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## What changes were proposed in this pull request? This is a tiny addendum to SPARK-19495 to remove the private visibility for copy, which is the only package private method in the entire file. ## How was this patch tested? N/A - no semantic change. Author: Reynold Xin <[email protected]> Closes #17555 from rxin/SPARK-19495-2.
## What changes were proposed in this pull request? Currently `LogicalRelation` has a `expectedOutputAttributes` parameter, which makes it hard to reason about what the actual output is. Like other leaf nodes, `LogicalRelation` should also take `output` as a parameter, to simplify the logic ## How was this patch tested? existing tests Author: Wenchen Fan <[email protected]> Closes #17552 from cloud-fan/minor.
## What changes were proposed in this pull request? The Dataframes-based support for the correlation statistics is added in #17108. This patch adds the Python interface for it. ## How was this patch tested? Python unit test. Please review http://spark.apache.org/contributing.html before opening a pull request. Author: Liang-Chi Hsieh <[email protected]> Closes #17494 from viirya/correlation-python-api.
…ription.
## What changes were proposed in this pull request?
1. '/applications/[app-id]/stages' in rest api.status should add description '?status=[active|complete|pending|failed] list only stages in the state.'
Now the lack of this description, resulting in the use of this api do not know the use of the status through the brush stage list.
2.'/applications/[app-id]/stages/[stage-id]' in REST API,remove redundant description ‘?status=[active|complete|pending|failed] list only stages in the state.’.
Because only one stage is determined based on stage-id.
code:
GET
def stageList(QueryParam("status") statuses: JList[StageStatus]): Seq[StageData] = {
val listener = ui.jobProgressListener
val stageAndStatus = AllStagesResource.stagesAndStatus(ui)
val adjStatuses = {
if (statuses.isEmpty()) {
Arrays.asList(StageStatus.values(): _*)
} else {
statuses
}
};
## How was this patch tested?
manual tests
Please review http://spark.apache.org/contributing.html before opening a pull request.
Author: 郭小龙 10207633 <[email protected]>
Closes #17534 from guoxiaolongzte/SPARK-20218.
…ing guide ## What changes were proposed in this pull request? Add Tweedie example for SparkR in programming guide. The doc was already updated in #17103. Author: actuaryzhang <[email protected]> Closes #17553 from actuaryzhang/programGuide.
## What changes were proposed in this pull request? Test failed because SPARK_HOME is not set before Spark is installed. Author: Felix Cheung <[email protected]> Closes #17516 from felixcheung/rdircheckincran.
…programming guide (did not converge)
## What changes were proposed in this pull request?
SparkR logistic regression example did not converge in programming guide (for IRWLS). All estimates are essentially zero:
```
training2 <- read.df("data/mllib/sample_binary_classification_data.txt", source = "libsvm")
df_list2 <- randomSplit(training2, c(7,3), 2)
binomialDF <- df_list2[[1]]
binomialTestDF <- df_list2[[2]]
binomialGLM <- spark.glm(binomialDF, label ~ features, family = "binomial")
17/04/07 11:42:03 WARN WeightedLeastSquares: Cholesky solver failed due to singular covariance matrix. Retrying with Quasi-Newton solver.
> summary(binomialGLM)
Coefficients:
Estimate
(Intercept) 9.0255e+00
features_0 0.0000e+00
features_1 0.0000e+00
features_2 0.0000e+00
features_3 0.0000e+00
features_4 0.0000e+00
features_5 0.0000e+00
features_6 0.0000e+00
features_7 0.0000e+00
```
Author: actuaryzhang <[email protected]>
Closes #17571 from actuaryzhang/programGuide2.
## What changes were proposed in this pull request Trying to get a grip on the `FileIndex` hierarchy, I was confused by the following inconsistency: On the one hand, `PartitioningAwareFileIndex` defines `leafFiles` and `leafDirToChildrenFiles` as abstract, but on the other it fully implements `listLeafFiles` which does all the listing of files. However, the latter is only used by `InMemoryFileIndex`. I'm hereby proposing to move this method (and all its dependencies) to the implementation class that actually uses it, and thus unclutter the `PartitioningAwareFileIndex` interface. ## How was this patch tested? `./build/sbt sql/test` Author: Adrian Ionescu <[email protected]> Closes #17570 from adrian-ionescu/list-leaf-files.
