### What changes were proposed in this pull request?
TL;DR:
- This PR completes the support of archives in Spark itself instead of Yarn-only
- It makes `--archives` option work in other cluster modes too and adds `spark.archives` configuration.
- After this PR, PySpark users can leverage Conda to ship Python packages together as below:
```python
conda create -y -n pyspark_env -c conda-forge pyarrow==2.0.0 pandas==1.1.4 conda-pack==0.5.0
conda activate pyspark_env
conda pack -f -o pyspark_env.tar.gz
PYSPARK_DRIVER_PYTHON=python PYSPARK_PYTHON=./environment/bin/python pyspark --archives pyspark_env.tar.gz#environment
```
- Issue a warning that undocumented and hidden behavior of partial archive handling in `spark.files` / `SparkContext.addFile` will be deprecated, and users can use `spark.archives` and `SparkContext.addArchive`.
This PR proposes to add Spark's native `--archives` in Spark submit, and `spark.archives` configuration. Currently, both are supported only in Yarn mode:
```bash
./bin/spark-submit --help
```
```
Options:
...
Spark on YARN only:
--queue QUEUE_NAME The YARN queue to submit to (Default: "default").
--archives ARCHIVES Comma separated list of archives to be extracted into the
working directory of each executor.
```
This `archives` feature is useful often when you have to ship a directory and unpack into executors. One example is native libraries to use e.g. JNI. Another example is to ship Python packages together by Conda environment.
Especially for Conda, PySpark currently does not have a nice way to ship a package that works in general, please see also https://hyukjin-spark.readthedocs.io/en/stable/user_guide/python_packaging.html#using-zipped-virtual-environment (PySpark new documentation demo for 3.1.0).
The neatest way is arguably to use Conda environment by shipping zipped Conda environment but this is currently dependent on this archive feature. NOTE that we are able to use `spark.files` by relying on its undocumented behaviour that untars `tar.gz` but I don't think we should document such ways and promote people to more rely on it.
Also, note that this PR does not target to add the feature parity of `spark.files.overwrite`, `spark.files.useFetchCache`, etc. yet. I documented that this is an experimental feature as well.
### Why are the changes needed?
To complete the feature parity, and to provide a better support of shipping Python libraries together with Conda env.
### Does this PR introduce _any_ user-facing change?
Yes, this makes `--archives` works in Spark instead of Yarn-only, and adds a new configuration `spark.archives`.
### How was this patch tested?
I added unittests. Also, manually tested in standalone cluster, local-cluster, and local modes.
Closes#30486 from HyukjinKwon/native-archive.
Authored-by: HyukjinKwon <gurwls223@apache.org>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
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