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https://issues.apache.org/jira/browse/SPARK-48380?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=17850486#comment-17850486
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Zheng Shao commented on SPARK-48380:
A second look at the stacktrace shows that the current issue is
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https://issues.apache.org/jira/browse/SPARK-48380?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=17848375#comment-17848375
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Zheng Shao commented on SPARK-48380:
A draft PR can be found here:
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Zheng Shao updated SPARK-48380:
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Description:
AutoBatchedPickler assumes that the row sizes are more or less uniform. That's
of
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Zheng Shao updated SPARK-48380:
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Description:
AutoBatchedPickler assumes that the row sizes are more or less uniform. That's
of
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Zheng Shao updated SPARK-48380:
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Description:
The stacktrace:
{{```}}
{{Py4JJavaError: An error occurred while calling
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Zheng Shao updated SPARK-48380:
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Description:
The stacktrace:
{{```}}
{{Py4JJavaError: An error occurred while calling
Zheng Shao created SPARK-48380:
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Summary: AutoBatchedPickler caused Unsafe allocate to fail due to
2GB limit
Key: SPARK-48380
URL: https://issues.apache.org/jira/browse/SPARK-48380
Project: Spark
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https://issues.apache.org/jira/browse/SPARK-47959?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Zheng Shao updated SPARK-47959:
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Description:
We have a Spark executor that is running 32 workers in parallel. The query is
a
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https://issues.apache.org/jira/browse/SPARK-47959?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Zheng Shao updated SPARK-47959:
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Description:
We have a Spark executor that is running 32 workers in parallel. The query is
a
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https://issues.apache.org/jira/browse/SPARK-47959?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Zheng Shao updated SPARK-47959:
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Description:
We have a Spark executor that is running 32 workers in parallel. The query is
a
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https://issues.apache.org/jira/browse/SPARK-47959?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Zheng Shao updated SPARK-47959:
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Description:
We have a Spark executor that is running 32 workers in parallel. The query is
a
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https://issues.apache.org/jira/browse/SPARK-47959?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Zheng Shao updated SPARK-47959:
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Description:
We have a Spark executor that is running 32 workers in parallel. The query is
a
Zheng Shao created SPARK-47959:
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Summary: Improve GET_JSON_OBJECT performance on executors running
multiple tasks
Key: SPARK-47959
URL: https://issues.apache.org/jira/browse/SPARK-47959
Project: Spark
Zheng Shao created SPARK-47801:
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Summary: Use simdjson-java in JSON related UDFs
Key: SPARK-47801
URL: https://issues.apache.org/jira/browse/SPARK-47801
Project: Spark
Issue Type: Improvement
Zheng Shao created SPARK-47670:
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Summary: Multiple calls to GET_JSON_OBJECT with the same JSON str
should parse it just one time
Key: SPARK-47670
URL: https://issues.apache.org/jira/browse/SPARK-47670
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https://issues.apache.org/jira/browse/SPARK-26764?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=17370770#comment-17370770
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Zheng Shao commented on SPARK-26764:
[~adrian-wang] It has been over 2 years since this issue was
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https://issues.apache.org/jira/browse/SPARK-29038?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=17370768#comment-17370768
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Zheng Shao commented on SPARK-29038:
[~cltlfcjin] and [~AidenZhang]. I also recently started to look
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https://issues.apache.org/jira/browse/SPARK-1529?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16924940#comment-16924940
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Zheng Shao commented on SPARK-1529:
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For huge Spark jobs, we are seeing frequent failures due to the
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https://issues.apache.org/jira/browse/SPARK-6951?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15889588#comment-15889588
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Zheng Shao commented on SPARK-6951:
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Did we consider using a distributed store to solve the scalability
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