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MaxGekk
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Jul 14, 2019
…nput of UDF as double in the failed test in udf-aggregate_part1.sql ## What changes were proposed in this pull request? It still can be flaky on certain environments due to float limitation described at apache#25110 . See apache#25110 (comment) - https://amplab.cs.berkeley.edu/jenkins/view/Spark%20QA%20Test%20(Dashboard)/job/spark-master-test-maven-hadoop-2.7/6584/testReport/org.apache.spark.sql/SQLQueryTestSuite/udf_pgSQL_udf_aggregates_part1_sql___Regular_Python_UDF/ ``` Expected "700000000000[6] 1", but got "700000000000[5] 1" Result did not match for query apache#33 SELECT CAST(avg(udf(CAST(x AS DOUBLE))) AS long), CAST(udf(var_pop(CAST(x AS DOUBLE))) AS decimal(10,3)) FROM (VALUES (7000000000005), (7000000000007)) v(x) ``` Here;s what's going on: apache#25110 (comment) ``` scala> Seq("7000000000004.999", "7000000000006.999").toDF().selectExpr("CAST(avg(value) AS long)").show() +--------------------------+ |CAST(avg(value) AS BIGINT)| +--------------------------+ | 7000000000005| +--------------------------+ ``` Therefore, this PR just avoid to cast in the specific test. This is a temp fix. We need more robust way to avoid such cases. ## How was this patch tested? It passes with Maven in my local before/after this PR. I believe the problem seems similarly the Python or OS installed in the machine. I should test this against PR builder with `test-maven` for sure.. Closes apache#25128 from HyukjinKwon/SPARK-28270-2. Authored-by: HyukjinKwon <[email protected]> Signed-off-by: HyukjinKwon <[email protected]>
MaxGekk
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Nov 16, 2019
… Arrow on JDK9+ ### What changes were proposed in this pull request? This PR aims to add `io.netty.tryReflectionSetAccessible=true` to the testing configuration for JDK11 because this is an officially documented requirement of Apache Arrow. Apache Arrow community documented this requirement at `0.15.0` ([ARROW-6206](apache/arrow#5078)). > #### For java 9 or later, should set "-Dio.netty.tryReflectionSetAccessible=true". > This fixes `java.lang.UnsupportedOperationException: sun.misc.Unsafe or java.nio.DirectByteBuffer.(long, int) not available`. thrown by netty. ### Why are the changes needed? After ARROW-3191, Arrow Java library requires the property `io.netty.tryReflectionSetAccessible` to be set to true for JDK >= 9. After apache#26133, JDK11 Jenkins job seem to fail. - https://amplab.cs.berkeley.edu/jenkins/view/Spark%20QA%20Test%20(Dashboard)/job/spark-master-test-maven-hadoop-3.2-jdk-11/676/ - https://amplab.cs.berkeley.edu/jenkins/view/Spark%20QA%20Test%20(Dashboard)/job/spark-master-test-maven-hadoop-3.2-jdk-11/677/ - https://amplab.cs.berkeley.edu/jenkins/view/Spark%20QA%20Test%20(Dashboard)/job/spark-master-test-maven-hadoop-3.2-jdk-11/678/ ```scala Previous exception in task: sun.misc.Unsafe or java.nio.DirectByteBuffer.<init>(long, int) not available io.netty.util.internal.PlatformDependent.directBuffer(PlatformDependent.java:473) io.netty.buffer.NettyArrowBuf.getDirectBuffer(NettyArrowBuf.java:243) io.netty.buffer.NettyArrowBuf.nioBuffer(NettyArrowBuf.java:233) io.netty.buffer.ArrowBuf.nioBuffer(ArrowBuf.java:245) org.apache.arrow.vector.ipc.message.ArrowRecordBatch.computeBodyLength(ArrowRecordBatch.java:222) ``` ### Does this PR introduce any user-facing change? No. ### How was this patch tested? Pass the Jenkins with JDK11. Closes apache#26552 from dongjoon-hyun/SPARK-ARROW-JDK11. Authored-by: Dongjoon Hyun <[email protected]> Signed-off-by: Dongjoon Hyun <[email protected]>
MaxGekk
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Dec 16, 2020
