Improve LIKE performance for Dictionary arrays

datafusion/optimizer/src/analyzer/type_coercion.rs

@@ -265,7 +265,10 @@ impl<'a> TreeNodeRewriter for TypeCoercionRewriter<'a> {
                         "There isn't a common type to coerce {left_type} and {right_type} in {op_name} expression"
                     )
                 })?;
-                let expr = Box::new(expr.cast_to(&coerced_type, self.schema)?);
+                let expr = match left_type {
+                    DataType::Dictionary(_, Utf8) => expr,
+                    _ => Box::new(expr.cast_to(&coerced_type, self.schema)?),
+                };
                 let pattern = Box::new(pattern.cast_to(&coerced_type, self.schema)?);
                 Ok(Transformed::yes(Expr::Like(Like::new(
                     negated,

datafusion/physical-expr/src/expressions/like.rs

@@ -148,6 +148,14 @@ impl PartialEq<dyn Any> for LikeExpr {
     }
 }
 
+/// used for optimize Dictionary like
+fn can_like_type(from_type: &DataType) -> bool {
+    match from_type {
+        DataType::Dictionary(_, inner_type_from) => **inner_type_from == DataType::Utf8,
+        _ => false,
+    }
+}
+
 /// Create a like expression, erroring if the argument types are not compatible.
 pub fn like(
     negated: bool,
@@ -158,7 +166,7 @@ pub fn like(
 ) -> Result<Arc<dyn PhysicalExpr>> {
     let expr_type = &expr.data_type(input_schema)?;
     let pattern_type = &pattern.data_type(input_schema)?;
-    if !expr_type.eq(pattern_type) {
+    if !expr_type.eq(pattern_type) && !can_like_type(expr_type) {
         return internal_err!(
             "The type of {expr_type} AND {pattern_type} of like physical should be same"
         );

datafusion/sqllogictest/test_files/regexp.slt

@@ -322,3 +322,29 @@ true
 
 statement ok
 drop table t;
+
+statement ok
+create or replace table strings as values
+  ('FooBar'),
+  ('Foo'),
+  ('Foo'),
+  ('Bar'),
+  ('FooBar'),
+  ('Bar'),
+  ('Baz');
+
+statement ok
+create or replace table dict_table as
+select arrow_cast(column1, 'Dictionary(Int32, Utf8)') as column1
+from strings;
+
+query TT
+explain select column1 from dict_table where column1 LIKE '%oo%';
+----
+logical_plan
+01)Filter: dict_table.column1 LIKE Utf8("%oo%")
+02)--TableScan: dict_table projection=[column1]
+physical_plan
+01)CoalesceBatchesExec: target_batch_size=8192
+02)--FilterExec: column1@0 LIKE %oo%
+03)----MemoryExec: partitions=1, partition_sizes=[1]