> I’m relatively happy with the revision history data model at this point.
I forgot to make a note, but which of the various models are you
referring to by "revision history data model". There's been so many
without firm names that my brain is having a hard time parsing that
one.
On Thu, Feb 7, 2019 at 9:35 PM Adam Kocoloski <kocol...@apache.org> wrote:
>
> Bob, Garren, Jan - heard you loud and clear, K.I.S.S. I do think it’s a bit
> “simplistic" to exclusively choose simplicity over performance and storage
> density. We’re (re)building a database here, one that has some users with
> pretty demanding performance and scalability requirements. And yes, we should
> certainly be testing and measuring. Kyle and team are setting up
> infrastructure in IBM land to help with that now, but I also believe we can
> design the data model and architecture with a basic performance model of
> FoundationDB in mind:
>
> - reads cost 1ms
> - short range reads are the same cost as a single lookup
> - reads of independent parts of the keyspace can be parallelized for cheap
> - writes are zero-cost until commit time
>
> We ought to be able to use these assumptions to drive some decisions about
> data models ahead of any end-to-end performance test.
>
> If there are specific elements of the edit conflicts management where you
> think greater simplicity is warranted, let’s get those called out. Ilya noted
> (correctly, in my opinion) that the term sharing stuff is one of those items.
> It’s relatively complex, potentially a performance hit, and only saves on
> storage density in the corner case of lots of edit conflicts. That’s a good
> one to drop.
>
> I’m relatively happy with the revision history data model at this point.
> Hopefully folks find it easy to grok, and it’s efficient for both reads and
> writes. It costs some extra storage for conflict revisions compared to the
> current tree representation (up to 16K per edit branch, with default
> _revs_limit) but knowing what we know about the performance death spiral for
> wide revision trees today I’ll happily make a storage vs. performance
> tradeoff here :)
>
> Setting the shared term approach aside, I’ve still been mulling over the key
> structure for the actual document data:
>
> - I thought about trying to construct a special _conflicts subspace, but I
> don’t like that approach because the choice of a “winning" revision can flip
> back and forth very quickly with concurrent writers to different edit
> branches. I think we really want to have a way for revisions to naturally
> sort themselves so the winner is the first or last revision in a list.
>
> - Assuming we’re using key paths of the form (docid, revision-ish, path, to,
> field), the goal here is to find an efficient way to get the last key with
> prefix “docid” (assuming winner sorts last), and then all the keys that share
> the same (docid, revision-ish) prefix as that one. I see two possible
> approaches so far, neither perfect:
>
> Option 1: Execute a get_key() operation with a key selector that asks for the
> last key less than “docid\xFF” (again assuming winner sorts last), and then
> do a get_range_startswith() request setting the streaming mode to “want_all”
> and the prefix to the docid plus whatever revision-ish we found from the
> get_key() request. This is two roundtrips instead of one, but it always
> retrieves exactly the right set of keys, and the second step is executed as
> fast as possible.
>
> Option 2: Jump straight to get_range_startswith() request using only “docid”
> as the prefix, then cancel the iteration once we reach a revision not equal
> to the first one we see. We might transfer too much data, or we might end up
> doing multiple roundtrips if the default “iterator” streaming mode sends too
> little data to start (I haven’t checked what the default iteration block is
> there), but in the typical case of zero edit conflicts we have a good chance
> of retrieving the full document in one roundtrip.
>
> I don’t have a good sense of which option wins out here from a performance
> perspective, but they’re both operating on the same data model so easy enough
> to test the alternatives. The important bit is getting the revision-ish
> things to sort correctly. I think we can do that by generating something like
>
> revision-ish = NotDeleted/1bit : RevPos : RevHash
>
> with some suitable order-preserving encoding on the RevPos integer.
>
> Apologies for the long email. Happy for any comments, either here or over on
> IRC. Cheers,
>
> Adam
>
> > On Feb 7, 2019, at 4:52 PM, Robert Newson <rnew...@apache.org> wrote:
> >
> > I think we should choose simple. We can then see if performance is too low
> > or storage overhead too high and then see what we can do about it.
> >
> > B.
