, frag)
 			cteArgs = append(cteArgs, args)
 		}
@@ -294,7 +256,7 @@ func (b *MetricQueryStatementBuilder) buildTemporalAggDeltaFastPath(
 	query qbtypes.QueryBuilderQuery[qbtypes.MetricAggregation],
 	timeSeriesCTE string,
 	timeSeriesCTEArgs []any,
-) (string, []any) {
+) (string, []any, error) {
 	stepSec := int64(query.StepInterval.Seconds())
 
 	sb := sqlbuilder.NewSelectBuilder()
@@ -307,10 +269,13 @@ func (b *MetricQueryStatementBuilder) buildTemporalAggDeltaFastPath(
 		sb.SelectMore(fmt.Sprintf("`%s`", g.TelemetryFieldKey.Name))
 	}
 
-	aggCol := AggregationColumnForSamplesTable(
+	aggCol, err := AggregationColumnForSamplesTable(
 		start, end, query.Aggregations[0].Type, query.Aggregations[0].Temporality,
 		query.Aggregations[0].TimeAggregation, query.Aggregations[0].TableHints,
 	)
+	if err != nil {
+		return "", []any{}, err
+	}
 	if query.Aggregations[0].TimeAggregation == metrictypes.TimeAggregationRate {
 		aggCol = fmt.Sprintf("%s/%d", aggCol, stepSec)
 	}
@@ -334,7 +299,7 @@ func (b *MetricQueryStatementBuilder) buildTemporalAggDeltaFastPath(
 	sb.GroupBy(querybuilder.GroupByKeys(query.GroupBy)...)
 
 	q, args := sb.BuildWithFlavor(sqlbuilder.ClickHouse, timeSeriesCTEArgs...)
-	return fmt.Sprintf("__spatial_aggregation_cte AS (%s)", q), args
+	return fmt.Sprintf("__spatial_aggregation_cte AS (%s)", q), args, nil
 }
 
 func (b *MetricQueryStatementBuilder) buildTimeSeriesCTE(
@@ -437,7 +402,10 @@ func (b *MetricQueryStatementBuilder) buildTemporalAggDelta(
 		sb.SelectMore(fmt.Sprintf("`%s`", g.TelemetryFieldKey.Name))
 	}
 
-	aggCol := AggregationColumnForSamplesTable(start, end, query.Aggregations[0].Type, query.Aggregations[0].Temporality, query.Aggregations[0].TimeAggregation, query.Aggregations[0].TableHints)
+	aggCol, err := AggregationColumnForSamplesTable(start, end, query.Aggregations[0].Type, query.Aggregations[0].Temporality, query.Aggregations[0].TimeAggregation, query.Aggregations[0].TableHints)
+	if err != nil {
+		return "", []any{}, err
+	}
 	if query.Aggregations[0].TimeAggregation == metrictypes.TimeAggregationRate {
 		aggCol = fmt.Sprintf("%s/%d", aggCol, stepSec)
 	}
@@ -461,7 +429,7 @@ func (b *MetricQueryStatementBuilder) buildTemporalAggDelta(
 }
 
 func (b *MetricQueryStatementBuilder) buildTemporalAggCumulativeOrUnspecified(
-	ctx context.Context,
+	_ context.Context,
 	start, end uint64,
 	query qbtypes.QueryBuilderQuery[qbtypes.MetricAggregation],
 	timeSeriesCTE string,
@@ -479,7 +447,10 @@ func (b *MetricQueryStatementBuilder) buildTemporalAggCumulativeOrUnspecified(
 		baseSb.SelectMore(fmt.Sprintf("`%s`", g.TelemetryFieldKey.Name))
 	}
 
-	aggCol := AggregationColumnForSamplesTable(start, end, query.Aggregations[0].Type, query.Aggregations[0].Temporality, query.Aggregations[0].TimeAggregation, query.Aggregations[0].TableHints)
+	aggCol, err := AggregationColumnForSamplesTable(start, end, query.Aggregations[0].Type, query.Aggregations[0].Temporality, query.Aggregations[0].TimeAggregation, query.Aggregations[0].TableHints)
+	if err != nil {
+		return "", []any{}, err
+	}
 	baseSb.SelectMore(fmt.Sprintf("%s AS per_series_value", aggCol))
 
 	tbl := WhichSamplesTableToUse(start, end, query.Aggregations[0].Type, query.Aggregations[0].TimeAggregation, query.Aggregations[0].TableHints)
@@ -496,36 +467,25 @@ func (b *MetricQueryStatementBuilder) buildTemporalAggCumulativeOrUnspecified(
 
 	innerQuery, innerArgs := baseSb.BuildWithFlavor(sqlbuilder.ClickHouse, timeSeriesCTEArgs...)
 
