Internet DRAFT - draft-gibson-pnfs-problem-statement





INTERNET-DRAFT                                              Garth Gibson 
Expires: January 2005                                 Panasas Inc. & CMU 
                                                           Peter Corbett 
                                                 Network Appliance, Inc. 
                                                                         
Document: draft-gibson-pnfs-problem-statement-01.txt           July 2004 
    
    
    
    
                          pNFS Problem Statement 
    
    
    
    
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Abstract 
    
   This draft considers the problem of limited bandwidth to NFS servers.  
   The bandwidth limitation exists because an NFS server has limited 
   network, CPU, memory and disk I/O resources.  Yet, access to any one 
   file system through the NFSv4 protocol requires that a single server 
   be accessed.  While NFSv4 allows file system migration, it does not 
   provide a mechanism that supports multiple servers simultaneously 
   exporting a single writable file system. 
    
   This problem has become aggravated in recent years with the advent of 
   very cheap and easily expanded clusters of application servers that 
   are also NFS clients.  The aggregate bandwidth demands of such 
   clustered clients, typically working on a shared data set 
   preferentially stored in a single file system, can increase much more 
   quickly than the bandwidth of any server.  The proposed solution is 
   to provide for the parallelization of file services, by enhancing 
   NFSv4 in a minor version.  
    
    
Table of Contents 
    
   1. Introduction...................................................2 
   2. Bandwidth Scaling in Clusters..................................4 
   3. Clustered Applications.........................................4 
   4. Existing File Systems for Clusters.............................6 
   5. Eliminating the Bottleneck.....................................7 
   6. Separated control and data access techniques...................8 
   7. Security Considerations........................................9 
   8. Informative References.........................................9 
   9. Acknowledgments...............................................11 
   10. Author's Addresses...........................................11 
   11. Full Copyright Statement.....................................11 
    
    
1. Introduction 
    
   The storage I/O bandwidth requirements of clients are rapidly 
   outstripping the ability of network file servers to supply them.  
   Increasingly, this problem is being encountered in installations 
   running the NFS protocol.  The problem can be solved by increasing 
   the server bandwidth.  This draft suggests that an effort be mounted 
   to enable NFS file service to scale with its clusters of clients.  
   The proposed approach is to increase the aggregate bandwidth possible 
   to a single file system by parallelizing the file service, resulting 
   in multiple network connections to multiple server endpoints 
   participating in the transfer of requested data.  This should be 

 
 
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   achievable within the framework of NFS, possibly in a minor version 
   of the NFSv4 protocol. 
    
   In many application areas, single system servers are rapidly being 
   replaced by clusters of inexpensive commodity computers. As 
   clustering technology has improved, the barriers to running 
   application codes on very large clusters have been lowered. Examples 
   of application areas that are seeing the rapid adoption of scalable 
   client clusters are data intensive applications such as genomics, 
   seismic processing, data mining, content and video distribution, and 
   high performance computing. The aggregate storage I/O requirements of 
   a cluster can scale proportionally to the number of computers in the 
   cluster.  It is not unusual for clusters today to make bandwidth 
   demands that far outstrip the capabilities of traditional file 
   servers.  A natural solution to this problem is to enable file 
   service to scale as well, by increasing the number of server nodes 
   that are able to service a single file system to a cluster of 
   clients. 
    
   Scalable bandwidth can be claimed by simply adding multiple 
   independent servers to the network. Unfortunately, this leaves to 
   file system users the task of spreading data across these independent 
   servers.  Because the data processed by a given data-intensive 
   application is usually logically associated, users routinely co-
   locate this data in a single file system, directory or even a single 
   file.  The NFSv4 protocol currently requires that all the data in a 
   single file system be accessible through a single exported network 
   endpoint, constraining access to be through a single NFS server. 
    
   A better way of increasing the bandwidth to a single file system is 
   to enable access to be provided through multiple endpoints in a 
   coordinated or coherent fashion.  Separation of control and data 
   flows provides a straightforward framework to accomplish this, by 
   allowing transfers of data to proceed in parallel from many clients 
   to many data storage endpoints.  Control and file management 
   operations, inherently more difficult to parallelize, can remain the 
   province of a single NFS server, inheriting the simple management of 
   today's NFS file service, while offloading data transfer operations 
   allows bandwidth scalability.  Data transfer may be done using NFS or 
   other protocols, such as iSCSI.  
    
