I was trying the latest code at https://github.com/apache/mesos. Take spark for example. I created a tgz of spark binary and put it on HDFS. After a job is submitted, it is decomposed into many tasks. For each task, the assigned mesos slave downloads the tgz, unzips it, and executes some script to launch the task. This seems very wasteful and unnecessary.
Does the following suggestion make sense? When a spark job is submitted, the spark/mesos master calculates a checksum or something the like for the tgz distribution. Then the checksum is sent to the slaves when tasks are assigned. If the same file has been downloaded/unzipped, a slave directly launches the task. This way the tgz is processed at most once for each job (which may have thousands of tasks). The aggregated saving would be tremendous. Let me know if you have already considered/evaluated this scheme. Du
