[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"me":3,"catalog:en:data-engineer\u002Fdata-partitioning-scaling":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","","data-partitioning-scaling","Data Partitioning Scaling","en",75,600,[14,15,16],"junior","mid","senior",[18,21,24,25,28,31,34,37],{"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":8,"name":9,"count":11},{"key":26,"name":27,"count":11},"data-pipeline-design","Data Pipeline Design",{"key":29,"name":30,"count":11},"data-pipeline-orchestration","Data Pipeline Orchestration",{"key":32,"name":33,"count":11},"data-pipeline-reliability","Data Pipeline Reliability",{"key":35,"name":36,"count":11},"data-quality-validation","Data Quality Validation",{"key":38,"name":39,"count":11},"streaming-fundamentals","Streaming Fundamentals",[],[42,60,74,87,100,113],{"id":43,"topic":9,"difficulty":44,"body":45,"options":46,"correct_key":54,"explanation":59},"019f6a40-d6e4-7bbf-9779-344a2e3d02e2",1,"In data engineering, what does \"partitioning\" mean at a basic level?",[47,50,53,56],{"key":48,"text":49},"a","Encrypting a table so only authorized users can read it",{"key":51,"text":52},"b","Compressing a table to reduce its disk footprint",{"key":54,"text":55},"c","Splitting data into smaller chunks based on a column's value",{"key":57,"text":58},"d","Renaming columns to follow a naming convention","Partitioning divides a dataset into smaller chunks (partitions), typically based on a column's value range or category, so that data is physically or logically grouped.",{"id":61,"topic":9,"difficulty":62,"body":63,"options":64,"correct_key":51,"explanation":73},"019f6a40-d6e5-7412-b785-b5c329b0b5b0",2,"Why does partitioning typically help query performance?",[65,67,69,71],{"key":48,"text":66},"It automatically deletes old rows that are no longer needed",{"key":51,"text":68},"A query can skip scanning partitions it doesn't need",{"key":54,"text":70},"It forces every query to scan the entire dataset for consistency",{"key":57,"text":72},"It converts all columns to a single fixed data type","When a query's filter aligns with the partition key, the engine can skip partitions that cannot contain matching rows, reducing the amount of data scanned and speeding up the query.",{"id":75,"topic":9,"difficulty":62,"body":76,"options":77,"correct_key":51,"explanation":86},"019f6a40-d6e5-7c9e-82c6-fc5104624212","What is the \"partition key\" in the context of partitioning?",[78,80,82,84],{"key":48,"text":79},"The primary key used to uniquely identify a row across the whole table",{"key":51,"text":81},"The column whose value decides a row's partition",{"key":54,"text":83},"The encryption key used to protect partition contents",{"key":57,"text":85},"The name of the physical disk where the first partition is stored","The partition key is the column (or combination of columns) whose values decide how rows are grouped into partitions, e.g. a date column or a region column.",{"id":88,"topic":9,"difficulty":62,"body":89,"options":90,"correct_key":57,"explanation":99},"019f6a40-d6e6-73e1-898d-6b161c5d6606","Which of the following is a reasonable basic criterion when choosing a partition key?",[91,93,95,97],{"key":48,"text":92},"It should be a column that is never used in any query filter",{"key":51,"text":94},"It should always be a randomly generated value unrelated to the data",{"key":54,"text":96},"It should be a column with only one possible value across the whole dataset",{"key":57,"text":98},"A column commonly used in filters that spreads data reasonably evenly","A good partition key is frequently used in query filters (so pruning helps) and distributes rows across partitions without concentrating most rows into a single partition.",{"id":101,"topic":9,"difficulty":44,"body":102,"options":103,"correct_key":54,"explanation":112},"019f6a40-d6e6-7a25-aa20-6b5fef9bffcd","What is \"data skew\" in the context of partitioning?",[104,106,108,110],{"key":48,"text":105},"When data is stored in the wrong column type",{"key":51,"text":107},"When a table has no partition key defined at all",{"key":54,"text":109},"One partition becomes much larger or busier than the others",{"key":57,"text":111},"When query results are returned in a different sort order than requested","Data skew happens when rows are not evenly distributed across partitions, so one or a few partitions hold much more data or traffic than the rest.",{"id":114,"topic":9,"difficulty":62,"body":115,"options":116,"correct_key":51,"explanation":125},"019f6a40-d6e7-742c-b4d5-0c104cfe1705","A dataset is partitioned by country. 90% of all rows belong to a single large country while the rest are spread across 40 smaller countries. What is this an example of?",[117,119,121,123],{"key":48,"text":118},"Partition pruning working correctly",{"key":51,"text":120},"Data skew, since one partition holds most of the data",{"key":54,"text":122},"A well-balanced partitioning scheme",{"key":57,"text":124},"A repartitioning operation in progress","Because a single country partition holds the vast majority of rows, that partition is disproportionately large compared to the others — this is data skew.",{"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":62,"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]