-	// ! TODO (balanikaran) Get OrgID via function parameter instead of valuer.GenerateUUID()
-	interpolationEnabled := b.flagger.BooleanOrEmpty(ctx, flagger.FeatureInterpolationEnabled, featuretypes.NewFlaggerEvaluationContext(valuer.GenerateUUID()))
-
 	switch query.Aggregations[0].TimeAggregation {
 	case metrictypes.TimeAggregationRate:
-		rateExpr := fmt.Sprintf(RateWithoutNegative, start, start)
-		if interpolationEnabled {
-			rateExpr = RateWithInterpolation
-		}
 		wrapped := sqlbuilder.NewSelectBuilder()
 		wrapped.Select("ts")
 		for _, g := range query.GroupBy {
 			wrapped.SelectMore(fmt.Sprintf("`%s`", g.TelemetryFieldKey.Name))
 		}
-		wrapped.SelectMore(fmt.Sprintf("%s AS per_series_value", rateExpr))
+		wrapped.SelectMore(fmt.Sprintf("%s AS per_series_value", RateTmpl))
 		wrapped.From(fmt.Sprintf("(%s) WINDOW rate_window AS (PARTITION BY fingerprint ORDER BY fingerprint, ts)", innerQuery))
 		q, args := wrapped.BuildWithFlavor(sqlbuilder.ClickHouse, innerArgs...)
 		return fmt.Sprintf("__temporal_aggregation_cte AS (%s)", q), args, nil
 
 	case metrictypes.TimeAggregationIncrease:
-		incExpr := fmt.Sprintf(IncreaseWithoutNegative, start, start)
-		if interpolationEnabled {
-			incExpr = IncreaseWithInterpolation
-		}
 		wrapped := sqlbuilder.NewSelectBuilder()
 		wrapped.Select("ts")
 		for _, g := range query.GroupBy {
 			wrapped.SelectMore(fmt.Sprintf("`%s`", g.TelemetryFieldKey.Name))
 		}
-		wrapped.SelectMore(fmt.Sprintf("%s AS per_series_value", incExpr))
+		wrapped.SelectMore(fmt.Sprintf("%s AS per_series_value", IncreaseTmpl))
 		wrapped.From(fmt.Sprintf("(%s) WINDOW rate_window AS (PARTITION BY fingerprint ORDER BY fingerprint, ts)", innerQuery))
 		q, args := wrapped.BuildWithFlavor(sqlbuilder.ClickHouse, innerArgs...)
 		return fmt.Sprintf("__temporal_aggregation_cte AS (%s)", q), args, nil
@@ -534,7 +494,6 @@ func (b *MetricQueryStatementBuilder) buildTemporalAggCumulativeOrUnspecified(
 	}
 }
 
-// because RateInterpolation is not enabled anywhere due to some gaps in the logic wrt cache handling, it hasn't been considered for the multi temporality
 func (b *MetricQueryStatementBuilder) buildTemporalAggForMultipleTemporalities(
 	_ context.Context,
 	start, end uint64,
@@ -553,18 +512,32 @@ func (b *MetricQueryStatementBuilder) buildTemporalAggForMultipleTemporalities(
 		sb.SelectMore(fmt.Sprintf("`%s`", g.TelemetryFieldKey.Name))
 	}
 
-	aggForDeltaTemporality := AggregationColumnForSamplesTable(start, end, query.Aggregations[0].Type, metrictypes.Delta, query.Aggregations[0].TimeAggregation, query.Aggregations[0].TableHints)
-	aggForCumulativeTemporality := AggregationColumnForSamplesTable(start, end, query.Aggregations[0].Type, metrictypes.Cumulative, query.Aggregations[0].TimeAggregation, query.Aggregations[0].TableHints)
+	aggForDeltaTemporality, err := AggregationColumnForSamplesTable(start, end, query.Aggregations[0].Type, metrictypes.Delta, query.Aggregations[0].TimeAggregation, query.Aggregations[0].TableHints)
+	if err != nil {
+		return "", []any{}, err
+	}
+	aggForCumulativeTemporality, err := AggregationColumnForSamplesTable(start, end, query.Aggregations[0].Type, metrictypes.Cumulative, query.Aggregations[0].TimeAggregation, query.Aggregations[0].TableHints)
+	if err != nil {
+		return "", []any{}, err
+	}
 	if query.Aggregations[0].TimeAggregation == metrictypes.TimeAggregationRate {
 		aggForDeltaTemporality = fmt.Sprintf("%s/%d", aggForDeltaTemporality, stepSec)
 	}
 