> >
> > --
> > Robert Samuel Newson
> > rnew...@apache.org
> >
> > On Thu, 7 Feb 2019, at 20:36, Ilya Khlopotov wrote:
> >> We cannot do simple thing if we want to support sharing of JSON terms. I
> >> think if we want the simplest path we should move sharing out of the
> >> scope. The problem with sharing is we need to know the location of
> >> shared terms when we do write. This means that we have to read full
> >> document on every write. There might be tricks to replace full document
> >> read with some sort of hierarchical signature or sketch of a document.
> >> However these tricks do not fall into simplest solution category. We
> >> need to choose the design goals:
> >> - simple
> >> - performance
> >> - reduced storage overhead
> >>
> >> best regards,
> >> iilyak
> >>
> >> On 2019/02/07 12:45:34, Garren Smith <gar...@apache.org> wrote:
> >>> I’m also in favor of keeping it really simple and then testing and
> >>> measuring it.
> >>>
> >>> What is the best way to measure that we have something that works? I’m not
> >>> sure just relying on our current tests will prove that? Should we define
> >>> and build some more complex situations e.g docs with lots of conflicts or
> >>> docs with wide revisions and make sure we can solve for those?
> >>>
> >>> On Thu, Feb 7, 2019 at 12:33 PM Jan Lehnardt <j...@apache.org> wrote:
> >>>
> >>>> I’m also very much in favour with starting with the simplest thing that
> >>>> can possibly work and doesn’t go against the advertised best practices of
> >>>> FoundationDB. Let’s get that going and get a feel for how it all works
> >>>> together, before trying to optimise things we can’t measure yet.
> >>>>
> >>>> Best
> >>>> Jan
> >>>> —
> >>>>
> >>>>> On 6. Feb 2019, at 16:58, Robert Samuel Newson <rnew...@apache.org>
> >>>> wrote:
> >>>>>
> >>>>> Hi,
> >>>>>
> >>>>> With the Redwood storage engine under development and with prefix
> >>>> elision part of its design, I don’t think we should get too hung up on
> >>>> adding complications and indirections in the key space just yet. We
> >>>> haven’t
> >>>> written a line of code or run any tests, this is premature optimisation.
> >>>>>
> >>>>> I’d like to focus on the simplest solution that yields all required
> >>>> properties. We can embellish later (if warranted).
> >>>>>
> >>>>> I am intrigued by all the ideas that might allow us cheaper inserts and
> >>>> updates than the current code where there are multiple edit branches in
> >>>> the
> >>>> stored document.
> >>>>>
> >>>>> B.
> >>>>>
> >>>>>> On 6 Feb 2019, at 02:18, Ilya Khlopotov <iil...@apache.org> wrote:
> >>>>>>
> >>>>>> While reading Adam's proposal I came to realize that: we don't have to
> >>>> calculate winning revision at read time.
> >>>>>> Since FDB's transactions are atomic we can calculate it when we write.
> >>>> This means we can just write latest values into separate range. This
> >>>> makes
> >>>> lookup of latest version fast.
> >>>>>> Another realization is if we want to share values for some json paths
> >>>> we would have to introduce a level of indirection.
> >>>>>> Bellow is the data model inspired by Adam's idea to share json_paths.
> >>>> In this model the json_path is stored in the revision where it was first
> >>>> added (we call that revision an owner of a json_path). The values for
> >>>> json_path key can be scalar values, parts of scalar values or pointers to
> >>>> owner location.
> >>>>>> The below snippets are sketches of transactions.
> >>>>>> The transactions will include updates to other keys as needed
> >>>> (`external_size`, `by_seq` and so on). The revision tree management is
> >>>> not
> >>>> covered yet.
> >>>>>> The `rev -> vsn` indirection is not strictly required. It is added
> >>>> because it saves some space since `rev` is a long string and `vsn` is FDB
> >>>> versionstamp of fixed size.
