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On import, Titan gets GC loops. Checking
Smalyshev added a comment.
@GWicke, it looks like it, the loader script reports processing 51K rows, which
means 51K vertices inserted/updated, so 48K is pretty close to that number (not
sure why they are not equal though). The script now commits every 1000 rows,
but I'm not sure how Titan
Smalyshev added a comment.
@manybubbles I can give you the heap dumps (or attach it here if huge files are
ok here) if it helps. Also, the code I'm using is here:
https://github.com/smalyshev/wikidata-gremlin/tree/titan
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Smalyshev added a comment.
Oh, another missing piece - the data is loaded now by somethine like:
dataLoader.gzipFile(/Users/smalyshev/Downloads/xaax.gz).load(100)
So DataLoader is the starting point. Sorry, it's work in progress, a bit messy
now :)
@aude will definitely check it out
Smalyshev added a comment.
Yes, the docs say:
https://thinkaurelius.github.io/titan/javadoc/current/com/thinkaurelius/titan/core/TitanGraph.html#getManagementSystem()
TitanManagement getManagementSystem()
Returns the management system for this graph instance. The management system
provides
Smalyshev closed blocking task T76509: Figure out why Titan gets OOM when
importing data as Resolved.
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Smalyshev added a comment.
OK, setting `thrift_framed_transport_size_in_mb` in `cassandra.yaml` in both
Cassandra and Titan (they both have the yaml file) to 256 seems to eliminate
the Frame size error, now `g.wd('Q5').in('P31').labelEn[0]` words and produces
'Douglas Adams' as it should
Smalyshev added a comment.
@janzerebecki The issue here is that many items do not have preferred state.
I.e. take https://www.wikidata.org/wiki/Q30.
What is the population of the USA? We don't have any number marked as
preferred. We either have to report we have no idea about US population
Smalyshev added a comment.
So we have chicken-and-egg problem here. Should we code for data that is ranked
properly (but does not exist yet) and hope the data will catch up, and the
querying will be complicated until then, or should we code for current data to
make querying the current data
Smalyshev added a comment.
OK, this can be done but the issue here is we can't evaluate a solution (e.g.
for performance, fitness to data, etc.) such as Titan/Gremlin if we have no
data to test it on. Meaning, assume we coded up all the queries under
assumption the data is ranked properly
Smalyshev added a comment.
Here is my initial proposal about the data model:
https://www.mediawiki.org/wiki/Wikibase/Indexing/Data_Model
Please comment.
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I also put some more comments to the discussion page
https://www.mediawiki.org/wiki/Talk:Wikibase/Indexing/Data_Model - I think it
makes sense to discuss/clarify things there, but if anybody thinks there's a
better place please tell.
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https://www.mediawiki.org/wiki/Wikibase/Indexing has been updated according to
the comments. Main change - claims are now vertices.
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Doing the import with the new model I see that the import is significantly
slower when claims have their own vertices. Not sure if it's a big deal or not.
If it's an issue we may want to reconsider going back to claims as edges
model.
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Smalyshev added a comment.
Maybe worth checking out this:
http://www.tinkerpop.com/docs/3.0.0.M6/#vertex-properties
Titan 0.9 has TinkerPop 3, which has significantly expanded property model - in
particular, the property can have multiple other properties attached to it, and
itself can have
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I
Smalyshev added a comment.
Probably will have to switch to use content hashes as identifier for change.
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Smalyshev added a comment.
We'll use content hash instead of claim ID to detect changes. We'll also use
lastrevid on the item to track revisions.
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Smalyshev closed blocking task T85045: Figure out how to detect that claim is
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Smalyshev added a comment.
Are we considering supporting WDQ API mini-language as the option for the
queries or it's not a viable option?
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For SET it won't be more complex to maintain, probably, but I'm not sure if the
lookups would be fast enough. I could create an additional field for that and
see how it behaves, and then we could drop the field that is not needed.
For Date, I wonder if support can't
Smalyshev added a comment.
@janZerebecki Gremlin is basically shell access, since it can run arbitrary
Java code. So we can have it for internal purposes, but we need frontend API
since we probably won't be comfortable with giving everybody shell access, and
sanitizing Gremlin probably would
Smalyshev added a comment.
Elasticsearch totally supports sets.
Right, but Titan unfortunately doesn't support mixed indexes on SET properties.
I would assume it's not a hard limitation but rather them not getting to
implementing it yet. The mixed index type support is very limited now
http
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Agreed, format like JSON would be much better since everybody knows how to
handle it.
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Proposed storage format for dates:
1. Dates are stored as long signed integers, representing number of seconds
since 1970-01-01 00:00:00 UTC.
2. This gives us range of 292 bln years
http://www.wolframalpha.com/input/?i=9223372036854775807+seconds+in+years.
3. When
Smalyshev added a comment.
@GWicke Do we really need per-second precision transitioning between year 292M
and 292M+1? I'm not sure it is ever required. We should ensure, of course, that
seconds(292M-12-31T23:59:59) seconds(292M+1) and also the same for low dates,
but beyond that I'm not sure
Smalyshev added a comment.
For dates beyond real Gregorian calendar, the values more precise than years
have little meaning anyway, so I don't think it matters too much as long as
comparisons and lookups (i.e. which Greek philosopher was born in 427 BCE) work.
