[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"me":3,"catalog:en:data-engineer\u002Fstreaming-fundamentals":4,"config":126},null,{"field_key":5,"field_name":6,"seniority":7,"topic_key":8,"topic_name":9,"spec_key":7,"spec_name":7,"locale":10,"cell_total":11,"field_total":12,"seniorities":13,"topics":17,"specs":40,"samples":41},"data-engineer","Data Engineer","","streaming-fundamentals","Streaming Fundamentals","en",75,600,[14,15,16],"junior","mid","senior",[18,21,24,27,30,33,36,39],{"key":19,"name":20,"count":11},"data-governance-lineage","Data Governance Lineage",{"key":22,"name":23,"count":11},"data-modeling-warehousing","Data Modeling Warehousing",{"key":25,"name":26,"count":11},"data-partitioning-scaling","Data Partitioning Scaling",{"key":28,"name":29,"count":11},"data-pipeline-design","Data Pipeline Design",{"key":31,"name":32,"count":11},"data-pipeline-orchestration","Data Pipeline Orchestration",{"key":34,"name":35,"count":11},"data-pipeline-reliability","Data Pipeline Reliability",{"key":37,"name":38,"count":11},"data-quality-validation","Data Quality Validation",{"key":8,"name":9,"count":11},[],[42,60,73,87,100,113],{"id":43,"topic":9,"difficulty":44,"body":45,"options":46,"correct_key":48,"explanation":59},"019f6a40-d753-7bf4-8212-a72b4af9c94c",1,"What best describes batch processing in data systems?",[47,50,53,56],{"key":48,"text":49},"a","Data is collected over a period of time and processed together as a group at scheduled intervals",{"key":51,"text":52},"b","Data is processed continuously as each individual record arrives, with results available within milliseconds of each event",{"key":54,"text":55},"c","Data is processed only when a downstream consumer explicitly requests it, one record at a time",{"key":57,"text":58},"d","Data is discarded immediately after processing so no history is retained","Batch processing accumulates data over a window and processes it together at scheduled intervals, trading immediacy for higher throughput and simpler handling. Option b actually describes stream processing. Option c describes an on-demand pull pattern, not batch. Option d confuses the processing model with a data retention policy.",{"id":61,"topic":9,"difficulty":44,"body":62,"options":63,"correct_key":51,"explanation":72},"019f6a40-d754-766e-8788-8aa9ca947bed","What best describes stream processing in data systems?",[64,66,68,70],{"key":48,"text":65},"Data is grouped into large historical batches and processed once per day regardless of when it was generated",{"key":51,"text":67},"Data is processed continuously, record by record, as it arrives, with low latency",{"key":54,"text":69},"Data can only be processed after being fully loaded into a single data warehouse table",{"key":57,"text":71},"Data is processed exactly once per week on a fixed schedule","Stream processing handles data continuously as it arrives, in contrast to batch's fixed-schedule grouping. Options b and d describe batch-like fixed schedules, not streaming. Option c describes a load-then-query pattern rather than continuous processing.",{"id":74,"topic":9,"difficulty":75,"body":76,"options":77,"correct_key":54,"explanation":86},"019f6a40-d755-7319-a30d-6f25eaed5466",2,"A retail company needs to generate a report of yesterday's total sales by region, delivered each morning to the finance team. Which processing approach fits this need best?",[78,80,82,84],{"key":48,"text":79},"Neither approach applies, since financial reports must be generated manually",{"key":51,"text":81},"Stream processing, since finance always requires millisecond-level freshness even for daily reports",{"key":54,"text":83},"Batch processing, since the report reflects a finalized day and can tolerate hours of delay",{"key":57,"text":85},"Stream processing, since batch systems cannot aggregate data by region","Since the report only needs to reflect a finalized day and tolerates hours