diff --git a/docs/VictoriaLogs/CHANGELOG.md b/docs/VictoriaLogs/CHANGELOG.md
index 3c60273ed..f24aa9376 100644
--- a/docs/VictoriaLogs/CHANGELOG.md
+++ b/docs/VictoriaLogs/CHANGELOG.md
@@ -21,9 +21,7 @@ according to [these docs](https://docs.victoriametrics.com/VictoriaLogs/QuickSta
 
 * FEATURE: return all the log fields by default in query results. Previously only [`_stream`](https://docs.victoriametrics.com/victorialogs/keyconcepts/#stream-fields), [`_time`](https://docs.victoriametrics.com/victorialogs/keyconcepts/#time-field) and [`_msg`](https://docs.victoriametrics.com/victorialogs/keyconcepts/#message-field) fields were returned by default.
 * FEATURE: add support for returning only the requested log [fields](https://docs.victoriametrics.com/victorialogs/keyconcepts/#data-model). See [these docs](https://docs.victoriametrics.com/victorialogs/logsql/#querying-specific-fields).
-* FEATURE: add support for calculating the number of matching logs and the number of logs with non-empty [fields](https://docs.victoriametrics.com/victorialogs/keyconcepts/#data-model). Grouping by arbitrary set of [log fields](https://docs.victoriametrics.com/victorialogs/keyconcepts/#data-model) is supported. See [these docs](https://docs.victoriametrics.com/victorialogs/logsql/#stats) for details.
-* FEATURE: add support for counting the number of unique values for [log fields](https://docs.victoriametrics.com/victorialogs/keyconcepts/#data-model). See [these docs](https://docs.victoriametrics.com/victorialogs/logsql/#stats) for details.
-* FEATURE: add support for summing [log field](https://docs.victoriametrics.com/victorialogs/keyconcepts/#data-model) values. See [these docs](https://docs.victoriametrics.com/victorialogs/logsql/#stats) for details.
+* FEATURE: add support for calculating `count()`, `uniq()`, `sum()`, `min()` and `max()` over [log fields](https://docs.victoriametrics.com/victorialogs/keyconcepts/#data-model). Grouping by arbitrary set of [log fields](https://docs.victoriametrics.com/victorialogs/keyconcepts/#data-model) is supported. See [these docs](https://docs.victoriametrics.com/victorialogs/logsql/#stats) for details.
 * FEATURE: add support for limiting the number of returned results. See [these docs](https://docs.victoriametrics.com/victorialogs/logsql/#limiters).
 * FEATURE: optimize performance for [LogsQL query](https://docs.victoriametrics.com/victorialogs/logsql/), which contains multiple filters for [words](https://docs.victoriametrics.com/victorialogs/logsql/#word-filter) or [phrases](https://docs.victoriametrics.com/victorialogs/logsql/#phrase-filter) delimited with [`AND` operator](https://docs.victoriametrics.com/victorialogs/logsql/#logical-filter). For example, `foo AND bar` query must find [log messages](https://docs.victoriametrics.com/victorialogs/keyconcepts/#message-field) with `foo` and `bar` words at faster speed.
 * FEATURE: allow using `_` inside numbers. For example, `score:range[1_000, 5_000_000]` for [`range` filter](https://docs.victoriametrics.com/victorialogs/logsql/#range-filter).
diff --git a/lib/logstorage/block_result.go b/lib/logstorage/block_result.go
index 6c92cc13b..637873e31 100644
--- a/lib/logstorage/block_result.go
+++ b/lib/logstorage/block_result.go
@@ -750,7 +750,7 @@ func (c *blockResultColumn) getMaxValue(br *blockResult) float64 {
 
