name nits #11
Merged
name nits #11
Conversation
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
MaxGekk
pushed a commit
that referenced
this pull request
Oct 31, 2018
…/`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 <gengliang.wang@databricks.com>
Signed-off-by: gatorsmile <gatorsmile@gmail.com>
MaxGekk
pushed a commit
that referenced
this pull request
Feb 16, 2019
…from_avro`/`to_avro` Back port apache#22890 to branch-2.4. It is a bug fix for this issue: https://issues.apache.org/jira/browse/SPARK-26063 ## 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#23047 from gengliangwang/backport_avro_pretty_name. Authored-by: Gengliang Wang <gengliang.wang@databricks.com> Signed-off-by: hyukjinkwon <gurwls223@apache.org>
MaxGekk
pushed a commit
that referenced
this pull request
Dec 31, 2019
### 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 <lijunqing@baidu.com> Co-authored-by: stczwd <qcsd2011@163.com> Signed-off-by: Wenchen Fan <wenchen@databricks.com>
MaxGekk
pushed a commit
that referenced
this pull request
Feb 26, 2024
…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 <ruifengz@apache.org>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
MaxGekk
pushed a commit
that referenced
this pull request
Sep 13, 2024
…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 apache#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 <yangjie01@baidu.com> Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
What changes were proposed in this pull request?
(Please fill in changes proposed in this fix)
How was this patch tested?
(Please explain how this patch was tested. E.g. unit tests, integration tests, manual tests)
(If this patch involves UI changes, please attach a screenshot; otherwise, remove this)
Please review http://spark.apache.org/contributing.html before opening a pull request.