Yin helped me with that, and I appreciate the onlist followup. A few questions: Why is this the case? I guess, does building it with thriftserver add much more time/size to the final build? It seems that unless documented well, people will miss that and this situation would occur, why would we not just build the thrift server in? (I am not a programming expert, and not trying to judge the decision to have it in a separate profile, I would just like to understand why it'd done that way)
On Mon, Aug 11, 2014 at 11:47 AM, Cheng Lian <lian.cs....@gmail.com> wrote: > Hi John, the JDBC Thrift server resides in its own build profile and need > to be enabled explicitly by ./sbt/sbt -Phive-thriftserver assembly. > > > > On Tue, Aug 5, 2014 at 4:54 AM, John Omernik <j...@omernik.com> wrote: > >> I am using spark-1.1.0-SNAPSHOT right now and trying to get familiar with >> the JDBC thrift server. I have everything compiled correctly, I can access >> data in spark-shell on yarn from my hive installation. Cached tables, etc >> all work. >> >> When I execute ./sbin/start-thriftserver.sh >> >> I get the error below. Shouldn't it just ready my spark-env? I guess I am >> lost on how to make this work. >> >> Thanks1 >> >> $ ./start-thriftserver.sh >> >> >> Spark assembly has been built with Hive, including Datanucleus jars on >> classpath >> >> Exception in thread "main" java.lang.ClassNotFoundException: >> org.apache.spark.sql.hive.thriftserver.HiveThriftServer2 >> >> at java.net.URLClassLoader$1.run(URLClassLoader.java:366) >> >> at java.net.URLClassLoader$1.run(URLClassLoader.java:355) >> >> at java.security.AccessController.doPrivileged(Native Method) >> >> at java.net.URLClassLoader.findClass(URLClassLoader.java:354) >> >> at java.lang.ClassLoader.loadClass(ClassLoader.java:425) >> >> at java.lang.ClassLoader.loadClass(ClassLoader.java:358) >> >> at java.lang.Class.forName0(Native Method) >> >> at java.lang.Class.forName(Class.java:270) >> >> at org.apache.spark.deploy.SparkSubmit$.launch(SparkSubmit.scala:311) >> >> at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:73) >> >> at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala) >> > >
