[jira] [Created] (SPARK-48040) Spark connect supports set scheduler pool name
xie shuiahu created SPARK-48040: --- Summary: Spark connect supports set scheduler pool name Key: SPARK-48040 URL: https://issues.apache.org/jira/browse/SPARK-48040 Project: Spark Issue Type: New Feature Components: Connect Affects Versions: 3.5.1 Reporter: xie shuiahu Spark supports fair scheduler and grouping job into pools, but spark connect don't support this feature. -- This message was sent by Atlassian Jira (v8.20.10#820010) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Created] (SPARK-46732) Propagate ArtifactSet to broadcast execution thread
xie shuiahu created SPARK-46732: --- Summary: Propagate ArtifactSet to broadcast execution thread Key: SPARK-46732 URL: https://issues.apache.org/jira/browse/SPARK-46732 Project: Spark Issue Type: New Feature Components: Connect Affects Versions: 3.5.0 Reporter: xie shuiahu Similar with SPARK-44794，the JobArtifactState is not propagated to broadcast execution thread -- This message was sent by Atlassian Jira (v8.20.10#820010) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Updated] (SPARK-46732) Propagate JobArtifactSet to broadcast execution thread
[ https://issues.apache.org/jira/browse/SPARK-46732?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] xie shuiahu updated SPARK-46732: Summary: Propagate JobArtifactSet to broadcast execution thread (was: Propagate ArtifactSet to broadcast execution thread) > Propagate JobArtifactSet to broadcast execution thread > -- > > Key: SPARK-46732 > URL: https://issues.apache.org/jira/browse/SPARK-46732 > Project: Spark > Issue Type: New Feature > Components: Connect >Affects Versions: 3.5.0 >Reporter: xie shuiahu >Priority: Major > > Similar with SPARK-44794，the JobArtifactState is not propagated to broadcast > execution thread -- This message was sent by Atlassian Jira (v8.20.10#820010) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Created] (SPARK-45821) SparkSession._apply_options shouldn't catch all exceptions
xie shuiahu created SPARK-45821: --- Summary: SparkSession._apply_options shouldn't catch all exceptions Key: SPARK-45821 URL: https://issues.apache.org/jira/browse/SPARK-45821 Project: Spark Issue Type: Bug Components: Connect, PySpark Affects Versions: 3.5.0 Reporter: xie shuiahu `SparkSession._apply_options` catches all exceptions, which is unexpected. -- This message was sent by Atlassian Jira (v8.20.10#820010) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Created] (SPARK-45814) ArrowConverters.createEmptyArrowBatch may cause memory leak
xie shuiahu created SPARK-45814: --- Summary: ArrowConverters.createEmptyArrowBatch may cause memory leak Key: SPARK-45814 URL: https://issues.apache.org/jira/browse/SPARK-45814 Project: Spark Issue Type: Bug Components: Connect, SQL Affects Versions: 3.5.0, 3.4.1 Reporter: xie shuiahu ArrowConverters.createEmptyArrowBatch don't call hasNext, if TaskContext.get is None, then memory leak happens -- This message was sent by Atlassian Jira (v8.20.10#820010) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Resolved] (SPARK-45738) client will wait forever if session in spark connect server is evicted
[
https://issues.apache.org/jira/browse/SPARK-45738?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
xie shuiahu resolved SPARK-45738.
