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pwendell commented Mar 1, 2014

Thanks tom - merged.

@asfgit asfgit closed this in 4ba3f70 Mar 1, 2014
jhartlaub referenced this pull request in jhartlaub/spark May 27, 2014
add Function3 and WrappedFunction3

I need these two to add more API to spark streaming
JasonMWhite pushed a commit to JasonMWhite/spark that referenced this pull request Dec 2, 2015
JasonMWhite pushed a commit to JasonMWhite/spark that referenced this pull request Dec 2, 2015
…ump"

This reverts commit a970f6e, reversing
changes made to c6ac972.
JasonMWhite pushed a commit to JasonMWhite/spark that referenced this pull request Dec 2, 2015
JasonMWhite pushed a commit to JasonMWhite/spark that referenced this pull request Dec 2, 2015
asfgit pushed a commit that referenced this pull request Apr 27, 2016
…w queries

## What changes were proposed in this pull request?

This PR aims to implement decimal aggregation optimization for window queries by improving existing `DecimalAggregates`. Historically, `DecimalAggregates` optimizer is designed to transform general `sum/avg(decimal)`, but it breaks recently added windows queries like the followings. The following queries work well without the current `DecimalAggregates` optimizer.

**Sum**
```scala
scala> sql("select sum(a) over () from (select explode(array(1.0,2.0)) a) t").head
java.lang.RuntimeException: Unsupported window function: MakeDecimal((sum(UnscaledValue(a#31)),mode=Complete,isDistinct=false),12,1)
scala> sql("select sum(a) over () from (select explode(array(1.0,2.0)) a) t").explain()
== Physical Plan ==
WholeStageCodegen
:  +- Project [sum(a) OVER (  ROWS BETWEEN UNBOUNDED PRECEDING AND UNBOUNDED FOLLOWING)#23]
:     +- INPUT
+- Window [MakeDecimal((sum(UnscaledValue(a#21)),mode=Complete,isDistinct=false),12,1) windowspecdefinition(ROWS BETWEEN UNBOUNDED PRECEDING AND UNBOUNDED FOLLOWING) AS sum(a) OVER (  ROWS BETWEEN UNBOUNDED PRECEDING AND UNBOUNDED FOLLOWING)#23]
   +- Exchange SinglePartition, None
      +- Generate explode([1.0,2.0]), false, false, [a#21]
         +- Scan OneRowRelation[]
```

**Average**
```scala
scala> sql("select avg(a) over () from (select explode(array(1.0,2.0)) a) t").head
java.lang.RuntimeException: Unsupported window function: cast(((avg(UnscaledValue(a#40)),mode=Complete,isDistinct=false) / 10.0) as decimal(6,5))
scala> sql("select avg(a) over () from (select explode(array(1.0,2.0)) a) t").explain()
== Physical Plan ==
WholeStageCodegen
:  +- Project [avg(a) OVER (  ROWS BETWEEN UNBOUNDED PRECEDING AND UNBOUNDED FOLLOWING)#44]
:     +- INPUT
+- Window [cast(((avg(UnscaledValue(a#42)),mode=Complete,isDistinct=false) / 10.0) as decimal(6,5)) windowspecdefinition(ROWS BETWEEN UNBOUNDED PRECEDING AND UNBOUNDED FOLLOWING) AS avg(a) OVER (  ROWS BETWEEN UNBOUNDED PRECEDING AND UNBOUNDED FOLLOWING)#44]
   +- Exchange SinglePartition, None
      +- Generate explode([1.0,2.0]), false, false, [a#42]
         +- Scan OneRowRelation[]
```

After this PR, those queries work fine and new optimized physical plans look like the followings.

