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    <title>topic Re: Saving PySpark standard out and standard error logs to cloud object storage in Data Engineering</title>
    <link>https://community.databricks.com/t5/data-engineering/saving-pyspark-standard-out-and-standard-error-logs-to-cloud/m-p/14592#M9064</link>
    <description>&lt;P&gt;You can write a script in which export job output is taken via REST API and save it to BLOB &lt;A href="https://docs.databricks.com/dev-tools/api/latest/jobs.html#operation/JobsRunsExport" target="test_blank"&gt;https://docs.databricks.com/dev-tools/api/latest/jobs.html#operation/JobsRunsExport&lt;/A&gt;&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;You can also save cluster logging to dbfs in cluster settings, but in REST API, you can get exactly what you need (as you need standard output).&lt;/P&gt;</description>
    <pubDate>Wed, 06 Jul 2022 13:09:34 GMT</pubDate>
    <dc:creator>Hubert-Dudek</dc:creator>
    <dc:date>2022-07-06T13:09:34Z</dc:date>
    <item>
      <title>Saving PySpark standard out and standard error logs to cloud object storage</title>
      <link>https://community.databricks.com/t5/data-engineering/saving-pyspark-standard-out-and-standard-error-logs-to-cloud/m-p/14591#M9063</link>
      <description>&lt;P&gt;I am running my PySpark data pipeline code on a standard databricks cluster. I need to save all Python/PySpark standard output and standard error messages into a file in an Azure BLOB account.&lt;/P&gt;&lt;P&gt;When I run my Python code locally I can see all messages including errors in the terminal and save them to a log file. How can something similar be accomplished with Databricks and Azure BLOB for PySpark data pipeline code? Can this be done?&lt;/P&gt;</description>
      <pubDate>Tue, 05 Jul 2022 18:01:48 GMT</pubDate>
      <guid>https://community.databricks.com/t5/data-engineering/saving-pyspark-standard-out-and-standard-error-logs-to-cloud/m-p/14591#M9063</guid>
      <dc:creator>sage5616</dc:creator>
      <dc:date>2022-07-05T18:01:48Z</dc:date>
    </item>
    <item>
      <title>Re: Saving PySpark standard out and standard error logs to cloud object storage</title>
      <link>https://community.databricks.com/t5/data-engineering/saving-pyspark-standard-out-and-standard-error-logs-to-cloud/m-p/14592#M9064</link>
      <description>&lt;P&gt;You can write a script in which export job output is taken via REST API and save it to BLOB &lt;A href="https://docs.databricks.com/dev-tools/api/latest/jobs.html#operation/JobsRunsExport" target="test_blank"&gt;https://docs.databricks.com/dev-tools/api/latest/jobs.html#operation/JobsRunsExport&lt;/A&gt;&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;You can also save cluster logging to dbfs in cluster settings, but in REST API, you can get exactly what you need (as you need standard output).&lt;/P&gt;</description>
      <pubDate>Wed, 06 Jul 2022 13:09:34 GMT</pubDate>
      <guid>https://community.databricks.com/t5/data-engineering/saving-pyspark-standard-out-and-standard-error-logs-to-cloud/m-p/14592#M9064</guid>
      <dc:creator>Hubert-Dudek</dc:creator>
      <dc:date>2022-07-06T13:09:34Z</dc:date>
    </item>
    <item>
      <title>Re: Saving PySpark standard out and standard error logs to cloud object storage</title>
      <link>https://community.databricks.com/t5/data-engineering/saving-pyspark-standard-out-and-standard-error-logs-to-cloud/m-p/14594#M9066</link>
      <description>&lt;P&gt;This is the approach I am currently taking. It is documented here: &lt;A href="https://stackoverflow.com/questions/62774448/how-to-capture-cells-output-in-databricks-notebook" target="test_blank"&gt;https://stackoverflow.com/questions/62774448/how-to-capture-cells-output-in-databricks-notebook&lt;/A&gt; &lt;/P&gt;&lt;PRE&gt;&lt;CODE&gt;from IPython.utils.capture import CapturedIO   
capture = CapturedIO(sys.stdout, sys.stderr)
...
...
# at the end of desired output:
cmem = capture.stdout&lt;/CODE&gt;&lt;/PRE&gt;&lt;P&gt;I am writing the contents of cmem variable to a file in BLOB. BLOB is mounted to DBFS.&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;It would be good to see a working example supporting the @Hubert Dudek​&amp;nbsp;'s REST API approach that he mentioned above.&lt;/P&gt;&lt;P&gt;&lt;/P&gt;</description>
      <pubDate>Fri, 08 Jul 2022 15:28:18 GMT</pubDate>
      <guid>https://community.databricks.com/t5/data-engineering/saving-pyspark-standard-out-and-standard-error-logs-to-cloud/m-p/14594#M9066</guid>
      <dc:creator>sage5616</dc:creator>
      <dc:date>2022-07-08T15:28:18Z</dc:date>
    </item>
    <item>
      <title>Re: Saving PySpark standard out and standard error logs to cloud object storage</title>
      <link>https://community.databricks.com/t5/data-engineering/saving-pyspark-standard-out-and-standard-error-logs-to-cloud/m-p/14595#M9067</link>
      <description>&lt;P&gt;This does not work for databricks runtime 11.0.&lt;/P&gt;&lt;P&gt;&lt;B&gt;&lt;U&gt;Code:&lt;/U&gt;&lt;/B&gt;&lt;/P&gt;&lt;P&gt;&lt;B&gt;from&lt;/B&gt; IPython.utils.capture &lt;B&gt;import&lt;/B&gt; CapturedIO&lt;/P&gt;&lt;P&gt;&lt;B&gt;import&lt;/B&gt; sys&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;capture = CapturedIO(sys.stdout, sys.stderr)&lt;/P&gt;&lt;P&gt;print("asdfghjkjhgf")&lt;/P&gt;&lt;P&gt;cmem = capture.stdout&lt;/P&gt;&lt;P&gt;print(cmem)&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;&lt;B&gt;&lt;U&gt;Output:&lt;/U&gt;&lt;/B&gt;&lt;/P&gt;&lt;P&gt;asdfghjkjhgf&lt;/P&gt;&lt;P&gt;&lt;I&gt;AttributeError: 'OutStream' object has no attribute 'getvalue'&lt;/I&gt;&lt;/P&gt;</description>
      <pubDate>Fri, 18 Nov 2022 06:55:19 GMT</pubDate>
      <guid>https://community.databricks.com/t5/data-engineering/saving-pyspark-standard-out-and-standard-error-logs-to-cloud/m-p/14595#M9067</guid>
      <dc:creator>dasroya</dc:creator>
      <dc:date>2022-11-18T06:55:19Z</dc:date>
    </item>
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