[{"data":1,"prerenderedAt":56},["ShallowReactive",2],{"workflow-orchestrate-emr-serverless-job":3},{"id":4,"title":5,"cleanup":6,"contributors":10,"deploy":12,"description":16,"diagram":17,"extension":18,"framework":19,"gitHub":20,"introBox":29,"level":33,"meta":34,"resources":35,"s3URL":44,"services":45,"simplicity":47,"stem":48,"testing":49,"type":53,"usecase":54,"videoId":28,"__hash__":55},"workflows\u002Fworkflows\u002Forchestrate-emr-serverless-job.json","Orchestrate an EMR Serverless job",{"headline":7,"text":8},"Cleanup",[9],"1. Delete the stack: \u003Ccode>cdk destroy\u003C\u002Fcode>.",[11],"content\u002Fcontributors\u002Fandrea-filippo-la-scola.json",{"text":13},[14,15],"1. Bootstrap CDK, if needed: cdk bootstrap aws:\u002F\u002F{your-aws-account-number}\u002F{your-aws-region}","2. Deploy the stack: cdk deploy","This workflow implements a job submission to Amazon EMR Serverless. The workflow checks for the job status and waits for job completeness before terminating\u002Fproceeding","\u002Fassets\u002Fimages\u002Fworkflows\u002Forchestrate-emr-serverless-job.png","json","AWS CDK",{"template":21,"payloads":26},{"repoURL":22,"templateDir":23,"templateFile":24,"ASL":25},"https:\u002F\u002Fgithub.com\u002Faws-samples\u002Fstep-functions-workflows-collection\u002Ftree\u002Fmain\u002Fstep-functions-emr-serverless-cdk","step-functions-emr-serverless-cdk\u002F","\u002Ftypescript\u002Flib\u002Fstep-functions-emr-serverless-cdk-stack.ts","\u002Ftypescript\u002Fstatemachine\u002Fstatemachine.asl.json",[27],{"headline":28,"payloadURL":28},"",{"headline":30,"text":31},"How it works",[32],"This workflow enables the execution of big data jobs using Step Functions to coordinate an EMR Serverless application. EMR Serverless, when configured with autoStart and autoStop, remains inactive until a job is submitted, providing a true serverless experience for big data processing. The Step Functions initiates a job submission to the EMR Serverless application and periodically checks its status before proceeding to the next iteration. In a practical scenario, subsequent steps in the workflow might rely on the completion of the EMR job to perform operations such as manipulating the job's output files.     The workflow leverages the native integration between Step Functions and AWS services, eliminating the need for custom code or AWS Lambda functions. The 'CallAwsService' functionality is utilized to minimize the maintenance of application code.","100",{},{"headline":36,"bullets":37},"Additional resources",[38,41],{"text":39,"link":40},"Open Source big data analytics with EMR serverless","https:\u002F\u002Faws.amazon.com\u002Femr\u002Fserverless\u002F",{"text":42,"link":43},"EMR serverless and Step Functions blog post","https:\u002F\u002Faws.amazon.com\u002Fblogs\u002Fbig-data\u002Frun-a-data-processing-job-on-amazon-emr-serverless-with-aws-step-functions\u002F",null,[46],"sfn","2 - Pattern","workflows\u002Forchestrate-emr-serverless-job",{"headline":50,"text":51},"Testing",[52],"See the GitHub repo for detailed testing instructions.","Standard","Data Processing","OBitjxni-6xeBMPVIouMq7jumIWEGUYXdNMgbuk2Qcg",1779273340920]