**Sum**
```scala
scala> sql("select sum(a) over () from (select explode(array(1.0,2.0)) a) t").explain()
== Physical Plan ==
WholeStageCodegen
:  +- Project [sum(a) OVER (  ROWS BETWEEN UNBOUNDED PRECEDING AND UNBOUNDED FOLLOWING)#35]
:     +- INPUT
+- Window [MakeDecimal((sum(UnscaledValue(a#33)),mode=Complete,isDistinct=false) windowspecdefinition(ROWS BETWEEN UNBOUNDED PRECEDING AND UNBOUNDED FOLLOWING),12,1) AS sum(a) OVER (  ROWS BETWEEN UNBOUNDED PRECEDING AND UNBOUNDED FOLLOWING)#35]
   +- Exchange SinglePartition, None
      +- Generate explode([1.0,2.0]), false, false, [a#33]
         +- Scan OneRowRelation[]
```

**Average**
```scala
scala> sql("select avg(a) over () from (select explode(array(1.0,2.0)) a) t").explain()
== Physical Plan ==
WholeStageCodegen
:  +- Project [avg(a) OVER (  ROWS BETWEEN UNBOUNDED PRECEDING AND UNBOUNDED FOLLOWING)#47]
:     +- INPUT
+- Window [cast(((avg(UnscaledValue(a#45)),mode=Complete,isDistinct=false) windowspecdefinition(ROWS BETWEEN UNBOUNDED PRECEDING AND UNBOUNDED FOLLOWING) / 10.0) as decimal(6,5)) AS avg(a) OVER (  ROWS BETWEEN UNBOUNDED PRECEDING AND UNBOUNDED FOLLOWING)#47]
   +- Exchange SinglePartition, None
      +- Generate explode([1.0,2.0]), false, false, [a#45]
         +- Scan OneRowRelation[]
```

In this PR, *SUM over window* pattern matching is based on the code of hvanhovell ; he should be credited for the work he did.

## How was this patch tested?

Pass the Jenkins tests (with newly added testcases)

Author: Dongjoon Hyun <[email protected]>

Closes #12421 from dongjoon-hyun/SPARK-14664.
vlad17 pushed a commit to vlad17/spark that referenced this pull request Aug 23, 2016
## What changes were proposed in this pull request?
This patch was originally authored by davies. The patch implements dynamic partition pruning for branch-2.0.

## How was this patch tested?
An end-to-end test was added in SQLQuerySuite.

Author: Davies Liu <[email protected]>

Closes apache#47 from rxin/rxin-dynamic-partition-pruning.
jzhuge added a commit to jzhuge/spark that referenced this pull request Mar 7, 2019
…dv2table to netflix/2.3.2-unstable

Squashed commit of the following:

commit fec21fd4abab2ef27ae1f4199e3c75217b6a3e8e
Author: Vinitha Gankidi <[email protected]>
Date:   Tue Feb 26 14:58:13 2019 -0800

    NETFLIX-BUILD: loadV2Table should throw NoSuchTableException instead of returning None
hn5092 pushed a commit to hn5092/spark that referenced this pull request Nov 4, 2019
hn5092 pushed a commit to hn5092/spark that referenced this pull request Nov 4, 2019
apache#47 ShuffleMapTask ignore spark.driver.maxResultSize
cloud-fan pushed a commit that referenced this pull request Nov 10, 2020
### What changes were proposed in this pull request?
Push down filter through expand.  For case below:
```
create table t1(pid int, uid int, sid int, dt date, suid int) using parquet;
create table t2(pid int, vs int, uid int, csid int) using parquet;

SELECT
       years,
       appversion,
       SUM(uusers) AS users
FROM   (SELECT
               Date_trunc('year', dt)          AS years,
               CASE
                 WHEN h.pid = 3 THEN 'iOS'
                 WHEN h.pid = 4 THEN 'Android'
                 ELSE 'Other'
               END                             AS viewport,
               h.vs                            AS appversion,
               Count(DISTINCT u.uid)           AS uusers
               ,Count(DISTINCT u.suid)         AS srcusers
        FROM   t1 u
               join t2 h
                 ON h.uid = u.uid
        GROUP  BY 1,
                  2,
                  3) AS a
WHERE  viewport = 'iOS'
GROUP  BY 1,
          2
```

