[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"$fAOoEzrpoI8TC-S6-1Or6EflDMLbbPmk9pBZve9S9R60":3},{"answer":4,"createTime":5,"id":6,"options":7,"origin":12,"question":19,"related":20,"source":30,"type":31},[],"2023-06-08 22:54:25",54195877,[8,9,10,11],"Spark应用在复杂的批量数据处理","Spark SQL是基于历史数据的交互式查询","Spark Streaming是基于历史数据的数据挖掘","GraphX是图结构数据的处理",{"count":13,"courseId":14,"courseImg":15,"courseName":16,"workId":17,"workName":18},15,"bc194bb56a5674e93b64f52c0295f658","https:\u002F\u002Ftihai-oss-cloud.itihey.com\u002Fimg\u002F4ee5514cd4ee403a360e48511bc68fd0.jpg","大数据技术与应用","work_28040646","第10章 Spark作业","在Spark生态系统组件的应用场景中,下列哪项说法是错误的",[21,32,40,49,58,61,70,79,88,95],{"answer":22,"createTime":5,"id":23,"options":24,"question":29,"source":30,"type":31},[],54195873,[25,26,27,28],"Spark最初由美国加州伯克利大学(UCBerkeley)的AMP实验室于2009年开发","Spark在2014年打破了Hadoop保持的基准排序纪录","Spark用十分之一的计算资源,获得了比Hadoop快3倍的速度","Spark运行模式单一","下列关于Spark的描述,错误的是哪一项","v1",0,{"answer":33,"createTime":5,"id":34,"options":35,"question":29,"source":30,"type":31},[],54195874,[36,37,38,39],"使用DAG执行引擎以支持循环数据流与内存计算析","可运行于独立的集群模式中,可运行于Hadoop中,也可运行于Amazon EC2等云环境中","支持使用Scala、Java、Python和R语言进行编程,但是不可以通过Spark Shell进行交互式编程","Spark运行模式不是单一的",{"answer":41,"createTime":5,"id":42,"options":43,"question":48,"source":30,"type":31},[],54195875,[44,45,46,47],"Scala语法复杂,但是能提供优雅的API计算","Scala具备强大的并发性,支持函数式编程,可以更好地支持分布式系统","Scala兼容Java,运行速度快,且能融合到Hadoop生态圈中","Scala是Spark的主要编程语言","下列关于Scala特性的描述,错误的是哪一项",{"answer":50,"createTime":5,"id":51,"options":52,"question":57,"source":30,"type":31},[],54195876,[53,54,55,56],"相对于Spark来说,使用Hadoop进行迭代计算非常耗资源","Spark将数据载入内存后,之后的迭代计算都可以直接使用内存中的中间结果作运算,避免了从磁盘中频繁读取数据","Hadoop的设计遵循&quot;一个软件栈满足不同应用场景&quot;的理念","Spark可以部署在资源管理器YARN之上,提供一站式的大数据解决方案","下列说法哪项有误",{"answer":59,"createTime":5,"id":6,"options":60,"question":19,"source":30,"type":31},[],[8,9,10,11],{"answer":62,"createTime":5,"id":63,"options":64,"question":69,"source":30,"type":31},[],54195878,[65,66,67,68],"RDD(Resillient Distributed Dataset)是运行在工作节点(WorkerNode)的一个进程,负责运行Task","Application是用户编写的Spark应用程序","一个Job包含多个RDD及作用于相应RDD上的各种操作","Directed Acyclic Graph反映RDD之间的依赖关系","下列说法错误的是",{"answer":71,"createTime":5,"id":72,"options":73,"question":78,"source":30,"type":31},[],54195879,[74,75,76,77],"一个RDD就是一个分布式对象集合,本质上是一个只读的分区记录集合","每个RDD可分成多个分区,每个分区就是一个数据集片段","RDD是可以直接修改的","RDD提供了一种高度受限的共享内存模型","下列关于RDD说法,描述有误的是",{"answer":80,"createTime":5,"id":81,"options":82,"question":87,"source":30,"type":31},[],54195880,[83,84,85,86],"基于历史数据的数据挖掘","图结构数据的处理","基于历史数据的交互式查询","基于实时数据流的数据处理","Spark生态系统组件Spark Streaming的应用场景是",{"answer":89,"createTime":90,"id":91,"options":92,"question":93,"source":30,"type":94},[],"2023-06-16 23:51:35",66289928,[],"Spark是基于内存计算的大数据计算平台,试述Spark的主要特点",4,{"answer":96,"createTime":90,"id":97,"options":98,"question":99,"source":30,"type":94},[],66289929,[],"Spark的出现是为了解决Hadoop MapReduce的不足,试列举Hadoop MapReduce的几个缺陷,并说明Spark具备哪些优点"]