of delay until the next morning, batch processing is the simpler, sufficient choice. Option b demands unnecessary freshness the use case doesn't need. Option d is factually wrong — batch systems routinely aggregate by any dimension, including region.",{"id":88,"topic":9,"difficulty":75,"body":89,"options":90,"correct_key":57,"explanation":99},"019f6a40-d755-7dfa-b839-007463f4faa9","An e-commerce platform wants to flag a payment as potentially fraudulent within a couple of seconds of the transaction happening, before the payment is approved. Which processing approach fits this need best?",[91,93,95,97],{"key":48,"text":92},"Either approach is equally suitable, since latency does not matter for fraud detection",{"key":51,"text":94},"Batch processing, since a nightly job can catch fraud early enough for most cases",{"key":54,"text":96},"Batch processing, since fraud patterns only emerge after collecting a full month of data",{"key":57,"text":98},"Stream processing, since decisions must be made instantly as transactions arrive","Fraud detection that must act within seconds, before approval, needs continuous, low-latency processing as events happen — that is stream processing. Options b and c both wrongly assume a delay of hours or a month is acceptable, which defeats the purpose of catching fraud before the payment is approved.",{"id":101,"topic":9,"difficulty":44,"body":102,"options":103,"correct_key":48,"explanation":112},"019f6a40-d756-7662-b40d-7ddb9be535a7","In stream processing, what does 'at-least-once' delivery semantics guarantee?",[104,106,108,110],{"key":48,"text":105},"Every record will be processed one or more times, but no record will be silently dropped",{"key":51,"text":107},"Every record is guaranteed to be processed exactly one time, with no duplicates and no omissions",{"key":54,"text":109},"Some records may be silently dropped, but no record will ever be processed more than once",{"key":57,"text":111},"Records are only processed if the consumer explicitly polls for them within a fixed time limit","At-least-once guarantees no silent loss but allows duplicates, since a record may be redelivered until it is acknowledged as processed. Option b describes exactly-once semantics. Option c describes at-most-once (loss allowed, duplicates not).",{"id":114,"topic":9,"difficulty":75,"body":115,"options":116,"correct_key":51,"explanation":125},"019f6a40-d757-70c8-a2ba-eaa76aa22cf6","In stream processing, what does 'at-most-once' delivery semantics guarantee?",[117,119,121,123],{"key":48,"text":118},"Each record is delivered one or more times, and duplicates are always eliminated automatically by the system",{"key":51,"text":120},"Each record is delivered zero or one times; it may be lost, but it will never be processed more than once",{"key":54,"text":122},"Each record is guaranteed to be delivered and processed precisely one time, no exceptions",{"key":57,"text":124},"Records are held until every downstream consumer confirms processing before being removed","At-most-once prioritizes never duplicating over never losing data — a record might simply not arrive at all. Option b describes at-least-once semantics. Option c describes exactly-once semantics.",{"fields":127,"seniorities":311,"interview_shapes":312,"locales":317,"oauth":319,"question_count":322,"coach_enabled":323,"jd_match_enabled":323},[128,153,173,190,214,227,246,265,287,294,298,305],{"key":129,"name_tr":130,"name_en":130,"sort":44,"specializations":131},"backend","Backend",[132,135,138,141,144,147,150],{"key":133,"name":134,"field":129},"general","Genel",{"key":136,"name":137,"field":129},"go","Go",{"key":139,"name":140,"field":129},"python","Python",{"key":142,"name":143,"field":129},"java","Java",{"key":145,"name":146,"field":129},"csharp","C#\u002F.NET",{"key":148,"name":149,"field":129},"nodejs","Node.js",{"key":151,"name":152,"field":129},"php","PHP",{"key":154,"name