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scala - Error initializing SparkContext: A master URL must be set in your configuration

I used this code

My error is:

Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties

17/02/03 20:39:24 INFO SparkContext: Running Spark version 2.1.0

17/02/03 20:39:25 WARN NativeCodeLoader: Unable to load native-hadoop 
library for your platform... using builtin-java classes where applicable

17/02/03 20:39:25 WARN SparkConf: Detected deprecated memory fraction 
settings: [spark.storage.memoryFraction]. As of Spark 1.6, execution and  
storage memory management are unified. All memory fractions used in the old 
model are now deprecated and no longer read. If you wish to use the old 
memory management, you may explicitly enable `spark.memory.useLegacyMode` 
(not recommended).

17/02/03 20:39:25 ERROR SparkContext: Error initializing SparkContext.

org.apache.spark.SparkException: A master URL must be set in your 
configuration
at org.apache.spark.SparkContext.<init>(SparkContext.scala:379)
at PCA$.main(PCA.scala:26)
at PCA.main(PCA.scala)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at com.intellij.rt.execution.application.AppMain.main(AppMain.java:144)

17/02/03 20:39:25 INFO SparkContext: Successfully stopped SparkContext
Exception in thread "main" org.apache.spark.SparkException: A master URL must be set in your configuration
at org.apache.spark.SparkContext.<init>(SparkContext.scala:379)
at PCA$.main(PCA.scala:26)
at PCA.main(PCA.scala)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at 
   sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at   
    sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)

at java.lang.reflect.Method.invoke(Method.java:498)
at com.intellij.rt.execution.application.AppMain.main(AppMain.java:144)

Process finished with exit code 1
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1 Answer

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by (71.8m points)

If you are running spark stand alone then

val conf = new SparkConf().setMaster("spark://master") //missing 

and you can pass parameter while submit job

spark-submit --master spark://master

If you are running spark local then

val conf = new SparkConf().setMaster("local[2]") //missing 

you can pass parameter while submit job

spark-submit --master local

if you are running spark on yarn then

spark-submit --master yarn

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