To make this work I had to rename the defaults file. Otherwise
maven's pattern matching rules included it when trying to match
other log4j.properties files.
I also fixed a bug in the existing maven build where two
<transformers> tags were present in assembly/pom.xml
such that one overwrote the other.
Suggested small changes to Java code for slightly more standard style, encapsulation and in some cases performance
Sorry if this is too abrupt or not a welcome set of changes, but thought I'd see if I could contribute a little. I'm a Java developer and just getting seriously into Spark. So I thought I'd suggest a number of small changes to the couple Java parts of the code to make it a little tighter, more standard and even a bit faster.
Feel free to take all, some or none of this. Happy to explain any of it.
Conf improvements
There are two new features.
1. Allow users to set arbitrary akka configurations via spark conf.
2. Allow configuration to be printed in logs for diagnosis.
Add a script to download sbt if not present on the system
As per the discussion on the dev mailing list this script will use the system sbt if present or otherwise attempt to install the sbt launcher. The fall back error message in the event it fails instructs the user to install sbt. While the URLs it fetches from aren't controlled by the spark project directly, they are stable and the current authoritative sources.
Update stop-slaves.sh
The most recently version has changed the directory structure, but this script "sbin/stop-all.sh" doesn't change with it accordingly. This mistake makes "sbin/stop-all.sh" can't stop the slave node.
The most recently version has changed the directory structure, but this script "sbin/stop-all.sh" doesn't change with it accordingly. This mistake makes "sbin/stop-all.sh" can't stop the slave node.
Fix test breaking downstream builds
This wasn't detected in the pull-request-builder because it manually sets SPARK_HOME. I'm going to change that (it should't do this) to make it like the other builds.
Change protobuf version for yarn alpha back to 2.4.1
The maven build for yarn-alpha uses the wrong protobuf version and hence the generated assembly jar doesn't work with Hadoop 0.23. Removing the setting for the yarn-alpha profile since the default protobuf version is 2.4.1 at the top of the pom file.
Fix handling of empty SPARK_EXAMPLES_JAR
Currently if SPARK_EXAMPLES_JAR is left unset you get a null pointer exception when running the examples (atleast on spark on yarn). The null now gets turned into a string of "null" when its put into the SparkConf so addJar no longer properly ignores it. This fixes that so that it can be left unset.
Quiet ERROR-level Akka Logs
This fixes an issue I've seen where akka logs a bunch of things at ERROR level when connecting to a standalone cluster, even in the normal case. I noticed that even when lifecycle logging was disabled, the netty code inside of akka still logged away via akka's EndpointWriter class. There are also some other log streams that I think are new in akka 2.2.1 that I've disabled.
Finally, I added some better logging to the standalone client. This makes it more clear when a connection failure occurs what is going on. Previously it never explicitly said if a connection attempt had failed.
The commit messages here have some more detail.
Removing SPARK_EXAMPLES_JAR in the code
This re-writes all of the examples to use the `SparkContext.jarOfClass` mechanism for loading the examples jar. This necessary for environments like YARN and the Standalone mode where example programs will be submit from inside the cluster rather than at the client using `./spark-example`.
This still leaves SPARK_EXAMPLES_JAR in place in the shell scripts for setting up the classpath if `./spark-example` is run.
Fall back to zero-arg constructor for Serializer initialization if there is no constructor that accepts SparkConf.
This maintains backward compatibility with older serializers implemented by users.
Without these it's a bit less clear what's going on for the user.
One thing I realize when doing this is that akka itself actually retries
the initial association. So the retry we currently have is redundant with
akka's.
I noticed when connecting to a standalone cluster Spark gives a bunch
of Akka ERROR logs that make it seem like something is failing.
This patch does two things:
1. Akka dead letter logging is turned on/off according to the existing
lifecycle spark property.
2. We explicitly silence akka's EndpointWriter log in log4j. This is necessary
because for some reason that log doesn't pick up on the lifecycle
logging settings. After a few hours of debugging this was the only solution
I found that worked.
standard Naive Bayes classifier
Has implemented the standard Naive Bayes classifier. This is an updated version of #288, which is closed because of misoperations.