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…pressions
## What changes were proposed in this pull request?
This PR changes the direction of expression transformation in the DecimalPrecision rule. Previously, the expressions were transformed down, which led to incorrect result types when decimal expressions had other decimal expressions as their operands. The root cause of this issue was in visiting outer nodes before their children. Consider the example below:
```
val inputSchema = StructType(StructField("col", DecimalType(26, 6)) :: Nil)
val sc = spark.sparkContext
val rdd = sc.parallelize(1 to 2).map(_ => Row(BigDecimal(12)))
val df = spark.createDataFrame(rdd, inputSchema)
// Works correctly since no nested decimal expression is involved
// Expected result type: (26, 6) * (26, 6) = (38, 12)
df.select($"col" * $"col").explain(true)
df.select($"col" * $"col").printSchema()
// Gives a wrong result since there is a nested decimal expression that should be visited first
// Expected result type: ((26, 6) * (26, 6)) * (26, 6) = (38, 12) * (26, 6) = (38, 18)
df.select($"col" * $"col" * $"col").explain(true)
df.select($"col" * $"col" * $"col").printSchema()
```
The example above gives the following output:
```
// Correct result without sub-expressions
== Parsed Logical Plan ==
'Project [('col * 'col) AS (col * col)#4]
+- LogicalRDD [col#1]
== Analyzed Logical Plan ==
(col * col): decimal(38,12)
Project [CheckOverflow((promote_precision(cast(col#1 as decimal(26,6))) * promote_precision(cast(col#1 as decimal(26,6)))), DecimalType(38,12)) AS (col * col)#4]
+- LogicalRDD [col#1]
== Optimized Logical Plan ==
Project [CheckOverflow((col#1 * col#1), DecimalType(38,12)) AS (col * col)#4]
+- LogicalRDD [col#1]
== Physical Plan ==
*Project [CheckOverflow((col#1 * col#1), DecimalType(38,12)) AS (col * col)#4]
+- Scan ExistingRDD[col#1]
// Schema
root
|-- (col * col): decimal(38,12) (nullable = true)
// Incorrect result with sub-expressions
== Parsed Logical Plan ==
'Project [(('col * 'col) * 'col) AS ((col * col) * col)#11]
+- LogicalRDD [col#1]
== Analyzed Logical Plan ==
((col * col) * col): decimal(38,12)
Project [CheckOverflow((promote_precision(cast(CheckOverflow((promote_precision(cast(col#1 as decimal(26,6))) * promote_precision(cast(col#1 as decimal(26,6)))), DecimalType(38,12)) as decimal(26,6))) * promote_precision(cast(col#1 as decimal(26,6)))), DecimalType(38,12)) AS ((col * col) * col)#11]
+- LogicalRDD [col#1]
== Optimized Logical Plan ==
Project [CheckOverflow((cast(CheckOverflow((col#1 * col#1), DecimalType(38,12)) as decimal(26,6)) * col#1), DecimalType(38,12)) AS ((col * col) * col)#11]
+- LogicalRDD [col#1]
== Physical Plan ==
*Project [CheckOverflow((cast(CheckOverflow((col#1 * col#1), DecimalType(38,12)) as decimal(26,6)) * col#1), DecimalType(38,12)) AS ((col * col) * col)#11]
+- Scan ExistingRDD[col#1]
// Schema
root
|-- ((col * col) * col): decimal(38,12) (nullable = true)
```
## How was this patch tested?
This PR was tested with available unit tests. Moreover, there are tests to cover previously failing scenarios.
Author: aokolnychyi <[email protected]>
Closes apache#18583 from aokolnychyi/spark-21332.
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…/`to_avro`
## What changes were proposed in this pull request?
Previously in from_avro/to_avro, we override the method `simpleString` and `sql` for the string output. However, the override only affects the alias naming:
```
Project [from_avro('col,
...
, (mode,PERMISSIVE)) AS from_avro(col, struct<col1:bigint,col2:double>, Map(mode -> PERMISSIVE))#11]
```
It only makes the alias name quite long: `from_avro(col, struct<col1:bigint,col2:double>, Map(mode -> PERMISSIVE))`).
