data management in grid. comparative analysis of storage systems in wlcg

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Data management in grid. Comparative analysis of storage systems in WLCG.

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Page 1: Data management in grid. Comparative analysis of storage systems in WLCG

Data management in grid. Comparative analysis of

storage systems in WLCG.

Page 2: Data management in grid. Comparative analysis of storage systems in WLCG

Really Two Data Problems

• The amount of data

– High-performance tools needed to manage the huge raw volume of data

• Store it

• Move it

– Measure in terabytes, petabytes, and ???

• The number of data files

– High-performance tools needed to manage the huge number of filenames

• 1012 filenames is expected soon

• Collection of 1012 of anything is a lot to handle efficiently

Page 3: Data management in grid. Comparative analysis of storage systems in WLCG

Data Questions on the Grid

• Questions for which you want Grid tools to address

• Where are the files I want?

• How to move data/files to where I want?

Page 4: Data management in grid. Comparative analysis of storage systems in WLCG

Data intensive applications • Medical and biomedical:

– Image processing (digital X-ray image analysis)

– Simulation for radiation therapy

• Climate studies• Physics:

– High Energy and other accelerator physics

– Theoretical physics, lattice calculations of all sorts

• Material sciences

Page 5: Data management in grid. Comparative analysis of storage systems in WLCG

LHC as a data source

500 MB/sec

15 PB/year

15 years

Page 6: Data management in grid. Comparative analysis of storage systems in WLCG

A Model Architecture for Data Grids

Metadata Catalog

Replica Catalog

Tape Library

Disk Cache

Attribute Specification

Logical Collection and Logical File Name

Disk Array Disk Cache

Application/Data Management

System

Replica Selection

Multiple LocationsSelectedReplica

SRM commands PerformanceInformation and

Predictions

Replica Location 1 Replica Location 2 Replica Location 3

MDS

Page 7: Data management in grid. Comparative analysis of storage systems in WLCG

SRM: Main conceptsSRM: Main concepts

– Space reservations

– Dynamic space management

– Pinning file in spaces

– Support abstract concept of a file name: Site URL

– Temporary assignment of file names for transfer: Transfer URL

– Directory management and authorization

– Transfer protocol negotiation

– Support for peer to peer request

– Support for asynchronous multi-file requests

– Support abort, suspend, and resume operations

– Non-interference with local policies

Page 8: Data management in grid. Comparative analysis of storage systems in WLCG

Storage properties

• Access Latency (ONLINE, NEARLINE, OFFLINE)

• Retention Policy (REPLICA, OUTPUT, CUSTODIAL)

Page 9: Data management in grid. Comparative analysis of storage systems in WLCG

Use cases

Access Latency (ONLINE, NEARLINE, OFFLINE) Retention Policy (REPLICA, OUTPUT, CUSTODIAL)

Page 10: Data management in grid. Comparative analysis of storage systems in WLCG

Logical File Name (LFN)Logical File Name (LFN)

Also called a User Alias,

In case the LCG File Catalog is used the LFNs are organized in a hierarchical directory-like structure, and they will have the following format: lfn:/grid/<MyVO>/<MyDirs>/<MyFile>

Page 11: Data management in grid. Comparative analysis of storage systems in WLCG

Site URL and Transfer URLSite URL and Transfer URL

• Provide: Site URL (SURL)Provide: Site URL (SURL)– URL known externally – e.g. in Replica Catalogs– e.g. srm://ibm.cnaf.infn.it:8444/dteam/test.10193

• Get back: Transfer URL (TURL)Get back: Transfer URL (TURL)– Path can be different from SURL – SRM internal mapping– Protocol chosen by SRM based on request protocol preference– e.g. gsiftp://ibm139.cnaf.infn.it:2811//gpfs/sto1/dteam/test.10193