   While NFS is a widely used network file system protocol, most of the 
   world's data resides in data stores that are not accessible through 
   NFS.  Much of this data is stored in Storage Area Networks, 
   accessible by SCSI's Fibre Channel Protocol (FCP), or increasingly, 
   by iSCSI.  Storage Area Networks routinely provide much higher data 
   bandwidths than do NFS file servers.  Unfortunately, the simple array 
   of blocks interface into Storage Area Networks does not lend itself 
   to controlling multiple clients that are simultaneously reading and 
 
 
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   writing the blocks of the same or different files, a workload usually 
   referred to as data sharing.  NFS file service, with its hierarchical 
   namespace of separately controlled files, offers simpler and more 
   cost-effective management.  One might conclude that users must chose 
   between high bandwidth and data sharing.  Not only is this conclusion 
   false, but it should also be possible to allow data stored in SAN 
   devices, FCP or iSCSI, to be accessed under the control of an NFS 
   server.  Such an approach protects the industry's large investment in 
   NFS, since the bandwidth bottleneck no longer needs to drive users to 
   adopt a proprietary alternative solution, and leverages SAN storage 
   infrastructures, all within a common architectural framework. 
    
    
2. Bandwidth Scaling in Clusters 
    
   When applied to data-intensive applications, clusters can generate 
   unprecedented demand for storage bandwidth.  At present, each node in 
   the cluster is likely to be a dual processor, with each processor 
   running at multiple GHz, with gigabytes of DRAM.  Depending on the 
   specific application, each node is capable of sustaining a demand of 
   10s to 100s of MB/s of data from storage.  In addition, the number of 
   nodes in a cluster is commonly in the 100s, with many instances of 
   1000s to 10,000s of nodes.  The result is that storage systems may be 
   called upon to provide an aggregate bandwidth of GB/s ranging upwards 
   toward TB/s. 
    
   The performance of a single NFS server has been improving, but it is 
   not able to keep pace with cluster demand. Directly connected storage 
   devices behind an NFS server have given way to disk arrays and 
   networked disk arrays, making it now possible for an NFS server to 
   directly access 100s to 1000s of disk drives whose aggregate capacity 
   reaches upwards to PBs and whose raw bandwidths range upwards to 10s 
   of GB/s.   
    
   An NFS server is interposed between the scalable storage subsystem 
   and the scalable client cluster.  Multiple NIC endpoints help network 
   bandwidth keep up with DRAM bandwidth.  However, the rate of 
   improvement of NFS server performance is not faster than the rate of 
   improvement in each client node. As long as an NFS file system is 
   associated with a single client-side network endpoint, the aggregate 
   capabilities of a single NFS server to move data between storage 
   networks and client networks will not be able to keep pace with the 
   aggregate demand of clustered clients and large disk subsystems. 
    
    
3. Clustered Applications 
    
   Large datasets and high bandwidth processing of large datasets are 
   increasingly common in a wide variety of applications.  As most 
 
 
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   computer users can affirm, the size of everyday presentations, 
   pictures and programs seems to grow continuously, and in fact average 
   file size does grow with time [Ousterhout85, Baker91].  Simple 
   copying, viewing, archiving and sharing of even this baseline use of 
   growing files in day-to-day business and personal computing drives up 
   the bandwidth demand on servers.   
    
   Some applications, however, make much larger demands on file and file 
   system capacity and bandwidth.  Databases of DNA sequences, used in 
   bioinformatics search, range up to tens of GBs and are often in use 
   by all cluster users are the same time [NIH03].  These huge files may 
   experience bursts of many concurrent clients loading the whole file 
   independently.   
    
   Bioinformatics is an example of extensive search in science 
   application.  Extensive search is much broader than science.  Wall 
   Street has taken to collecting long-term transaction record 
   histories.  Looking for patterns of unbilled transactions, fraud or 
   predictable market trends is a growing financial opportunity 
   [Agarwal95, Senator95].   
    
   Security and authentication are driving a need for image search, such 
   as face recognition [Flickner95].  Databasing the faces of approved 
   or suspected individuals and searching through many camera feeds 
   involves huge data and bandwidths.  Traditional database indexing in 
   these high dimension data structures often fails to avoid full 
   database scans of these huge files [Berchtold97]. 
    
   With huge storage repositories and fast computers, huge sensor 
   capture is increasingly used in many applications.  Consumer digital 
   photography fits this model, with photo touch-up and slide show 
   generation tools driving bandwidth, although much more demanding 
   applications are not unusual.   
    
   Medical test imagery is being captured at very high resolution and 
   tools are being developed for automatic preliminary diagnosis, for 
   example [Afework98]. In the science world, even larger datasets are 
   captured from satellites, telescopes, and atom-smashers, for example 
   [Greiman97].  Preliminary processing of a sky survey suggests that 
   thousand node clusters may sustain GB/s storage bandwidths [Gray03].  
   Seismic trace data, often measured in helicopter loads, commands 
   large clusters for days to months [Knott03]. 
    
