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/
> >
> >
>