> >>>>>>
> >>>>>> - `{NS} / {docid} / _by_rev / {rev} = vsn`
> >>>>>> - `{NS} / {docid} / _used_by / {json_path} / {another_vsn} = NIL`
> >>>>>> - `{NS} / {docid} / _data / {json_path} = latest_value | part`
> >>>>>> - `{NS} / {docid} / {vsn} / _data / {json_path} = value | part |
> >>>> {another_vsn}`
> >>>>>>
> >>>>>> ```
> >>>>>> write(txn, doc_id, prev_rev, json):
> >>>>>> txn.add_write_conflict_key("{NS} / {doc_id} / _rev")
> >>>>>> rev = generate_new_rev()
> >>>>>> txn["{NS} / {docid} / _by_rev / {rev}"] = vsn
> >>>>>> for every json_path in flattened json
> >>>>>> - {NS} / {docid} / _used_by / {json_path} / {another_vsn} = NIL
> >>>>>> if rev is HEAD:
> >>>>>> # this range contains values for all json paths for the latest
> >>>> revision (read optimization)
> >>>>>> - {NS} / {docid} / _data / {json_path} = latest_value | part
> >>>>>> - {NS} / {docid} / {vsn} / _data / {json_path} = value | part |
> >>>> {another_vsn}
> >>>>>> txn["{NS} / {doc_id} / _rev"] = rev
> >>>>>>
> >>>>>> get_current(txn, doc_id):
> >>>>>> # there is no sharing of json_paths in this range (read optimization)
> >>>>>> txn.get_range("{NS} / {docid} / _data / 0x00", "{NS} / {docid} / _data
> >>>> / 0xFF" )
> >>>>>>
> >>>>>> get_revision(txn, doc_id, rev):
> >>>>>> vsn = txn["{NS} / {docid} / _by_rev / {rev}"]
> >>>>>> json_paths = txn.get_range("{NS} / {vsn} / {docid} / _data / 0x00",
> >>>> "{NS} / {vsn} / {docid} / _data / 0xFF" )
> >>>>>> for every json_path in json_paths:
> >>>>>> if value has type vsn:
> >>>>>> another_vsn = value
> >>>>>> value = txn["{NS} / {docid} / {another_vsn} / _data /
> >>>> {json_path}"]
> >>>>>> result[json_path] = value
> >>>>>>
> >>>>>> delete_revision(txn, doc_id, rev):
> >>>>>> vsn = txn["{NS} / {docid} / _by_rev / {rev}"]
> >>>>>> json_paths = txn.get_range("{NS} / {vsn} / {docid} / _data / 0x00",
> >>>> "{NS} / {vsn} / {docid} / _data / 0xFF" )
> >>>>>> for every json_path in json_paths:
> >>>>>> if value has type vsn:
> >>>>>> # remove reference to deleted revision from the owner
> >>>>>> del txn[{NS} / {docid} / _used_by / {json_path} / {vsn}]
> >>>>>> # check if deleted revision of json_path is not used by anything else
> >>>>>> if txn.get_range("{NS} / {docid} / _used_by / {json_path} / {vsn}",
> >>>> limit=1) == []:
> >>>>>> del txn["{NS} / {docid} / {vsn} / _data / {json_path}"]
> >>>>>> if vsn is HEAD:
> >>>>>> copy range for winning revision into "{NS} / {docid} / _data /
> >>>> {json_path}"
> >>>>>> ```
> >>>>>>
> >>>>>> best regards,
> >>>>>> iilyak
> >>>>>>
> >>>>>> On 2019/02/04 23:22:09, Adam Kocoloski <kocol...@apache.org> wrote:
> >>>>>>> I think it’s fine to start a focused discussion here as it might help
> >>>> inform some of the broader debate over in that thread.
> >>>>>>>
> >>>>>>> As a reminder, today CouchDB writes the entire body of each document
> >>>> revision on disk as a separate blob. Edit conflicts that have common
> >>>> fields
> >>>> between them do not share any storage on disk. The revision tree is
> >>>> encoded
> >>>> into a compact format and a copy of it is stored directly in both the
> >>>> by_id
> >>>> tree and the by_seq tree. Each leaf entry in the revision tree contain a
> >>>> pointer to the position of the associated doc revision on disk.
> >>>>>>>
> >>>>>>> As a further reminder, CouchDB 2.x clusters can generate edit conflict
> >>>> revisions just from multiple clients concurrently updating the same
> >>>> document in a single cluster. This won’t happen when FoundationDB is
> >>>> running under the hood, but users who deploy multiple CouchDB or PouchDB
> >>>> servers and replicate between them can of course still produce conflicts
> >>>> just like they could in CouchDB 1.x, so we need a solution.
