Separating Abstractions from Resources in a Tactical Storage System Douglas Thain University of Notre Dame

Abstract Users of distributed systems encounter many practical barriers between their jobs and the data they wish to access. Problem: Users have access to many resources (disks), but are stuck with the abstractions (cluster NFS) provided by administrators. Solution: Tactical Storage Systems allow any user to create, reconfigure, and tear down abstractions without bugging the administrator.

Transparent Distributed Filesystem shared disk The Standard Model

Transparent Distributed Filesystem shared disk Transparent Distributed Filesystem shared disk private disk private disk private disk private disk FTP, SCP, RSYNC, HTTP,...

Problems with the Standard Model Users encounter partitions in the WAN. –Easy to access data inside cluster, hard outside. –Must use different mechanisms on diff links. –Difficult to combine resources together. Resources go unused. –Disks on each node of a cluster. –Unorganized resources in a department/lab. Unnecessary cross-talk between users. –User A demands async NFS for performance. –User B demands sync NFS for consistency. A global file system is not possible!

What if... Users could easily access any storage? I could borrow an unused disk for NFS? An entire cluster can be used as storage? Multiple clusters could be combined? I could reconfigure structures without root? –(Or bugging the administrator daily.) Solution: Tactical Storage System (TSS)

Outline Problems with the Standard Model Tactical Storage Systems –File Servers, Catalogs, Abstractions, Adapters Applications: –Remote Dynamic Linking in HEP Simulation –Remote Database Access in HEP Simulation –Expandable Filesystem for Experimental Data –Expandable Database for Bioinformatics Simulation Ongoing Work –Malloc, Dynamic Views, DACLs, PINS Final Thought

Tactical Storage Systems (TSS) A TSS allows any node to serve as a file server or as a file system client. All components can be deployed without special privileges – but with security. Users can build up complex structures. –Filesystems, databases, caches,... Two Independent Concepts: –Resources – The raw storage to be used. –Abstractions – The organization of storage.

file system file system file system file system file system file system file system Central Filesystem App Distributed Database Abstraction Adapter App Distributed Filesystem Abstraction Adapter App Cluster administrator controls policy on all storage in cluster UNIX Workstations owners control policy on each machine. file server file server file server file server file server file server file server UNIX ??? Adapter

Components of a TSS: 1 – File Servers 2 – Catalogs 3 – Abstractions 4 – Adapters

1 – File Servers Unix-Like Interface –open/close/read/write –getfile/putfile to stream whole files –opendir/stat/rename/unlink Complete Independence –choose friends –limit bandwidth/space –evict users? Trivial to Deploy –run server + setacl –no privilege required –can be thrown into a grid system Flexible Access Control file server A file server B Chirp Protocol file system owner of server A owner of server B

Access Control in File Servers Unix Security is not Sufficient –No global user database possible/desirable. –Mapping external credentials to Unix gets messy. Instead, Make External Names First-Class –Perform access control on remote, not local, names. –Types: Globus, Kerberos, Unix, Hostname, Address Each directory has an ACL: globus:/O=NotreDame/CN=DThain RWLA RWL hostname:*.cs.nd.edu RL address: * RWLA

Problem: Shared Namespace file server globus:/O=NotreDame/* RWLAX a.out test.ctest.dat cms.exe

Solution: Reservation (V) Right file server O=NotreDame/CN=* V(RWLA) /O=NotreDame/CN=Monk RWLA mkdir a.outtest.c /O=NotreDame/CN=Monk mkdir /O=NotreDame/CN=Ted RWLA a.outtest.c /O=NotreDame/CN=Ted mkdir only!

2 - Catalogs catalog server catalog server periodic UDP updates HTTP XML, TXT, ClassAds

3 - Abstractions An abstraction is an organizational layer built on top of one or more file servers. End Users choose what abstractions to employ. Working Examples: –CFS: Central File System –DSFS: Distributed Shared File System –DSDB: Distributed Shared Database Others Possible? –Distributed Backup System –Striped File System (RAID/Zebra)

CFS: Central File System file server adapter appl file CFS

ptr DSFS: Dist. Shared File System file server appl file server file server file adapter DSFS lookup file location access data

