diff --git a/quesma/model/pipeline_aggregations/average_bucket.go b/quesma/model/pipeline_aggregations/average_bucket.go
index 832c15607..948c14b82 100644
--- a/quesma/model/pipeline_aggregations/average_bucket.go
+++ b/quesma/model/pipeline_aggregations/average_bucket.go
@@ -7,7 +7,6 @@ import (
 	"fmt"
 	"quesma/logger"
 	"quesma/model"
-	"quesma/queryprocessor"
 	"quesma/util"
 )
 
@@ -32,7 +31,7 @@ func (query AverageBucket) CalculateResultWhenMissing(parentRows []model.QueryRe
 	if len(parentRows) == 0 {
 		return resultRows // maybe null?
 	}
-	qp := queryprocessor.NewQueryProcessor(query.ctx)
+	qp := model.NewQueryProcessor(query.ctx)
 	parentFieldsCnt := len(parentRows[0].Cols) - 2 // -2, because row is [parent_cols..., current_key, current_value]
 	// in calculateSingleAvgBucket we calculate avg all current_keys with the same parent_cols
 	// so we need to split into buckets based on parent_cols
diff --git a/quesma/model/pipeline_aggregations/max_bucket.go b/quesma/model/pipeline_aggregations/max_bucket.go
index 0c4af6726..c8a2d587c 100644
--- a/quesma/model/pipeline_aggregations/max_bucket.go
+++ b/quesma/model/pipeline_aggregations/max_bucket.go
@@ -7,7 +7,6 @@ import (
 	"fmt"
 	"quesma/logger"
 	"quesma/model"
-	"quesma/queryprocessor"
 	"quesma/util"
 )
 
@@ -47,7 +46,7 @@ func (query MaxBucket) CalculateResultWhenMissing(parentRows []model.QueryResult
 	if len(parentRows) == 0 {
 		return resultRows // maybe null?
 	}
-	qp := queryprocessor.NewQueryProcessor(query.ctx)
+	qp := model.NewQueryProcessor(query.ctx)
 	parentFieldsCnt := len(parentRows[0].Cols) - 2 // -2, because row is [parent_cols..., current_key, current_value]
 	// in calculateSingleAvgBucket we calculate avg all current_keys with the same parent_cols
 	// so we need to split into buckets based on parent_cols
diff --git a/quesma/model/pipeline_aggregations/min_bucket.go b/quesma/model/pipeline_aggregations/min_bucket.go
index 200233394..43f5f471e 100644
--- a/quesma/model/pipeline_aggregations/min_bucket.go
+++ b/quesma/model/pipeline_aggregations/min_bucket.go
@@ -7,7 +7,6 @@ import (
 	"fmt"
 	"quesma/logger"
 	"quesma/model"
-	"quesma/queryprocessor"
 	"quesma/util"
 )
 
@@ -43,7 +42,7 @@ func (query MinBucket) CalculateResultWhenMissing(parentRows []model.QueryResult
 	if len(parentRows) == 0 {
 		return resultRows // maybe null?
 	}
-	qp := queryprocessor.NewQueryProcessor(query.ctx)
+	qp := model.NewQueryProcessor(query.ctx)
 	parentFieldsCnt := len(parentRows[0].Cols) - 2 // -2, because row is [parent_cols..., current_key, current_value]
 	// in calculateSingleAvgBucket we calculate avg all current_keys with the same parent_cols
 	// so we need to split into buckets based on parent_cols
diff --git a/quesma/model/pipeline_aggregations/sum_bucket.go b/quesma/model/pipeline_aggregations/sum_bucket.go
index 42be987d9..2bfafda05 100644
--- a/quesma/model/pipeline_aggregations/sum_bucket.go
+++ b/quesma/model/pipeline_aggregations/sum_bucket.go
@@ -7,7 +7,6 @@ import (
 	"fmt"
 	"quesma/logger"
 	"quesma/model"
-	"quesma/queryprocessor"
 	"quesma/util"
 	"time"
 )
@@ -44,7 +43,7 @@ func (query SumBucket) CalculateResultWhenMissing(parentRows []model.QueryResult
 	if len(parentRows) == 0 {
 		return resultRows // maybe null?
 	}
-	qp := queryprocessor.NewQueryProcessor(query.ctx)
+	qp := model.NewQueryProcessor(query.ctx)
 	parentFieldsCnt := len(parentRows[0].Cols) - 2 // -2, because row is [parent_cols..., current_key, current_value]
 	// in calculateSingleAvgBucket we calculate avg all current_keys with the same parent_cols
 	// so we need to split into buckets based on parent_cols
diff --git a/quesma/queryprocessor/query_processor.go b/quesma/model/query_processor.go
similarity index 82%
rename from quesma/queryprocessor/query_processor.go
rename to quesma/model/query_processor.go
index 57f6a1f44..4b43edf64 100644
--- a/quesma/queryprocessor/query_processor.go
+++ b/quesma/model/query_processor.go
@@ -1,10 +1,9 @@
 // Copyright Quesma, licensed under the Elastic License 2.0.
 // SPDX-License-Identifier: Elastic-2.0
-package queryprocessor
+package model
 
 import (
 	"context"
-	"quesma/model"
 	"reflect"
 )
 
@@ -17,7 +16,7 @@ func NewQueryProcessor(ctx context.Context) QueryProcessor {
 }
 
 // Returns if row1 and row2 have the same values for the first level fields
-func (qp *QueryProcessor) sameGroupByFields(row1, row2 model.QueryResultRow, level int) bool {
+func (qp *QueryProcessor) sameGroupByFields(row1, row2 QueryResultRow, level int) bool {
 
 	isArray := func(val interface{}) bool {
 		if val == nil {
@@ -49,18 +48,18 @@ func (qp *QueryProcessor) sameGroupByFields(row1, row2 model.QueryResultRow, lev
 // Splits ResultSet into buckets, based on the first level fields
 // E.g. if level == 0, we split into buckets based on the first field,
 // e.g. [row(1, ...), row(1, ...), row(2, ...), row(2, ...), row(3, ...)] -> [[row(1, ...), row(1, ...)], [row(2, ...), row(2, ...)], [row(3, ...)]]
-func (qp *QueryProcessor) SplitResultSetIntoBuckets(ResultSet []model.QueryResultRow, level int) [][]model.QueryResultRow {
+func (qp *QueryProcessor) SplitResultSetIntoBuckets(ResultSet []QueryResultRow, level int) [][]QueryResultRow {
 	if len(ResultSet) == 0 {
-		return [][]model.QueryResultRow{{}}
+		return [][]QueryResultRow{{}}
 	}
 
 	lastRow := ResultSet[0]
-	buckets := [][]model.QueryResultRow{{lastRow}}
+	buckets := [][]QueryResultRow{{lastRow}}
 	for _, row := range ResultSet[1:] {
 		if qp.sameGroupByFields(row, lastRow, level) {
 			buckets[len(buckets)-1] = append(buckets[len(buckets)-1], row)
 		} else {
-			buckets = append(buckets, []model.QueryResultRow{row})
+			buckets = append(buckets, []QueryResultRow{row})
 		}
 		lastRow = row
 	}