 	switch query.Aggregations[0].TimeAggregation {
 	case metrictypes.TimeAggregationRate:
-		rateExpr := fmt.Sprintf(RateWithoutNegativeMultiTemporality, aggForDeltaTemporality, aggForCumulativeTemporality, aggForCumulativeTemporality, aggForCumulativeTemporality, start, aggForCumulativeTemporality, aggForCumulativeTemporality, start)
+		rateExpr := fmt.Sprintf(RateWithoutNegativeMultiTemporality,
+			aggForDeltaTemporality,
+			aggForCumulativeTemporality, aggForCumulativeTemporality, aggForCumulativeTemporality,
+			aggForCumulativeTemporality, aggForCumulativeTemporality,
+		)
 		sb.SelectMore(rateExpr)
 	case metrictypes.TimeAggregationIncrease:
-		increaseExpr := fmt.Sprintf(IncreaseWithoutNegativeMultiTemporality, aggForDeltaTemporality, aggForCumulativeTemporality, aggForCumulativeTemporality, aggForCumulativeTemporality, aggForCumulativeTemporality, aggForCumulativeTemporality, start, start)
+		increaseExpr := fmt.Sprintf(IncreaseWithoutNegativeMultiTemporality,
+			aggForDeltaTemporality,
+			aggForCumulativeTemporality, aggForCumulativeTemporality, aggForCumulativeTemporality,
+			aggForCumulativeTemporality, aggForCumulativeTemporality,
+		)
 		sb.SelectMore(increaseExpr)
 	default:
 		expr := fmt.Sprintf(OthersMultiTemporality, aggForDeltaTemporality, aggForCumulativeTemporality)
@@ -592,7 +565,14 @@ func (b *MetricQueryStatementBuilder) buildSpatialAggregationCTE(
 	_ uint64,
 	query qbtypes.QueryBuilderQuery[qbtypes.MetricAggregation],
 	_ map[string][]*telemetrytypes.TelemetryFieldKey,
-) (string, []any) {
+) (string, []any, error) {
+	if query.Aggregations[0].SpaceAggregation.IsZero() {
+		return "", []any{}, errors.Newf(
+			errors.TypeInvalidInput,
+			errors.CodeInvalidInput,
+			"invalid space aggregation, should be one of the following: [`sum`, `avg`, `min`, `max`, `count`, `p50`, `p75`, `p90`, `p95`, `p99`]",
+		)
+	}
 	sb := sqlbuilder.NewSelectBuilder()
 
 	sb.Select("ts")
@@ -609,7 +589,7 @@ func (b *MetricQueryStatementBuilder) buildSpatialAggregationCTE(
 	sb.GroupBy(querybuilder.GroupByKeys(query.GroupBy)...)
 
 	q, args := sb.BuildWithFlavor(sqlbuilder.ClickHouse)
-	return fmt.Sprintf("__spatial_aggregation_cte AS (%s)", q), args
+	return fmt.Sprintf("__spatial_aggregation_cte AS (%s)", q), args, nil
 }
 
 func (b *MetricQueryStatementBuilder) BuildFinalSelect(

pkg/telemetrymetrics/tables.go

@@ -3,6 +3,7 @@ package telemetrymetrics
 import (
 	"time"
 
+	"github.com/SigNoz/signoz/pkg/errors"
 	"github.com/SigNoz/signoz/pkg/types/metrictypes"
 )
 
