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…ingBuilder` ### What changes were proposed in this pull request? This PR aims to improve `toString` by `JEP-280` instead of `ToStringBuilder`. In addition, `Scalastyle` and `Checkstyle` rules are added to prevent a future regression. ### Why are the changes needed? Since Java 9, `String Concatenation` has been handled better by default. | ID | DESCRIPTION | | - | - | | JEP-280 | [Indify String Concatenation](https://openjdk.org/jeps/280) | For example, this PR improves `OpenBlocks` like the following. Both Java source code and byte code are simplified a lot by utilizing JEP-280 properly. **CODE CHANGE** ```java - return new ToStringBuilder(this, ToStringStyle.SHORT_PREFIX_STYLE) - .append("appId", appId) - .append("execId", execId) - .append("blockIds", Arrays.toString(blockIds)) - .toString(); + return "OpenBlocks[appId=" + appId + ",execId=" + execId + ",blockIds=" + + Arrays.toString(blockIds) + "]"; ``` **BEFORE** ``` public java.lang.String toString(); Code: 0: new apache#39 // class org/apache/commons/lang3/builder/ToStringBuilder 3: dup 4: aload_0 5: getstatic apache#41 // Field org/apache/commons/lang3/builder/ToStringStyle.SHORT_PREFIX_STYLE:Lorg/apache/commons/lang3/builder/ToStringStyle; 8: invokespecial apache#47 // Method org/apache/commons/lang3/builder/ToStringBuilder."<init>":(Ljava/lang/Object;Lorg/apache/commons/lang3/builder/ToStringStyle;)V 11: ldc apache#50 // String appId 13: aload_0 14: getfield #7 // Field appId:Ljava/lang/String; 17: invokevirtual apache#51 // Method org/apache/commons/lang3/builder/ToStringBuilder.append:(Ljava/lang/String;Ljava/lang/Object;)Lorg/apache/commons/lang3/builder/ToStringBuilder; 20: ldc apache#55 // String execId 22: aload_0 23: getfield #13 // Field execId:Ljava/lang/String; 26: invokevirtual apache#51 // Method org/apache/commons/lang3/builder/ToStringBuilder.append:(Ljava/lang/String;Ljava/lang/Object;)Lorg/apache/commons/lang3/builder/ToStringBuilder; 29: ldc apache#56 // String blockIds 31: aload_0 32: getfield #16 // Field blockIds:[Ljava/lang/String; 35: invokestatic apache#57 // Method java/util/Arrays.toString:([Ljava/lang/Object;)Ljava/lang/String; 38: invokevirtual apache#51 // Method org/apache/commons/lang3/builder/ToStringBuilder.append:(Ljava/lang/String;Ljava/lang/Object;)Lorg/apache/commons/lang3/builder/ToStringBuilder; 41: invokevirtual apache#61 // Method org/apache/commons/lang3/builder/ToStringBuilder.toString:()Ljava/lang/String; 44: areturn ``` **AFTER** ``` public java.lang.String toString(); Code: 0: aload_0 1: getfield #7 // Field appId:Ljava/lang/String; 4: aload_0 5: getfield #13 // Field execId:Ljava/lang/String; 8: aload_0 9: getfield #16 // Field blockIds:[Ljava/lang/String; 12: invokestatic apache#39 // Method java/util/Arrays.toString:([Ljava/lang/Object;)Ljava/lang/String; 15: invokedynamic apache#43, 0 // InvokeDynamic #0:makeConcatWithConstants:(Ljava/lang/String;Ljava/lang/String;Ljava/lang/String;)Ljava/lang/String; 20: areturn ``` ### Does this PR introduce _any_ user-facing change? No. This is an `toString` implementation improvement. ### How was this patch tested? Pass the CIs. ### Was this patch authored or co-authored using generative AI tooling? No. Closes apache#51572 from dongjoon-hyun/SPARK-52880. Authored-by: Dongjoon Hyun <[email protected]> Signed-off-by: Dongjoon Hyun <[email protected]>
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…onicalized expressions
### What changes were proposed in this pull request?
Make PullOutNonDeterministic use canonicalized expressions to dedup group and aggregate expressions. This affects pyspark udfs in particular. Example:
```
from pyspark.sql.functions import col, avg, udf
pythonUDF = udf(lambda x: x).asNondeterministic()
spark.range(10)\
.selectExpr("id", "id % 3 as value")\
.groupBy(pythonUDF(col("value")))\
.agg(avg("id"), pythonUDF(col("value")))\
.explain(extended=True)
```
Currently results in a plan like this:
```
Aggregate [_nondeterministic#15](#15), [_nondeterministic#15 AS dummyNondeterministicUDF(value)#12, avg(id#0L) AS avg(id)#13, dummyNondeterministicUDF(value#6L)#8 AS dummyNondeterministicUDF(value)#14](#15%20AS%20dummyNondeterministicUDF(value)#12,%20avg(id#0L)%20AS%20avg(id)#13,%20dummyNondeterministicUDF(value#6L)#8%20AS%20dummyNondeterministicUDF(value)#14)
+- Project [id#0L, value#6L, dummyNondeterministicUDF(value#6L)#7 AS _nondeterministic#15](#0L,%20value#6L,%20dummyNondeterministicUDF(value#6L)#7%20AS%20_nondeterministic#15)
+- Project [id#0L, (id#0L % cast(3 as bigint)) AS value#6L](#0L,%20(id#0L%20%%20cast(3%20as%20bigint))%20AS%20value#6L)
+- Range (0, 10, step=1, splits=Some(2))
```
and then it throws:
```
[[MISSING_AGGREGATION] The non-aggregating expression "value" is based on columns which are not participating in the GROUP BY clause. Add the columns or the expression to the GROUP BY, aggregate the expression, or use "any_value(value)" if you do not care which of the values within a group is returned. SQLSTATE: 42803
```
- how canonicalized fixes this:
- nondeterministic PythonUDF expressions always have distinct resultIds per udf
- The fix is to canonicalize the expressions when matching. Canonicalized means that we're setting the resultIds to -1, allowing us to dedup the PythonUDF expressions.
- for deterministic UDFs, this rule does not apply and "Post Analysis" batch extracts and deduplicates the expressions, as expected
### Why are the changes needed?
- the output of the query with the fix applied still makes sense - the nondeterministic UDF is invoked only once, in the project.
### Does this PR introduce _any_ user-facing change?
Yes, it's additive, it enables queries to run that previously threw errors.
### How was this patch tested?
- added unit test
### Was this patch authored or co-authored using generative AI tooling?
No
Closes apache#52061 from benrobby/adhoc-fix-pull-out-nondeterministic.
Authored-by: Ben Hurdelhey <[email protected]>
Signed-off-by: Wenchen Fan <[email protected]>
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What changes were proposed in this pull request?
Why are the changes needed?
Does this PR introduce any user-facing change?
How was this patch tested?
Was this patch authored or co-authored using generative AI tooling?