Hello, I'm interested in hearing use cases and parallelism problems where Spark was *not* a good fit for you. This is an effort to understand the limits of MapReduce style parallelism.
Some broad things that pop out: -- recursion -- problems where the task graph is not known ahead of time -- some graph problems (http://www.frankmcsherry.org/graph/scalability/cost/2015/01/15/COST.html) This is not in anyway an attack on Spark. It's an amazing tool that does it's job very well. I'm just curious where it starts breaking down. Let me know if you have any experiences! Thanks very much, Ben -- View this message in context: http://apache-spark-user-list.1001560.n3.nabble.com/Poor-use-cases-for-Spark-tp25158.html Sent from the Apache Spark User List mailing list archive at Nabble.com. --------------------------------------------------------------------- To unsubscribe, e-mail: user-unsubscr...@spark.apache.org For additional commands, e-mail: user-h...@spark.apache.org
