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Let us consider the run() method of the BinaryClassification example:

  def run(params: Params) {
    val conf = new SparkConf().setAppName(s"BinaryClassification with $params")
    val sc = new SparkContext(conf)


Notice that the SparkConf did not provide any means to configure the SparkMaster.

When running this program from Intellij with the following arguments:

--algorithm LR --regType L2 --regParam 1.0 data/mllib/sample_binary_classification_data.txt


the following error occurs:

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:166)
    at org.apache.spark.examples.mllib.BinaryClassification$.run(BinaryClassification.scala:105)

 

I have also tried adding in the Spark Master url anyways (though the code seems NOT to support it ..)

  spark://10.213.39.125:17088   --algorithm LR --regType L2 --regParam 1.0
  data/mllib/sample_binary_classification_data.txt


and

--algorithm LR --regType L2 --regParam 1.0 spark://10.213.39.125:17088
data/mllib/sample_binary_classification_data.txt


Both do not work with error:

Error: Unknown argument 'data/mllib/sample_binary_classification_data.txt'
 

1 Answer

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by (32.3k points)

One approach to resolve your errors is that you can set the Spark master from the command-line by adding the JVM parameter:

-Dspark.master=spark://myhost:7077

Also, if you want to get this done from code you can use .setMaster(...) when creating the SparkConf:

val conf = new SparkConf().setAppName("Simple Application")

                          .setMaster("spark://myhost:7077")

And for Spark 2.x + do:

val spark = SparkSession.builder()

                        .appName("app_name")

                        .getOrCreate()

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