We should follow `from_csv`/`from_json` here, to override the method prettyName only, and we will get a clean alias name
```
... AS from_avro(col)#11
```
## How was this patch tested?
Manual check
Closes apache#22890 from gengliangwang/revise_from_to_avro.
Authored-by: Gengliang Wang <[email protected]>
Signed-off-by: gatorsmile <[email protected]>
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### Why are the changes needed? `EnsureRequirements` adds `ShuffleExchangeExec` (RangePartitioning) after Sort if `RoundRobinPartitioning` behinds it. This will cause 2 shuffles, and the number of partitions in the final stage is not the number specified by `RoundRobinPartitioning. **Example SQL** ``` SELECT /*+ REPARTITION(5) */ * FROM test ORDER BY a ``` **BEFORE** ``` == Physical Plan == *(1) Sort [a#0 ASC NULLS FIRST], true, 0 +- Exchange rangepartitioning(a#0 ASC NULLS FIRST, 200), true, [id=#11] +- Exchange RoundRobinPartitioning(5), false, [id=#9] +- Scan hive default.test [a#0, b#1], HiveTableRelation `default`.`test`, org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe, [a#0, b#1] ``` **AFTER** ``` == Physical Plan == *(1) Sort [a#0 ASC NULLS FIRST], true, 0 +- Exchange rangepartitioning(a#0 ASC NULLS FIRST, 5), true, [id=#11] +- Scan hive default.test [a#0, b#1], HiveTableRelation `default`.`test`, org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe, [a#0, b#1] ``` ### Does this PR introduce any user-facing change? No ### How was this patch tested? Run suite Tests and add new test for this. Closes apache#26946 from stczwd/RoundRobinPartitioning. Lead-authored-by: lijunqing <[email protected]> Co-authored-by: stczwd <[email protected]> Signed-off-by: Wenchen Fan <[email protected]>
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…n properly
### What changes were proposed in this pull request?
Make `ResolveRelations` handle plan id properly
### Why are the changes needed?
bug fix for Spark Connect, it won't affect classic Spark SQL
before this PR:
```
from pyspark.sql import functions as sf
spark.range(10).withColumn("value_1", sf.lit(1)).write.saveAsTable("test_table_1")
spark.range(10).withColumnRenamed("id", "index").withColumn("value_2", sf.lit(2)).write.saveAsTable("test_table_2")
df1 = spark.read.table("test_table_1")
df2 = spark.read.table("test_table_2")
df3 = spark.read.table("test_table_1")
join1 = df1.join(df2, on=df1.id==df2.index).select(df2.index, df2.value_2)
join2 = df3.join(join1, how="left", on=join1.index==df3.id)
join2.schema
```
fails with
```
AnalysisException: [CANNOT_RESOLVE_DATAFRAME_COLUMN] Cannot resolve dataframe column "id". It's probably because of illegal references like `df1.select(df2.col("a"))`. SQLSTATE: 42704
```
That is due to existing plan caching in `ResolveRelations` doesn't work with Spark Connect
```
=== Applying Rule org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveRelations ===
'[#12]Join LeftOuter, '`==`('index, 'id) '[#12]Join LeftOuter, '`==`('index, 'id)
!:- '[#9]UnresolvedRelation [test_table_1], [], false :- '[#9]SubqueryAlias spark_catalog.default.test_table_1
!+- '[#11]Project ['index, 'value_2] : +- 'UnresolvedCatalogRelation `spark_catalog`.`default`.`test_table_1`, [], false
! +- '[#10]Join Inner, '`==`('id, 'index) +- '[#11]Project ['index, 'value_2]
! :- '[#7]UnresolvedRelation [test_table_1], [], false +- '[#10]Join Inner, '`==`('id, 'index)
! +- '[#8]UnresolvedRelation [test_table_2], [], false :- '[#9]SubqueryAlias spark_catalog.default.test_table_1
! : +- 'UnresolvedCatalogRelation `spark_catalog`.`default`.`test_table_1`, [], false
! +- '[#8]SubqueryAlias spark_catalog.default.test_table_2
! +- 'UnresolvedCatalogRelation `spark_catalog`.`default`.`test_table_2`, [], false
Can not resolve 'id with plan 7
```
`[#7]UnresolvedRelation [test_table_1], [], false` was wrongly resolved to the cached one
```
:- '[#9]SubqueryAlias spark_catalog.default.test_table_1
+- 'UnresolvedCatalogRelation `spark_catalog`.`default`.`test_table_1`, [], false
```
### Does this PR introduce _any_ user-facing change?
yes, bug fix
### How was this patch tested?
added ut
### Was this patch authored or co-authored using generative AI tooling?
ci
Closes apache#45214 from zhengruifeng/connect_fix_read_join.
