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docs: remove the redundant (and therefore bit-rotting) parts of mutable-DSA.txt and instead refer to mutable.txt

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Zooko O'Whielacronx 2008-04-29 15:51:58 -07:00
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@ -6,99 +6,9 @@ mutable files that were introduced in tahoe-0.7.0 . This proposal has not yet
been implemented. Please see mutable-DSA.svg for a quick picture of the
crypto scheme described herein)
= Mutable Files =
Mutable File Slots are places with a stable identifier that can hold data
that changes over time. In contrast to CHK slots, for which the
URI/identifier is derived from the contents themselves, the Mutable File Slot
URI remains fixed for the life of the slot, regardless of what data is placed
inside it.
Each mutable slot is referenced by two different URIs. The "read-write" URI
grants read-write access to its holder, allowing them to put whatever
contents they like into the slot. The "read-only" URI is less powerful, only
granting read access, and not enabling modification of the data. The
read-write URI can be turned into the read-only URI, but not the other way
around.
The data in these slots is distributed over a number of servers, using the
same erasure coding that CHK files use, with 3-of-10 being a typical choice
of encoding parameters. The data is encrypted and signed in such a way that
only the holders of the read-write URI will be able to set the contents of
the slot, and only the holders of the read-only URI will be able to read
those contents. Holders of either URI will be able to validate the contents
as being written by someone with the read-write URI. The servers who hold the
shares cannot read or modify them: the worst they can do is deny service (by
deleting or corrupting the shares), or attempt a rollback attack (which can
only succeed with the cooperation of at least k servers).
== Consistency vs Availability ==
There is an age-old battle between consistency and availability. Epic papers
have been written, elaborate proofs have been established, and generations of
theorists have learned that you cannot simultaneously achieve guaranteed
consistency with guaranteed reliability. In addition, the closer to 0 you get
on either axis, the cost and complexity of the design goes up.
Tahoe's design goals are to largely favor design simplicity, then slightly
favor read availability, over the other criteria.
As we develop more sophisticated mutable slots, the API may expose multiple
read versions to the application layer. The tahoe philosophy is to defer most
consistency recovery logic to the higher layers. Some applications have
effective ways to merge multiple versions, so inconsistency is not
necessarily a problem (i.e. directory nodes can usually merge multiple "add
child" operations).
== The Prime Coordination Directive: "Don't Do That" ==
The current rule for applications which run on top of Tahoe is "do not
perform simultaneous uncoordinated writes". That means you need non-tahoe
means to make sure that two parties are not trying to modify the same mutable
slot at the same time. For example:
* don't give the read-write URI to anyone else. Dirnodes in a private
directory generally satisfy this case, as long as you don't use two
clients on the same account at the same time
* if you give a read-write URI to someone else, stop using it yourself. An
inbox would be a good example of this.
* if you give a read-write URI to someone else, call them on the phone
before you write into it
* build an automated mechanism to have your agents coordinate writes.
For example, we expect a future release to include a FURL for a
"coordination server" in the dirnodes. The rule can be that you must
contact the coordination server and obtain a lock/lease on the file
before you're allowed to modify it.
If you do not follow this rule, Bad Things will happen. The worst-case Bad
Thing is that the entire file will be lost. A less-bad Bad Thing is that one
or more of the simultaneous writers will lose their changes. An observer of
the file may not see monotonically-increasing changes to the file, i.e. they
may see version 1, then version 2, then 3, then 2 again.
Tahoe takes some amount of care to reduce the badness of these Bad Things.
One way you can help nudge it from the "lose your file" case into the "lose
some changes" case is to reduce the number of competing versions: multiple
versions of the file that different parties are trying to establish as the
one true current contents. Each simultaneous writer counts as a "competing
version", as does the previous version of the file. If the count "S" of these
competing versions is larger than N/k, then the file runs the risk of being
lost completely. If at least one of the writers remains running after the
collision is detected, it will attempt to recover, but if S>(N/k) and all
writers crash after writing a few shares, the file will be lost.
== Small Distributed Mutable Files ==
SDMF slots are suitable for small (<1MB) files that are editing by rewriting
the entire file. The three operations are:
* allocate (with initial contents)
* set (with new contents)
* get (old contents)
The first use of SDMF slots will be to hold directories (dirnodes), which map
encrypted child names to rw-URI/ro-URI pairs.
