BIGDATAMYEXPERIENCEATCERNLUCAMENICHETT I

Università RomaTre,BigData,6June2016

CERN

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LargeHadronCollider

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Experiments

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Events

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Tier 0 (CERN Computing Centre)Data Recording &Offline Analysis

(perogniesperimento…)

DataFlow

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Storage

200-400 MB/sec

Data flow to permanent storage: 4-6 GB/sec

1.25 GB/sec

1-2 GB/se

1-2 GB/sec

Reconstructionandarchival

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Tiers- WLCG

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Tier-0 (CERN):•Data recording•Initial data reconstruction

•Data distribution

Tier-1 (11 centres):•Permanent storage•Re-processing•Analysis

Tier-2 (~130 centres):• Simulation• End-user analysis

WLCG

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Hadoop◦ ExperimentsandITservicesrunning24/7◦ Millionofjobssubmitteddailyinthegrid(physicists)◦ Monitoringdataforeachservicearecollectedandproperlystoredindependently

◦ Crossprojectanalysisactivitiesarecoordinatedbyworkinggroupsthatareoftensharingacommonplatformwheretodumpdataandrunjobs(IT)

◦ Amongthese:HadoopServiceprovidedbyCERNIT◦ Acommonrepository(datalake)◦ Aproductionenvironmentforotherservices

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Main activities◦ Serviceprovider◦ Cluster(s)maintenance(ROTA)◦ Framework/Applicationstroubleshooting◦ Analysisenvironmentconfiguration(clients)◦ Externalserviceintegration(fromtransportlayeruntilUI)◦ …

◦ Dataanalysis◦ Mainlyaboutresourcesutilizationandjobsperformance◦ Fileformatandframeworksevaluation◦ Usersupport◦ …

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DataFlow:ETL◦ DataarestoredinHDFSusingRESTAPIs,streaming(SparkorFlume)orSqoop jobs◦ ExtractionTransformationandLoad(orELT)proceduresarerunningdailyforeachdataset◦ ResultsareCSV,JSON,Avro,Parquet,…◦ Eachdatasetcanbepresentmorethanonce◦ Writtenwithdifferenttechnologiesorformats◦ Mergedwithotherdatasets(denormalization)◦ Writtenwithlessormorefields

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DataAnalysiswithinHadoop◦Howtoansweryourquestion?◦Differentframeworksandtoolscanbeused,dependingontheusecase:◦ Datasize◦ Frequency◦ Numberoffieldsperrecord◦ Finalresult

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ApacheSpark◦ Fast(in-memoryapproach)◦ Easytolearnandtouse◦ RDDandDataFrame bringsthefocusonthedataset◦ SparkComponents!◦ SparkSQL,MLlib,GraphX

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Analysisexample- workflow

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Dashboard(experiment

jobs)

LSF(batchjobs)

LanDB(hostinfo)

SqoopFlume

AnalysisExamples◦ JobefficiencyWignervsGeneva◦ Spark,Python(Pandas)

◦ Memoryprofiling◦ Spark(SQL)

◦ Datapopularity(blockreplicaslocaltion)◦ Pig,Spark(SQL,GraphX)

◦ Jobmonitoringsystemdiscrepancyanalysis◦ Spark,Python(Pandas)

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WebNotebooks

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◦ Itis“aninteractivecomputationalenvironment,inwhichyoucancombinecodeexecution,richtext,mathematics,plotsandrichmedia”[http://ipython.org/notebook.html]

IPython /Jupyter

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Jupyter example- matplotlib

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Zeppelin

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Zeppelin– ExampleDF

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Zeppelin– ExampleChart

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WallClock

CPU

Circlesize:jobduration

Zeppelin– ExamplePlot

Theend

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