Fixes #100

SequenceIO and KafkaWordCount do not load related jars. Working on this.
I had investigated these a while back. Below is a summary:
StormSubmitter uploads a jar using Thrift - so nimbus will speak thrift with the local thrift client. 

SparkSubmit will use YARN (it does not support mesos cluster mode right now) so it assumes that the jar is made available as 'app.jar' under HDFS. It expects all dependencies (except spark dependencies which it assumes are already available) have been bundled in app.jar. It uses org.apache.spark.deploy.yarn.Client to wrap the actual mainClass and sets up a number of system properties: "spark.jars", "spark.files", "spark.yarn.jar","spark.yarn.dist.files", "spark.yarn.dist.archives". 

In both cases there is no opportunity to check argument syntax for a given client so the local submitter has no need to load the application prior to uploading the jar. Additionally, in both cases new software stacks are brought into play: thrift and yarn. Neither would be preferable to using akka.io to transfer potentially large jars or using akka with an increased message frame size. The current approach is the latter and to transfer the jar as part of the AppDescription which will then be saved as a .jar on the remote worker and added to each executor's classpath prior to starting the executor. This assumes that akka.io does not need to be used and we can transfer jars if necessary by increasing NettyConfig.messageBatchSize which defaults to 262144 - although we may need to address this at a later time using akka.io. A application can also specify an extraClasspath using a conf file for the executor which assumes resources have already been made available on the remote node.