> >>>>>>>
> >>>>>>> Let’s consider the two sub-topics separately: 1) storage of edit
> >>>> conflict bodies and 2) revision trees
> >>>>>>>
> >>>>>>> ## Edit Conflict Storage
> >>>>>>>
> >>>>>>> The simplest possible solution would be to store each document
> >>>> revision separately, like we do today. We could store document bodies
> >>>> with
> >>>> (“docid”, “revid”) as the key prefix, and each transaction could clear
> >>>> the
> >>>> key range associated with the base revision against which the edit is
> >>>> being
> >>>> attempted. This would work, but I think we can try to be a bit more
> >>>> clever
> >>>> and save on storage space given that we’re splitting JSON documents into
> >>>> multiple KV pairs.
> >>>>>>>
> >>>>>>> One thought I’d had is to introduce a special enum Value which
> >>>> indicates that the subtree “beneath” the given Key is in conflict. For
> >>>> example, consider the documents
> >>>>>>>
> >>>>>>> {
> >>>>>>> “_id”: “foo”,
> >>>>>>> “_rev”: “1-abc”,
> >>>>>>> “owner”: “alice”,
> >>>>>>> “active”: true
> >>>>>>> }
> >>>>>>>
> >>>>>>> and
> >>>>>>>
> >>>>>>> {
> >>>>>>> “_id”: “foo”,
> >>>>>>> “_rev”: “1-def”,
> >>>>>>> “owner”: “bob”,
> >>>>>>> “active”: true
> >>>>>>> }
> >>>>>>>
> >>>>>>> We could represent these using the following set of KVs:
> >>>>>>>
> >>>>>>> (“foo”, “active”) = true
> >>>>>>> (“foo”, “owner”) = kCONFLICT
> >>>>>>> (“foo”, “owner”, “1-abc”) = “alice”
> >>>>>>> (“foo”, “owner”, “1-def”) = “bob”
> >>>>>>>
> >>>>>>> This approach also extends to conflicts where the two versions have
> >>>> different data types. Consider a more complicated example where bob
> >>>> dropped
> >>>> the “active” field and changed the “owner” field to an object:
> >>>>>>>
> >>>>>>> {
> >>>>>>> “_id”: “foo”,
> >>>>>>> “_rev”: “1-def”,
> >>>>>>> “owner”: {
> >>>>>>> “name”: “bob”,
> >>>>>>> “email”: “b...@example.com"
> >>>>>>> }
> >>>>>>> }
> >>>>>>>
> >>>>>>> Now the set of KVs for “foo” looks like this (note that a missing
> >>>> field needs to be handled explicitly):
> >>>>>>>
> >>>>>>> (“foo”, “active”) = kCONFLICT
> >>>>>>> (“foo”, “active”, “1-abc”) = true
> >>>>>>> (“foo”, “active”, “1-def”) = kMISSING
> >>>>>>> (“foo”, “owner”) = kCONFLICT
> >>>>>>> (“foo”, “owner”, “1-abc”) = “alice”
> >>>>>>> (“foo”, “owner”, “1-def”, “name”) = “bob”
> >>>>>>> (“foo”, “owner”, “1-def”, “email”) = “b...@example.com”
> >>>>>>>
> >>>>>>> I like this approach for the common case where documents share most of
> >>>> their data in common but have a conflict in a very specific field or set
> >>>> of
> >>>> fields.
> >>>>>>>
> >>>>>>> I’ve encountered one important downside, though: an edit that
> >>>> replicates in and conflicts with the entire document can cause a bit of a
> >>>> data explosion. Consider a case where I have 10 conflicting versions of a
> >>>> 100KB document, but the conflicts are all related to a single scalar
> >>>> value.
> >>>> Now I replicate in an empty document, and suddenly I have a kCONFLICT at
> >>>> the root. In this model I now need to list out every path of every one of
> >>>> the 10 existing revisions and I end up with a 1MB update. Yuck. That’s
> >>>> technically no worse in the end state than the “zero sharing” case above,
> >>>> but one could easily imagine overrunning the transaction size limit this
> >>>> way.
> >>>>>>>
> >>>>>>> I suspect there’s a smart path out of this. Maybe the system detects a
> >>>> “default” value for each field and uses that instead of writing out the
> >>>> value for every revision in a conflicted subtree. Worth some discussion.