This file shows only the differences from RSA-based mutable files to
(EC)DSA-based mutable files. You have to read and understand mutable.txt before
reading this file (mutable-DSA.txt).
=== SDMF slots overview ===
@ -380,166 +290,6 @@ which the public key can be hashed three times to produce the desired portion
of the storage index. We believe that 64 bits of material is sufficiently
resistant to this form of pre-image attack to serve as a suitable deterrent.
=== Server Storage Protocol ===
The storage servers will provide a mutable slot container which is oblivious
to the details of the data being contained inside it. Each storage index
refers to a "bucket", and each bucket has one or more shares inside it. (In a
well-provisioned network, each bucket will have only one share). The bucket
is stored as a directory, using the base32-encoded storage index as the
directory name. Each share is stored in a single file, using the share number
as the filename.
The container holds space for a container magic number (for versioning), the
write enabler, the nodeid which accepted the write enabler (used for share
migration, described below), a small number of lease structures, the embedded
data itself, and expansion space for additional lease structures.
# offset size name
1 0 32 magic verstr "tahoe mutable container v1" plus binary
2 32 20 write enabler's nodeid
3 52 32 write enabler
4 84 8 data size (actual share data present) (a)
5 92 8 offset of (8) count of extra leases (after data)
6 100 368 four leases, 92 bytes each
0 4 ownerid (0 means "no lease here")
4 4 expiration timestamp
8 32 renewal token
40 32 cancel token
72 20 nodeid which accepted the tokens
7 468 (a) data
8 ?? 4 count of extra leases
9 ?? n*92 extra leases
The "extra leases" field must be copied and rewritten each time the size of
the enclosed data changes. The hope is that most buckets will have four or
fewer leases and this extra copying will not usually be necessary.
The (4) "data size" field contains the actual number of bytes of data present
in field (7), such that a client request to read beyond 504+(a) will result
in an error. This allows the client to (one day) read relative to the end of
the file. The container size (that is, (8)-(7)) might be larger, especially
if extra size was pre-allocated in anticipation of filling the container with
a lot of data.
The offset in (5) points at the *count* of extra leases, at (8). The actual
leases (at (9)) begin 4 bytes later. If the container size changes, both (8)
and (9) must be relocated by copying.
The server will honor any write commands that provide the write token and do
not exceed the server-wide storage size limitations. Read and write commands
MUST be restricted to the 'data' portion of the container: the implementation
of those commands MUST perform correct bounds-checking to make sure other
portions of the container are inaccessible to the clients.
The two methods provided by the storage server on these "MutableSlot" share
objects are:
* readv(ListOf(offset=int, length=int))
* returns a list of bytestrings, of the various requested lengths
* offset < 0 is interpreted relative to the end of the data
* spans which hit the end of the data will return truncated data
* testv_and_writev(write_enabler, test_vector, write_vector)
* this is a test-and-set operation which performs the given tests and only
applies the desired writes if all tests succeed. This is used to detect
simultaneous writers, and to reduce the chance that an update will lose
data recently written by some other party (written after the last time
this slot was read).
* test_vector=ListOf(TupleOf(offset, length, opcode, specimen))
* the opcode is a string, from the set [gt, ge, eq, le, lt, ne]
* each element of the test vector is read from the slot's data and
compared against the specimen using the desired (in)equality. If all
tests evaluate True, the write is performed
* write_vector=ListOf(TupleOf(offset, newdata))
* offset < 0 is not yet defined, it probably means relative to the
end of the data, which probably means append, but we haven't nailed
it down quite yet
* write vectors are executed in order, which specifies the results of
overlapping writes
* return value:
* error: OutOfSpace
* error: something else (io error, out of memory, whatever)
* (True, old_test_data): the write was accepted (test_vector passed)
* (False, old_test_data): the write was rejected (test_vector failed)
* both 'accepted' and 'rejected' return the old data that was used
for the test_vector comparison. This can be used by the client
to detect write collisions, including collisions for which the
desired behavior was to overwrite the old version.
In addition, the storage server provides several methods to access these
share objects:
* allocate_mutable_slot(storage_index, sharenums=SetOf(int))
* returns DictOf(int, MutableSlot)
* get_mutable_slot(storage_index)
* returns DictOf(int, MutableSlot)
* or raises KeyError
We intend to add an interface which allows small slots to allocate-and-write
in a single call, as well as do update or read in a single call. The goal is
to allow a reasonably-sized dirnode to be created (or updated, or read) in
just one round trip (to all N shareholders in parallel).
