[{"data":1,"prerenderedAt":54},["ShallowReactive",2],{"workflow-distributed-map-montecarlo-simulation":3},{"id":4,"title":5,"cleanup":6,"contributors":10,"deploy":12,"description":15,"diagram":16,"extension":17,"framework":18,"gitHub":19,"introBox":28,"level":35,"meta":36,"resources":37,"s3URL":40,"services":41,"simplicity":45,"stem":46,"testing":47,"type":51,"usecase":52,"videoId":27,"__hash__":53},"workflows\u002Fworkflows\u002Fdistributed-map-montecarlo-simulation.json","Distributed Map - MonteCarlo Simulation",{"headline":7,"text":8},"Cleanup",[9],"1. Delete the stack: \u003Ccode>sam delete\u003C\u002Fcode>.",[11],"content\u002Fcontributors\u002Fharun-hasdal.json",{"text":13},[14],"sam deploy --guided","This workflow is an application of a Step Functions distributed map state, implementing a Monte Carlo simulation with parallel calculations.","\u002Fassets\u002Fimages\u002Fworkflows\u002Fdistributed-map-montecarlo-simulation.png","json","AWS SAM",{"template":20,"payloads":25},{"repoURL":21,"templateDir":22,"templateFile":23,"ASL":24},"https:\u002F\u002Fgithub.com\u002Faws-samples\u002Fstep-functions-workflows-collection\u002Ftree\u002Fmain\u002Fdistributed-map-montecarlo\u002F","distributed-map-montecarlo\u002F","template.yaml","statemachine\u002Fstatemachine.asl.json",[26],{"headline":27,"payloadURL":27},"",{"headline":29,"text":30},"How it works",[31,32,33,34],"The state machine performs random sampling of input parameters to generate inputs in S3.","The distributed map uses the input samples to run calculations in parallel.","For each input sample the Step Functionswill call a child state machine to run calculation.","The results are stored in S3, and pre-signed URLs are returned in execution outputs.","200",{},{"headline":38,"bullets":39},"Additional resources",[],null,[42,43,44],"s3","sfn","lambda","3 - Application","workflows\u002Fdistributed-map-montecarlo-simulation",{"headline":48,"text":49},"Testing",[50],"See the GitHub repo for detailed testing instructions.","Standard","Data Processing","iGpkIIUgsaOwytSaRlrkrwu10XydsyO4LYKGfVOwarM",1778846889007]