欢迎来到天天文库
浏览记录
ID:39507525
大小:1.12 MB
页数:60页
时间:2019-07-04
《dtcc14-spark-runtime-internals(001)》由会员上传分享,免费在线阅读,更多相关内容在学术论文-天天文库。
1、RuntimeInternals连城lian@databricks.comcheng.lian@ciilabs.orgWhatis•Afastandgeneralengineforlarge-scaledataprocessing•AnopensourceimplementationofResilientDistributedDatasets(RDD)•HasanadvancedDAGexecutionenginethatsupportscyclicdataflowandin-memorycomputingWhy•Fast–Runmachinelearninglikeiterativeprog
2、ramsupto100xfasterthanHadoopMapReduceinmemory,or10xfasterondisk–RunHiveQLcompatiblequeries100xfasterthanHive(withShark/SparkSQL)Why•Easytouse–FluentScala/Java/PythonAPI–Interactiveshell–2-5xlesscode(thanHadoopMapReduce)Why•Easytouse–FluentScala/Java/PythonAPI–Interactiveshell–2-5xlesscode(thanHadoop
3、MapReduce)sc.textFile("hdfs://...").flatMap(_.split("")).map(_->1).reduceByKey(_+_).collectAsMap()Why•Easytouse–FluentScala/Java/PythonAPI–Interactiveshell–2-5xlesscode(thanHadoopMapReduce)sc.textFile("hdfs://...").flatMap(_.split(""))Canyouwritedown.map(_->1)WordCount.reduceByKey(_+_)in30secondswit
4、h.collectAsMap()HadoopMapReduce?Why•Unifiedbigdatapipelinefor:–Batch/Interactive(SparkCorevsMR/Tez)–SQL(Shark/SparkSQLvsHive)–Streaming(SparkStreamingvsStorm)–Machinelearning(MLlibvsMahout)–Graph(GraphXvsGiraph)ABiggerPicture...AnEvenBiggerPicture...•ComponentsoftheSparkstackfocusonbigdataanalysisan
5、darecompatiblewithexistingHadoopstoragesystems•Usersdon’tneedtosufferexpensiveETLcosttousetheSparkstack“OneStackToRuleThemAll”•Well,mostly:-)•Anddon'tforgetShark/SparkSQLvsHiveResilientDistributedDatasetsResilientDistributedDatasets•Conceptually,RDDscanberoughlyviewedaspartitioned,localityawaredistr
6、ibutedvectors•AnRDD…–eitherpointstoadirectdatasource–orappliessometransformationtoitsparentRDD(s)togeneratenewdataelements–ComputationcanberepresentedbylazyevaluatedlineageDAGscomposedbyconnectedRDDsResilientDistributedDatasets•FrequentlyusedRDDscanbematerializedandcachedin-memorytoacceleratecomputa
7、tion•SparkschedulertakesdatalocalityintoaccountTheIn-MemoryMagic•“Infact,onestudy[1]analyzedtheaccesspatternsintheHivewarehousesatFacebookanddiscoveredthatforthevastmajority(96%)ofjobs,theentireinputs
此文档下载收益归作者所有