Plan. before this pr:
```
== Physical Plan ==
*(5) HashAggregate(keys=[years#30, appversion#32], functions=[sum(uusers#33L)])
+- Exchange hashpartitioning(years#30, appversion#32, 200), true, [id=#251]
   +- *(4) HashAggregate(keys=[years#30, appversion#32], functions=[partial_sum(uusers#33L)])
      +- *(4) HashAggregate(keys=[date_trunc('year', CAST(u.`dt` AS TIMESTAMP))#45, CASE WHEN (h.`pid` = 3) THEN 'iOS' WHEN (h.`pid` = 4) THEN 'Android' ELSE 'Other' END#46, vs#12], functions=[count(if ((gid#44 = 1)) u.`uid`#47 else null)])
         +- Exchange hashpartitioning(date_trunc('year', CAST(u.`dt` AS TIMESTAMP))#45, CASE WHEN (h.`pid` = 3) THEN 'iOS' WHEN (h.`pid` = 4) THEN 'Android' ELSE 'Other' END#46, vs#12, 200), true, [id=#246]
            +- *(3) HashAggregate(keys=[date_trunc('year', CAST(u.`dt` AS TIMESTAMP))#45, CASE WHEN (h.`pid` = 3) THEN 'iOS' WHEN (h.`pid` = 4) THEN 'Android' ELSE 'Other' END#46, vs#12], functions=[partial_count(if ((gid#44 = 1)) u.`uid`#47 else null)])
               +- *(3) HashAggregate(keys=[date_trunc('year', CAST(u.`dt` AS TIMESTAMP))#45, CASE WHEN (h.`pid` = 3) THEN 'iOS' WHEN (h.`pid` = 4) THEN 'Android' ELSE 'Other' END#46, vs#12, u.`uid`#47, u.`suid`#48, gid#44], functions=[])
                  +- Exchange hashpartitioning(date_trunc('year', CAST(u.`dt` AS TIMESTAMP))#45, CASE WHEN (h.`pid` = 3) THEN 'iOS' WHEN (h.`pid` = 4) THEN 'Android' ELSE 'Other' END#46, vs#12, u.`uid`#47, u.`suid`#48, gid#44, 200), true, [id=#241]
                     +- *(2) HashAggregate(keys=[date_trunc('year', CAST(u.`dt` AS TIMESTAMP))#45, CASE WHEN (h.`pid` = 3) THEN 'iOS' WHEN (h.`pid` = 4) THEN 'Android' ELSE 'Other' END#46, vs#12, u.`uid`#47, u.`suid`#48, gid#44], functions=[])
                        +- *(2) Filter (CASE WHEN (h.`pid` = 3) THEN 'iOS' WHEN (h.`pid` = 4) THEN 'Android' ELSE 'Other' END#46 = iOS)
                           +- *(2) Expand [ArrayBuffer(date_trunc(year, cast(dt#9 as timestamp), Some(Etc/GMT+7)), CASE WHEN (pid#11 = 3) THEN iOS WHEN (pid#11 = 4) THEN Android ELSE Other END, vs#12, uid#7, null, 1), ArrayBuffer(date_trunc(year, cast(dt#9 as timestamp), Some(Etc/GMT+7)), CASE WHEN (pid#11 = 3) THEN iOS WHEN (pid#11 = 4) THEN Android ELSE Other END, vs#12, null, suid#10, 2)], [date_trunc('year', CAST(u.`dt` AS TIMESTAMP))#45, CASE WHEN (h.`pid` = 3) THEN 'iOS' WHEN (h.`pid` = 4) THEN 'Android' ELSE 'Other' END#46, vs#12, u.`uid`#47, u.`suid`#48, gid#44]
                              +- *(2) Project [uid#7, dt#9, suid#10, pid#11, vs#12]
                                 +- *(2) BroadcastHashJoin [uid#7], [uid#13], Inner, BuildRight
                                    :- *(2) Project [uid#7, dt#9, suid#10]
                                    :  +- *(2) Filter isnotnull(uid#7)
                                    :     +- *(2) ColumnarToRow
                                    :        +- FileScan parquet default.t1[uid#7,dt#9,suid#10] Batched: true, DataFilters: [isnotnull(uid#7)], Format: Parquet, Location: InMemoryFileIndex[file:/root/spark-3.0.0-bin-hadoop3.2/spark-warehouse/t1], PartitionFilters: [], PushedFilters: [IsNotNull(uid)], ReadSchema: struct<uid:int,dt:date,suid:int>
                                    +- BroadcastExchange HashedRelationBroadcastMode(List(cast(input[2, int, true] as bigint))), [id=#233]
                                       +- *(1) Project [pid#11, vs#12, uid#13]
                                          +- *(1) Filter isnotnull(uid#13)
                                             +- *(1) ColumnarToRow
                                                +- FileScan parquet default.t2[pid#11,vs#12,uid#13] Batched: true, DataFilters: [isnotnull(uid#13)], Format: Parquet, Location: InMemoryFileIndex[file:/root/spark-3.0.0-bin-hadoop3.2/spark-warehouse/t2], PartitionFilters: [], PushedFilters: [IsNotNull(uid)], ReadSchema: struct<pid:int,vs:int,uid:int>
```

