Distributed File Systems
http://net.pku.edu.cn/~course/cs402/2010
Hongfei Yan
School of EECS, Peking University
7/29/2010
DFS@wikipedia (1/2)
• In computing, a distributed file system or network file
system is any file system that allows access to files from
multiple hosts sharing via a computer network.[1] This
makes it possible for multiple users on multiple machines
to share files and storage resources.
• The client nodes do not have direct access to the
underlying block storage but interact over the network
using a protocol. This makes it possible to restrict access
to the file system depending on access lists or
capabilities on both the servers and the clients,
depending on how the protocol is designed.
DFS@wikipedia (2/2)
• In contrast, in a shared disk file system all nodes have
equal access to the block storage where the file system
is located. On these systems the access control must
reside on the client.
• Distributed file systems may include facilities for
transparent replication and fault tolerance. That is, when
a limited number of nodes in a file system go offline, the
system continues to work without any data loss.
• The difference between a distributed file system and a
distributed data store can be vague, but DFSes are
generally geared towards use on local area networks.
Outline
• File systems overview
• NFS & AFS (Andrew File System)
• Google File System
File Systems Overview
• System that permanently stores data
• Usually layered on top of a lower-level
physical storage medium
• Divided into logical units called “files”
– Addressable by a filename (“foo.txt”)
– Usually supports hierarchical nesting
(directories)
File Paths
• A file path joins file & directory names into
a relative or absolute address to identify
a file
– Absolute: /home/aaron/foo.txt
– Relative: docs/someFile.doc
• The shortest absolute path to a file is
called its canonical path
• The set of all canonical paths establishes
the namespace for the file system
What Gets Stored
• User data itself is the bulk of the file
system's contents
• Also includes meta-data on a drive-wide
and per-file basis:
Drive-wide:
Per-file:
available space
name
formatting info
owner
character set
modification date
...
physical layout...
High-Level Organization
• Files are organized in a “tree” structure
made of nested directories
• One directory acts as the “root”
• “links” (symlinks, shortcuts, etc) provide
simple means of providing multiple access
paths to one file
• Other file systems can be “mounted” and
dropped in as sub-hierarchies (other drives,
network shares)
Low-Level Organization (1/2)
• File data and meta-data stored separately
• File descriptors + meta-data stored in
inodes
– Large tree or table at designated location on
disk
– Tells how to look up file contents
• Meta-data may be replicated to increase
system reliability
Low-Level Organization (2/2)
• “Standard” read-write medium is a hard
drive (other media: CDROM, tape, ...)
• Viewed as a sequential array of blocks
• Must address ~1 KB chunk at a time
• Tree structure is “flattened” into blocks
• Overlapping reads/writes/deletes can
cause fragmentation: files are often not
stored with a linear layout
– inodes store all block ids related to file
Fragmentation
A
B
C
(free space)
A
B
C
A
(free space)
A
(free space)
C
A
(free space)
A
D
C
A
D
(free)
Design Considerations
• Smaller block size reduces amount of
wasted space
• Larger block size increases speed of
sequential reads (may not help random
access)
• Should the file system be faster or more
reliable?
• But faster at what: Large files? Small files?
Lots of reading? Frequent writers,
occasional readers?
File system Security
• File systems in multi-user environments
need to secure private data
– Notion of username is heavily built into FS
– Different users have different access writes to
files
UNIX Permission Bits
• World is divided into three scopes:
– User – The person who owns (usually created)
the file
– Group – A list of particular users who have
“group ownership” of the file
– Other – Everyone else
• “Read,” “write” and “execute” permissions
applicable at each level
UNIX Permission Bits: Limits
• Only one group can be associated with a
file
• No higher-order groups (groups of groups)
• Makes it difficult to express more
complicated ownership sets
Access Control Lists
• More general permissions mechanism
• Implemented in Windows
• Richer notion of privileges than r/w/x
– e.g., SetPrivilege, Delete, Copy…
• Allow for inheritance as well as deny lists
– Can be complicated to reason about and lead
to security gaps
Process Permissions
• Important note: processes running on
behalf of user X have permissions
associated with X, not process file owner
Y
• So if root owns ls, user aaron can not use
ls to peek at other users’ files
• Exception: special permission “setuid” sets
the user-id associated with a running
process to the owner of the program file
Disk Encryption
• Data storage medium is another security
concern
– Most file systems store data in the clear, rely on
runtime security to deny access
– Assumes the physical disk won’t be stolen
• The disk itself can be encrypted
– Hopefully by using separate passkeys for each user’s
files
– (Challenge: how do you implement read access for
group members?)
