1) make sure your beeline client connected to Hiveserver2 of Spark SQL. You can found execution logs of Hiveserver2 in the environment of start-thriftserver.sh. 2) what about your scale of data. If cache with small data, it will take more time to schedule workload between different executors. Look the configuration of spark execution environment. Whether there are enough memory for RDD storage, if not, it will take some time to serialize/deserialize data between memory and disk.
2014-11-21 11:06 GMT+08:00 Judy Nash <judyn...@exchange.microsoft.com>: > Hi friends, > > > > I have successfully setup thrift server and execute beeline on top. > > > > Beeline can handle select queries just fine, but it cannot seem to do any > kind of caching/RDD operations. > > > > i.e. > > 1) Command “cache table” doesn’t work. See error: > > Error: Error while processing statement: FAILED: ParseException line 1:0 > cannot > > recognize input near 'cache' 'table' 'hivesampletable' > (state=42000,code=40000) > > > > 2) Re-run SQL commands do not have any performance improvements. > > > > By comparison, Spark-SQL shell can execute “cache table” command and > rerunning SQL command has a huge performance boost. > > > > Am I missing something or this is expected when execute through Spark > thrift server? > > > > Thanks! > > Judy > > >