   At the high end of science application, accurate physical simulation, 
   its visualization and fault-tolerance checkpointing, has been 
   estimated to need 10 GB/s bandwidth and 100 TB of capacity for every 
   thousand nodes in a cluster [SGPFS01].   
    

 
 
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   Most of these applications make heavy use of shared data across many 
   clients, users and applications, have limited budgets available to 
   fund aggressive computational goals, and have technical or scientific 
   users with strong preferences for file systems and no patience for 
   tuning storage.  NFS file service, appropriately scaled up in 
   capacity and bandwidth, is highly desired.   
    
   In addition to these search, sensor and science applications, 
   traditional database applications are increasingly employing NFS 
   servers.  These applications often have hotspot tables, leading to 
   high bandwidth storage demands.   Yet SAN-based solutions are 
   sometimes harder to manage than NFS based solutions, especially in 
   databases with a large number of tables. NFS servers with scalable 
   bandwidth would accelerate the adoption of NFS for database 
   applications. 
    
   These examples suggest that there is no shortage of applications 
   frustrated by the limitations of a single network endpoint on a 
   single NFS server exporting a single file system or single huge file. 
    
    
4. Existing File Systems for Clusters 
    
   The server bottleneck has induced various vendors to develop 
   proprietary alternatives to NFS. 
    
   Known variously as asymmetric, out-of-band, clustered or SAN file 
   systems, these proprietary alternatives exploit the scalability of 
   storage networks by attaching all nodes in the client cluster to the 
   storage network.  Then, by reorganizing client and server code 
   functionality to separate data traffic from control traffic, client 
   nodes are able to access storage devices directly rather than 
   requesting all data from the same single network endpoint in the file 
   server that handles control traffic. 
    
   Most proprietary alternative solutions have been tailored to storage 
   area networks based on the fixed-sized block SCSI storage device 
   command set and its Fibrechannel SCSI transport.  Examples in this 
   class include EMC's High Road (www.emc.com); IBM's TotalStorage SAN 
   FS, SANergy and GPFS (www.ibm.com); Sistina/Redhat's GFS 
   (www.readhat.com); SGI's CXFS (www.sgi.com); Veritas' SANPoint Direct 
   and CFS (www.veritas.com); and Sun's QFS (www.sun.com).  The 
   Fibrechannel SCSI transport used in these systems may soon be 
   replaceable by a TCP/IP SCSI transport, iSCSI, enabling these 
   proprietary alternatives to operate on the same equipment and IETF 
   protocols commonly used by NFS servers. 
    
   While fixed-sized block SCSI storage devices are used in most file 
   systems with separated data and control paths, this is not the only 
 
 
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   alternative available today.  SCSI's newly emerging command set, the 
   Object Storage Device (OSD) command set, transmits variable length 
   storage objects over SCSI transports [T10-03].  Panasas' ActiveScale 
   storage cluster employs a proto-OSD command set over iSCSI on its 
   separated data path (www.panasas.com).  IBM's research is also 
   demonstrating a variant of their TotalStorage SAN FS employing proto-
   OSD commands [Azagury02].  
    
   Even more distinctive is Zforce's File Switch technology 
   (www.zforce.com).  Zforce virtualizes a CIFS file server spreading 
   the contents of a file share over many backend CIFS storage servers 
   and places their control path functionality inside a network switch 
   in order to have some of the properties of both separated and non-
   separated data and control paths.  However, striping files over 
   multiple file-based storage servers is not a new concept.  Berkeley's 
   Zebra file system, the successor to the log-based file system 
   developed for RAID storage, had a separated data and control path 
   with file protocols to both [Hartman95]. 
    
    
5. Eliminating the Bottleneck 
    
   The restriction of a single network endpoint results from the way NFS 
   associates file servers and file systems.  Essentially, each client 
   machine "mounts" each exported file system; these mount operations 
   bind a network endpoint to all files in the exported file system, 
   instructing the client to address that network endpoint with all 
   requests associated with all files in that file system.  Mechanisms 
   intended for primarily for failover have been established for giving 
   clients a list of network endpoints associated with a given file 
   system.  
    