– Metadata encryption may be a separate concern
Outline
• File systems overview
• NFS & AFS (Andrew File System)
• Google File System
Distributed Filesystems
• Support access to files on remote servers
• Must support concurrency
– Make varying guarantees about locking, who
“wins” with concurrent writes, etc...
– Must gracefully handle dropped connections
• Can offer support for replication and local
caching
• Different implementations sit in different
places on complexity/feature scale
Distributed File Systems
• General goal: Try to make a file system transparently
available to remote clients.
• (a) The remote access model.
(b) The upload/download model.
Network File System (NFS)
• First developed in 1980s by Sun
• Presented with standard UNIX FS interface
• Network drives are mounted into local
directory hierarchy
– Type ‘man mount’, 'mount' some time at the
prompt if curious
NFS Protocol
• Initially completely stateless
– Operated over UDP; did not use TCP streams
– File locking, etc, implemented in higher-level
protocols
• Modern implementations use TCP/IP &
stateful protocols
NFS Architecture for UNIX systems
• NFS is implemented using the Virtual File System abstraction,
which is now used for lots of different operating systems:
• Essence: VFS provides standard file system interface, and
allows to hide difference between accessing local or remote
file system.
Server-side Implementation
• NFS defines a virtual file system
– Does not actually manage local disk layout on server
• Server instantiates NFS volume on top of local
file system
– Local hard drives managed by concrete file systems
(EXT, ReiserFS, ...)
NFS server
User-visible filesystem
EXT3 fs
EXT3 fs
Hard Drive 1
Hard Drive 2
Server filesystem
NFS client
EXT2 fs
ReiserFS
Hard Drive 1
Hard Drive 2
Typical implementation
• Assuming a Unix-style scenario in which one machine requires
access to data stored on another machine:
1. The server implements NFS daemon processes in order to
make its data generically available to clients.
2. The server administrator determines what to make available,
exporting the names and parameters of directories.
3. The server security-administration ensures that it can
recognize and approve validated clients.
4. The server network configuration ensures that appropriate
clients can negotiate with it through any firewall system.
5. The client machine requests access to exported data, typically
by issuing a mount command.
6. If all goes well, users on the client machine can then view and
interact with mounted filesystems on the server within the
parameters permitted.
[webg@index1 ~]$ vi /etc/exports
# the file /etc/exports serves as the access control list for
# file systems which may be exported to NFS clients.
/home/infomall/udata
192.168.100.0/24(rw,async)
222.29.154.11(rw,async)
/home/infomall/hist
192.168.100.0/24(rw,async)
NFS Locking
• NFS v4 supports stateful locking of files
– Clients inform server of intent to lock
– Server can notify clients of outstanding lock
requests
– Locking is lease-based: clients must
continually renew locks before a timeout
– Loss of contact with server abandons locks
NFS Client Caching
• NFS Clients are allowed to cache copies of
remote files for subsequent accesses
• Supports close-to-open cache consistency
– When client A closes a file, its contents are
synchronized with the master, and timestamp
is changed
– When client B opens the file, it checks that
local timestamp agrees with server timestamp.
If not, it discards local copy.
– Concurrent reader/writers must use flags to
disable caching
NFS: Tradeoffs
• NFS Volume managed by single server
– Higher load on central server
– Simplifies coherency protocols
• Full POSIX system means it “drops in” very
easily, but isn’t “great” for any specific
need
Distributed FS Security
• Security is a concern at several levels
throughout DFS stack
– Authentication
– Data transfer
– Privilege escalation
• How are these applied in NFS?
Authentication in NFS
• Initial NFS system trusted client programs
– User login credentials were passed to OS
kernel which forwarded them to NFS server
– … A malicious client could easily subvert this
• Modern implementations use more
sophisticated systems (e.g., Kerberos)
Data Privacy
• Early NFS implementations sent data in
“plaintext” over network
– Modern versions tunnel through SSH
• Double problem with UDP (connectionless)
protocol:
– Observers could watch which files were being
opened and then insert “write” requests with
fake credentials to corrupt data
Privilege Escalation
• Local file system username is used as
NFS username
– Implication: being “root” on local machine
gives you root access to entire NFS cluster
• Solution: “root squash” – NFS hard-codes
a privilege de-escalation from “root” down
to “nobody” for all accesses.