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I've noticed there are bad dates for some items in Wikidata - e.g.
https://www.wikidata.org/wiki/Q5906
and https://www.wikidata.org/wiki
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Right now we represent
Smalyshev added a comment.
From WDQ source
https://bitbucket.org/magnusmanske/wikidataquery/src/f1667a81c3c693606c519587d6588c7bde8af455/wd_inmem.cpp?at=master#cl-103,
WDQ treats it as double. So maybe Double precision is enough?
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Smalyshev added a comment.
I think I'll decide to represent them as Double for now. If anybody objects, we
can reopen and change it.
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Turns out there is a complication - Titan can not use floats (including double)
in Vertex indices:
http://s3.thinkaurelius.com/docs/titan/0.5.2/common-questions.html#_floating_point_numbers_in_vertex_centric_indices
Need
Smalyshev reopened blocking task T85298: Figure out quantity representation as
Open.
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Right now
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See also description in:
https://groups.google.com/forum/#!topic/aureliusgraphs/Ktq1B1AGEb0
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Smalyshev added a comment.
Titan allows indexing the floats, but not in vertex-centric indexes.
Elasticsearch indexes support floats, for example. I'm not sure what is the
actual impact of this limitation yet - it probably depends on the kind of
lookups we would do, as for some vertix-centered
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https://www.youtube.com/watch?v=vodd6C5ryUU
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@JanZerebecki is master/slave not enough for us? The only write scenario is
updates, and these can be done on master, all queries are read-only and as such
can be run on slaves.
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Smalyshev added a comment.
Preliminary notes:
- Graph is a set of vertex collections and edge collections, both document
collection with some special attributes.
- ArangoDB keeps indexes only in memory and rebuilds them on collection load.
Which takes about 1 hour for the dump of 3M objects
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Smalyshev added a comment.
Here is the list of all TinkerPop implementations (not TP3, but may be helpful
as a starting point): https://github.com/tinkerpop/blueprints/wiki
On OrientDB there are a number of questions about TP3 but no answers so far
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Also we probably need to get to implementing value ranges/precision eventually.
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@manybubbles Do you have a backtrace per chance? That'd help.
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Moving to nodes didn't work either - when defining indexes for every property,
it creates over 20K lucene files and tries to open all of them and gets out of
filehandles, even though I've put a high limit on file descriptors (10)
somehow it's not enough. Looks
Smalyshev added a comment.
Main problem with Neo4j so far is indexing - edge indexes are either manual
addition (http://neo4j.com/docs/2.2.0-M03/indexing-add.html) or auto-indexing
(http://neo4j.com/docs/2.2.0-M03/auto-indexing.html) which requires
pre-defining all properties in configuration
Smalyshev added a comment.
@Neunhoef In current data model, each edge carries a primary value, a boolean
flag and a small set (usually well under 10, in most cases 1-3 or none)
secondary values, each of which need to be indexed. It also can keep a set of
auxiliary values for each of those
Smalyshev added a comment.
In https://phabricator.wikimedia.org/T88549#1022562, @Fceller wrote:
Still, I must admit that I'm not familiar with the internal data model of
Wikipedia. I've checked with George Washington (Q23) that he as a lot of
properties associated with him. However, I fail
Smalyshev added a comment.
@Fceller for the test, I used two of the attributes that are present in each
document for hash indexes, and two that may or may not be present, for skiplist
ones. In typical situation, most of the indexable attributes would not be
present, but some will be always
Smalyshev added a comment.
@Fceller many thanks to you for your explanations!
I certainly understand the reasons for your choices, however I'm still not sure
how given our data sizes - ~16M vertices, ~100M edges, 2-3 thousands indexed
fields - can be supported in current ArangoDB model. Maybe
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Apache is good for me.
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References implementation:
https://www.mediawiki.org/w/index.php?title=Wikibase/Indexing/Data_Model#Representing_references
Not 100% happy with it but the best I could come up with so far.
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TASK DESCRIPTION
Analyze indexes that exist for the query engine
(https://www.mediawiki.org
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@Beebs.systap this looks pretty good. How it is done - i.e. what is used to
create the triples, how they are imported, etc. - is this code available?
Also, I assume we'd want eventually to support qualifiers/references, i.e.
queries like countries list by population
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openjdk-8-jdk seems to be running ok on einsteinium but not sure if we actually
need it or not.
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So, what should the dump look like? Nothing is a wikibase:Item, something else
is a wikibase:Item ? If we think that entity:Q23 is the thing, should we have
`entity:Q23 a entity:Q5`? Should we drop `data:Q23 a schema:Dataset`?
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Smalyshev added a comment.
Closing as not relevant after the Titan's demise.
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Smalyshev added a comment.
Currently, we have two known issues with our RDF vs. BlazeGraph:
1. Date values (aka 13 billion BCE)
2. Geopoints notation
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Smalyshev added a comment.
We currently do not index descriptions, because they are big and are searchable
by other means, but we could store the fact that certain item has description
in certain language pretty cheaply. For labels, we store them so it's easy to
check which items do not have
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Currently, unknown/novalue nodes have no labels. This leads to various errors
in queries which
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Since many objects do not have labels in specific language (such as English),
displaying arbitrary
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Smalyshev added a comment.
**This changes the structure, and the original structure is no longer
represented and can no longer be faithfully recovered.**
This is not correct, original structure can be recovered, though I see no
reason why would you want to do so. Can you name one?
**a mere 40
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