This is a "big" question, that I don't know how to start, so I hope some of you can give me a direction. And if this is not a "good" question, I will close the thread with an apology.
I wish to go through the database of Wikipedia (let's say the English one), and do statistics. For example, I am interested in how many active editors (which should be defined) Wikipedia had at each point of time (let's say in the last 2 years).
I don't know how to build such a database, how to access it, how to know which types of data it has and so on. So my questions are:
What tools do I need for this (besides basic R) ? MySQL on my computer? RODBC database connection?
How do you start planning for such a project?
You'll want to start here:
http://en.wikipedia.org/wiki/Wikipedia:Database_download
Which will take you to here:
http://download.wikimedia.org/enwiki/20100312/
And the file you probably want is:
# 2010-03-17 04:33:50 done Log events to all pages.
* This contains the log of actions performed on pages.
* pages-logging.xml.gz 1.0 GB
http://download.wikimedia.org/enwiki/20100312/enwiki-20100312-pages-logging.xml.gz
You'll then import the xml into MySQL. Generating a histogram of users per day, week, year, etc. won't require R. You'll be able to do that with a single MySQL query. Something like:
select DAYOFYEAR(wiki_edit_timestamp), count(*)
from page_logs
group by DAYOFYEAR(wiki_edit_timestamp)
order by DAYOFYEAR(wiki_edit_timestamp);
etc.
(I'm not sure what their actual schema is, but it'll be something like that.)
You'll run into issues, no doubt, but you'll learn a lot too. Good luck!
You could
work with the wikipedia database dumps, as already mentioned
work with the live mediawiki API, see this minimal example at Rosettacode or my unfinished approach with a S3 class or this package by Peter Konings
work with dbpedia, an effort to extract knowledge from wikipedia into a knowledge base. They offer an online sparql access I don't know much about, and also datasets as n-triples for download. See this python script which might be a starting point for an R script. This approach might be useful to access the content stored in the wikipedia (such as the infoboxes) but I am not sure if information on contributors to the wikipedia is available.
Try WikiXRay (Python/R) and zotero.
Related
We can use the functions from Wikipedia API to getting some results from Wikipedia.
For example:
**import Wikipedia
print(Wikipedia.search("Bill", results=2)).**
My question, how can I use Wikipedia API functions for a specific version of Wikipedia (e.g. just Wikipedia 2017)?!!
I doubt that this is possible. PyWikibot is using the online API of MediaWiki (in this case for the site Wikipedia). This one is always the live data.
The dumps, which you mention, are offline snapshots of the data of Wikipedia (assuming you're talking about https://dumps.wikimedia.org/). This data is not connected to the MediaWiki API in any way and can therefore not being queried with it.
What you can do to go through the data of Wikipedia in a specific time:
If it's a limited number of pages only: You could write a script which goes through the available revisions of the page and selects the one, that is closest to the time you want. That's probably error prone, a lot of work and does not really scale
Download the dump you want to query on and write a script which can work on the files (e.g. the database dump or the static html dump depending on what you want to do, that's not really clear from your question)
On the dump file with specific version, we can not use Wikipedia API. We just can read the dump file by our code and make what we need on this file.
(postgre/my)sql/php/html/css/javascript vs xml/xsl/xsd/php/css/javascript
Trying to decide whether to go with an xml-document-based app or with SQl. Each xml document would be about 30k; say 2000 files. Essentially a choice between serving up html/javascript, or serving a 30k xml file (plus xsl/xsd/javascript). Involves some financial (ie non-floating.point) math, plus substantial data entry one day per week.
SQL-solution would invove fragmenting/reassembling data using, say, ten separate cross-referenced tables, and tie users into SQL access control systems.
Assuming xml-based solution really is more straightforward to install/maintain, and using money=cents-as-integers is okay, and "other things are equal", my questions are:
1) Is it really a good plan to have the server read/update/save a 30k xml files, say 2000 times over 8 hours once a week, every time data is updated? Or is that just a trivial load?
(so that depends what else the server is doing I guess, and how fast the internet connection is)
2) How would that scale compared to an SQL-based solution? What would be the limiting factor?
3) Most importantly: what am I overlooking?
1) Not a good plan. Even if the load is not a problem you are basically building yourself a database when the problem is a solved one.
2) SQL is going to scale better base don what you've told.
3) NoSQL or XML based DB solutions like BaseX.
You want to look at your solution architecture... Where are the XML files coming from and how do you get hold of them. You also need to look at the navigation you are looking for. How do users navigate to one specific XML file - these navigational data need to be available. So to answer your question:
It is not a plan at all :-) - is is a tiny fragment of your solution, the load doesn't look big. You need to have a look at your meta data.