Plan. after. this pr. :
```
== Physical Plan ==
AdaptiveSparkPlan isFinalPlan=false
+- HashAggregate(keys=[years#0, appversion#2], functions=[sum(uusers#3L)], output=[years#0, appversion#2, users#5L])
   +- Exchange hashpartitioning(years#0, appversion#2, 5), true, [id=#71]
      +- HashAggregate(keys=[years#0, appversion#2], functions=[partial_sum(uusers#3L)], output=[years#0, appversion#2, sum#22L])
         +- HashAggregate(keys=[date_trunc(year, cast(dt#9 as timestamp), Some(America/Los_Angeles))#23, CASE WHEN (pid#11 = 3) THEN iOS WHEN (pid#11 = 4) THEN Android ELSE Other END#24, vs#12], functions=[count(distinct uid#7)], output=[years#0, appversion#2, uusers#3L])
            +- Exchange hashpartitioning(date_trunc(year, cast(dt#9 as timestamp), Some(America/Los_Angeles))#23, CASE WHEN (pid#11 = 3) THEN iOS WHEN (pid#11 = 4) THEN Android ELSE Other END#24, vs#12, 5), true, [id=#67]
               +- HashAggregate(keys=[date_trunc(year, cast(dt#9 as timestamp), Some(America/Los_Angeles))#23, CASE WHEN (pid#11 = 3) THEN iOS WHEN (pid#11 = 4) THEN Android ELSE Other END#24, vs#12], functions=[partial_count(distinct uid#7)], output=[date_trunc(year, cast(dt#9 as timestamp), Some(America/Los_Angeles))#23, CASE WHEN (pid#11 = 3) THEN iOS WHEN (pid#11 = 4) THEN Android ELSE Other END#24, vs#12, count#27L])
                  +- HashAggregate(keys=[date_trunc(year, cast(dt#9 as timestamp), Some(America/Los_Angeles))#23, CASE WHEN (pid#11 = 3) THEN iOS WHEN (pid#11 = 4) THEN Android ELSE Other END#24, vs#12, uid#7], functions=[], output=[date_trunc(year, cast(dt#9 as timestamp), Some(America/Los_Angeles))#23, CASE WHEN (pid#11 = 3) THEN iOS WHEN (pid#11 = 4) THEN Android ELSE Other END#24, vs#12, uid#7])
                     +- Exchange hashpartitioning(date_trunc(year, cast(dt#9 as timestamp), Some(America/Los_Angeles))#23, CASE WHEN (pid#11 = 3) THEN iOS WHEN (pid#11 = 4) THEN Android ELSE Other END#24, vs#12, uid#7, 5), true, [id=#63]
                        +- HashAggregate(keys=[date_trunc(year, cast(dt#9 as timestamp), Some(America/Los_Angeles)) AS date_trunc(year, cast(dt#9 as timestamp), Some(America/Los_Angeles))#23, CASE WHEN (pid#11 = 3) THEN iOS WHEN (pid#11 = 4) THEN Android ELSE Other END AS CASE WHEN (pid#11 = 3) THEN iOS WHEN (pid#11 = 4) THEN Android ELSE Other END#24, vs#12, uid#7], functions=[], output=[date_trunc(year, cast(dt#9 as timestamp), Some(America/Los_Angeles))#23, CASE WHEN (pid#11 = 3) THEN iOS WHEN (pid#11 = 4) THEN Android ELSE Other END#24, vs#12, uid#7])
                           +- Project [uid#7, dt#9, pid#11, vs#12]
                              +- BroadcastHashJoin [uid#7], [uid#13], Inner, BuildRight, false
                                 :- Filter isnotnull(uid#7)
                                 :  +- FileScan parquet default.t1[uid#7,dt#9] Batched: true, DataFilters: [isnotnull(uid#7)], Format: Parquet, Location: InMemoryFileIndex[file:/private/var/folders/4l/7_c5c97s1_gb0d9_d6shygx00000gn/T/warehouse-c069d87..., PartitionFilters: [], PushedFilters: [IsNotNull(uid)], ReadSchema: struct<uid:int,dt:date>
                                 +- BroadcastExchange HashedRelationBroadcastMode(List(cast(input[2, int, false] as bigint)),false), [id=#58]
                                    +- Filter ((CASE WHEN (pid#11 = 3) THEN iOS WHEN (pid#11 = 4) THEN Android ELSE Other END = iOS) AND isnotnull(uid#13))
                                       +- FileScan parquet default.t2[pid#11,vs#12,uid#13] Batched: true, DataFilters: [(CASE WHEN (pid#11 = 3) THEN iOS WHEN (pid#11 = 4) THEN Android ELSE Other END = iOS), isnotnull..., Format: Parquet, Location: InMemoryFileIndex[file:/private/var/folders/4l/7_c5c97s1_gb0d9_d6shygx00000gn/T/warehouse-c069d87..., PartitionFilters: [], PushedFilters: [IsNotNull(uid)], ReadSchema: struct<pid:int,vs:int,uid:int>