 	switch c.valueType {
 	case valueTypeString:
-		max := math.Inf(-1)
+		max := nan
 		f := float64(0)
 		ok := false
 		values := c.encodedValues
@@ -758,13 +758,10 @@ func (c *blockResultColumn) getMaxValue(br *blockResult) float64 {
 			if i == 0 || values[i-1] != values[i] {
 				f, ok = tryParseFloat64(values[i])
 			}
-			if ok && f > max {
+			if ok && (f > max || math.IsNaN(max)) {
 				max = f
 			}
 		}
-		if math.IsInf(max, -1) {
-			return nan
-		}
 		return max
 	case valueTypeDict:
 		a := encoding.GetFloat64s(len(c.dictValues))
@@ -776,18 +773,15 @@ func (c *blockResultColumn) getMaxValue(br *blockResult) float64 {
 			}
 			dictValuesFloat[i] = f
 		}
-		max := math.Inf(-1)
+		max := nan
 		for _, v := range c.encodedValues {
 			dictIdx := v[0]
 			f := dictValuesFloat[dictIdx]
-			if f > max {
+			if f > max || math.IsNaN(max) {
 				max = f
 			}
 		}
 		encoding.PutFloat64s(a)
-		if math.IsInf(max, -1) {
-			return nan
-		}
 		return max
 	case valueTypeUint8:
 		max := math.Inf(-1)
@@ -853,7 +847,7 @@ func (c *blockResultColumn) getMinValue(br *blockResult) float64 {
 
 	switch c.valueType {
 	case valueTypeString:
-		min := math.Inf(1)
+		min := nan
 		f := float64(0)
 		ok := false
 		values := c.encodedValues
@@ -861,13 +855,10 @@ func (c *blockResultColumn) getMinValue(br *blockResult) float64 {
 			if i == 0 || values[i-1] != values[i] {
 				f, ok = tryParseFloat64(values[i])
 			}
-			if ok && f < min {
+			if ok && (f < min || math.IsNaN(min)) {
 				min = f
 			}
 		}
-		if math.IsInf(min, 1) {
-			return nan
-		}
 		return min
 	case valueTypeDict:
 		a := encoding.GetFloat64s(len(c.dictValues))
@@ -879,18 +870,15 @@ func (c *blockResultColumn) getMinValue(br *blockResult) float64 {
 			}
 			dictValuesFloat[i] = f
 		}
-		min := math.Inf(1)
+		min := nan
 		for _, v := range c.encodedValues {
 			dictIdx := v[0]
 			f := dictValuesFloat[dictIdx]
-			if f < min {
+			if f < min || math.IsNaN(min) {
 				min = f
 			}
 		}
 		encoding.PutFloat64s(a)
-		if math.IsInf(min, 1) {
-			return nan
-		}
 		return min
 	case valueTypeUint8:
 		min := math.Inf(1)
@@ -941,22 +929,23 @@ func (c *blockResultColumn) getMinValue(br *blockResult) float64 {
 	}
 }
 
-func (c *blockResultColumn) sumValues(br *blockResult) float64 {
+func (c *blockResultColumn) sumValues(br *blockResult) (float64, int) {
 	if c.isConst {
 		v := c.encodedValues[0]
 		f, ok := tryParseFloat64(v)
 		if !ok {
-			return 0
+			return 0, 0
 		}
-		return f * float64(len(br.timestamps))
+		return f * float64(len(br.timestamps)), len(br.timestamps)
 	}
 	if c.isTime {
-		return 0
+		return 0, 0
 	}
 
 	switch c.valueType {
 	case valueTypeString:
 		sum := float64(0)
+		count := 0
 		f := float64(0)
 		ok := false
 		values := c.encodedValues
@@ -966,53 +955,59 @@ func (c *blockResultColumn) sumValues(br *blockResult) float64 {
 			}
 			if ok {
 				sum += f
+				count++
 			}
 		}
-		return sum
+		return sum, count
 	case valueTypeDict:
 		a := encoding.GetFloat64s(len(c.dictValues))
 		dictValuesFloat := a.A
 		for i, v := range c.dictValues {
 			f, ok := tryParseFloat64(v)
 			if !ok {
-				f = 0
+				f = nan
 			}
 			dictValuesFloat[i] = f
 		}
 		sum := float64(0)
+		count := 0
 		for _, v := range c.encodedValues {
 			dictIdx := v[0]
-			sum += dictValuesFloat[dictIdx]
+			f := dictValuesFloat[dictIdx]
+			if !math.IsNaN(f) {
+				sum += f
+				count++
+			}
 		}
 		encoding.PutFloat64s(a)
-		return sum
+		return sum, count
 	case valueTypeUint8:
 		sum := uint64(0)
 		for _, v := range c.encodedValues {
 			sum += uint64(v[0])
 		}
-		return float64(sum)
+		return float64(sum), len(br.timestamps)
 	case valueTypeUint16:
 		sum := uint64(0)
 		for _, v := range c.encodedValues {
 			b := bytesutil.ToUnsafeBytes(v)
 			sum += uint64(encoding.UnmarshalUint16(b))
 		}
-		return float64(sum)
+		return float64(sum), len(br.timestamps)
 	case valueTypeUint32:
 		sum := uint64(0)
 		for _, v := range c.encodedValues {
 			b := bytesutil.ToUnsafeBytes(v)
 			sum += uint64(encoding.UnmarshalUint32(b))
 		}
-		return float64(sum)
+		return float64(sum), len(br.timestamps)
 	case valueTypeUint64:
 		sum := float64(0)
 		for _, v := range c.encodedValues {
 			b := bytesutil.ToUnsafeBytes(v)
 			sum += float64(encoding.UnmarshalUint64(b))
 		}
-		return sum
+		return sum, len(br.timestamps)
 	case valueTypeFloat64:
 		sum := float64(0)
 		for _, v := range c.encodedValues {
@@ -1023,14 +1018,14 @@ func (c *blockResultColumn) sumValues(br *blockResult) float64 {
 				sum += f
 			}
 		}
-		return sum
+		return sum, len(br.timestamps)
 	case valueTypeIPv4:
-		return 0
+		return 0, 0
 	case valueTypeTimestampISO8601:
-		return 0
+		return 0, 0
 	default:
 		logger.Panicf("BUG: unknown valueType=%d", c.valueType)
-		return 0
+		return 0, 0
 	}
 }
 