DSDB: Dist. Shared Database adapter appl file server file server file database server file index query direct access insert create file DSDB

system calls trapped via ptrace tcsh catvi tcsh catvi file table process table Like an OS Kernel –Tracks procs, files, etc. –Adds new capabilities. –Enforces owner’s policies. Delegated Syscalls –Trapped via ptrace interface. –Action taken by Parrot. –Resources chrgd to Parrot. User Chooses Abstr. –Appears as a filesystem. –Option: Timeout tolerance. –Option: Cons. semantics. –Option: Servers to use. –Option: Auth mechanisms. 4 - Adapter Adapter - Parrot Abstractions: CFS – DSFS - DSDB

file system file system file system file system file system file system file system Central Filesystem App Distributed Database Abstraction Adapter App Distributed Filesystem Abstraction Adapter App Cluster administrator controls policy on all storage in cluster UNIX Workstations owners control policy on each machine. file server file server file server file server file server file server file server UNIX ??? Adapter

Performance Summary Nothing comes for free! –System calls: order of magnitude slower. –Memory bandwidth overhead: extra copies. –TSS can drive network/switch to limits. Compared to NFS Protocol: –TSS slightly better on small operations. (no lookup) –TSS much better in network bandwidth. (TCP) –NFS caches, TSS doesn’t (today), mixed blessing. On real applications: –Measurable slowdown –Benefit: far more flexible and scalable.

Outline Problems with the Standard Model Tactical Storage Systems –File Servers, Catalogs, Abstractions, Adapters Applications: –Remote Dynamic Linking in HEP Simulation –Remote Database Access in HEP Simulation –Expandable Filesystem for Astrophysics Data –Expandable Database for Mol. Dynamics Simulation Ongoing Work –Malloc, Dynamic Views, DACLs, PINS Final Thoughts

Remote Dynamic Linking appl adapter ld.so FTP server file system liba.so libb.so libc.so WAN Credit: Igor Fermi National Lab FTP driver Modular Simulation Needs Many Libraries –Devel. on workstations, then ported to grid. –Selection of library depends on analysis tech. Solution: Dynamic Link with TSS and FTP: –LD_LIBRARY_PATH=/ftp/server.name/libs Send adapter along with job. Send adapter along with job. select several MB from 60 GB of libraries Anon. Login.

Related Work Lots of file services for the Grid: –GridFTP, Freeldr, NeST, IBP, SRB, RFIO,... –Adapter interfaces with many of these! Why have another file server? –Reason 1: Must have precise Unix semantics! Apps distinguish ENOENT vs EACCES vs EISDIR. FTP always returns error 550, regardless of error. –Reason 2: TSS focused on easy deployment. No privilege required, no config files, no rebuilding, flexible access control,...

Remote Database Access script adapter TSS file server file system DB data libdb.so sim.exe WAN CFS HEP Simulation Needs Direct DB Access –App linked against Objectivity DB. –Objectivity accesses filesystem directly. –How to distribute application securely? Solution: Remote Root Mount via TSS: parrot –M /=/chirp/fileserver/rootdir parrot –M /=/chirp/fileserver/rootdir DB code can read/write/lock files directly. DB code can read/write/lock files directly. GSI Auth GSI Credit: Sander NIKHEF

Performance on EDG Testbed Setup Time to Init Time/Event Unix 446 +/ /- 4664s LAN/NFS / s LAN/TSS / s WAN/TSS / s

Expandable Filesystem for Experimental Data Credit: John Notre Dame Astrophysics Dept. buffer disk 10 GB/day today could be lots more! daily tape daily tape daily tape daily tape daily tape 25-year archive analysis code Can only analyze the most recent data. Project GRAND

Expandable Filesystem for Experimental Data Credit: John Notre Dame Astrophysics Dept. buffer disk 10 GB/day today could be lots more! daily tape daily tape daily tape daily tape daily tape 25-year archive Project GRAND file server file server file server file server Distributed Shared Filesystem Adapter analysis code Can analyze all data over large time scales.

Appl: Distributed MD Database State of Molecular Dynamics Research: –Easy to run lots of simulations! –Difficult to understand the “big picture” –Hard to systematically share results and ask questions. Desired Questions and Activities: –“What parameters have I explored?” –“How can I share results with friends?” –“Replicate these items five times for safety.” –“Recompute everything that relied on this machine.” GEMS: Grid Enabled Molecular Sims –Distributed database for MD siml at Notre Dame. –XML database for indexing, TSS for storage/policy.

