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https://issues.apache.org/jira/browse/SPARK-61055?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Hyukjin Kwon reassigned SPARK-61055:
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Assignee: Hyukjin Kwon
> Return the status and the exception of a StreamingQuery, and check the
> timeouts of its waits, in the Python client as PySpark does
> ----------------------------------------------------------------------------------------------------------------------------------
>
> Key: SPARK-61055
> URL: https://issues.apache.org/jira/browse/SPARK-61055
> Project: Spark
> Issue Type: Bug
> Components: Connect
> Affects Versions: connect-rust-4.3.0
> Reporter: Hyukjin Kwon
> Assignee: Hyukjin Kwon
> Priority: Major
> Labels: pull-request-available
> Fix For: connect-rust-4.3.0
>
>
> In PySpark Connect, {{StreamingQuery.status}} is a dict of the {{message}},
> {{isDataAvailable}} and {{isTriggerActive}} of the query, and
> {{StreamingQuery.exception()}} returns the {{StreamingQueryException}} of
> {{pyspark.errors}} of a failed query: of the message of the server, with its
> JVM stack trace, and of the error class as its reason.
> {{pyspark.sql.streaming.StreamingQueryException}} and
> {{pyspark.sql.streaming.query.StreamingQueryException}} are that class of
> {{pyspark.errors}}. {{awaitTermination(timeout)}} and
> {{spark.streams.awaitAnyTermination(timeout)}} raise {{VALUE_NOT_POSITIVE}}
> of {{timeout}} for a timeout that is not a positive number, and
> {{explain(extended)}} takes an int as a bool.
> The Rust-backed Python client returns an object of {{status_message}},
> {{is_data_available}} and {{is_trigger_active}} attributes for {{status}},
> which is neither subscriptable nor iterable, and an object that is not an
> exception for {{exception()}}, whose {{str()}} is its repr. Its
> {{pyspark.sql.streaming.StreamingQueryException}} is that class, so {{except
> StreamingQueryException:}} raises a {{TypeError}}. It raises
> {{INVALID_TIMEOUT}}, or a {{TypeError}}, for the timeouts, and a
> {{TypeError}} for an int of {{explain}}. Return and raise them as PySpark
> does.
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