[query] avoid hanging the JVM in Dataproc #13916
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Non-daemon threads [keep a JVM alive](https://docs.oracle.com/javase/8/docs/api/java/lang/Thread.html): > When a Java Virtual Machine starts up, there is usually a single non-daemon thread (which > typically calls the method named main of some designated class). The Java Virtual Machine > continues to execute threads until either of the following occurs: > > The exit method of class Runtime has been called and the security manager has permitted the exit > operation to take place. > > All threads that are not daemon threads have died, either by returning from the call to the run > method or by throwing an exception that propagates beyond the run method. Spark appears to wait for the JVM to terminate before it considers a job complete.
daniel-goldstein
previously approved these changes
Oct 26, 2023
|
WIP until #13919 merges. |
added 3 commits
October 26, 2023 12:46
`aiohttp.ClientOSError` inherits from `OSError`, so we can just use `errno` or `strerror` directly.
We should not directly use the `args` because one of the subclasses of `ClientOSError` sets them
to *its* arguments after initializing its super classes with the expected arguments:
```python3
class ClientConnectorError(ClientOSError):
"""Client connector error.
Raised in :class:`aiohttp.connector.TCPConnector` if
a connection can not be established.
"""
def __init__(self, connection_key: ConnectionKey, os_error: OSError) -> None:
self._conn_key = connection_key
self._os_error = os_error
super().__init__(os_error.errno, os_error.strerror)
self.args = (connection_key, os_error)
```
I also tried to remove `e.args` from the `ClientPayloadError` case (the one right above this, and
the only one still using `e.args`), but neither that class nor any super class sets a field with
the error message (in fact, no fields are ever set so we can only use `e.args`).
danking
dismissed
daniel-goldstein’s stale review
@daniel-goldstein, for expediency's sake, I merged #13921 into here; can you re-approve consider that new code?
daniel-goldstein
approved these changes
Oct 26, 2023
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Non-daemon threads keep a JVM alive:
Spark appears to wait for the JVM to terminate before it considers a job complete.