- A wrapper of spark-ec2 that can be plugged into sbt and let sbt deploy spark cluster and run spark jobs easily on Amazon EC2.
- Currently supports to Spark 1.3.1
- This project is not in active development, please check spark-deployer.
- Set the environment variables
AWS_ACCESS_KEY_ID and AWS_SECRET_ACCESS_KEY for AWS.
- In your sbt project, create
project/plugins.sbt:
addSbtPlugin("net.pishen" % "sbt-spark-ec2" % "0.7.2")
- Create
sbt-spark-ec2.conf:
cluster-name = "pishen-spark"
keypair = "pishen"
pem = "/home/pishen/.ssh/pishen.pem"
region = "us-west-2"
# zone is optional
zone = "us-west-2a"
master-type = "m3.medium"
slave-type = "m3.medium"
num-of-slaves = 1
main-class = "mypackage.Main"
# optional configurations
app-name = "my-spark-job"
spark-version = "1.3.1"
driver-memory = "1G"
executor-memory = "1G"
vpc-id = "vpc-xxxxxxxx"
subnet-id = "subnet-xxxxxxxx"
use-private-ips = true
# delete the security groups when destroying cluster (optional)
delete-groups = true
- Create
build.sbt (Here we give a simple example):
lazy val root = (project in file(".")).settings(
name := "my-project-name",
version := "0.1",
scalaVersion := "2.10.5",
libraryDependencies ++= Seq(
"org.apache.spark" %% "spark-core" % "1.3.1" % "provided"
)
)
- Write your job's algorithm in
src/main/scala/mypackage/Main.scala:
package mypackage
import org.apache.spark.SparkConf
import org.apache.spark.SparkContext
import org.apache.spark.SparkContext._
object Main {
def main(args: Array[String]) {
//setup spark
val sc = new SparkContext(new SparkConf())
//your algorithm
sc.textFile("s3n://my-bucket/input.gz").collect().foreach(println)
}
}
- Launch Spark cluster by
sbt sparkLaunchCluster, you can also execute sbt first and type sparkLaunchCluster (support TAB completion) in the sbt console.
- Once launched, submit your job by
sbt sparkSubmitJob <args>
sbt sparkConfsbt sparkEc2Dirsbt sparkEc2Runsbt sparkLaunchClustersbt sparkDestroyClustersbt sparkStartClustersbt sparkStopClustersbt sparkShowMachinessbt sparkLoginMastersbt sparkShowSpaceUsage Show the i-node and disk usage of all the instances.sbt sparkUploadJarsbt sparkSubmitJob <args> Start the job remotely from local machine.sbt sparkRemoveS3Dir <dir-name> Remove the s3 directory with the _$folder$ folder file. (ex. sbt sparkRemoveS3Dir s3://bucket_name/middle_folder/target_folder)
