Hi there, I was wondering if anybody could help me find an efficient way to make a MapReduce program like this:
1) For each map function, it need access some huge files, which is around 6GB 2) These files are READ-ONLY. Actually they are like some huge look-up table, which will not change during 2~3 years. I tried two ways to make the program work, but neither of them is efficient: 1) The first approach I tried is to let each map function load those files independently, like this: map (...) { load(files); DoMapTask(...)} 2) The second approach I tried is to load the files before RDD.map(...) and broadcast the files. However, because the files are too large, the broadcasting overhead is 30min ~ 1 hour. Could anybody help me find an efficient way to solve it? Thanks very much. -- View this message in context: http://apache-spark-user-list.1001560.n3.nabble.com/What-if-there-are-large-read-only-variables-shared-by-all-map-functions-tp10435.html Sent from the Apache Spark User List mailing list archive at Nabble.com.