…mand ### What changes were proposed in this pull request? This PR proposes to sort table properties in DESCRIBE TABLE command. This is consistent with DSv2 command as well: https://github.com/apache/spark/blob/e3058ba17cb4512537953eb4ded884e24ee93ba2/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/v2/DescribeTableExec.scala#L63 This PR fixes the test case in Scala 2.13 build as well where the table properties have different order in the map. ### Why are the changes needed? To keep the deterministic and pretty output, and fix the tests in Scala 2.13 build. See https://amplab.cs.berkeley.edu/jenkins/job/spark-master-test-maven-hadoop-3.2-scala-2.13/49/testReport/junit/org.apache.spark.sql/SQLQueryTestSuite/describe_sql/ ``` describe.sql Expected "...spark_catalog, view.[query.out.col.2=c, view.referredTempFunctionsNames=[], view.catalogAndNamespace.part.1=default]]", but got "...spark_catalog, view.[catalogAndNamespace.part.1=default, view.query.out.col.2=c, view.referredTempFunctionsNames=[]]]" Result did not match for query apache#29 DESC FORMATTED v ``` ### Does this PR introduce _any_ user-facing change? Yes, it will change the text output from `DESCRIBE [EXTENDED|FORMATTED] table_name`. Now the table properties are sorted by its key. ### How was this patch tested? Related unittests were fixed accordingly. Closes apache#30799 from HyukjinKwon/SPARK-33803. Authored-by: HyukjinKwon <[email protected]> Signed-off-by: Wenchen Fan <[email protected]>
MaxGekk
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Dec 17, 2020
…mand ### What changes were proposed in this pull request? This PR proposes to sort table properties in DESCRIBE TABLE command. This is consistent with DSv2 command as well: https://github.com/apache/spark/blob/e3058ba17cb4512537953eb4ded884e24ee93ba2/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/v2/DescribeTableExec.scala#L63 This PR fixes the test case in Scala 2.13 build as well where the table properties have different order in the map. ### Why are the changes needed? To keep the deterministic and pretty output, and fix the tests in Scala 2.13 build. See https://amplab.cs.berkeley.edu/jenkins/job/spark-master-test-maven-hadoop-3.2-scala-2.13/49/testReport/junit/org.apache.spark.sql/SQLQueryTestSuite/describe_sql/ ``` describe.sql Expected "...spark_catalog, view.[query.out.col.2=c, view.referredTempFunctionsNames=[], view.catalogAndNamespace.part.1=default]]", but got "...spark_catalog, view.[catalogAndNamespace.part.1=default, view.query.out.col.2=c, view.referredTempFunctionsNames=[]]]" Result did not match for query apache#29 DESC FORMATTED v ``` ### Does this PR introduce _any_ user-facing change? Yes, it will change the text output from `DESCRIBE [EXTENDED|FORMATTED] table_name`. Now the table properties are sorted by its key. ### How was this patch tested? Related unittests were fixed accordingly. Closes apache#30799 from HyukjinKwon/SPARK-33803. Authored-by: HyukjinKwon <[email protected]> Signed-off-by: Wenchen Fan <[email protected]> (cherry picked from commit 7845865) Signed-off-by: Wenchen Fan <[email protected]>
MaxGekk
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Mar 14, 2022
…aceable
### What changes were proposed in this pull request?
This PR uses a manual recursion to replace `RuntimeReplaceable` expressions instead of `transformAllExpressionsWithPruning`. The problem of `transformAllExpressionsWithPruning` is it will automatically make the replacement expression inherit the function alias name from the parent node, which is quite misleading. For example, `select date_part('month', c) from t`, the optimized plan in EXPLAIN before this PR is
```
Project [date_part(cast(c#18 as date)) AS date_part(month, c)#19]
+- Relation default.t[c#18] parquet
```
Now it's
```
Project [month(cast(c#9 as date)) AS date_part(month, c)#10]
+- Relation default.t[c#9] parquet
```
### Why are the changes needed?
fix misleading EXPLAIN result
### Does this PR introduce _any_ user-facing change?
no
### How was this patch tested?
new test
Closes apache#35821 from cloud-fan/follow2.
Authored-by: Wenchen Fan <[email protected]>
Signed-off-by: Dongjoon Hyun <[email protected]>
MaxGekk
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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 <[email protected]>
Signed-off-by: Dongjoon Hyun <[email protected]>
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