diff --git a/components/parquet_ext/src/prune/equal.rs b/components/parquet_ext/src/prune/equal.rs
index 63d73e68dc..b33bdf2eab 100644
--- a/components/parquet_ext/src/prune/equal.rs
+++ b/components/parquet_ext/src/prune/equal.rs
@@ -1,10 +1,72 @@
 // Copyright 2022 CeresDB Project Authors. Licensed under Apache-2.0.
 
+use arrow::datatypes::SchemaRef;
 use datafusion::{logical_plan::Column, scalar::ScalarValue};
 use datafusion_expr::{Expr, Operator};
 
 const MAX_ELEMS_IN_LIST_FOR_FILTER: usize = 100;
 
+/// A position used to describe the location of a column in the row groups.
+#[derive(Debug, Clone, Copy)]
+pub struct ColumnPosition {
+    pub row_group_idx: usize,
+    pub column_idx: usize,
+}
+
+/// Filter the row groups according to the `exprs`.
+///
+/// The return value is the filtered row group indexes. And the `is_equal`
+/// closure receive three parameters:
+/// - The position of the column in the row groups;
+/// - The value of the column used to determine equality;
+/// - Whether this compare is negated;
+pub fn filter_row_groups<E>(
+    schema: SchemaRef,
+    exprs: &[Expr],
+    row_group_num: usize,
+    is_equal: E,
+) -> Vec<usize>
+where
+    E: Fn(ColumnPosition, &ScalarValue, bool) -> bool,
+{
+    let mut should_reads = vec![true; row_group_num];
+    for expr in exprs {
+        let pruner = EqPruner::new(expr);
+        for (row_group_idx, should_read) in should_reads.iter_mut().enumerate() {
+            if !*should_read {
+                continue;
+            }
+
+            let f = |column: &Column, val: &ScalarValue, negated: bool| -> bool {
+                match schema.column_with_name(&column.name) {
+                    Some((column_idx, _)) => {
+                        let pos = ColumnPosition {
+                            row_group_idx,
+                            column_idx,
+                        };
+                        is_equal(pos, val, negated)
+                    }
+                    _ => true,
+                }
+            };
+
+            *should_read = pruner.prune(&f);
+        }
+    }
+
+    should_reads
+        .iter()
+        .enumerate()
+        .filter_map(|(row_group_idx, should_read)| {
+            if *should_read {
+                Some(row_group_idx)
+            } else {
+                None
+            }
+        })
+        .collect()
+}
+
 /// A pruner based on (not)equal predicates, including in-list predicate.
 #[derive(Debug, Clone)]
 pub struct EqPruner {
@@ -22,9 +84,9 @@ impl EqPruner {
     /// Use the prune function provided by caller to finish pruning.
     ///
     /// The prune function receives three parameters:
-    /// - the column
-    /// - the value of the column
-    /// - equal or not
+    /// - the column to compare;
+    /// - the value of the column used to determine equality;
+    /// - Whether this compare is negated;
     pub fn prune<F>(&self, f: &F) -> bool
     where
         F: Fn(&Column, &ScalarValue, bool) -> bool,
@@ -70,8 +132,8 @@ impl NormalizedExpr {
         match self {
             NormalizedExpr::And { left, right } => left.compute(f) && right.compute(f),
             NormalizedExpr::Or { left, right } => left.compute(f) || right.compute(f),
-            NormalizedExpr::Eq { column, value } => f(column, value, true),
-            NormalizedExpr::NotEq { column, value } => f(column, value, false),
+            NormalizedExpr::Eq { column, value } => f(column, value, false),
+            NormalizedExpr::NotEq { column, value } => f(column, value, true),
             NormalizedExpr::True => true,
             NormalizedExpr::False => false,
         }
@@ -151,6 +213,10 @@ fn normalize_equal_expr(left: &Expr, right: &Expr, is_equal: bool) -> Normalized
 
 #[cfg(test)]
 mod tests {
+    use std::sync::Arc;
+
+    use arrow::datatypes::{DataType, Field, Schema};
+
     use super::*;
 
     fn make_column_expr(name: &str) -> Expr {
@@ -311,7 +377,7 @@ mod tests {
 
     #[test]
     fn test_prune() {
-        let f = |column: &Column, val: &ScalarValue, equal: bool| -> bool {
+        let f = |column: &Column, val: &ScalarValue, negated: bool| -> bool {
             let val = match val {
                 ScalarValue::Int32(v) => v.unwrap(),
                 _ => panic!("Unexpected value type"),
@@ -323,7 +389,7 @@ mod tests {
                 "c2" => val == 2,
                 _ => panic!("Unexpected column"),
             };
-            if !equal {
+            if negated {
                 !res
             } else {
                 res
@@ -361,4 +427,55 @@ mod tests {
         );
         assert!(!EqPruner::new(&false_expr).prune(&f));
     }
+
+    #[test]
+    fn test_filter_row_groups() {
+        // Provide three row groups (one row in one row group).
+        // | c0 | c1 | c2 |
+        // | 0  | 1  | 2  |
+        // | 1  | 2  | 3  |
+        // | 2  | 3  | 4  |
+        let row_groups = vec![vec![0, 1, 2], vec![1, 2, 3], vec![2, 3, 4]];
+        let is_equal = |pos: ColumnPosition, val: &ScalarValue, negated: bool| -> bool {
+            let expect_val = row_groups[pos.row_group_idx][pos.column_idx];
+            let val = if let ScalarValue::Int32(v) = val {
+                v.expect("Unexpected value")
+            } else {
+                panic!("Unexpected value type")
+            };
+
+            if negated {
+                expect_val != val
+            } else {
+                expect_val == val
+            }
+        };
+
+        // (c0 in [1, 3]) or c1 not in [1, 2]
+        let predicate1 = Expr::or(
+            Expr::in_list(
+                make_column_expr("c0"),
+                vec![make_literal_expr(1), make_literal_expr(3)],
+                false,
+            ),
+            Expr::in_list(
+                make_column_expr("c1"),
+                vec![make_literal_expr(1), make_literal_expr(2)],
+                true,
+            ),
+        );
+
+        // c2 != 2
+        let predicate2 = Expr::not_eq(make_literal_expr(2), make_column_expr("c2"));
+
+        let schema = Schema::new(vec![
+            Field::new("c0", DataType::Int32, false),
+            Field::new("c1", DataType::Int32, false),
+            Field::new("c2", DataType::Int32, false),
+        ]);
+        let filtered_row_groups =
+            filter_row_groups(Arc::new(schema), &vec![predicate1, predicate2], 3, is_equal);
+
+        assert_eq!(vec![1, 2], filtered_row_groups)
+    }
 }