dtenedor opened a new pull request, #44678:
URL: https://github.com/apache/spark/pull/44678
### What changes were proposed in this pull request?
This PR creates a Python UDTF API to acquire execution memory for 'eval' and
'terminate' methods.
For example, this UDTF accepts an argument representing the requested amount
of memory to allocate (of which it will receive some subset), and a second
argument containing the minimum memory allowed. It sets a status column to
indicate an "out of memory" condition if the latter exceeds the memory
allocated by Spark:
```
from dataclasses import dataclass
from pyspark.sql.functions import AnalyzeResult
from pyspark.sql.types import IntegerType, LongType, StringType, StructType
@dataclass
class CustomAnalyzeResult(AnalyzeResult):
minMemoryMb: int = 0
class $name:
def __init__(self, analyze_result):
self._analyze_result = analyze_result
@staticmethod
def analyze(**kwargs):
argument = kwargs.get("argument")
min_memory_mb = kwargs.get("min_memory_mb").value
if argument is not None:
assert(argument.dataType == IntegerType() or argument.dataType
== LongType())
argument_value = argument.value
else:
argument_value = None
return CustomAnalyzeResult(
schema=StructType()
.add("initial_request", LongType())
.add("acquired_memory", LongType())
.add("min_memory", LongType())
.add("status", StringType()),
acquireExecutionMemoryMbRequested=argument_value,
minMemoryMb=min_memory_mb)
def eval(self, **kwargs):
pass
def terminate(self):
yield (
self._analyze_result.acquireExecutionMemoryMbRequested,
self._analyze_result.acquireExecutionMemoryMbActual,
self._analyze_result.minMemoryMb,
"OK" if self._analyze_result.acquireExecutionMemoryMbActual >=
self._analyze_result.minMemoryMb else "Insufficient
memory")
```
Invoking it yields the following:
```
SELECT * FROM UDTFAcquireExecutionMemory(argument => 4, min_memory_mb => 0)
> 4 4 0 OK
SELECT * FROM UDTFAcquireExecutionMemory(argument => 4, min_memory_mb => 10)
> 4 4 10 Insufficient memory
```
### Why are the changes needed?
Python UDTFs that import large libraries or otherwise use up a lot of memory
from storing many input rows in memory need to register this memory usage with
Spark executors in order to protect against OOM crashes.
### Does this PR introduce _any_ user-facing change?
Yes, see above.
### How was this patch tested?
This PR adds test coverage.
### Was this patch authored or co-authored using generative AI tooling?
No.
--
This is an automated message from the Apache Git Service.
To respond to the message, please log on to GitHub and use the
URL above to go to the specific comment.
To unsubscribe, e-mail: [email protected]
For queries about this service, please contact Infrastructure at:
[email protected]
---------------------------------------------------------------------
To unsubscribe, e-mail: [email protected]
For additional commands, e-mail: [email protected]