@@ -168,7 +169,7 @@ func AggregationColumnForSamplesTable(
 	temporality metrictypes.Temporality,
 	timeAggregation metrictypes.TimeAggregation,
 	tableHints *metrictypes.MetricTableHints,
-) string {
+) (string, error) {
 	tableName := WhichSamplesTableToUse(start, end, metricType, timeAggregation, tableHints)
 	var aggregationColumn string
 	switch temporality {
@@ -298,5 +299,12 @@ func AggregationColumnForSamplesTable(
 			}
 		}
 	}
-	return aggregationColumn
+	if aggregationColumn == "" {
+		return "", errors.Newf(
+			errors.TypeInvalidInput,
+			errors.CodeInvalidInput,
+			"invalid time aggregation, should be one of the following: [`latest`, `sum`, `avg`, `min`, `max`, `count`, `rate`, `increase`]",
+		)
+	}
+	return aggregationColumn, nil
 }

pkg/telemetrytraces/condition_builder.go

@@ -35,13 +35,7 @@ func (c *conditionBuilder) conditionFor(
 	sb *sqlbuilder.SelectBuilder,
 ) (string, error) {
 
-	switch operator {
-	case qbtypes.FilterOperatorContains,
-		qbtypes.FilterOperatorNotContains,
-		qbtypes.FilterOperatorILike,
-		qbtypes.FilterOperatorNotILike,
-		qbtypes.FilterOperatorLike,
-		qbtypes.FilterOperatorNotLike:
+	if operator.IsStringSearchOperator() {
 		value = querybuilder.FormatValueForContains(value)
 	}
 

pkg/types/querybuildertypes/querybuildertypesv5/builder_elements.go

@@ -152,7 +152,9 @@ func (f FilterOperator) IsStringSearchOperator() bool {
 		FilterOperatorILike,
 		FilterOperatorNotILike,
 		FilterOperatorLike,
-		FilterOperatorNotLike:
+		FilterOperatorNotLike,
+		FilterOperatorRegexp,
+		FilterOperatorNotRegexp:
 		return true
 	default:
 		return false

pkg/types/querybuildertypes/querybuildertypesv5/qb.go

@@ -12,6 +12,7 @@ import (
 var (
 	ErrColumnNotFound      = errors.Newf(errors.TypeNotFound, errors.CodeNotFound, "field not found")
 	ErrBetweenValues       = errors.Newf(errors.TypeInvalidInput, errors.CodeInvalidInput, "(not) between operator requires two values")
+	ErrBetweenValuesType   = errors.Newf(errors.TypeInvalidInput, errors.CodeInvalidInput, "(not) between operator requires two values of the number type")
 	ErrInValues            = errors.Newf(errors.TypeInvalidInput, errors.CodeInvalidInput, "(not) in operator requires a list of values")
 	ErrUnsupportedOperator = errors.Newf(errors.TypeInvalidInput, errors.CodeInvalidInput, "unsupported operator")
 )

