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Python Bindings for launching PySpark Jobs from the JVM (apache-spark…
…-on-k8s#364) * Adding PySpark Submit functionality. Launching Python from JVM * Addressing scala idioms related to PR351 * Removing extends Logging which was necessary for LogInfo * Refactored code to leverage the ContainerLocalizedFileResolver * Modified Unit tests so that they would pass * Modified Unit Test input to pass Unit Tests * Setup working environent for integration tests for PySpark * Comment out Python thread logic until Jenkins has python in Python * Modifying PythonExec to pass on Jenkins * Modifying python exec * Added unit tests to ClientV2 and refactored to include pyspark submission resources * Modified unit test check * Scalastyle * PR 348 file conflicts * Refactored unit tests and styles * further scala stylzing and logic * Modified unit tests to be more specific towards Class in question * Removed space delimiting for methods * Submission client redesign to use a step-based builder pattern. This change overhauls the underlying architecture of the submission client, but it is intended to entirely preserve existing behavior of Spark applications. Therefore users will find this to be an invisible change. The philosophy behind this design is to reconsider the breakdown of the submission process. It operates off the abstraction of "submission steps", which are transformation functions that take the previous state of the driver and return the new state of the driver. The driver's state includes its Spark configurations and the Kubernetes resources that will be used to deploy it. Such a refactor moves away from a features-first API design, which considers different containers to serve a set of features. The previous design, for example, had a container files resolver API object that returned different resolutions of the dependencies added by the user. However, it was up to the main Client to know how to intelligently invoke all of those APIs. Therefore the API surface area of the file resolver became untenably large and it was not intuitive of how it was to be used or extended. This design changes the encapsulation layout; every module is now responsible for changing the driver specification directly. An orchestrator builds the correct chain of steps and hands it to the client, which then calls it verbatim. The main client then makes any final modifications that put the different pieces of the driver together, particularly to attach the driver container itself to the pod and to apply the Spark configuration as command-line arguments. * Don't add the init-container step if all URIs are local. * Python arguments patch + tests + docs * Revert "Python arguments patch + tests + docs" This reverts commit 4533df2. * Revert "Don't add the init-container step if all URIs are local." This reverts commit e103225. * Revert "Submission client redesign to use a step-based builder pattern." This reverts commit 5499f6d. * style changes * space for styling
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