diff --git a/lib/logstorage/stats_max.go b/lib/logstorage/stats_max.go
index ce57f9577..34ada87a1 100644
--- a/lib/logstorage/stats_max.go
+++ b/lib/logstorage/stats_max.go
@@ -2,6 +2,7 @@ package logstorage
 
 import (
 	"fmt"
+	"math"
 	"slices"
 	"strconv"
 	"unsafe"
@@ -22,7 +23,8 @@ func (sm *statsMax) neededFields() []string {
 
 func (sm *statsMax) newStatsProcessor() (statsProcessor, int) {
 	smp := &statsMaxProcessor{
-		sm: sm,
+		sm:  sm,
+		max: nan,
 	}
 	return smp, int(unsafe.Sizeof(*smp))
 }
@@ -38,7 +40,7 @@ func (smp *statsMaxProcessor) updateStatsForAllRows(br *blockResult) int {
 		// Find the maximum value across all the columns
 		for _, c := range br.getColumns() {
 			f := c.getMaxValue(br)
-			if f > smp.max {
+			if f > smp.max || math.IsNaN(smp.max) {
 				smp.max = f
 			}
 		}
@@ -49,7 +51,7 @@ func (smp *statsMaxProcessor) updateStatsForAllRows(br *blockResult) int {
 	for _, field := range smp.sm.fields {
 		c := br.getColumnByName(field)
 		f := c.getMaxValue(br)
-		if f > smp.max {
+		if f > smp.max || math.IsNaN(smp.max) {
 			smp.max = f
 		}
 	}
@@ -61,7 +63,7 @@ func (smp *statsMaxProcessor) updateStatsForRow(br *blockResult, rowIdx int) int
 		// Find the maximum value across all the fields for the given row
 		for _, c := range br.getColumns() {
 			f := c.getFloatValueAtRow(rowIdx)
-			if f > smp.max {
+			if f > smp.max || math.IsNaN(smp.max) {
 				smp.max = f
 			}
 		}
@@ -72,7 +74,7 @@ func (smp *statsMaxProcessor) updateStatsForRow(br *blockResult, rowIdx int) int
 	for _, field := range smp.sm.fields {
 		c := br.getColumnByName(field)
 		f := c.getFloatValueAtRow(rowIdx)
-		if f > smp.max {
+		if f > smp.max || math.IsNaN(smp.max) {
 			smp.max = f
 		}
 	}
diff --git a/lib/logstorage/stats_min.go b/lib/logstorage/stats_min.go
index 67852de7d..50e47e1fd 100644
--- a/lib/logstorage/stats_min.go
+++ b/lib/logstorage/stats_min.go
@@ -2,6 +2,7 @@ package logstorage
 
 import (
 	"fmt"
+	"math"
 	"slices"
 	"strconv"
 	"unsafe"
@@ -22,7 +23,8 @@ func (sm *statsMin) neededFields() []string {
 