-
Resolution: Implemented
> client will wait forever if session in spark connect server is evicted
> --
>
> Key: SPARK-45738
> URL: https://issues.apache.org/jira/browse/SPARK-45738
> Project: Spark
> Issue Type: Bug
> Components: Connect
>Affects Versions: 3.5.0
>Reporter: xie shuiahu
>Priority: Critical
> Labels: pull-request-available, query-lifecycle
>
> Step1. start a spark connect server
> Step2. submit a spark job which will run long
> {code:java}
> from pyspark.sql import SparkSession
> spark = SparkSession.builder.remote(f"sc://HOST:PORT/;user_id=job").create()
> spark.sql("A SQL will run longer than creating 100 sessions").show() {code}
>
> Step3. create more than 100 sessions
> Tips: Run concurrently with step2
> {code:java}
> for i in range(0, 200):
> spark =
> SparkSession.builder.remote(f"sc://HOST:PORT/;user_id={i}").create()
> spark.sql("show databases") {code}
>
> *When the python code in step3 is executed, the session created in step2 will
> be evicted, and the client will wait forever*
>
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[jira] [Updated] (SPARK-45738) client will wait forever if session in spark connect server is evicted
[
https://issues.apache.org/jira/browse/SPARK-45738?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
xie shuiahu updated SPARK-45738:
Labels: pull-request-available query-lifecycle (was:
pull-request-available)
> client will wait forever if session in spark connect server is evicted
> --
>
> Key: SPARK-45738
> URL: https://issues.apache.org/jira/browse/SPARK-45738
> Project: Spark
> Issue Type: Bug
> Components: Connect
>Affects Versions: 3.5.0
>Reporter: xie shuiahu
>Priority: Critical
> Labels: pull-request-available, query-lifecycle
>
> Step1. start a spark connect server
> Step2. submit a spark job which will run long
> {code:java}
> from pyspark.sql import SparkSession
> spark = SparkSession.builder.remote(f"sc://HOST:PORT/;user_id=job").create()
> spark.sql("A SQL will run longer than creating 100 sessions").show() {code}
>
> Step3. create more than 100 sessions
> Tips: Run concurrently with step2
> {code:java}
> for i in range(0, 200):
> spark =
> SparkSession.builder.remote(f"sc://HOST:PORT/;user_id={i}").create()
> spark.sql("show databases") {code}
>
> *When the python code in step3 is executed, the session created in step2 will
> be evicted, and the client will wait forever*
>
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[jira] [Updated] (SPARK-45738) client will wait forever if session in spark connect server is evicted
[
https://issues.apache.org/jira/browse/SPARK-45738?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
xie shuiahu updated SPARK-45738:
Description:
Step1. start a spark connect server
Step2. submit a spark job which will run long
{code:java}
from pyspark.sql import SparkSession
spark = SparkSession.builder.remote(f"sc://HOST:PORT/;user_id=job").create()
spark.sql("A SQL will run longer than creating 100 sessions").show() {code}
Step3. create more than 100 sessions
Tips: Run concurrently with step2
{code:java}
for i in range(0, 200):
spark = SparkSession.builder.remote(f"sc://HOST:PORT/;user_id={i}").create()
spark.sql("show databases") {code}
*When the python code in step3 is executed, the session created in step2 will
be evicted, and the client will wait forever*
was:
Step1. start a spark connect server
Step2. submit a spark job which will run long
{code:java}
from pyspark.sql import SparkSession
spark = SparkSession.builder.remote(f"sc://HOST:PORT/;user_id=job").create()
spark.sql("A SQL will run longer than creating 100 sessions").show() {code}
Step3. create more than 100 sessions
Tips: Run concurrently with step2
{code:java}
for i in range(0, 200):
spark = SparkSession.builder.remote(f"sc://HOST:PORT/;user_id={i}").create()
spark.sql("show databases") {code}
