spark1.1.1 + Hbase (CDH5.3.1). 20 nodes each with 4 cores and 32G memory. 3 cores and 16G memory were assigned to spark in each worker node. Standalone mode. Data set is 3.8 T. wondering how to fix this. Thanks!
org.apache.spark.rdd.PairRDDFunctions.saveAsNewAPIHadoopDataset(PairRDDFunctions.scala:935) org.apache.spark.api.python.PythonRDD$.saveAsHadoopDataset(PythonRDD.scala:691) org.apache.spark.api.python.PythonRDD.saveAsHadoopDataset(PythonRDD.scala) sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method) sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57) sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43) java.lang.reflect.Method.invoke(Method.java:606) py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:231) py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:379) py4j.Gateway.invoke(Gateway.java:259) py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:133) py4j.commands.CallCommand.execute(CallCommand.java:79) py4j.GatewayConnection.run(GatewayConnection.java:207) java.lang.Thread.run(Thread.java:745) -- View this message in context: http://apache-spark-user-list.1001560.n3.nabble.com/Lots-of-fetch-failures-on-saveAsNewAPIHadoopDataset-PairRDDFunctions-tp22038.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