Prevent PyDataFrame serialization
#17364
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…to cudf-polars-dask-simple
…cudf-polars-dask-simple
Co-authored-by: Lawrence Mitchell <wence@gmx.li>
…cudf-polars-dask-simple
This is a prototype implementation of rapidsai/build-infra#139 The work that this builds on: * rapidsai/gha-tools#118, which adds a shell wrapper that automatically creates spans for the commands that it wraps. It also uses the `opentelemetry-instrument` command to set up monkeypatching for supported Python libraries, if the command is python-based * https://github.com/rapidsai/shared-workflows/tree/add-telemetry, which installs the gha-tools work from above and sets necessary environment variables. This is only done for the conda-cpp-build.yaml shared workflow at the time of submitting this PR. The goal of this PR is to observe telemetry data sent from a GitHub Actions build triggered by this PR as a proof of concept. Once it all works, the remaining work is: * merge rapidsai/gha-tools#118 * Move the opentelemetry-related install stuff in https://github.com/rapidsai/shared-workflows/compare/add-telemetry?expand=1#diff-ca6188672785b5d214aaac2bf77ce0528a48481b2a16b35aeb78ea877b2567bcR118-R125 into https://github.com/rapidsai/ci-imgs, and rebuild ci-imgs * expand coverage to other shared workflows * Incorporate the changes from this PR to other jobs and to other repos Authors: - Mike Sarahan (https://github.com/msarahan) Approvers: - Bradley Dice (https://github.com/bdice) URL: rapidsai#16924
Updates cmake to 3.28.6 in the JNI Dockerfile used to build the cudf jar. This helps avoid a bug in older cmake where FindCUDAToolkit can fail to find cufile libraries. Authors: - Jason Lowe (https://github.com/jlowe) Approvers: - Nghia Truong (https://github.com/ttnghia) - Gera Shegalov (https://github.com/gerashegalov) URL: rapidsai#17342
Apart of rapidsai#15162 Authors: - Matthew Murray (https://github.com/Matt711) Approvers: - Lawrence Mitchell (https://github.com/wence-) URL: rapidsai#17246
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| pdf = pl.DataFrame._from_pydf(df) | ||
| df = DataFrame.from_polars(df) | ||
| if projection is not None: | ||
| pdf = pdf.select(projection) | ||
| df = DataFrame.from_polars(pdf) | ||
| df = df.select(projection) |
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We were previously applying the column projection before converting from CPU to GPU. Now we are immediately moving everything to GPU, and then applying the column projection. I think we want this to be something like:
if projection is not None:
df = df.select(projection)
df = DataFrame.from_polars(df)
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Description
Prevent
PyDataFrameserialization and enable Distributed scheduler if available.This includes changes from #17262 and thus requires it to be merged first, also depends on changes from #17352 .
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