[GitHub] [arrow-datafusion] alamb commented on a diff in pull request #5816: feat: add optimization support to LOG and POWER functions

["alamb (via GitHub)" <gi...@apache.org>]

alamb commented on code in PR #5816:
URL: https://github.com/apache/arrow-datafusion/pull/5816#discussion_r1155932650


##########
datafusion/optimizer/src/simplify_expressions/expr_simplifier.rs:
##########
@@ -2210,6 +2222,68 @@ mod tests {
         assert_eq!(simplify(expr_eq), lit(true));
     }
 
+    #[test]
+    fn test_simplify_log() {
+        // Log(c3, 1) ===> 0
+        {
+            let expr = log(col("c3_non_null"), lit(1));
+            let expected = lit(0i64);
+            assert_eq!(simplify(expr), expected);
+        }
+        // Log(c3, c3) ===> 1
+        {
+            let expr = log(col("c3_non_null"), col("c3_non_null"));
+            let expected = lit(1i64);
+            assert_eq!(simplify(expr), expected);
+        }
+        // Log(c3, Power(c3, c4)) ===> c4
+        {
+            let expr = log(
+                col("c3_non_null"),
+                power(col("c3_non_null"), col("c4_non_null")),
+            );
+            let expected = col("c4_non_null");
+            assert_eq!(simplify(expr), expected);
+        }
+        // Log(c3, c4) ===> c4

Review Comment:
   ```suggestion
           // Log(c3, c4) ===> Log(c3, c4) 
   ```



##########
datafusion/optimizer/src/simplify_expressions/utils.rs:
##########
@@ -350,6 +351,73 @@ pub fn distribute_negation(expr: Expr) -> Expr {
     }
 }
 
+/// Simplify the `log` function by the relevant rules:
+/// 1. Log(a, 1) ===> 0
+/// 2. Log(a, a) ===> 1
+/// 3. Log(a, Power(a, b)) ===> b

Review Comment:
   I think this is a good set of changes for now. 



##########
datafusion/optimizer/src/simplify_expressions/expr_simplifier.rs:
##########
@@ -1072,6 +1072,18 @@ impl<'a, S: SimplifyInfo> TreeNodeRewriter for Simplifier<'a, S> {
                 out_expr.rewrite(self)?
             }
 
+            // log

Review Comment:
   I agree splitting it into smaller modules would be a great idea for a follow on PR



##########
datafusion/common/src/scalar.rs:
##########
@@ -1723,6 +1745,27 @@ impl ScalarValue {
         })
     }
 
+    pub fn new_ten(datatype: &DataType) -> Result<ScalarValue> {

Review Comment:
   It sounds like a reasonable idea. Thanks @izveigor 
   
   It might be possible to to use the traits defined in arrow-rs for this: https://docs.rs/arrow/latest/arrow/array/trait.ArrowPrimitiveType.html
   
   



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