==== migrating shares ====
If a share must be migrated from one server to another, two values become
invalid: the write enabler (since it was computed for the old server), and
the lease renew/cancel tokens.
Suppose that a slot was first created on nodeA, and was thus initialized with
WE(nodeA) (= H(WEM+nodeA)). Later, for provisioning reasons, the share is
moved from nodeA to nodeB.
Readers may still be able to find the share in its new home, depending upon
how many servers are present in the grid, where the new nodeid lands in the
permuted index for this particular storage index, and how many servers the
reading client is willing to contact.
When a client attempts to write to this migrated share, it will get a "bad
write enabler" error, since the WE it computes for nodeB will not match the
WE(nodeA) that was embedded in the share. When this occurs, the "bad write
enabler" message must include the old nodeid (e.g. nodeA) that was in the
share.
The client then computes H(nodeB+H(WEM+nodeA)), which is the same as
H(nodeB+WE(nodeA)). The client sends this along with the new WE(nodeB), which
is H(WEM+nodeB). Note that the client only sends WE(nodeB) to nodeB, never to
anyone else. Also note that the client does not send a value to nodeB that
would allow the node to impersonate the client to a third node: everything
sent to nodeB will include something specific to nodeB in it.
The server locally computes H(nodeB+WE(nodeA)), using its own node id and the
old write enabler from the share. It compares this against the value supplied
by the client. If they match, this serves as proof that the client was able
to compute the old write enabler. The server then accepts the client's new
WE(nodeB) and writes it into the container.
This WE-fixup process requires an extra round trip, and requires the error
message to include the old nodeid, but does not require any public key
operations on either client or server.
Migrating the leases will require a similar protocol. This protocol will be
defined concretely at a later date.
=== Code Details ===
The current FileNode class will be renamed ImmutableFileNode, and a new
MutableFileNode class will be created. Instances of this class will contain a
URI and a reference to the client (for peer selection and connection). The
methods of MutableFileNode are:
* replace(newdata) -> OK, ConsistencyError, NotEnoughSharesError
* get() -> [deferred] newdata, NotEnoughSharesError
* if there are multiple retrieveable versions in the grid, get() returns
the first version it can reconstruct, and silently ignores the others.
In the future, a more advanced API will signal and provide access to
the multiple heads.
The peer-selection and data-structure manipulation (and signing/verification)
steps will be implemented in a separate class in allmydata/mutable.py .
=== SMDF Slot Format ===
This SMDF data lives inside a server-side MutableSlot container. The server
@ -586,142 +336,8 @@ key sizes.
has tree (with root "R"), from which a minimal subset of hashes is put in
the share hash chain in (8).
=== Recovery ===
The first line of defense against damage caused by colliding writes is the
Prime Coordination Directive: "Don't Do That".
The second line of defense is to keep "S" (the number of competing versions)
lower than N/k. If this holds true, at least one competing version will have
k shares and thus be recoverable. Note that server unavailability counts
against us here: the old version stored on the unavailable server must be
included in the value of S.
The third line of defense is our use of testv_and_writev() (described below),
which increases the convergence of simultaneous writes: one of the writers
will be favored (the one with the highest "R"), and that version is more
likely to be accepted than the others. This defense is least effective in the
pathological situation where S simultaneous writers are active, the one with
the lowest "R" writes to N-k+1 of the shares and then dies, then the one with
the next-lowest "R" writes to N-2k+1 of the shares and dies, etc, until the
one with the highest "R" writes to k-1 shares and dies. Any other sequencing
will allow the highest "R" to write to at least k shares and establish a new
revision.
The fourth line of defense is the fact that each client keeps writing until
at least one version has N shares. This uses additional servers, if
necessary, to make sure that either the client's version or some
newer/overriding version is highly available.
The fifth line of defense is the recovery algorithm, which seeks to make sure
that at least *one* version is highly available, even if that version is
somebody else's.
The write-shares-to-peers algorithm is as follows:
* permute peers according to storage index
* walk through peers, trying to assign one share per peer
* for each peer:
* send testv_and_writev, using "old(seqnum+R) <= our(seqnum+R)" as the test
* this means that we will overwrite any old versions, and we will
overwrite simultaenous writers of the same version if our R is higher.