 func (sm *statsMin) newStatsProcessor() (statsProcessor, int) {
 	smp := &statsMinProcessor{
-		sm: sm,
+		sm:  sm,
+		min: nan,
 	}
 	return smp, int(unsafe.Sizeof(*smp))
 }
@@ -38,7 +40,7 @@ func (smp *statsMinProcessor) updateStatsForAllRows(br *blockResult) int {
 		// Find the minimum value across all the columns
 		for _, c := range br.getColumns() {
 			f := c.getMinValue(br)
-			if f < smp.min {
+			if f < smp.min || math.IsNaN(smp.min) {
 				smp.min = f
 			}
 		}
@@ -49,7 +51,7 @@ func (smp *statsMinProcessor) updateStatsForAllRows(br *blockResult) int {
 	for _, field := range smp.sm.fields {
 		c := br.getColumnByName(field)
 		f := c.getMinValue(br)
-		if f < smp.min {
+		if f < smp.min || math.IsNaN(smp.min) {
 			smp.min = f
 		}
 	}
@@ -61,7 +63,7 @@ func (smp *statsMinProcessor) updateStatsForRow(br *blockResult, rowIdx int) int
 		// Find the minimum value across all the fields for the given row
 		for _, c := range br.getColumns() {
 			f := c.getFloatValueAtRow(rowIdx)
-			if f < smp.min {
+			if f < smp.min || math.IsNaN(smp.min) {
 				smp.min = f
 			}
 		}
@@ -72,7 +74,7 @@ func (smp *statsMinProcessor) updateStatsForRow(br *blockResult, rowIdx int) int
 	for _, field := range smp.sm.fields {
 		c := br.getColumnByName(field)
 		f := c.getFloatValueAtRow(rowIdx)
-		if f < smp.min {
+		if f < smp.min || math.IsNaN(smp.min) {
 			smp.min = f
 		}
 	}
diff --git a/lib/logstorage/stats_sum.go b/lib/logstorage/stats_sum.go
index 1a328f0ef..7515abf15 100644
--- a/lib/logstorage/stats_sum.go
+++ b/lib/logstorage/stats_sum.go
@@ -23,7 +23,8 @@ func (ss *statsSum) neededFields() []string {
 
 func (ss *statsSum) newStatsProcessor() (statsProcessor, int) {
 	ssp := &statsSumProcessor{
-		ss: ss,
+		ss:  ss,
+		sum: nan,
 	}
 	return ssp, int(unsafe.Sizeof(*ssp))
 }
@@ -38,7 +39,14 @@ func (ssp *statsSumProcessor) updateStatsForAllRows(br *blockResult) int {
 	if ssp.ss.containsStar {
 		// Sum all the columns
 		for _, c := range br.getColumns() {
-			ssp.sum += c.sumValues(br)
+			f, count := c.sumValues(br)
+			if count > 0 {
+				if math.IsNaN(ssp.sum) {
+					ssp.sum = f
+				} else {
+					ssp.sum += f
+				}
+			}
 		}
 		return 0
 	}
@@ -46,7 +54,14 @@ func (ssp *statsSumProcessor) updateStatsForAllRows(br *blockResult) int {
 	// Sum the requested columns
 	for _, field := range ssp.ss.fields {
 		c := br.getColumnByName(field)
-		ssp.sum += c.sumValues(br)
+		f, count := c.sumValues(br)
+		if count > 0 {
+			if math.IsNaN(ssp.sum) {
+				ssp.sum = f
+			} else {
+				ssp.sum += f
+			}
+		}
 	}
 	return 0
 }
@@ -57,7 +72,11 @@ func (ssp *statsSumProcessor) updateStatsForRow(br *blockResult, rowIdx int) int
 		for _, c := range br.getColumns() {
 			f := c.getFloatValueAtRow(rowIdx)
 			if !math.IsNaN(f) {
-				ssp.sum += f
+				if math.IsNaN(ssp.sum) {
+					ssp.sum = f
+				} else {
+					ssp.sum += f
+				}
 			}
 		}
 		return 0
@@ -68,7 +87,11 @@ func (ssp *statsSumProcessor) updateStatsForRow(br *blockResult, rowIdx int) int
 		c := br.getColumnByName(field)
 		f := c.getFloatValueAtRow(rowIdx)
 		if !math.IsNaN(f) {
-			ssp.sum += f
+			if math.IsNaN(ssp.sum) {
+				ssp.sum = f
+			} else {
+				ssp.sum += f
+			}
 		}
 	}
 	return 0