*When the python code in step3 is executed, the session created in step2 will
be evicted, and the client will wait forever*
The server will log exception like this:
> client will wait forever if session in spark connect server is evicted
> --
>
> Key: SPARK-45738
> URL: https://issues.apache.org/jira/browse/SPARK-45738
> Project: Spark
> Issue Type: Bug
> Components: Connect
>Affects Versions: 3.5.0
>Reporter: xie shuiahu
>Priority: Critical
>
> Step1. start a spark connect server
> Step2. submit a spark job which will run long
> {code:java}
> from pyspark.sql import SparkSession
> spark = SparkSession.builder.remote(f"sc://HOST:PORT/;user_id=job").create()
> spark.sql("A SQL will run longer than creating 100 sessions").show() {code}
>
> Step3. create more than 100 sessions
> Tips: Run concurrently with step2
> {code:java}
> for i in range(0, 200):
> spark =
> SparkSession.builder.remote(f"sc://HOST:PORT/;user_id={i}").create()
> spark.sql("show databases") {code}
>
> *When the python code in step3 is executed, the session created in step2 will
> be evicted, and the client will wait forever*
>
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[jira] [Created] (SPARK-45738) client will wait forever if session in spark connect server is evicted
xie shuiahu created SPARK-45738:
---
Summary: client will wait forever if session in spark connect
server is evicted
Key: SPARK-45738
URL: https://issues.apache.org/jira/browse/SPARK-45738
Project: Spark
Issue Type: Bug
Components: Connect
Affects Versions: 3.5.0
Reporter: xie shuiahu
Step1. start a spark connect server
Step2. submit a spark job which will run long
{code:java}
from pyspark.sql import SparkSession
spark = SparkSession.builder.remote(f"sc://HOST:PORT/;user_id=job").create()
spark.sql("A SQL will run longer than creating 100 sessions").show() {code}
Step3. create more than 100 sessions
Tips: Run concurrently with step2
{code:java}
for i in range(0, 200):
spark = SparkSession.builder.remote(f"sc://HOST:PORT/;user_id={i}").create()
spark.sql("show databases") {code}
*When the python code in step3 is executed, the session created in step2 will
be evicted, and the client will wait forever*
The server will log exception like this:
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[jira] [Created] (SPARK-45538) pyspark connect overwrite_partitions bug
xie shuiahu created SPARK-45538: --- Summary: pyspark connect overwrite_partitions bug Key: SPARK-45538 URL: https://issues.apache.org/jira/browse/SPARK-45538 Project: Spark Issue Type: Improvement Components: Connect Affects Versions: 3.5.0 Environment: pyspark connect 3.5.0 Reporter: xie shuiahu DataFrameWriterV2.overwritePartitions set mode as *overwrite_partitions* [pyspark/sql/connect/readwriter.py, line 825], but WirteOperationV2 take it as *overwrite_partition* [pyspark/sql/connect/plan.py, line 1660] -- This message was sent by Atlassian Jira (v8.20.10#820010) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Commented] (SPARK-45201) NoClassDefFoundError: InternalFutureFailureAccess when compiling Spark 3.5.0
[
https://issues.apache.org/jira/browse/SPARK-45201?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17773976#comment-17773976
]
xie shuiahu commented on SPARK-45201:
-
[~sdaberdaku] I alse have the same issue. I solved it by putting
spark-connect.jar in spark-submit --jars, instead of SPARK_HOME/jars
> NoClassDefFoundError: InternalFutureFailureAccess when compiling Spark 3.5.0
>
>
> Key: SPARK-45201
> URL: https://issues.apache.org/jira/browse/SPARK-45201
> Project: Spark
> Issue Type: Bug
> Components: Connect
>Affects Versions: 3.5.0
>Reporter: Sebastian Daberdaku
>Priority: Major
> Attachments: Dockerfile, spark-3.5.0.patch
>
>
> I am trying to compile Spark 3.5.0 and make a distribution that supports
