28131a7794
### What changes were proposed in this pull request? This PR supplements the contents in the "Python Package Management". If there is no Python installed in the local for all nodes when using `venv-pack`, job would fail as below. ```python >>> from pyspark.sql.functions import pandas_udf >>> pandas_udf('double') ... def pandas_plus_one(v: pd.Series) -> pd.Series: ... return v + 1 ... >>> spark.range(10).select(pandas_plus_one("id")).show() ... Cannot run program "./environment/bin/python": error=2, No such file or directory ... ``` This is because the Python in the [packed environment via `venv-pack` has a symbolic link](https://github.com/jcrist/venv-pack/issues/5) that connects Python to the local one. To avoid this confusion, it seems better to have an additional explanation for this. ### Why are the changes needed? To provide more detailed information to users so that they don’t get confused ### Does this PR introduce _any_ user-facing change? Yes, this PR fixes the part of "Python Package Management" in the "User Guide" documents. ### How was this patch tested? Manually built the doc. ![Screen Shot 2021-01-21 at 7 10 38 PM](https://user-images.githubusercontent.com/44108233/105336258-5e8bec00-5c1c-11eb-870c-86acfc77c082.png) Closes #31280 from itholic/SPARK-34190. Authored-by: itholic <haejoon309@naver.com> Signed-off-by: HyukjinKwon <gurwls223@apache.org> |
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docs | ||
lib | ||
pyspark | ||
test_coverage | ||
test_support | ||
.coveragerc | ||
.gitignore | ||
MANIFEST.in | ||
mypy.ini | ||
pylintrc | ||
README.md | ||
run-tests | ||
run-tests-with-coverage | ||
run-tests.py | ||
setup.cfg | ||
setup.py |
Apache Spark
Spark is a unified analytics engine for large-scale data processing. It provides high-level APIs in Scala, Java, Python, and R, and an optimized engine that supports general computation graphs for data analysis. It also supports a rich set of higher-level tools including Spark SQL for SQL and DataFrames, MLlib for machine learning, GraphX for graph processing, and Structured Streaming for stream processing.
Online Documentation
You can find the latest Spark documentation, including a programming guide, on the project web page
Python Packaging
This README file only contains basic information related to pip installed PySpark. This packaging is currently experimental and may change in future versions (although we will do our best to keep compatibility). Using PySpark requires the Spark JARs, and if you are building this from source please see the builder instructions at "Building Spark".
The Python packaging for Spark is not intended to replace all of the other use cases. This Python packaged version of Spark is suitable for interacting with an existing cluster (be it Spark standalone, YARN, or Mesos) - but does not contain the tools required to set up your own standalone Spark cluster. You can download the full version of Spark from the Apache Spark downloads page.
NOTE: If you are using this with a Spark standalone cluster you must ensure that the version (including minor version) matches or you may experience odd errors.
Python Requirements
At its core PySpark depends on Py4J, but some additional sub-packages have their own extra requirements for some features (including numpy, pandas, and pyarrow).