Authored-by: Ruifeng Zheng <[email protected]>
Signed-off-by: Dongjoon Hyun <[email protected]>
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…r `postgreSQL/float4.sql` and `postgreSQL/int8.sql` ### What changes were proposed in this pull request? This pr regenerate Java 21 golden file for `postgreSQL/float4.sql` and `postgreSQL/int8.sql` to fix Java 21 daily test. ### Why are the changes needed? Fix Java 21 daily test: - https://github.com/apache/spark/actions/runs/10823897095/job/30030200710 ``` [info] - postgreSQL/float4.sql *** FAILED *** (1 second, 100 milliseconds) [info] postgreSQL/float4.sql [info] Expected "...arameters" : { [info] "[ansiConfig" : "\"spark.sql.ansi.enabled\"", [info] "]expression" : "'N A ...", but got "...arameters" : { [info] "[]expression" : "'N A ..." Result did not match for query #11 [info] SELECT float('N A N') (SQLQueryTestSuite.scala:663) ... [info] - postgreSQL/int8.sql *** FAILED *** (2 seconds, 474 milliseconds) [info] postgreSQL/int8.sql [info] Expected "...arameters" : { [info] "[ansiConfig" : "\"spark.sql.ansi.enabled\"", [info] "]sourceType" : "\"BIG...", but got "...arameters" : { [info] "[]sourceType" : "\"BIG..." Result did not match for query #66 [info] SELECT CAST(q1 AS int) FROM int8_tbl WHERE q2 <> 456 (SQLQueryTestSuite.scala:663) ... [info] *** 2 TESTS FAILED *** [error] Failed: Total 3559, Failed 2, Errors 0, Passed 3557, Ignored 4 [error] Failed tests: [error] org.apache.spark.sql.SQLQueryTestSuite [error] (sql / Test / test) sbt.TestsFailedException: Tests unsuccessful ``` ### Does this PR introduce _any_ user-facing change? No ### How was this patch tested? - Pass Github Acitons - Manual checked: `build/sbt "sql/testOnly org.apache.spark.sql.SQLQueryTestSuite" with Java 21, all test passed ` ### Was this patch authored or co-authored using generative AI tooling? No Closes apache#48089 from LuciferYang/SPARK-49578-FOLLOWUP. Authored-by: yangjie01 <[email protected]> Signed-off-by: Dongjoon Hyun <[email protected]>
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…e` building ### What changes were proposed in this pull request? This PR aims to add `libwebp-dev` to recover `spark-rm/Dockerfile` building. ### Why are the changes needed? `Apache Spark` release docker image compilation has been broken for last 7 days due to the SparkR package compilation. - https://github.com/apache/spark/actions/workflows/release.yml - https://github.com/apache/spark/actions/runs/17425825244 ``` #11 559.4 No package 'libwebpmux' found ... #11 559.4 -------------------------- [ERROR MESSAGE] --------------------------- #11 559.4 <stdin>:1:10: fatal error: ft2build.h: No such file or directory #11 559.4 compilation terminated. #11 559.4 -------------------------------------------------------------------- #11 559.4 ERROR: configuration failed for package 'ragg' ``` ### Does this PR introduce _any_ user-facing change? No, this is a fix for Apache Spark release tool. ### How was this patch tested? Manually build. ``` $ cd dev/create-release/spark-rm $ docker build . ``` **BEFORE** ``` ... Dockerfile:83 -------------------- 82 | # See more in SPARK-39959, roxygen2 < 7.2.1 83 | >>> RUN Rscript -e "install.packages(c('devtools', 'knitr', 'markdown', \ 84 | >>> 'rmarkdown', 'testthat', 'devtools', 'e1071', 'survival', 'arrow', \ 85 | >>> 'ggplot2', 'mvtnorm', 'statmod', 'xml2'), repos='https://cloud.r-project.org/')" && \ 86 | >>> Rscript -e "devtools::install_version('roxygen2', version='7.2.0', repos='https://cloud.r-project.org')" && \ 87 | >>> Rscript -e "devtools::install_version('lintr', version='2.0.1', repos='https://cloud.r-project.org')" && \ 88 | >>> Rscript -e "devtools::install_version('pkgdown', version='2.0.1', repos='https://cloud.r-project.org')" && \ 89 | >>> Rscript -e "devtools::install_version('preferably', version='0.4', repos='https://cloud.r-project.org')" 90 | -------------------- ERROR: failed to build: failed to solve: ``` **AFTER** ``` ... => [ 6/22] RUN add-apt-repository 'deb https://cloud.r-project.org/bin/linux/ubuntu jammy-cran40/' 3.8s => [ 7/22] RUN Rscript -e "install.packages(c('devtools', 'knitr', 'markdown', 'rmarkdown', 'testthat', 'devtools', 'e1071', 'survival', 'arrow', 892.2s => [ 8/22] RUN add-apt-repository ppa:pypy/ppa 15.3s ... ``` After merging this PR, we can validate via the daily release dry-run CI. - https://github.com/apache/spark/actions/workflows/release.yml ### Was this patch authored or co-authored using generative AI tooling? No. Closes apache#52290 from dongjoon-hyun/SPARK-53539. Authored-by: Dongjoon Hyun <[email protected]> Signed-off-by: Dongjoon Hyun <[email protected]>
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…rsion at the end ### What changes were proposed in this pull request? This PR aims to fix `spark-rm` Dockefile to install `pkgdown` version at the end. ### Why are the changes needed? Although `pkgdown` is supposed to be `2.0.1`, it's changed at the next package installation like the following. We should install `pkgdown` at the end to make it sure. https://github.com/apache/spark/blob/0311f44e33e5cf8ba60ccc330de3df4f688f5847/dev/create-release/spark-rm/Dockerfile#L89 - https://github.com/apache/spark/actions/workflows/release.yml - https://github.com/apache/spark/actions/runs/19386198324/job/55473421715 ``` #11 1007.3 Downloading package from url: https://cloud.r-project.org/src/contrib/Archive/preferably/preferably_0.4.tar.gz #11 1008.9 pkgdown (2.0.1 -> 2.2.0) [CRAN] #11 1008.9 Installing 1 packages: pkgdown #11 1008.9 Installing package into '/usr/local/lib/R/site-library' #11 1008.9 (as 'lib' is unspecified) #11 1009.4 trying URL 'https://cloud.r-project.org/src/contrib/pkgdown_2.2.0.tar.gz' #11 1009.7 Content type 'application/x-gzip' length 1280630 bytes (1.2 MB) #11 1009.7 ================================================== #11 1009.7 downloaded 1.2 MB #11 1009.7 #11 1010.2 * installing *source* package 'pkgdown' ... #11 1010.2 ** package 'pkgdown' successfully unpacked and MD5 sums checked #11 1010.2 ** using staged installation #11 1010.3 ** R #11 1010.3 ** inst #11 1010.3 ** byte-compile and prepare package for lazy loading #11 1013.1 ** help #11 1013.2 *** installing help indices #11 1013.2 *** copying figures #11 1013.2 ** building package indices #11 1013.5 ** installing vignettes #11 1013.5 ** testing if installed package can be loaded from temporary location #11 1013.8 ** testing if installed package can be loaded from final location #11 1014.1 ** testing if installed package keeps a record of temporary installation path #11 1014.1 * DONE (pkgdown) ``` ### Does this PR introduce _any_ user-facing change? No. ### How was this patch tested? Manual review. ``` $ dev/create-release/do-release-docker.sh -d /tmp/spark-4.1.0 -n -s docs $ docker run -it --rm --entrypoint /bin/bash spark-rm spark-rm923a388425fa:/opt/spark-rm/output$ Rscript -e 'installed.packages()' | grep pkgdown | head -n1 pkgdown "pkgdown" "/usr/local/lib/R/site-library" "2.0.1" ``` ### Was this patch authored or co-authored using generative AI tooling? No. Closes apache#53083 from dongjoon-hyun/SPARK-54371. Authored-by: Dongjoon Hyun <[email protected]> Signed-off-by: Dongjoon Hyun <[email protected]>
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Please review http://spark.apache.org/contributing.html before opening a pull request.