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Forum Posts

MarsSu
by New Contributor II
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How to implement merge multiple rows in single row with array and do not result in OOM?

Hi, Everyone.Currently I try to implement spark structured streaming with Pyspark. And I would like to merge multiple rows in single row with array and sink to downstream message queue for another service to use. Related example can follow as:* Befor...

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917074
New Contributor II
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Is there any solution to this, @MarsSu  were you able to solve this, kindly shed some light on this if you resolve this.

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Satty
by New Contributor
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Solution for ConnectException error: This is often caused by an OOM error that causes the connection to the Python REPL to be closed. Check your query's memory usage.

When ever I am trying to run and load multiple files in single dataframe for processing (overall file size is more than 15 gb in single dataframe at the end of the loop, my code is crashing everytime with the below error...ConnectException error: Thi...

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pvignesh92
Honored Contributor
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@Satish Agarwal​ It seems your system memory is not sufficient to load the 15GB file. I believe you are using Python Pandas data frame for loading 15GB file and not using Spark. Is there any particular reason that you cannot use Spark for this.

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James_209101
by New Contributor II
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  • 2 replies
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Using large dataframe in-memory (data not allowed to be "at rest") results in driver crash and/or out of memory

I'm having trouble working on Databricks with data that we are not allowed to save off or persist in any way. The data comes from an API (which returns a JSON response). We have a scala package on our cluster that makes the queries (almost 6k queries...

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Anonymous
Not applicable
  • 4 kudos

Hi @James Held​ Hope all is well! Just wanted to check in if you were able to resolve your issue and would you be happy to share the solution or mark an answer as best? Else please let us know if you need more help. We'd love to hear from you.Thanks!

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User16752245312
by New Contributor III
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How can I automatically capture the heap dump on the driver and executors in the event of an OOM error?

If you have a job that repeatedly run into Out-of-memory error (OOM) either on the driver or executors, automatically capture the heap dump on OOM event will help debugging the memory issue and identify the cause of the error.Spark config:spark.execu...

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John_360
New Contributor II
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Is it necessary to use exactly that HeapDumpPath? I find I'm unable to get driver heap dumps with a different path but otherwise the same configuration. I'm using spark_version 10.4.x-cpu-ml-scala2.12.

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Rnmj
by New Contributor III
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ConnectException: Connection refused (Connection refused) This is often caused by an OOM error

I am trying to run a python code where a json file is flattened to pipe separated file . The code works with smaller files but for huge files of 2.4 GB I get below error:ConnectException: Connection refused (Connection refused)Error while obtaining a...

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Rnmj
New Contributor III
  • 7 kudos

Hi @Jose Gonzalez​ , @Werner Stinckens​  @Kaniz Fatma​ ,Thanks for your response .Appreciate a lot. The issue was in the code, it was a python /panda code running on Spark. Due to this only driver node was being used. i did validate this by increasin...

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