pkg/types/querybuildertypes/querybuildertypesv5/validation.go

@@ -179,14 +179,6 @@ func (q *QueryBuilderQuery[T]) validateAggregations() error {
 					aggId,
 				)
 			}
-			// Validate metric-specific aggregations
-			if err := validateMetricAggregation(v); err != nil {
-				aggId := fmt.Sprintf("aggregation #%d", i+1)
-				if q.Name != "" {
-					aggId = fmt.Sprintf("aggregation #%d in query '%s'", i+1, q.Name)
-				}
-				return wrapValidationError(err, aggId, "invalid metric %s: %s")
-			}
 		case TraceAggregation:
 			if v.Expression == "" {
 				aggId := fmt.Sprintf("aggregation #%d", i+1)
@@ -803,85 +795,3 @@ func validateQueryEnvelope(envelope QueryEnvelope, requestType RequestType) erro
 		)
 	}
 }
-
-// validateMetricAggregation validates metric-specific aggregation parameters
-func validateMetricAggregation(agg MetricAggregation) error {
-	// we can't decide anything here without known temporality
-	if agg.Temporality == metrictypes.Unknown {
-		return nil
-	}
-
-	// Validate that rate/increase are only used with appropriate temporalities
-	if agg.TimeAggregation == metrictypes.TimeAggregationRate || agg.TimeAggregation == metrictypes.TimeAggregationIncrease {
-		// For gauge metrics (Unspecified temporality), rate/increase doesn't make sense
-		if agg.Temporality == metrictypes.Unspecified {
-			return errors.NewInvalidInputf(
-				errors.CodeInvalidInput,
-				"rate/increase aggregation cannot be used with gauge metrics (unspecified temporality)",
-			)
-		}
-	}
-
-	// Validate percentile aggregations are only used with histogram types
-	if agg.SpaceAggregation.IsPercentile() {
-		if agg.Type != metrictypes.HistogramType && agg.Type != metrictypes.ExpHistogramType && agg.Type != metrictypes.SummaryType {
-			return errors.NewInvalidInputf(
-				errors.CodeInvalidInput,
-				"percentile aggregation can only be used with histogram or summary metric types",
-			)
-		}
-	}
-
-	// Validate time aggregation values
-	validTimeAggregations := []metrictypes.TimeAggregation{
-		metrictypes.TimeAggregationUnspecified,
-		metrictypes.TimeAggregationLatest,
-		metrictypes.TimeAggregationSum,
-		metrictypes.TimeAggregationAvg,
-		metrictypes.TimeAggregationMin,
-		metrictypes.TimeAggregationMax,
-		metrictypes.TimeAggregationCount,
-		metrictypes.TimeAggregationCountDistinct,
-		metrictypes.TimeAggregationRate,
-		metrictypes.TimeAggregationIncrease,
-	}
-
-	validTimeAgg := slices.Contains(validTimeAggregations, agg.TimeAggregation)
-	if !validTimeAgg {
-		return errors.NewInvalidInputf(
-			errors.CodeInvalidInput,
-			"invalid time aggregation: %s",
-			agg.TimeAggregation.StringValue(),
-		).WithAdditional(
-			"Valid time aggregations: latest, sum, avg, min, max, count, count_distinct, rate, increase",
-		)
-	}
-
-	// Validate space aggregation values
-	validSpaceAggregations := []metrictypes.SpaceAggregation{
-		metrictypes.SpaceAggregationUnspecified,
-		metrictypes.SpaceAggregationSum,
-		metrictypes.SpaceAggregationAvg,
-		metrictypes.SpaceAggregationMin,
-		metrictypes.SpaceAggregationMax,
-		metrictypes.SpaceAggregationCount,
-		metrictypes.SpaceAggregationPercentile50,
-		metrictypes.SpaceAggregationPercentile75,
-		metrictypes.SpaceAggregationPercentile90,
-		metrictypes.SpaceAggregationPercentile95,
-		metrictypes.SpaceAggregationPercentile99,
-	}
-
-	validSpaceAgg := slices.Contains(validSpaceAggregations, agg.SpaceAggregation)
-	if !validSpaceAgg {
-		return errors.NewInvalidInputf(
-			errors.CodeInvalidInput,
-			"invalid space aggregation: %s",
-			agg.SpaceAggregation.StringValue(),
-		).WithAdditional(
-			"Valid space aggregations: sum, avg, min, max, count, p50, p75, p90, p95, p99",
-		)
-	}
-
-	return nil
-}

tests/integration/src/querier/05_metrics_rate_cumulative_counter.py

@@ -54,17 +54,17 @@ def test_rate_with_steady_values_and_reset(
 
     data = response.json()
     result_values = sorted(get_series_values(data, "A"), key=lambda x: x["timestamp"])
-    assert len(result_values) >= 59
+    assert len(result_values) >= 58
     # the counter reset happened at 31st minute
     assert (
-        result_values[30]["value"] == 0.0167
+        result_values[29]["value"] == 0.0167
     )  # i.e 2/120 i.e 29th to 31st minute changes
     assert (
-        result_values[31]["value"] == 0.133
+        result_values[30]["value"] == 0.133
     )  # i.e 10/60 i.e 31st to 32nd minute changes
     count_of_steady_rate = sum(1 for v in result_values if v["value"] == 0.0833)
     assert (
-        count_of_steady_rate >= 56
+        count_of_steady_rate >= 55
     )  # 59 - (1 reset + 1 high rate + 1 at the beginning)
     # All rates should be non-negative (stale periods = 0 rate)
     for v in result_values:

tests/integration/src/querier/07_metrics_multi_temporality.py

@@ -21,8 +21,13 @@ from fixtures.querier import (
 from fixtures.utils import get_testdata_file_path
 
 MULTI_TEMPORALITY_FILE = get_testdata_file_path("multi_temporality_counters_1h.jsonl")
-MULTI_TEMPORALITY_FILE_10h = get_testdata_file_path("multi_temporality_counters_10h.jsonl")
-MULTI_TEMPORALITY_FILE_24h = get_testdata_file_path("multi_temporality_counters_24h.jsonl")
+MULTI_TEMPORALITY_FILE_10h = get_testdata_file_path(
+    "multi_temporality_counters_10h.jsonl"
+)
+MULTI_TEMPORALITY_FILE_24h = get_testdata_file_path(
+    "multi_temporality_counters_24h.jsonl"
+)
+
 