GEMS Distributed Database database server catalog server catalog server XML ->host1:fileA host7:fileB host3:fileC ACB YZX XML ->host6:fileX host2:fileY host5:fileZ data XML+ Temp>300K Mol==CH 4 host5:fileZ host6:fileX Credit: Jesus Izaguirre and Aaron Striegel, Notre Dame CSE Dept.

Active Recovery in GEMS

GEMS and Tactical Storage Dynamic System Configuration –Add/remove servers, discovered via catalog Policy Control in File Servers –Groups can Collaborate within Constraints –Security Implemented within File Servers Direct Access via Adapters –Unmodified Simulations can use Database –Alternate Web/Viz Interfaces for Users.

Outline Problems with the Standard Model Tactical Storage Systems –File Servers, Catalogs, Abstractions, Adapters Applications: –Remote Dynamic Linking in HEP Simulation –Remote Database Access in HEP Simulation –Expandable Filesystem for Astrophysics Data –Expandable Database for Mol. Dynamics Simulation Ongoing Work –Malloc, Dynamic Views, DACLs, PINS Final Thoughts

Ongoing Work Malloc() for the Filesystem –Resource owners want to limit users. (quota) –End users need space assurance. (alloc) –Need per-user allocations, not just global limits. Dynamic Data Views –Convert from DB to FS and back again. Distributed Access Control –ACLs refer to group definitions elsewhere. –What’s new? Fault tolerance / policy management. Processing in Storage (PINS) –Move computation to data. –Needs new programming (scripting) model.

Malloc in the Filesystem Paper: “Grid3: Principles and Practice” –90% of jobs would fail, most due to disk! Users need to alloc disk like anything else. –(Not accessible to user: quotas, loopback) –Allocation integrated with directory tree: scratch 100 GB job2 80 GB job1 10 GB job3 20 GB inputoutput taska 40 GB taskb 40 GB

Dynamic Data Views The same data can be perceived as either a file system or a database. Example: –DB: get files s.t. (T>300K) && (Mol==“CH4”) –FS: then process using scripts and shell –DB: associate derived files with original –FS: export and tar files for others.

Dynamic Data Views database server ACBYZX XML ->host6:fileX host2:fileY host5:fileZ Temp>300K Mol==CH 4 Distributed Filesystem Abstraction App

Distributed Access Control Lists Users are very comfortable with the ACL and group model. Can it be adapted to a grid environment? –Yes, can let an ACL refer to remote server. –Challenges: failures, caching, sharing policy. TSS client file server A Access Control List hostname:*.nd.edu RL group:serverB/presidents RWL file server B Group “Presidents” /O=NotreDame/CN=Jenkins /O=Purdue/CN=Jischke /O=Indiana/CN=Herbert

PINS: Processing in Storage Observation: –Traditional clusters separate CPU and storage into two distinct systems/problems. –Distributed computing is always some direct combination of CPU and I/O needs. Idea: PINS –Cluster HW is already a tighly integrated complex of CPU and I/O. Make the SW reflect the HW. –Key: Always compute in the same place that the data is located. Leave newly created data in place.

Processing in Storage file server database server XML index of data files ABAC X DC (X 200) 1. Compute Y = F(X). 3. Y is stored on S3. S1 S2S3S4 Y F 2 Dispatch F to S3.

Outline Problems with the Standard Model Tactical Storage Systems –File Servers, Catalogs, Abstractions, Adapters Applications: –Remote Dynamic Linking in HEP Simulation –Remote Database Access in HEP Simulation –Expandable Filesystem for Astrophysics Data –Expandable Database for Mol. Dynamics Simulation Ongoing Work –Malloc, Dynamic Views, DACLs, PINS Final Thoughts

Tactical Storage Systems Separate Abstractions from Resources Components: –Servers, catalogs, abstractions, adapters. –Completely user level. –Performance acceptable for real applications. Independent but Cooperating Components –Owners of file servers set policy. –Users must work within policies. –Within policies, users are free to build.

Acknowledgments Science Collaborators: –Jesus Izaguirre –Sander Klous –Peter Kunzst –Erwin Laure –John Poirer –Igor Sfiligoi –Aaron Striegel CSE Graduate Students: –Paul Brenner –James Fitzgerald –Jeff Hemmes –Paul Madrid –Chris Moretti –Phil Snowberger –Justin Wozniak

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Extra Slides

Performance – System Calls

Performance - Applications parrot only

Performance – I/O Calls

Performance – Bandwidth

Performance – DSFS