gaogaotiantian opened a new pull request, #53086:
URL: https://github.com/apache/spark/pull/53086
### What changes were proposed in this pull request?
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Use the modern itertools to do `_batch` function in `BatchedSerializer` to
make code cleaner and faster.
The code is about 170% faster than the original implementation.
<details>
<summary>
Result with the following code
```
Batching batch_original took 0.3086 seconds
Batching batch_after took 0.1159 seconds
```
</summary>
```python
import itertools
import time
def batch_original(iterator, batch_size):
items = []
count = 0
for item in iterator:
items.append(item)
count += 1
if count == batch_size:
yield items
items = []
count = 0
if items:
yield items
def batch_list(iterator, batch_size):
n = len(iterator)
for i in range(0, n, batch_size):
yield iterator[i : i + batch_size]
def batch_after(iterator, batch_size):
it = iter(iterator)
while batch := list(itertools.islice(it, batch_size)):
yield batch
def do_test(iterator, batch):
result = []
start = time.perf_counter_ns()
for b in batch(iterator, 10000):
result.append(b)
end = time.perf_counter_ns()
print(f"Batching {batch.__name__} took {(end - start)/1e9:.4f} seconds")
return result
if __name__ == "__main__":
data = range(10000005)
result_original = do_test(data, batch_original)
result_after = do_test(data, batch_after)
assert result_original == result_after
data = list(range(10000005))
result_list = do_test(data, batch_list)
result_after = do_test(data, batch_after)
assert result_list == result_after
```
</details>
Notice that `__getslice__` is **removed** since Python 3.0, so the
optimization for known size iterators like lists is not working at all. There's
no simple way to know if an iterator supports slice operation now. The most
straightforward way is to try it out like `iterator[:1]` - I don't know how
frequent we are dealing with lists, if the iterator is often lists, then we can
do it. The raw `[:]` operation is 22% faster than this implementation.
I like the simplicity without the `try ... except ...` block.
### Why are the changes needed?
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Most importantly, the code is less verbose. Also it's much faster.
### Does this PR introduce _any_ user-facing change?
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Note that it means *any* user-facing change including all aspects such as
new features, bug fixes, or other behavior changes. Documentation-only updates
are not considered user-facing changes.
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- provide the console output, description and/or an example to show the
behavior difference if possible.
If possible, please also clarify if this is a user-facing change compared to
the released Spark versions or within the unreleased branches such as master.
If no, write 'No'.
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No.
### How was this patch tested?
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it was difficult to add.
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for the consistent environment, and the instructions could accord to:
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The script above checks if the result is the same as before. Also we will
have CI.
### Was this patch authored or co-authored using generative AI tooling?
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No
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