   Multiple NFS servers can be used instead of a single NFS server, and 
   many cluster administrators, programmers and end-users have 
   experimented with this alternative.  The principle compromise 
   involved in exploiting multiple NFS servers is that a single file or 
   single file system is decomposed into multiple files or file systems, 
   respectively. For instance, a single file can be decomposed into many 
   files, each located in a part of the namespace that is exported by a 
   different NFS server; or the files of a single directory can be 
   linked to files in directories located in file systems exported by 
   different NFS servers.  Because this decomposition is done without 
   NFS server support, the work of decomposing and recomposing and the 
   implications of the decomposition on capacity and load balancing, 
   backup consistency, error recovery, and namespace management all fall 
   to the customer. Moreover, the additional statefulness of NFSv4 makes 
   correct semantics for files decomposed over multiple services without 
   NFS support much more complex. Such extra work and extra problems are 

 
 
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   usually referred to as storage management costs, and are blamed for 
   causing a high total cost of ownership for storage. 
    
   Preserving the relative ease of use of NFS storage systems requires 
   solutions to the bandwidth bottleneck that do not decompose files and 
   directories in the file subtree namespace. 
   A solution to this problem should continue to use the existing single 
   network endpoint for control traffic, including namespace 
   manipulations. Decompositions of individual files and file systems 
   over multiple network endpoints can be provided via the separated 
   data paths, without separating the control and metadata paths. 
    
    
6. Separated control and data access techniques 
    
   Separating storage data flow from file system control flow 
   effectively moves the bottleneck away from the single endpoint of an 
   NFS server and distributes it across the bisectional bandwidth of the 
   storage network between the cluster nodes and storage devices.  Since 
   switch bandwidths of upwards of terabits per second are available 
   today, this bottleneck is at least two orders of magnitude better 
   than that of an NFS server network endpoint. 
    
   In an architecture that separates the storage data path from the NFS 
   control path there are choices of protocol for the data path.  One 
   straightforward answer is to extend the NFS protocol so it can 
   accommodate can be used on both control and separated data paths.  
   Another straightforward answer is to capture the existing market's 
   dominant separated data path, fixed-sized block SCSI storage. A third 
   alternative is the emerging object storage SCSI command set, OSD, 
   which is appearing in new products with separate data and control 
   paths. 
    
   A solution that accommodates all of these approaches provides the 
   broadest applicability for NFS.  Specifically, NFS extensions should 
   make minimal assumptions about the storage data server access 
   protocol.  The clients in such an extended NFS system should be 
   compatible with the current NFSv4 protocol, and should be compatible 
   with earlier versions of NFS as well.  A solution should be capable 
   of providing both asymmetric data access, with the data path 
   connected via NFS or other protocols and transports, and symmetric 
   parallel access to servers that run NFS on each server node.  
   Specifically, it is desirable to enable NFS to manage asymmetric 
   access to storage attached via iSCSI and Fibre Channel/SCSI storage 
   area networks. 
    
   As previously discussed, the root cause of the NFS server bottleneck 
   is the binding between one network endpoint and all the files in a 
   file system.  NFS extensions can allow the association of additional 
 
 
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   network endpoints with specific files.  These associations could be 
   represented as layout maps [Gibson98].  NFS clients could be extended 
   to have the ability to retrieve and use these layout maps. 
    
   NFSv4 provides an excellent foundation for this.  We may be able to 
   extend the current notion of file delegations to include the ability 
   to retrieve and utilize a file layout map.  A number of ideas have 
   been proposed for storing, accessing, and acting upon layout 
   information stored by NFS servers to allow separate access to file 
   data over separate data paths.  Data access can be supported over 
   multiple protocols, including NFSv4, iSCSI, and OSD. 
    
7. Security Considerations 
    
   Bandwidth scaling solutions that employ separation of control and 
   data paths will introduce new security concerns.  For example, the 
   data access methods will require authentication and access control 
   mechanisms that are consistent with the primary mechanisms on the 
   NFSv4 control paths.  Object storage employs revocable cryptographic 
   restrictions on each object, which can be created and revoked in the 
   control path. With iSCSI access methods, iSCSI security capabilities 
   are available, but do not contain NFS access control.  Fibre Channel 
   based SCSI access methods have less sophisticated security than 
   iSCSI.  These access methods typically use private networks to 
   provide security. 
    
   Any proposed solution must be analyzed for security threats and any 
   such threats must be addressed.  The IETF and the NFS working group 
   have significant expertise in this area. 
    
    
8. Informative References 
    
   [Afework98] A. Afework, M. Beynon, F. Bustamonte, A. Demarzo, R. 
      Ferriera, R. Miller, M. Silberman, J. Saltz, A. Sussman, H. Tang, 
      "Digital dynamic telepathology - the virtual microscope," Proc. of 
      the AMIA'98 Fall Symposium 1998. 
    
