[Datasets] Support different number of blocks/rows per block in zip(). by clarkzinzow · Pull Request #32795 · ray-project/ray

clarkzinzow · 2023-02-24T00:27:10Z

This PR adds support for a different number of blocks/rows per block in ds1.zip(ds2), by aligning the blocks in ds2 to ds1 with a lightweight repartition/block splitting.

Design

We heavily utilize the block splitting machinery that's use for ds.split() and ds.split_at_indices() to avoid an overly expensive repartition. Namely, for ds1.zip(ds2), we:

Calculate the block sizes for ds1 in order to get split indices.
Apply _split_at_indices() to ds2 in order to get a list of ds2 block chunks for every block in ds1, such that self_block.num_rows() == sum(other_block.num_rows() for other_block in other_split_blocks) for every self_block in ds1.
Zip together each block in ds1 with the one or more blocks from ds2 that constitute the block-aligned split for that ds1 block.

Related issue number

Closes #32375

Checks

I've signed off every commit(by using the -s flag, i.e., git commit -s) in this PR.
I've run scripts/format.sh to lint the changes in this PR.
I've included any doc changes needed for https://docs.ray.io/en/master/.
I've made sure the tests are passing. Note that there might be a few flaky tests, see the recent failures at https://flakey-tests.ray.io/
Testing Strategy
- Unit tests
- Release tests
- This PR is not tested :(

ericl

LGTM at high level

clarkzinzow · 2023-02-24T02:05:02Z

Tests look ok, @c21 @jianoaix could one of y'all take a look?

jianoaix · 2023-02-24T02:41:35Z

python/ray/data/_internal/stage_impl.py

        super().__init__("zip", None, do_zip_all)


+def _do_zip(block: Block, *other_blocks: Block) -> (Block, BlockMetadata):


Annotate other_blocks as List[Block] for readability?

Variadic args should have the type annotation of a single one of the arguments, not the collection. https://peps.python.org/pep-0484/#arbitrary-argument-lists-and-default-argument-values

It's List[ObjectRef[Block] from splitting output, any reason this to be a variadic arg?

This is used as a Ray task function, and Ray only resolves object refs that are top-level arguments, so we want to have each of these data blocks as top-level arguments to (1) get automatic materialization, (2) ensure the task isn't scheduled until all blocks are resolved, and (3) take advantage of locality-aware scheduling of the task; we wouldn't get any of those 3 things if we did a ray.get() in the task function, if that's what you're recommending.

We use this same pattern elsewhere, whenever we send a variable number of data blocks to a Ray task, we destructure it into a variadic arg so all of the above happens.

ok, makes sense!

python/ray/data/_internal/stage_impl.py

c21 · 2023-02-24T05:14:07Z

btw it would be great if we can create a benchmark for zip() from we learned.

python/ray/data/dataset.py

jianoaix · 2023-02-24T17:42:31Z

python/ray/data/_internal/stage_impl.py

        super().__init__("zip", None, do_zip_all)


+def _do_zip(block: Block, *other_blocks: Block) -> (Block, BlockMetadata):


It's List[ObjectRef[Block] from splitting output, any reason this to be a variadic arg?

ray-project#32795) This PR adds support for a different number of blocks/rows per block in `ds1.zip(ds2)`, by aligning the blocks in `ds2` to `ds1` with a lightweight repartition/block splitting. ## Design We heavily utilize the block splitting machinery that's use for `ds.split()` and `ds.split_at_indices()` to avoid an overly expensive repartition. Namely, for `ds1.zip(ds2)`, we: 1. Calculate the block sizes for `ds1` in order to get split indices. 2. Apply `_split_at_indices()` to `ds2` in order to get a list of `ds2` block chunks for every block in `ds1`, such that `self_block.num_rows() == sum(other_block.num_rows() for other_block in other_split_blocks)` for every `self_block` in `ds1`. 3. Zip together each block in `ds1` with the one or more blocks from `ds2` that constitute the block-aligned split for that `ds1` block.

#32795) (#32998) This PR adds support for a different number of blocks/rows per block in `ds1.zip(ds2)`, by aligning the blocks in `ds2` to `ds1` with a lightweight repartition/block splitting. ## Design We heavily utilize the block splitting machinery that's use for `ds.split()` and `ds.split_at_indices()` to avoid an overly expensive repartition. Namely, for `ds1.zip(ds2)`, we: 1. Calculate the block sizes for `ds1` in order to get split indices. 2. Apply `_split_at_indices()` to `ds2` in order to get a list of `ds2` block chunks for every block in `ds1`, such that `self_block.num_rows() == sum(other_block.num_rows() for other_block in other_split_blocks)` for every `self_block` in `ds1`. 3. Zip together each block in `ds1` with the one or more blocks from `ds2` that constitute the block-aligned split for that `ds1` block.