> >>>>>>>
> >>>>>>> ## Revision Trees
> >>>>>>>
> >>>>>>> In CouchDB we currently represent revisions as a hash history tree;
> >>>> each revision identifier is derived from the content of the revision
> >>>> including the revision identifier of its parent. Individual edit branches
> >>>> are bounded in *length* (I believe the default is 1000 entries), but the
> >>>> number of edit branches is technically unbounded.
> >>>>>>>
> >>>>>>> The size limits in FoundationDB preclude us from storing the entire
> >>>> key tree as a single value; in pathological situations the tree could
> >>>> exceed 100KB. Rather, I think it would make sense to store each edit
> >>>> *branch* as a separate KV. We stem the branch long before it hits the
> >>>> value
> >>>> size limit, and in the happy case of no edit conflicts this means we
> >>>> store
> >>>> the edit history metadata in a single KV. It also means that we can apply
> >>>> an interactive edit without retrieving the entire conflicted revision
> >>>> tree;
> >>>> we need only retrieve and modify the single branch against which the edit
> >>>> is being applied. The downside is that we duplicate historical revision
> >>>> identifiers shared by multiple edit branches, but I think this is a
> >>>> worthwhile tradeoff.
> >>>>>>>
> >>>>>>> I would furthermore try to structure the keys so that it is possible
> >>>> to retrieve the “winning” revision in a single limit=1 range query.
> >>>> Ideally
> >>>> I’d like to proide the following properties:
> >>>>>>>
> >>>>>>> 1) a document read does not need to retrieve the revision tree at all,
> >>>> just the winning revision identifier (which would be stored with the rest
> >>>> of the doc)
> >>>>>>> 2) a document update only needs to read the edit branch of the
> >>>> revision tree against which the update is being applied, and it can read
> >>>> that branch immediately knowing only the content of the edit that is
> >>>> being
> >>>> attempted (i.e., it does not need to read the current version of the
> >>>> document itself).
> >>>>>>>
> >>>>>>> So, I’d propose a separate subspace (maybe “_meta”?) for the revision
> >>>> trees, with keys and values that look like
> >>>>>>>
> >>>>>>> (“_meta”, DocID, IsDeleted, RevPosition, RevHash) = [ParentRev,
> >>>> GrandparentRev, …]
> >>>>>>>
> >>>>>>> The inclusion of IsDeleted, RevPosition and RevHash in the key should
> >>>> be sufficient (with the right encoding) to create a range query that
> >>>> automatically selects the “winner” according to CouchDB’s arcane rules,
> >>>> which are something like
> >>>>>>>
> >>>>>>> 1) deleted=false beats deleted=true
> >>>>>>> 2) longer paths (i.e. higher RevPosition) beat shorter ones
> >>>>>>> 3) RevHashes with larger binary values beat ones with smaller values
> >>>>>>>
> >>>>>>> ===========
> >>>>>>>
> >>>>>>> OK, that’s all on this topic from me for now. I think this is a
> >>>> particularly exciting area where we start to see the dividends of
> >>>> splitting
> >>>> up data into multiple KV pairs in FoundationDB :) Cheers,
> >>>>>>>
> >>>>>>> Adam
> >>>>>>>
> >>>>>>>
> >>>>>>>> On Feb 4, 2019, at 2:41 PM, Robert Newson <rnew...@apache.org> wrote:
> >>>>>>>>
> >>>>>>>> This one is quite tightly coupled to the other thread on data model,
> >>>> should we start much conversation here before that one gets closer to a
> >>>> solution?
> >>>>>>>>
> >>>>>>>> --
> >>>>>>>> Robert Samuel Newson
> >>>>>>>> rnew...@apache.org
> >>>>>>>>
> >>>>>>>> On Mon, 4 Feb 2019, at 19:25, Ilya Khlopotov wrote:
> >>>>>>>>> This is a beginning of a discussion thread about storage of edit
> >>>>>>>>> conflicts and everything which relates to revisions.
> >>>>>>>>>
> >>>>>>>>>
> >>>>>>>
> >>>>>>>
> >>>>>
> >>>>
> >>>> --
> >>>> Professional Support for Apache CouchDB:
> >>>> https://neighbourhood.ie/couchdb-support/
> >>>>
> >>>>
> >>>
>