> Spark Connect and Kubernetes. The compilation seems to complete correctly,
> but when I try to run the Spark Connect server on kubernetes I get a
> "NoClassDefFoundError" as follows:
> {code:java}
> Exception in thread "main" java.lang.NoClassDefFoundError:
> org/sparkproject/guava/util/concurrent/internal/InternalFutureFailureAccess
> at java.base/java.lang.ClassLoader.defineClass1(Native Method)
> at java.base/java.lang.ClassLoader.defineClass(ClassLoader.java:1017)
> at
> java.base/java.security.SecureClassLoader.defineClass(SecureClassLoader.java:150)
> at
> java.base/jdk.internal.loader.BuiltinClassLoader.defineClass(BuiltinClassLoader.java:862)
> at
> java.base/jdk.internal.loader.BuiltinClassLoader.findClassOnClassPathOrNull(BuiltinClassLoader.java:760)
> at
> java.base/jdk.internal.loader.BuiltinClassLoader.loadClassOrNull(BuiltinClassLoader.java:681)
> at
> java.base/jdk.internal.loader.BuiltinClassLoader.loadClass(BuiltinClassLoader.java:639)
> at
> java.base/jdk.internal.loader.ClassLoaders$AppClassLoader.loadClass(ClassLoaders.java:188)
> at java.base/java.lang.ClassLoader.loadClass(ClassLoader.java:525)
> at java.base/java.lang.ClassLoader.defineClass1(Native Method)
> at java.base/java.lang.ClassLoader.defineClass(ClassLoader.java:1017)
> at
> java.base/java.security.SecureClassLoader.defineClass(SecureClassLoader.java:150)
> at
> java.base/jdk.internal.loader.BuiltinClassLoader.defineClass(BuiltinClassLoader.java:862)
> at
> java.base/jdk.internal.loader.BuiltinClassLoader.findClassOnClassPathOrNull(BuiltinClassLoader.java:760)
> at
> java.base/jdk.internal.loader.BuiltinClassLoader.loadClassOrNull(BuiltinClassLoader.java:681)
> at
> java.base/jdk.internal.loader.BuiltinClassLoader.loadClass(BuiltinClassLoader.java:639)
> at
> java.base/jdk.internal.loader.ClassLoaders$AppClassLoader.loadClass(ClassLoaders.java:188)
> at java.base/java.lang.ClassLoader.loadClass(ClassLoader.java:525)
> at java.base/java.lang.ClassLoader.defineClass1(Native Method)
> at java.base/java.lang.ClassLoader.defineClass(ClassLoader.java:1017)
> at
> java.base/java.security.SecureClassLoader.defineClass(SecureClassLoader.java:150)
> at
> java.base/jdk.internal.loader.BuiltinClassLoader.defineClass(BuiltinClassLoader.java:862)
> at
> java.base/jdk.internal.loader.BuiltinClassLoader.findClassOnClassPathOrNull(BuiltinClassLoader.java:760)
> at
> java.base/jdk.internal.loader.BuiltinClassLoader.loadClassOrNull(BuiltinClassLoader.java:681)
> at
> java.base/jdk.internal.loader.BuiltinClassLoader.loadClass(BuiltinClassLoader.java:639)
> at
> java.base/jdk.internal.loader.ClassLoaders$AppClassLoader.loadClass(ClassLoaders.java:188)
> at java.base/java.lang.ClassLoader.loadClass(ClassLoader.java:525)
> at
> org.sparkproject.guava.cache.LocalCache$LoadingValueReference.(LocalCache.java:3511)
> at
> org.sparkproject.guava.cache.LocalCache$LoadingValueReference.(LocalCache.java:3515)
> at
> org.sparkproject.guava.cache.LocalCache$Segment.lockedGetOrLoad(LocalCache.java:2168)
> at
> org.sparkproject.guava.cache.LocalCache$Segment.get(LocalCache.java:2079)
> at org.sparkproject.guava.cache.LocalCache.get(LocalCache.java:4011)
> at org.sparkproject.guava.cache.LocalCache.getOrLoad(LocalCache.java:4034)
> at
> org.sparkproject.guava.cache.LocalCache$LocalLoadingCache.get(LocalCache.java:5010)
> at
> org.apache.spark.storage.BlockManagerId$.getCachedBlockManagerId(BlockManagerId.scala:146)
> at
> org.apache.spark.storage.BlockManagerId$.apply(BlockManagerId.scala:127)
> at
> org.apache.spark.storage.BlockManager.initialize(BlockManager.scala:536)
> at org.apache.spark.SparkContext.(SparkContext.scala:625)
> at org.apache.spark.SparkContext$.getOrCreate(SparkContext.scala:2888)
> at
> org.apache.spark.sql.SparkSession$Builder.$anonfun$getOrCreate$2(SparkSession.scala:1099)
> at scal