RPCs in File System
• Observation: Many (traditional) distributed file systems
deploy remote procedure calls to access files. When
wide-area networks need to be crossed, alternatives
need to be exploited:
File Sharing Semantics (1/2)
• Problem: When dealing with
distributed file systems, we need to
take into account the ordering of
concurrent read/write operations, and
expected semantics (=consistency).
File Sharing Semantics (2/2)
• UNIX semantics:
– a read operation returns the effect of the last write
operation => can only be implemented for remote
access models in which there is only a single copy of
the file
• Transaction semantics:
– the file system supports transactions on a single file
=> issue is how to allow concurrent access to a
physically distributed file
• Session semantics:
– the effects of read and write operations are seen only
by the client that has opened (a local copy) of the file
=> what happens when a file is closed (only one client
may actually win)
Consistency and Replication
• Observation: In modern distributed file systems, client
side caching is the preferred technique for attaining
performance; server-side replication is done for fault
tolerance.
• Observation: Clients are allowed to keep (large parts of)
a file, and will be notified when control is withdrawn =>
servers are now generally stateful
Fault Tolerance
• Observation: FT is handled by simply replicating file servers,
generally using a standard primary-backup protocol:
AFS (The Andrew File System)
• Developed at Carnegie Mellon
• Strong security, high scalability
– Supports 50,000+ clients at enterprise level
• AFS heavily influenced Version 4 of NFS.
Security in AFS
• Uses Kerberos authentication
• Supports richer set of access control bits
than UNIX
– Separate “administer”, “delete” bits
– Allows application-specific bits
Local Caching
• File reads/writes operate on locally cached
copy
• Local copy sent back to master when file is
closed
• Open local copies are notified of external
updates through callbacks
Local Caching - Tradeoffs
• Shared database files do not work well on
this system
• Does not support write-through to shared
medium
Replication
• AFS allows read-only copies of filesystem
volumes
• Copies are guaranteed to be atomic
checkpoints of entire FS at time of readonly copy generation
• Modifying data requires access to the sole
r/w volume
– Changes do not propagate to read-only
copies
AFS Conclusions
• Not quite POSIX
– Stronger security/permissions
– No file write-through
• High availability through replicas, local
caching
• Not appropriate for all file types
Outline
• File systems overview
• NFS & AFS (Andrew File System)
• Google File System
Motivation
• Google needed a good distributed file system
– Redundant storage of massive amounts of data on
cheap and unreliable computers
• Why not use an existing file system?
– Google’s problems are different from anyone else’s
• Different workload and design priorities
– GFS is designed for Google apps and workloads
– Google apps are designed for GFS
Assumptions
• High component failure rates
– Inexpensive commodity components fail often
• “Modest” number of HUGE files
– Just a few million
– Each is 100MB or larger; multi-GB files typical
• Files are write-once, mostly appended to
– Perhaps concurrently
• Large streaming reads
• High sustained throughput favored over low latency
GFS Design Decisions
• Files stored as chunks
– Fixed size (64MB)
• Reliability through replication
– Each chunk replicated across 3+ chunkservers
• Single master to coordinate access, keep metadata
– Simple centralized management
• No data caching
– Little benefit due to large data sets, streaming reads
• Familiar interface, but customize the API
– Simplify the problem; focus on Google apps
– Add snapshot and record append operations
GFS Client Block Diagram
Client computer
GFS-Aware Application
POSIX API
GFS Master
GFS API
GFS Chunkserver
Regular VFS with local and
NFS-supported files
Separate GFS view
Specific drivers...
Network stack
GFS Chunkserver
Cluster-Based Distributed File Systems
• Observation: When dealing with very large data
collections, following a simple client-server approach is
not going to work.
• Solution 1: For speeding up file accesses, apply striping
techniques by which files can be fetched in parallel:
• (a) whole-file distribution, (b) file-striped system
Example: Google File System
• Solution 2: Divide files in large 64 MB chunks, and
distribute/replicate chunks across many servers.