_tr":155,"name_en":155,"sort":75,"specializations":156},"frontend","Frontend",[157,158,161,164,167,170],{"key":133,"name":134,"field":154},{"key":159,"name":160,"field":154},"javascript","JavaScript",{"key":162,"name":163,"field":154},"typescript","TypeScript",{"key":165,"name":166,"field":154},"react","React",{"key":168,"name":169,"field":154},"vue","Vue",{"key":171,"name":172,"field":154},"angular","Angular",{"key":174,"name_tr":175,"name_en":175,"sort":176,"specializations":177},"fullstack","Fullstack",3,[178,179,180,181,182,183,184,185,186,187,188,189],{"key":133,"name":134,"field":174},{"key":136,"name":137,"field":129},{"key":139,"name":140,"field":129},{"key":142,"name":143,"field":129},{"key":145,"name":146,"field":129},{"key":148,"name":149,"field":129},{"key":151,"name":152,"field":129},{"key":159,"name":160,"field":154},{"key":162,"name":163,"field":154},{"key":165,"name":166,"field":154},{"key":168,"name":169,"field":154},{"key":171,"name":172,"field":154},{"key":191,"name_tr":192,"name_en":192,"sort":193,"specializations":194},"devops-cloud","DevOps \u002F Cloud",4,[195,196,199,202,205,208,211],{"key":133,"name":134,"field":191},{"key":197,"name":198,"field":191},"aws","AWS",{"key":200,"name":201,"field":191},"gcp","GCP",{"key":203,"name":204,"field":191},"azure","Azure",{"key":206,"name":207,"field":191},"kubernetes","Kubernetes",{"key":209,"name":210,"field":191},"terraform","Terraform",{"key":212,"name":213,"field":191},"linux","Linux",{"key":215,"name_tr":216,"name_en":216,"sort":217,"specializations":218},"ai-engineer","AI Engineer",5,[219,220,221,224],{"key":133,"name":134,"field":215},{"key":139,"name":140,"field":215},{"key":222,"name":223,"field":215},"llm-rag","LLM\u002FRAG",{"key":225,"name":226,"field":215},"mlops","MLOps",{"key":228,"name_tr":229,"name_en":230,"sort":231,"specializations":232},"database","Veritabanı","Database",6,[233,234,237,240,243],{"key":133,"name":134,"field":228},{"key":235,"name":236,"field":228},"postgresql","PostgreSQL",{"key":238,"name":239,"field":228},"mysql","MySQL",{"key":241,"name":242,"field":228},"mongodb","MongoDB",{"key":244,"name":245,"field":228},"redis","Redis",{"key":247,"name_tr":248,"name_en":249,"sort":250,"specializations":251},"mobile","Mobil","Mobile",7,[252,253,256,259,262],{"key":133,"name":134,"field":247},{"key":254,"name":255,"field":247},"ios-swift","iOS (Swift)",{"key":257,"name":258,"field":247},"android-kotlin","Android (Kotlin)",{"key":260,"name":261,"field":247},"flutter","Flutter",{"key":263,"name":264,"field":247},"react-native","React Native",{"key":266,"name_tr":267,"name_en":268,"sort":269,"specializations":270},"security","Güvenlik","Security",8,[271,272,275,278,281,284],{"key":133,"name":134,"field":266},{"key":273,"name":274,"field":266},"appsec","AppSec",{"key":276,"name":277,"field":266},"offensive-pentest","Offensive \u002F Pentest",{"key":279,"name":280,"field":266},"cloud-security","Cloud Security",{"key":282,"name":283,"field":266},"devsecops","DevSecOps",{"key":285,"name":286,"field":266},"blue-team-incident","Blue Team \u002F Incident",{"key":288,"name_tr":289,"name_en":290,"sort":291,"specializations":292},"qa-test-automation","QA \u002F Test Otomasyonu","QA \u002F Test Automation",9,[293],{"key":133,"name":134,"field":288},{"key":5,"name_tr":6,"name_en":6,"sort":295,"specializations":296},10,[297],{"key":133,"name":134,"field":5},{"key":299,"name_tr":300,"name_en":301,"sort":302,"specializations":303},"game-dev","Oyun Geliştirme","Game Development",11,[304],{"key":133,"name":134,"field":299},{"key":306,"name_tr":307,"name_en":307,"sort":308,"specializations":309},"ml-engineer","ML Engineer",12,[310],{"key":133,"name":134,"field":306},[14,15,16],{"junior":313,"mid":315,"senior":316},{"questions":314,"median_sec":3},20,{"questions":314,"median_sec":3},{"questions":314,"median_sec":3},[318,10],"tr",[320,321],"google","github",21750,true]