Hello Everyone, I’m just trying out the spark-shell on mesos and I don’t get any executors. To debug it I started the vagrant box from aurora and try it out there and I can the same issue as I’m getting on my cluster. On Mesos the only active framework is the spark-shel, it is running 1.6.1 and has 4 cores. Does someone else have the same issue ?
vagrant@aurora:~/spark-2.4.0-bin-hadoop2.7$ ./bin/spark-shell --master mesos://192.168.33.7:5050 --total-executor-cores 3 2019-03-18 06:43:30 WARN Utils:66 - Your hostname, aurora resolves to a loopback address: 127.0.1.1; using 10.0.2.15 instead (on interface eth0) 2019-03-18 06:43:30 WARN Utils:66 - Set SPARK_LOCAL_IP if you need to bind to another address 2019-03-18 06:43:31 WARN NativeCodeLoader:62 - Unable to load native-hadoop library for your platform... using builtin-java classes where applicable Setting default log level to "WARN". To adjust logging level use sc.setLogLevel(newLevel). For SparkR, use setLogLevel(newLevel). I0318 06:43:40.738236 5192 sched.cpp:232] Version: 1.6.1 I0318 06:43:40.743121 5188 sched.cpp:336] New master detected at master@192.168.33.7:5050 I0318 06:43:40.744252 5188 sched.cpp:351] No credentials provided. Attempting to register without authentication I0318 06:43:40.748190 5188 sched.cpp:749] Framework registered with 2c00bfa7-df7b-430b-8c92-c6452c447249-0004 Spark context Web UI available at http://10.0.2.15:4040 Spark context available as 'sc' (master = mesos://192.168.33.7:5050, app id = 2c00bfa7-df7b-430b-8c92-c6452c447249-0004). Spark session available as 'spark'. Welcome to ____ __ / __/__ ___ _____/ /__ _\ \/ _ \/ _ `/ __/ '_/ /___/ .__/\_,_/_/ /_/\_\ version 2.4.0 /_/ Using Scala version 2.11.12 (OpenJDK 64-Bit Server VM, Java 1.8.0_181) Type in expressions to have them evaluated. Type :help for more information. scala> val textFile = spark.read.textFile("README.md") textFile: org.apache.spark.sql.Dataset[String] = [value: string] scala> textFile.count() [Stage 0:> (0 + 0) / 1]2019-03-18 06:44:48 WARN TaskSchedulerImpl:66 - Initial job has not accepted any resources; check your cluster UI to ensure that workers are registered and have sufficient resources 2019-03-18 06:45:03 WARN TaskSchedulerImpl:66 - Initial job has not accepted any resources; check your cluster UI to ensure that workers are registered and have sufficient resources 2019-03-18 06:45:18 WARN TaskSchedulerImpl:66 - Initial job has not accepted any resources; check your cluster UI to ensure that workers are registered and have sufficient resources 2019-03-18 06:45:33 WARN TaskSchedulerImpl:66 - Initial job has not accepted any resources; check your cluster UI to ensure that workers are registered and have sufficient resources [Stage 0:> (0 + 0) / 1]2019-03-18 06:45:46 WARN Signaling:66 - Cancelling all active jobs, this can take a while. Press Ctrl+C again to exit now. --------------------------------------------------------------------- To unsubscribe e-mail: user-unsubscr...@spark.apache.org