使用REST触发Spark作业

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我最近尝试了 apache spark .我的问题是更具体地触发火花作业. 这里我已经发布了有关了解火花工作的问题.在忙于工作之后，我继续着自己的要求.

I have been of late trying out apache spark. My question is more specific to trigger spark jobs. Here I had posted question on understanding spark jobs. After getting dirty on jobs I moved on to my requirement.

我有一个REST端点，在这里我公开API来触发Jobs，我已经将Spring4.0用于Rest实施.现在，我想到了在Spring中实现Jobs as Service的工作，我将以编程方式提交Job，这意味着当端点触发时，使用给定的参数，我将触发该Job. 我现在有几个设计选项.

I have a REST end point where I expose API to trigger Jobs, I have used Spring4.0 for Rest Implementation. Now going ahead I thought of implementing Jobs as Service in Spring where I would submit Job programmatically, meaning when the endpoint is triggered, with given parameters I would trigger the job. I have now few design options.

• 类似于下面的书面工作，我需要维护几个由抽象类调用的Jobs可能是JobScheduler.

/*Can this Code be abstracted from the application and written as as a seperate job. Because my understanding is that the Application code itself has to have the addJars embedded which internally sparkContext takes care.*/ SparkConf sparkConf = new SparkConf().setAppName("MyApp").setJars( new String[] { "/path/to/jar/submit/cluster" }) .setMaster("/url/of/master/node"); sparkConf.setSparkHome("/path/to/spark/"); sparkConf.set("spark.scheduler.mode", "FAIR"); JavaSparkContext sc = new JavaSparkContext(sparkConf); sc.setLocalProperty("spark.scheduler.pool", "test"); // Application with Algorithm , transformations

延伸到上述位置的文件具有由服务处理的多个版本的作业.

extending above point have multiple versions of jobs handled by service.

或者使用Spark Job Server来执行此操作.

Or else use an Spark Job Server to do this.

首先，我想知道在这种情况下最佳的解决方案是明智的执行方式，同时还要明智地进行扩展.

Firstly, I would like to know what is the best solution in this case, execution wise and also scaling wise.

注意:我正在使用Spark的独立群集. 请帮忙.

Note : I am using a standalone cluster from spark. kindly help.

推荐答案

只需使用Spark JobServer github/spark-jobserver/spark-jobserver

Just use the Spark JobServer github/spark-jobserver/spark-jobserver

进行服务时要考虑很多事情，Spark JobServer已经涵盖了其中的大部分内容.如果您发现事情还不够好，那么发出请求并将代码添加到他们的系统中应该很容易，而不是从头开始重新发明它

There are a lot of things to consider with making a service, and the Spark JobServer has most of them covered already. If you find things that aren't good enough, it should be easy to make a request and add code to their system rather than reinventing it from scratch