 @pytest.mark.parametrize(
     "time_aggregation, expected_value_at_31st_minute, expected_value_at_32nd_minute, steady_value",
@@ -39,7 +44,7 @@ def test_with_steady_values_and_reset(
     time_aggregation: str,
     expected_value_at_31st_minute: float,
     expected_value_at_32nd_minute: float,
-    steady_value: float
+    steady_value: float,
 ) -> None:
     now = datetime.now(tz=timezone.utc).replace(second=0, microsecond=0)
     start_ms = int((now - timedelta(minutes=65)).timestamp() * 1000)
@@ -67,24 +72,24 @@ def test_with_steady_values_and_reset(
 
     data = response.json()
     result_values = sorted(get_series_values(data, "A"), key=lambda x: x["timestamp"])
-    assert len(result_values) >= 59
+    assert len(result_values) >= 58
     # the counter reset happened at 31st minute
+    # we skip the rate value for the first data point without previous value
+    assert result_values[29]["value"] == expected_value_at_31st_minute
+    assert result_values[30]["value"] == expected_value_at_32nd_minute
     assert (
-        result_values[30]["value"] == expected_value_at_31st_minute
-    )
-    assert (
-        result_values[31]["value"] == expected_value_at_32nd_minute
-    )
-    assert (
-        result_values[39]["value"] == steady_value
-    ) # 39th minute is when cumulative shifts to delta
+        result_values[38]["value"] == steady_value
+    )  # 38th minute is when cumulative shifts to delta
     count_of_steady_rate = sum(1 for v in result_values if v["value"] == steady_value)
     assert (
-        count_of_steady_rate >= 56
+        count_of_steady_rate >= 55
     )  # 59 - (1 reset + 1 high rate + 1 at the beginning)
     # All rates should be non-negative (stale periods = 0 rate)
     for v in result_values:
-        assert v["value"] >= 0, f"{time_aggregation} should not be negative: {v['value']}"
+        assert (
+            v["value"] >= 0
+        ), f"{time_aggregation} should not be negative: {v['value']}"
+
 
 @pytest.mark.parametrize(
     "time_aggregation, stable_health_value, stable_products_value, stable_checkout_value, spike_checkout_value, stable_orders_value, spike_users_value",
@@ -161,20 +166,26 @@ def test_group_by_endpoint(
     assert (
         len(health_values) >= 58
     ), f"Expected >= 58 values for /health, got {len(health_values)}"
-    count_steady_health = sum(1 for v in health_values if v["value"] == stable_health_value) 
+    count_steady_health = sum(
+        1 for v in health_values if v["value"] == stable_health_value
+    )
     assert (
         count_steady_health >= 57
     ), f"Expected >= 57 steady rate values ({stable_health_value}) for /health, got {count_steady_health}"
     # all /health rates should be state except possibly first/last due to boundaries
     for v in health_values[1:-1]:
-        assert v["value"] == stable_health_value, f"Expected /health rate {stable_health_value}, got {v['value']}"
+        assert (
+            v["value"] == stable_health_value
+        ), f"Expected /health rate {stable_health_value}, got {v['value']}"
 
     # /products: 51 data points with 10-minute gap (t20-t29 missing), steady +20/min
     products_values = endpoint_values["/products"]
     assert (
         len(products_values) >= 49
     ), f"Expected >= 49 values for /products, got {len(products_values)}"
-    count_steady_products = sum(1 for v in products_values if v["value"] == stable_products_value)
+    count_steady_products = sum(
+        1 for v in products_values if v["value"] == stable_products_value
+    )
 
     # most values should be stable, some boundary values differ due to 10-min gap
     assert (
@@ -182,7 +193,9 @@ def test_group_by_endpoint(
     ), f"Expected >= 46 steady rate values ({stable_products_value}) for /products, got {count_steady_products}"
 
