Github user tigerquoll commented on a diff in the pull request:
https://github.com/apache/spark/pull/2516#discussion_r18008488
--- Diff:
core/src/main/resources/org/apache/spark/deploy/spark-submit-defaults.prop ---
@@ -0,0 +1,90 @@
+# The master URL for the cluster egspark://host:port, mesos://host:port,
yarn, or local.
+# legacy env variable MASTER
+spark.master = local[*]
+
+# Should spark submit run in verbose mode: default is false
+spark.verbose = false
+
+# Comma-separated list of files to be placed in the working directory of
each executor
+# spark.files =
+
+# Comma-separated list of .zip, .egg, or .py files to place on the
PYTHONPATH for Python apps.
+# spark.submit.pyfiles =
+
+# Comma-separated list of local jars to include on the driver and executor
classpaths.
+# spark.jars =
+
+
+# Path to a bundled jar including your application and all dependencies.
+# The URL must be globally visible inside of your cluster, for instance,
+# an hdfs:// path or a file:// path that is present on all nodes.
+# spark.app.primaryResource =
+
+# A name of your application.
+spark.app.name = Unknown Application
+
+# Your application's main class (for Java / Scala apps).
+# spark.app.class =
--- End diff --
primaryResource, spark.app.name and spark.app,class have been removed from
the file. I note in sparkSubmit:
if (mainClass == null && !isPython && primaryResource != null) {
.. attempt to derive class from primaryResource
}
Does that mean it is valid to not have a main class defined at this stage
if we are running python? or should we error out if we still do not have a main
class after this code, regardless if we are running python or not?
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