…in zip(). (#32795) (#32998)" This reverts commit 6010649.

ray-project#32795) This PR adds support for a different number of blocks/rows per block in `ds1.zip(ds2)`, by aligning the blocks in `ds2` to `ds1` with a lightweight repartition/block splitting. ## Design We heavily utilize the block splitting machinery that's use for `ds.split()` and `ds.split_at_indices()` to avoid an overly expensive repartition. Namely, for `ds1.zip(ds2)`, we: 1. Calculate the block sizes for `ds1` in order to get split indices. 2. Apply `_split_at_indices()` to `ds2` in order to get a list of `ds2` block chunks for every block in `ds1`, such that `self_block.num_rows() == sum(other_block.num_rows() for other_block in other_split_blocks)` for every `self_block` in `ds1`. 3. Zip together each block in `ds1` with the one or more blocks from `ds2` that constitute the block-aligned split for that `ds1` block. Signed-off-by: Edward Oakes <ed.nmi.oakes@gmail.com>

ray-project#32795) This PR adds support for a different number of blocks/rows per block in `ds1.zip(ds2)`, by aligning the blocks in `ds2` to `ds1` with a lightweight repartition/block splitting. ## Design We heavily utilize the block splitting machinery that's use for `ds.split()` and `ds.split_at_indices()` to avoid an overly expensive repartition. Namely, for `ds1.zip(ds2)`, we: 1. Calculate the block sizes for `ds1` in order to get split indices. 2. Apply `_split_at_indices()` to `ds2` in order to get a list of `ds2` block chunks for every block in `ds1`, such that `self_block.num_rows() == sum(other_block.num_rows() for other_block in other_split_blocks)` for every `self_block` in `ds1`. 3. Zip together each block in `ds1` with the one or more blocks from `ds2` that constitute the block-aligned split for that `ds1` block.

ray-project#32795) This PR adds support for a different number of blocks/rows per block in `ds1.zip(ds2)`, by aligning the blocks in `ds2` to `ds1` with a lightweight repartition/block splitting. ## Design We heavily utilize the block splitting machinery that's use for `ds.split()` and `ds.split_at_indices()` to avoid an overly expensive repartition. Namely, for `ds1.zip(ds2)`, we: 1. Calculate the block sizes for `ds1` in order to get split indices. 2. Apply `_split_at_indices()` to `ds2` in order to get a list of `ds2` block chunks for every block in `ds1`, such that `self_block.num_rows() == sum(other_block.num_rows() for other_block in other_split_blocks)` for every `self_block` in `ds1`. 3. Zip together each block in `ds1` with the one or more blocks from `ds2` that constitute the block-aligned split for that `ds1` block. Signed-off-by: elliottower <elliot@elliottower.com>

Support different number of blocks/rows per block in zip().

e365106

clarkzinzow requested review from c21, ericl, jianoaix, jjyao and scv119 as code owners February 24, 2023 00:27

clarkzinzow assigned ericl, c21 and jianoaix Feb 24, 2023

ericl approved these changes Feb 24, 2023

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c21 reviewed Feb 24, 2023

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ericl added the @author-action-required The PR author is responsible for the next step. Remove tag to send back to the reviewer. label Feb 24, 2023

PR feedback.

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jianoaix reviewed Feb 24, 2023

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Improve docs.

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ericl merged commit e3f875c into ray-project:master Feb 24, 2023

jianoaix mentioned this pull request Feb 27, 2023

[Datasets] Streaming executor fixes #3 #32836

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clarkzinzow mentioned this pull request Mar 3, 2023

[Cherry-pick] [Datasets] Support different number of blocks/rows per block in zip() (#32795) #32998

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amogkam added a commit that referenced this pull request Mar 7, 2023

Revert "[Datasets] Support different number of blocks/rows per block …

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…in zip(). (#32795) (#32998)" This reverts commit 6010649.

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[Datasets] Support different number of blocks/rows per block in zip().#32795

[Datasets] Support different number of blocks/rows per block in zip().#32795
ericl merged 3 commits intoray-project:masterfrom
clarkzinzow:datasets/feat/enhance-zip

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		super().__init__("zip", None, do_zip_all)


		def _do_zip(block: Block, *other_blocks: Block) -> (Block, BlockMetadata):

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