     # check that non-stable values are due to gap averaging (should be lower)
-    gap_boundary_values = [v["value"] for v in products_values if v["value"] != stable_products_value]
+    gap_boundary_values = [
+        v["value"] for v in products_values if v["value"] != stable_products_value
+    ]
     for val in gap_boundary_values:
         assert (
             0 < val < stable_products_value
@@ -193,12 +206,16 @@ def test_group_by_endpoint(
     assert (
         len(checkout_values) >= 59
     ), f"Expected >= 59 values for /checkout, got {len(checkout_values)}"
-    count_steady_checkout = sum(1 for v in checkout_values if v["value"] == stable_checkout_value)
+    count_steady_checkout = sum(
+        1 for v in checkout_values if v["value"] == stable_checkout_value
+    )
     assert (
         count_steady_checkout >= 53
     ), f"Expected >= 53 steady {time_aggregation} values ({stable_checkout_value}) for /checkout, got {count_steady_checkout}"
     # check that spike values exist (traffic spike +50/min at t40-t44)
-    count_spike_checkout = sum(1 for v in checkout_values if v["value"] == spike_checkout_value)
+    count_spike_checkout = sum(
+        1 for v in checkout_values if v["value"] == spike_checkout_value
+    )
     assert (
         count_spike_checkout >= 4
     ), f"Expected >= 4 spike {time_aggregation} values ({spike_checkout_value}) for /checkout, got {count_spike_checkout}"
@@ -220,12 +237,16 @@ def test_group_by_endpoint(
     assert (
         len(orders_values) >= 58
     ), f"Expected >= 58 values for /orders, got {len(orders_values)}"
-    count_steady_orders = sum(1 for v in orders_values if v["value"] == stable_orders_value)
+    count_steady_orders = sum(
+        1 for v in orders_values if v["value"] == stable_orders_value
+    )
     assert (
         count_steady_orders >= 55
     ), f"Expected >= 55 steady {time_aggregation} values ({stable_orders_value}) for /orders, got {count_steady_orders}"
     # check for counter reset effects - there should be some non-standard values
-    non_standard_orders = [v["value"] for v in orders_values if v["value"] != stable_orders_value]
+    non_standard_orders = [
+        v["value"] for v in orders_values if v["value"] != stable_orders_value
+    ]
     assert (
         len(non_standard_orders) >= 2
     ), f"Expected >= 2 non-standard values due to counter reset, got {non_standard_orders}"
@@ -252,6 +273,7 @@ def test_group_by_endpoint(
         count_increment_rate >= 8
     ), f"Expected >= 8 increment {time_aggregation} values ({spike_users_value}) for /users, got {count_increment_rate}"
 
+
 @pytest.mark.parametrize(
     "time_aggregation, expected_value_at_30th_minute, expected_value_at_31st_minute, value_at_switch",
     [
@@ -267,7 +289,7 @@ def test_for_service_with_switch(
     time_aggregation: str,
     expected_value_at_30th_minute: float,
     expected_value_at_31st_minute: float,
-    value_at_switch: float
+    value_at_switch: float,
 ) -> None:
     now = datetime.now(tz=timezone.utc).replace(second=0, microsecond=0)
     start_ms = int((now - timedelta(minutes=65)).timestamp() * 1000)
@@ -295,22 +317,19 @@ def test_for_service_with_switch(
 
     data = response.json()
     result_values = sorted(get_series_values(data, "A"), key=lambda x: x["timestamp"])
-    assert len(result_values) >= 60
+    assert len(result_values) >= 59
+    assert result_values[29]["value"] == expected_value_at_30th_minute  # 0.183
+    assert result_values[30]["value"] == expected_value_at_31st_minute  # 0.183
+    assert result_values[37]["value"] == value_at_switch  # 0.25
     assert (
-        result_values[30]["value"] == expected_value_at_30th_minute #0.183
-    ) 
-    assert (
-        result_values[31]["value"] == expected_value_at_31st_minute # 0.183
-    )
-    assert (
-        result_values[38]["value"] == value_at_switch # 0.25
-    ) 
-    assert (
-        result_values[39]["value"] == value_at_switch # 0.25
-    ) # 39th minute is when cumulative shifts to delta
+        result_values[38]["value"] == value_at_switch  # 0.25
+    )  # 39th minute is when cumulative shifts to delta
     # All rates should be non-negative (stale periods = 0 rate)
     for v in result_values:
-        assert v["value"] >= 0, f"{time_aggregation} should not be negative: {v['value']}"
+        assert (
+            v["value"] >= 0
+        ), f"{time_aggregation} should not be negative: {v['value']}"
+
 
 @pytest.mark.parametrize(
     "time_aggregation, expected_value",
@@ -355,6 +374,7 @@ def test_for_week_long_time_range(
     for value in result_values[1:]:
         assert value["value"] == expected_value
 
+
 @pytest.mark.parametrize(
     "time_aggregation, expected_value",
     [