Github user j143 commented on the issue:
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Hi @witgo, Did you test this PR in production environment. If yes, can you
share the results on this
[jira](https://issues.apache.org/jira/browse/SPARK-6235). If you have problems
with downloading thi
Github user lklong commented on the issue:
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@witgo i am very sorry to ask you give me a zip to my email ,because i try
to get this branch more than 10 times ,but i can not download this branch ,my
email is 380312...@qq.com,please help me ï¼t
Github user lklong commented on the issue:
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@witgo thank you very much ,my product of next generation will use
spark-2.1,now i use spark-1.6,i am often meet 2g error ,i am very glad to see
you code! thanks! i just use spark-ml in my production
Github user witgo commented on the issue:
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I did not do much testing, but I think it can be used in the production
environment
the url:
https://github.com/witgo/spark/tree/SPARK-6235_Address_various_2G_limits
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Github user lklong commented on the issue:
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@witgo hi ,i want to know this patch can be used in preduct env?
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Github user lklong commented on the issue:
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hi@witgo ,i am glad to see this patch ,but i do not know how should i check
this patch,i need this very much, thank you for give me this patch url.please
and thanks!
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Github user witgo commented on the issue:
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Thanks, I am glad to hear this, and I want to solve the issues of reading,
storing and transmitting data as much as possible.
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Github user opme commented on the issue:
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@witgo I have a Pyspark application that was failing in 3 different places
but is able to run without errors now. I'm glad for this patch as I am not
sure how I would have explained to my professors
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Github user witgo commented on the issue:
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This PR is Test only, it used to
1. verify code through CI
2. verify the effectiveness of the solution
includes two underlying API changes.
1. Replace ByteBuffer with ChunkedBy
Github user opme commented on the issue:
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I compiled this pull request into the main branch. I can confirm it fixes
the problem where I was performing joins between tables with 2 million and 300
million records + making counts and then gettin
Github user srowen commented on the issue:
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This change is marked as not ready to merge, does not merge, hasn't been
reviewed, and isn't going to be reviewed as a huge 143-file, 4400 line change.
This has been discussed in many different ways
Github user witgo commented on the issue:
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@srowen
This PR is a comprehensive solution. Used to solve address various 2G
limits, RPC memory footprint and other issues.
Users often encounter these problems. Why don't we need to solve t
Github user srowen commented on the issue:
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@witgo if this is a stale WIP, would you mind closing it? as far as I know
it doesn't necessarily solve the problem in the JIRA and may be misleading to
those that think there is a solution available
Github user opme commented on the issue:
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What is the plan to incorporate this patch into a released version? I am
hitting this limit when doing simple joins of a table with 2 million records to
a table of 300 million records and performing a
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