   [Agarwal95] Agrawal, R. and Srikant, R. "Fast Algorithms for Mining 
      Association Rules" VLDB, September 1995. 
    
   [Azagury02] Azagury, A., Dreizin, V., Factor, M., Henis, E., Naor, 
      D., Rinetzky, N., Satran, J., Tavory, A., Yerushalmi, L, "Towards 
      an Object Store," IBM Storage Systems Technology Workshop, 
      November 2002. 
    
   [Baker91] Baker, M.G., Hartman, J.H., Kupfer, M.D., Shirriff, K.W. 
      and Ousterhout, J.K. "Measurements of a Distributed File System" 
      SOSP, October 1991. 
 
 
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   [Berchtold97] Berchtold, S., Boehm, C., Keim, D.A. and Kriegel, H. "A 
      Cost Model For Nearest Neighbor Search in High-Dimensional Data 
      Space" ACM PODS, May 1997. 
    
   [Fayyad98] Fayyad, U. "Taming the Giants and the Monsters: Mining 
      Large Databases for Nuggets of Knowledge" Database Programming and 
      Design, March 1998. 
    
   [Flickner95] Flickner, M., Sawhney, H., Niblack, W., Ashley, J., 
      Huang, Q., Dom, B., Gorkani, M., Hafner, J., Lee, D., Petkovic, 
      D., Steele, D. and Yanker, P. "Query by Image and Video Content: 
      the QBIC System" IEEE Computer, September 1995. 
    
   [Gibson98] Gibson, G. A., et. al., "A Cost-Effective, High-Bandwidth 
      Storage Architecture," International Conference on Architectural 
      Support for Programming Languages and Operating Systems (ASPLOS), 
      October 1998. 
    
   [Gray03] Jim Gray, "Distributed Computing Economics," Technical 
      Report MSR-TR-2003-24, March 2003. 
    
   [Greiman97] Greiman, W., W. E. Johnston, C. McParland, D. Olson, B. 
      Tierney, C. Tull, "High-Speed Distributed Data Handling for HENP," 
      Computing in High Energy Physics, April, 1997. Berlin, Germany. 
    
   [Hartman95] John H. Hartman and John K. Ousterhout, "The Zebra 
      Striped Network File System," ACM Transactions on Computer Systems 
      13, 3, August 1995. 
    
   [Knott03] Knott, T., "Computing colossus," BP Frontiers magazine, 
      Issue 6, April 2003, http://www.bp.com/frontiers. 
    
   [NIH03] "Easy Large-Scale Bioinformatics on the NIH Biowulf 
      Supercluster," http://biowulf.nih.gov/easy.html, 2003. 
    
   [Ousterhout85] Ousterhout, J.K., DaCosta, H., Harrison, D., Kunze, 
      J.A., Kupfer, M. and Thompson, J.G. "A Trace Drive Analysis of the 
      UNIX 4.2 BSD FIle System" SOSP, December 1985. 
    
   [Senator95] Senator, T.E., Goldberg, H.G., Wooten, J., Cottini, M.A., 
      Khan, A.F.U., Klinger, C.D., Llamas, W.M., Marrone, M.P. and Wong, 
      R.W.H. "The Financial Crimes Enforcement Network AI System (FAIS): 
      Identifying potential money laundering from reports of large cash 
      transactions"  AIMagazine 16 (4), Winter 1995. 
    
   [SGPFS01] SGS File System RFP, DOE NNCA and DOD NSA, April 25, 2001. 
    

 
 
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   [T10-03] Draft OSD Standard, T10 Committee, Storage Networking 
      Industry Association(SNIA), 
      ftp://www.t10.org/ftp/t10/drafts/osd/osd-r08.pdf 
    
    
9. Acknowledgments 
    
   David Black, Gary Grider, Benny Halevy, Dean Hildebrand, Dave Noveck, 
   Julian Satran, Tom Talpey, and Brent Welch contributed to the 
   development of this problem statement. 
    
    
10. Author's Addresses 
    
   Garth Gibson 
   Panasas Inc, and Carnegie Mellon University 
   1501 Reedsdale Street 
   Pittsburgh, PA 15233 USA 
   Phone: +1 412 323 3500 
   Email: ggibson@panasas.com 
    
   Peter Corbett 
   Network Appliance Inc. 
   375 Totten Pond Road 
   Waltham, MA 02451 USA 
   Phone: +1 781 768 5343 
   Email: peter@pcorbett.net 
    
    
11. Full Copyright Statement 
    
   Copyright (C) The Internet Society (2004).  This document is subject 
   to the rights, licenses and restrictions contained in BCP 78, and 
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