```

### Why are the changes needed?
Improve  performance, filter more data.

### Does this PR introduce _any_ user-facing change?
No

### How was this patch tested?
Added UT

Closes #30278 from AngersZhuuuu/SPARK-33302.

Authored-by: angerszhu <[email protected]>
Signed-off-by: Wenchen Fan <[email protected]>
dongjoon-hyun added a commit that referenced this pull request Jul 21, 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           #39                 // class org/apache/commons/lang3/builder/ToStringBuilder
       3: dup
       4: aload_0
       5: getstatic     #41                 // Field org/apache/commons/lang3/builder/ToStringStyle.SHORT_PREFIX_STYLE:Lorg/apache/commons/lang3/builder/ToStringStyle;
       8: invokespecial #47                 // Method org/apache/commons/lang3/builder/ToStringBuilder."<init>":(Ljava/lang/Object;Lorg/apache/commons/lang3/builder/ToStringStyle;)V
      11: ldc           #50                 // String appId
      13: aload_0
      14: getfield      #7                  // Field appId:Ljava/lang/String;
      17: invokevirtual #51                 // Method org/apache/commons/lang3/builder/ToStringBuilder.append:(Ljava/lang/String;Ljava/lang/Object;)Lorg/apache/commons/lang3/builder/ToStringBuilder;
      20: ldc           #55                 // String execId
      22: aload_0
      23: getfield      #13                 // Field execId:Ljava/lang/String;
      26: invokevirtual #51                 // Method org/apache/commons/lang3/builder/ToStringBuilder.append:(Ljava/lang/String;Ljava/lang/Object;)Lorg/apache/commons/lang3/builder/ToStringBuilder;
      29: ldc           #56                 // String blockIds
      31: aload_0
      32: getfield      #16                 // Field blockIds:[Ljava/lang/String;
      35: invokestatic  #57                 // Method java/util/Arrays.toString:([Ljava/lang/Object;)Ljava/lang/String;
      38: invokevirtual #51                 // Method org/apache/commons/lang3/builder/ToStringBuilder.append:(Ljava/lang/String;Ljava/lang/Object;)Lorg/apache/commons/lang3/builder/ToStringBuilder;
      41: invokevirtual #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  #39                 // Method java/util/Arrays.toString:([Ljava/lang/Object;)Ljava/lang/String;
      15: invokedynamic #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 #51572 from dongjoon-hyun/SPARK-52880.

Authored-by: Dongjoon Hyun <[email protected]>
Signed-off-by: Dongjoon Hyun <[email protected]>
haoyangeng-db pushed a commit to haoyangeng-db/apache-spark that referenced this pull request Jul 22, 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      apache#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      apache#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      apache#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      apache#7                  // Field appId:Ljava/lang/String;
       4: aload_0
       5: getfield      apache#13                 // Field execId:Ljava/lang/String;
       8: aload_0
       9: getfield      apache#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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3 participants