Hi there, We're trying out Spark and are experiencing some performance issues using Spark SQL. Anyone who can tell us if our results are normal?
We are using the Amazon EC2 scripts to create a cluster with 3 workers/executors (m1.large). Tried both spark 1.0.0 as well as the git master; the Scala as well as the Python shells. Running the following code takes about 5 minutes, which seems a long time for this query. val file = sc.textFile("s3n:// ... .csv"); val data = file.map(x => x.split('|')); // 300k rows case class BookingInfo(num_rooms: String, hotelId: String, toDate: String, ...); val rooms2 = data.filter(x => x(0) == "2").map(x => BookingInfo(x(0), x(1), ... , x(9))); // 50k rows val rooms3 = data.filter(x => x(0) == "3").map(x => BookingInfo(x(0), x(1), ... , x(9))); // 30k rows rooms2.registerAsTable("rooms2"); cacheTable("rooms2"); rooms3.registerAsTable("rooms3"); cacheTable("rooms3"); sql("SELECT * FROM rooms2 LEFT JOIN rooms3 ON rooms2.hotelId = rooms3.hotelId AND rooms2.toDate = rooms3.toDate").count(); Are we doing something wrong here? Thanks! -- View this message in context: http://apache-spark-user-list.1001560.n3.nabble.com/Performance-problems-on-SQL-JOIN-tp8001.html Sent from the Apache Spark User List mailing list archive at Nabble.com.