We will not overwrite writers using a higher seqnum.
* record the version that each share winds up with. If the write was
accepted, this is our own version. If it was rejected, read the
old_test_data to find out what version was retained.
* if old_test_data indicates the seqnum was equal or greater than our
own, mark the "Simultanous Writes Detected" flag, which will eventually
result in an error being reported to the writer (in their close() call).
* build a histogram of "R" values
* repeat until the histogram indicate that some version (possibly ours)
has N shares. Use new servers if necessary.
* If we run out of servers:
* if there are at least shares-of-happiness of any one version, we're
happy, so return. (the close() might still get an error)
* not happy, need to reinforce something, goto RECOVERY
RECOVERY:
* read all shares, count the versions, identify the recoverable ones,
discard the unrecoverable ones.
* sort versions: locate max(seqnums), put all versions with that seqnum
in the list, sort by number of outstanding shares. Then put our own
version. (TODO: put versions with seqnum <max but >us ahead of us?).
* for each version:
* attempt to recover that version
* if not possible, remove it from the list, go to next one
* if recovered, start at beginning of peer list, push that version,
continue until N shares are placed
* if pushing our own version, bump up the seqnum to one higher than
the max seqnum we saw
* if we run out of servers:
* schedule retry and exponential backoff to repeat RECOVERY
* admit defeat after some period? presumeably the client will be shut down
eventually, maybe keep trying (once per hour?) until then.
== Medium Distributed Mutable Files ==
These are just like the SDMF case, but:
* we actually take advantage of the Merkle hash tree over the blocks, by
reading a single segment of data at a time (and its necessary hashes), to
reduce the read-time alacrity
* we allow arbitrary writes to the file (i.e. seek() is provided, and
O_TRUNC is no longer required)
* we write more code on the client side (in the MutableFileNode class), to
first read each segment that a write must modify. This looks exactly like
the way a normal filesystem uses a block device, or how a CPU must perform
a cache-line fill before modifying a single word.
* we might implement some sort of copy-based atomic update server call,
to allow multiple writev() calls to appear atomic to any readers.
MDMF slots provide fairly efficient in-place edits of very large files (a few
GB). Appending data is also fairly efficient, although each time a power of 2
boundary is crossed, the entire file must effectively be re-uploaded (because
the size of the block hash tree changes), so if the filesize is known in
advance, that space ought to be pre-allocated (by leaving extra space between
the block hash tree and the actual data).
MDMF1 uses the Merkle tree to enable low-alacrity random-access reads. MDMF2
adds cache-line reads to allow random-access writes.
== Large Distributed Mutable Files ==
LDMF slots use a fundamentally different way to store the file, inspired by
Mercurial's "revlog" format. They enable very efficient insert/remove/replace
editing of arbitrary spans. Multiple versions of the file can be retained, in
a revision graph that can have multiple heads. Each revision can be
referenced by a cryptographic identifier. There are two forms of the URI, one
that means "most recent version", and a longer one that points to a specific
revision.
Metadata can be attached to the revisions, like timestamps, to enable rolling
back an entire tree to a specific point in history.
LDMF1 provides deltas but tries to avoid dealing with multiple heads. LDMF2
provides explicit support for revision identifiers and branching.
== TODO ==
improve allocate-and-write or get-writer-buckets API to allow one-call (or
maybe two-call) updates. The challenge is in figuring out which shares are on
which machines. First cut will have lots of round trips.
(eventually) define behavior when seqnum wraps. At the very least make sure
it can't cause a security problem. "the slot is worn out" is acceptable.
(eventually) define share-migration lease update protocol. Including the
nodeid who accepted the lease is useful, we can use the same protocol as we
do for updating the write enabler. However we need to know which lease to
update.. maybe send back a list of all old nodeids that we find, then try all
of them when we accept the update?
We now do this in a specially-formatted IndexError exception:
"UNABLE to renew non-existent lease. I have leases accepted by " +
"nodeids: '12345','abcde','44221' ."
Every node in a given tahoe grid must have the same common DSA moduli and
exponent, but different grids could use different parameters. We haven't
figured out how to define a "grid id" yet, but I think the DSA parameters