• One SURL can have many TURLsOne SURL can have many TURLs– Files can be replicated in multiple storage components– Files may be in near-line and/or on-line storage– In a light-weight SRM (a single file system on disk) SURL may be the

same as TURL except protocol

Page 12: Data management in grid. Comparative analysis of storage systems in WLCG

July 11-15. 2005 Lecture 4: Grid Data Management 12

Third party transfer• Controller can be separate from src/dest

Site ASite B

Control channels

Data channel

ServerServer

Client

Page 13: Data management in grid. Comparative analysis of storage systems in WLCG

July 11-15. 2005 Lecture 4: Grid Data Management 13

Going fast – parallel streams• Use several data channels

Site ASite B

Control channel

Data channelsServer

Page 14: Data management in grid. Comparative analysis of storage systems in WLCG

SRB(iRODS)

SDSCSINICALBNLEGEE

Interoperability in SRM v2.2Interoperability in SRM v2.2

ClientUser/application

CASTOR

DPMDisk

SRMBerkele

y

BeStMan

xrootd

BNLSLACLBNL

dCache

Page 15: Data management in grid. Comparative analysis of storage systems in WLCG

Total Online Space Share

Page 16: Data management in grid. Comparative analysis of storage systems in WLCG

Popularity

Page 17: Data management in grid. Comparative analysis of storage systems in WLCG

CASTOR Architecture

VDQMserver

NAMEserver

STAGER

RFIOD(DISK

MOVER)

DISK POOL MSGD

NAMEserver

VOLUMEmanager

RTCPD

RTCPD(TAPE

MOVER)

TPDAEMON(PVR)

VDQMserver

CUPV

RFIOClient

Page 18: Data management in grid. Comparative analysis of storage systems in WLCG

Basic dCache Design

Page 19: Data management in grid. Comparative analysis of storage systems in WLCG

DPM

Data ServerGridftp Daemon

Rfio DaemonDPM Daemon

DPNS Daemon

DPM Database

Data ServerGridftp Daemon

Rfio Daemon

Data ServerGridftp Daemon

Rfio Daemon

Client DPNS Database

SRM Daemon

Very important

to backup !

Store physical files

-- Namespace-- Authorization-- Replicas

-- DPM config-- All requests (SRM, transfers…)

Standard Storage Interface

Can all be installed

on a single machine

Page 20: Data management in grid. Comparative analysis of storage systems in WLCG

EOS: What is it ...

• Easy to use standalone disk-only storage for user• and group data with in-memory namespace• – Few ms read/write open latency• – Focusing on end-user analysis with chaotic access• – Based on XROOT server plugin architecture• – Adopting ideas implemented in Hadoop, XROOT,• Lustre et al.• – Running on low cost hardware• • no high-end storage• – At CERN: Complementary to CASTOR

Page 21: Data management in grid. Comparative analysis of storage systems in WLCG

EOS: Access Protocol

• EOS uses XROOT as primary file access protocol• – The XROOT framework allows flexibility for• enhancements• • Protocol choice is not the key to performance as• long as it implements the required operations• – Client caching matters most• • Actively developed, towards full integration in ROOT• (rewrite of XRootD client at CERN)• • SRM and GridFTP provided as well• – BeStMan, GridFTP-to-XROOT gateway

Page 22: Data management in grid. Comparative analysis of storage systems in WLCG

Thank you

Grid, Storage and SRM. OSG

Managed Data Storage and Data Access Services for Data Grids. . M. Ernst, P. Fuhrmann, T. Mkrtchyan DESY

J. Bakken, I. Fisk, T. Perelmutov, D. Petravick Fermilab

dCache. Dmitry Litvintsev, Fermilab. OSG Storage Forum, September 21, 2010

GridFTP: File Transfer Protocol in Grid Computing Networks. Caitlin Minteer

Light weight Disk Pool Manager status and plans. Jean-Philippe Baud, IT-GD, CERN

Storage and Data Management in EGEE, Graeme A Stewart1, David Cameron, Greig A Cowan and Gavin McCance

and many others