Spark 具有 REST api,可通过调用 spark master 主机名来提交作业。
提交申请:
curl -X POST http://spark-cluster-ip:6066/v1/submissions/create --header "Content-Type:application/json;charset=UTF-8" --data '{
"action" : "CreateSubmissionRequest",
"appArgs" : [ "myAppArgument1" ],
"appResource" : "file:/myfilepath/spark-job-1.0.jar",
"clientSparkVersion" : "1.5.0",
"environmentVariables" : {
"SPARK_ENV_LOADED" : "1"
},
"mainClass" : "com.mycompany.MyJob",
"sparkProperties" : {
"spark.jars" : "file:/myfilepath/spark-job-1.0.jar",
"spark.driver.supervise" : "false",
"spark.app.name" : "MyJob",
"spark.eventLog.enabled": "true",
"spark.submit.deployMode" : "cluster",
"spark.master" : "spark://spark-cluster-ip:6066"
}
}'
提交回复:
{
"action" : "CreateSubmissionResponse",
"message" : "Driver successfully submitted as driver-20151008145126-0000",
"serverSparkVersion" : "1.5.0",
"submissionId" : "driver-20151008145126-0000",
"success" : true
}
获取已提交申请的状态
curl http://spark-cluster-ip:6066/v1/submissions/status/driver-20151008145126-0000
状态响应
{
"action" : "SubmissionStatusResponse",
"driverState" : "FINISHED",
"serverSparkVersion" : "1.5.0",
"submissionId" : "driver-20151008145126-0000",
"success" : true,
"workerHostPort" : "192.168.3.153:46894",
"workerId" : "worker-20151007093409-192.168.3.153-46894"
}
现在在您提交的 spark 应用程序中应该执行所有操作,save output to any datasource and access the data via thrift server 因为没有太多数据要传输(如果您想在 MVC 应用程序数据库和 Hadoop 集群之间传输数据,可以考虑使用 sqoop) .
学分:link1、link2
编辑:(根据评论中的问题)
构建具有必要依赖项的 spark 应用程序 jar 并在本地模式下运行作业。以读取 CSV 并使用 MLib 的方式编写 jar,然后将预测输出存储在某个数据源中,以便从 Web 应用程序访问它。