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Josh Rosen authored
This patch adds error-detection logic to throw an exception when attempting to create multiple active SparkContexts in the same JVM, since this is currently unsupported and has been known to cause confusing behavior (see SPARK-2243 for more details).

**The solution implemented here is only a partial fix.**  A complete fix would have the following properties:

1. Only one SparkContext may ever be under construction at any given time.
2. Once a SparkContext has been successfully constructed, any subsequent construction attempts should fail until the active SparkContext is stopped.
3. If the SparkContext constructor throws an exception, then all resources created in the constructor should be cleaned up (SPARK-4194).
4. If a user attempts to create a SparkContext but the creation fails, then the user should be able to create new SparkContexts.

This PR only provides 2) and 4); we should be able to provide all of these properties, but the correct fix will involve larger changes to SparkContext's construction / initialization, so we'll target it for a different Spark release.

### The correct solution:

I think that the correct way to do this would be to move the construction of SparkContext's dependencies into a static method in the SparkContext companion object.  Specifically, we could make the default SparkContext constructor `private` and change it to accept a `SparkContextDependencies` object that contains all of SparkContext's dependencies (e.g. DAGScheduler, ContextCleaner, etc.).  Secondary constructors could call a method on the SparkContext companion object to create the `SparkContextDependencies` and pass the result to the primary SparkContext constructor.  For example:

```scala
class SparkContext private (deps: SparkContextDependencies) {
  def this(conf: SparkConf) {
    this(SparkContext.getDeps(conf))
  }
}

object SparkContext(
  private[spark] def getDeps(conf: SparkConf): SparkContextDependencies = synchronized {
    if (anotherSparkContextIsActive) { throw Exception(...) }
    var dagScheduler: DAGScheduler = null
    try {
        dagScheduler = new DAGScheduler(...)
        [...]
    } catch {
      case e: Exception =>
         Option(dagScheduler).foreach(_.stop())
          [...]
    }
    SparkContextDependencies(dagScheduler, ....)
  }
}
```

This gives us mutual exclusion and ensures that any resources created during the failed SparkContext initialization are properly cleaned up.

This indirection is necessary to maintain binary compatibility.  In retrospect, it would have been nice if SparkContext had no private constructors and could only be created through builder / factory methods on its companion object, since this buys us lots of flexibility and makes dependency injection easier.

### Alternative solutions:

As an alternative solution, we could refactor SparkContext's primary constructor to perform all object creation in a giant `try-finally` block.  Unfortunately, this will require us to turn a bunch of `vals` into `vars` so that they can be assigned from the `try` block.  If we still want `vals`, we could wrap each `val` in its own `try` block (since the try block can return a value), but this will lead to extremely messy code and won't guard against the introduction of future code which doesn't properly handle failures.

The more complex approach outlined above gives us some nice dependency injection benefits, so I think that might be preferable to a `var`-ification.

### This PR's solution:

- At the start of the constructor, check whether some other SparkContext is active; if so, throw an exception.
- If another SparkContext might be under construction (or has thrown an exception during construction), allow the new SparkContext to begin construction but log a warning (since resources might have been leaked from a failed creation attempt).
- At the end of the SparkContext constructor, check whether some other SparkContext constructor has raced and successfully created an active context.  If so, throw an exception.

This guarantees that no two SparkContexts will ever be active and exposed to users (since we check at the very end of the constructor).  If two threads race to construct SparkContexts, then one of them will win and another will throw an exception.

This exception can be turned into a warning by setting `spark.driver.allowMultipleContexts = true`.  The exception is disabled in unit tests, since there are some suites (such as Hive) that may require more significant refactoring to clean up their SparkContexts.  I've made a few changes to other suites' test fixtures to properly clean up SparkContexts so that the unit test logs contain fewer warnings.