• A couple of important details:
– The master maintains only a (file name, chunk server) table in main
memory ) minimal I/O
– Files are replicated using a primary-backup scheme; the master is kept
out of the loop
Single master
• From distributed systems we know this is a:
– Single point of failure
– Scalability bottleneck
• GFS solutions:
– Shadow masters
– Minimize master involvement
• never move data through it, use only for metadata
– and cache metadata at clients
• large chunk size
• master delegates authority to primary replicas in data mutations
(chunk leases)
• Simple, and good enough!
Metadata (1/2)
• Global metadata is stored on the master
– File and chunk namespaces
– Mapping from files to chunks
– Locations of each chunk’s replicas
• All in memory (64 bytes / chunk)
– Fast
– Easily accessible
Metadata (2/2)
• Master has an operation log for persistent
logging of critical metadata updates
– persistent on local disk
– replicated
– checkpoints for faster recovery
Mutations
• Mutation = write or append
– must be done for all replicas
• Goal: minimize master involvement
• Lease mechanism:
– master picks one replica as primary; gives it a “lease”
for mutations
– primary defines a serial order of mutations
– all replicas follow this order
• Data flow decoupled from control flow
Mutations Diagram
Mutation Example
1. Client 1 opens "foo" for modify. Replicas are named A,
B, and C. B is declared primary.
2. Client 1 sends data X for chunk to chunk servers
3. Client 2 opens "foo" for modify. Replica B still primary
4. Client 2 sends data Y for chunk to chunk servers
5. Server B declares that X will be applied before Y
6. Other servers signal receipt of data
7. All servers commit X then Y
8. Clients 1 & 2 close connections
9. B's lease on chunk is lost
Atomic record append
• Client specifies data
• GFS appends it to the file atomically at least
once
– GFS picks the offset
– works for concurrent writers
• Used heavily by Google apps
– e.g., for files that serve as multiple-producer/singleconsumer queues
Relaxed consistency model (1/2)
• “Consistent” = all replicas have the same value
• “Defined” = replica reflects the mutation,
consistent
• Some properties:
– concurrent writes leave region consistent, but possibly
undefined
– failed writes leave the region inconsistent
• Some work has moved into the applications:
– e.g., self-validating, self-identifying records
Relaxed consistency model (2/2)
• Simple, efficient
– Google apps can live with it
– what about other apps?
• Namespace updates atomic and serializable
Master’s responsibilities (1/2)
• Metadata storage
• Namespace management/locking
• Periodic communication with chunkservers
– give instructions, collect state, track cluster health
• Chunk creation, re-replication, rebalancing
– balance space utilization and access speed
– spread replicas across racks to reduce correlated
failures
– re-replicate data if redundancy falls below threshold
– rebalance data to smooth out storage and request
load
Master’s responsibilities (2/2)
• Garbage Collection
– simpler, more reliable than traditional file delete
– master logs the deletion, renames the file to a hidden
name
– lazily garbage collects hidden files
• Stale replica deletion
– detect “stale” replicas using chunk version numbers
Fault Tolerance
• High availability
– fast recovery
• master and chunkservers restartable in a few seconds
– chunk replication
• default: 3 replicas.
– shadow masters
• Data integrity
– checksum every 64KB block in each chunk
Scalability
• Scales with available machines, subject to
bandwidth
– Rack- and datacenter-aware locality and
replica creation policies help
• Single master has limited responsibility,
does not rate-limit system
Scalability
•Microbenchmarks: 1—16 servers
•Read performance 75—80% efficient (good!)
•Write performance ~50% (network stack overhead)
Performance
Security
• … Basically none
• Relies on Google’s network being private
• File permissions not mentioned in paper
– Individual users / applications must cooperate
Deployment in Google
•
•
•
•
50+ GFS clusters
Each with thousands of storage nodes
Managing petabytes of data
GFS is under BigTable, etc.
Conclusion
• GFS demonstrates how to support large-scale
processing workloads on commodity hardware
– design to tolerate frequent component failures
– optimize for huge files that are mostly appended and
read
– feel free to relax and extend FS interface as required
– go for simple solutions (e.g., single master)
• GFS has met Google’s storage needs… it
must be good!
References
• Some definitions of concepts form Wikipedia,
– e.g., DFS, file system
• [Ghemawat, et al.,2003] S. Ghemawat, H. Gobioff, and
S.-T. Leung, "The Google file system," SIGOPS Oper.
Syst. Rev., vol. 37, pp. 29-43, 2003.
• Chapter 11 of [Tanenbaum, 2007]