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@ericm-db ericm-db commented Jun 27, 2024

What changes were proposed in this pull request?

Introducing the OperatorStateMetadataV2 format, and writing this out with the OperatorStateMetadataLog. This file has a pointer to the State Schema file, and is written in the planning phase.

Why are the changes needed?

We can keep arbitrary operator properties as a part of the OperatorStateMetadata type, and using the metadata file, we can read the latest state schema file.

Does this PR introduce any user-facing change?

No

How was this patch tested?

Added unit tests in the TransformWithStateSuite

Was this patch authored or co-authored using generative AI tooling?

No

@ericm-db ericm-db force-pushed the op-state-metadata branch from fd4396f to 2c35d5f Compare June 27, 2024 00:02
@ericm-db ericm-db force-pushed the op-state-metadata branch 3 times, most recently from 37362b2 to 5458d30 Compare July 2, 2024 23:17
@ericm-db ericm-db changed the title Op state metadata Introducing OperatorStateMetadataV2 for TransformWithState operator Jul 2, 2024
@ericm-db ericm-db force-pushed the op-state-metadata branch 2 times, most recently from 5a3fab4 to 9f24341 Compare July 3, 2024 22:02
@ericm-db ericm-db force-pushed the op-state-metadata branch from f48db5b to 44da39a Compare July 9, 2024 16:31
@ericm-db ericm-db force-pushed the op-state-metadata branch from 44da39a to 6ff37f4 Compare July 9, 2024 17:43
@ericm-db ericm-db changed the title Introducing OperatorStateMetadataV2 for TransformWithState operator [SPARK-48849][SS]Create OperatorStateMetadataV2 for the TransformWithStateExec operator Jul 9, 2024
@ericm-db ericm-db closed this Jul 9, 2024
ericm-db pushed a commit that referenced this pull request Jul 24, 2025
…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]>
ericm-db pushed a commit that referenced this pull request Aug 26, 2025
…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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