Author: Josh Rosen <joshrosen@databricks.com>

Closes #3121 from JoshRosen/SPARK-4180 and squashes the following commits:

23c7123 [Josh Rosen] Merge remote-tracking branch 'origin/master' into SPARK-4180
d38251b [Josh Rosen] Address latest round of feedback.
c0987d3 [Josh Rosen] Accept boolean instead of SparkConf in methods.
85a424a [Josh Rosen] Incorporate more review feedback.
372d0d3 [Josh Rosen] Merge remote-tracking branch 'origin/master' into SPARK-4180
f5bb78c [Josh Rosen] Update mvn build, too.
d809cb4 [Josh Rosen] Improve handling of failed SparkContext creation attempts.
79a7e6f [Josh Rosen] Fix commented out test
a1cba65 [Josh Rosen] Merge remote-tracking branch 'origin/master' into SPARK-4180
7ba6db8 [Josh Rosen] Add utility to set system properties in tests.
4629d5c [Josh Rosen] Set spark.driver.allowMultipleContexts=true in tests.
ed17e14 [Josh Rosen] Address review feedback; expose hack workaround for existing unit tests.
1c66070 [Josh Rosen] Merge remote-tracking branch 'origin/master' into SPARK-4180
06c5c54 [Josh Rosen] Add / improve SparkContext cleanup in streaming BasicOperationsSuite
d0437eb [Josh Rosen] StreamingContext.stop() should stop SparkContext even if StreamingContext has not been started yet.
c4d35a2 [Josh Rosen] Log long form of creation site to aid debugging.
918e878 [Josh Rosen] Document "one SparkContext per JVM" limitation.
afaa7e3 [Josh Rosen] [SPARK-4180] Prevent creations of multiple active SparkContexts.
0f3ceb56
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Welcome to the Spark documentation!

This readme will walk you through navigating and building the Spark documentation, which is included here with the Spark source code. You can also find documentation specific to release versions of Spark at http://spark.apache.org/documentation.html.

Read on to learn more about viewing documentation in plain text (i.e., markdown) or building the documentation yourself. Why build it yourself? So that you have the docs that corresponds to whichever version of Spark you currently have checked out of revision control.

Generating the Documentation HTML

We include the Spark documentation as part of the source (as opposed to using a hosted wiki, such as the github wiki, as the definitive documentation) to enable the documentation to evolve along with the source code and be captured by revision control (currently git). This way the code automatically includes the version of the documentation that is relevant regardless of which version or release you have checked out or downloaded.

In this directory you will find textfiles formatted using Markdown, with an ".md" suffix. You can read those text files directly if you want. Start with index.md.

The markdown code can be compiled to HTML using the Jekyll tool. Jekyll and a few dependencies must be installed for this to work. We recommend installing via the Ruby Gem dependency manager. Since the exact HTML output varies between versions of Jekyll and its dependencies, we list specific versions here in some cases:

$ sudo gem install jekyll
$ sudo gem install jekyll-redirect-from

Execute jekyll from the docs/ directory. Compiling the site with Jekyll will create a directory called _site containing index.html as well as the rest of the compiled files.

You can modify the default Jekyll build as follows:

# Skip generating API docs (which takes a while)
$ SKIP_API=1 jekyll build
# Serve content locally on port 4000
$ jekyll serve --watch
# Build the site with extra features used on the live page
$ PRODUCTION=1 jekyll build

Pygments

We also use pygments (http://pygments.org) for syntax highlighting in documentation markdown pages, so you will also need to install that (it requires Python) by running sudo easy_install Pygments.

To mark a block of code in your markdown to be syntax highlighted by jekyll during the compile phase, use the following sytax:

{% highlight scala %}
// Your scala code goes here, you can replace scala with many other
// supported languages too.
{% endhighlight %}

API Docs (Scaladoc and Sphinx)

You can build just the Spark scaladoc by running sbt/sbt doc from the SPARK_PROJECT_ROOT directory.

Similarly, you can build just the PySpark docs by running make html from the SPARK_PROJECT_ROOT/python/docs directory. Documentation is only generated for classes that are listed as public in __init__.py.

When you run jekyll in the docs directory, it will also copy over the scaladoc for the various Spark subprojects into the docs directory (and then also into the _site directory). We use a jekyll plugin to run sbt/sbt doc before building the site so if you haven't run it (recently) it may take some time as it generates all of the scaladoc. The jekyll plugin also generates the PySpark docs Sphinx.

NOTE: To skip the step of building and copying over the Scala and Python API docs, run SKIP_API=1 jekyll.