It might not be an OR question. All SQL systems know XML column data types today: PrgressQL, MS-SQL, Oracle, IBM DB/2 (including the free community edition). I like DB/2 (probably because I work for IBM :-) )
CouchDB, MongoDB -> JSON stores, XML databases as Karl suggested. Most important: caching, caching, caching! If you build in Java, use the guava libraries for a cache - once a file is transformed to the stuff you send down to the browser (using XSLT), cache that with generous expiry and have your load routine invalidate the cache
Hope that helps!
I was searching the net for something like a wiki database, just like wikipedia but instead stores structured content, editable by users. What I was looking for was an online database accessible by everyone where people can design the schema and data with proper versioning of both schema and data. I couldn't find any such site. I am not sure if it is my search skills or if there really is no wiki database as of now. Does anyone out there know anything like this?
I think there is a great potential for something like this. A possible example will be a website with a GUI for querying a MySQL DB where any website visitor can create DB objects and populate data.
UPDATE: I had registered the domain wikidatabase.org to get started on a tool but I didn't find enough time yet. If anyone is interested in spending some time and coding on this, please let me know at wikidatabase.org
It's not quite what you're looking for, but Semantic Mediawiki adds database-like features to MediaWiki:
http://semantic-mediawiki.org/wiki/Semantic_MediaWiki
It's still fundamentally a Wiki, but you can add semantic tags to pages ([[foo::bar]] [[baz::1000]]) and then do database-type queries across them: SELECT baz FROM pages WHERE foo=bar would be {{#ask: [[foo::bar]] | ?baz}}. There is even an embryonic SPARQL implementation for pseudo-SQL queries.
OK this question is old, but Google led me here, so for anyone else out there looking for a wiki for structured data: Take a look at Foswiki.
This might be like what you're looking for: dbpedia.org. They're working on extracting data from Wikipedia, and encoding it in a structured format using RDF, so that it can be queried using SPARQL.
Linkeddata.org has a big list of RDF data sets.
Do you mean something like http://www.freebase.com?
You should check out https://www.wikidata.org/wiki/Wikidata:Main_Page which is a bit different but still may be of interest.
Something that might come close to your requirements is Google Docs.
What's offered is document editing roughly similar to MS Word, and spreadsheets roughly similar to Excel. I'm thinking of the latter, of course.
In Google Docs, You can create spreadsheets for free; being spreadsheets, they naturally have a row-and-column structure similar to a database, and which you can define flexibly. You can also share these sheets with other people. This seems to be a by-invite-only process rather than open-to-all, but there may be other possibilities I'm not aware of, or that level of sharing might be enough for you in any case.
mindtouch should be able to do it. It's rather easy to get data in / out. (for example: it's trivial to aggregate all the IP's for servers into one table).
I pretty much use it as a DB in the wiki itself (pages have tables, key/value..inheritance, templates, etc...) but you can also interface with the API, write dekiscript, grab the XML...
I like this idea. I have heard of some sites that are trying to pull together large datasets for various things for open consumption, but none that would allow a wiki feel.
You could start with something as simple as an installation of phpMyAdmin with a known password that would allow people to log in, create a database, edit data and query from any other site on the web.
It might suffer from more accuracy problems than wikipedia though.
OpenRecord, development of which seems to have halted in 2008, seems to approach this. It is a structured wiki in which pages are views on the data. Unlike RDBMSes it is loosely typed - the system tries to make a best guess about what data you entered, but defaults to text when it cannot guess. Schemas appear to have been implied.
http://openrecord.org
An example of the typing that is given is that of a date. If you enter '2008' in a record, the system interprets this as a date. If you enter 'unknown' however, the system allows that as well.
Perhaps you might be interested in Couch DB:
Apache CouchDB is a document-oriented
database that can be queried and
indexed in a MapReduce fashion using
JavaScript. CouchDB also offers
incremental replication with
bi-directional conflict detection and
resolution.
I'm working on an Open Source PHP / Symfony / PostgreSQL app that does this.
It allows multiple projects, each project can have multiple directories, each directory has a defined field structure. Admins set all this up.
Then members of the public can suggest new records, edit or report existing ones. All this is moderated and versioned.
It's early days yet but it basically works and is already in real world use in several projects.
Future plans already in progress include tools to help keep the data up to date, better searching/querying and field types that allow translations of content between languages.
There is more at http://www.directoki.org/
I'm surprised that nobody has mentioned Wikibase yet, which is the software that powers Wikidata.
I'm about to release a FOSS data generator that can generate random yet meaningful data in CSV format. Rather belatedly, I guess, I need to poll the state of the art for such products - because if there is a well known and useful existing tool, I can write my work off to experience. I am aware of of a couple of SQL Server specific tools, but mine is not database specific.
So, links? And if you have used such a product,
what features did you find it was missing?
Edit: To add a bit more info on my tool (Ooh, Matron!) it is intended to allow generation of any kind of random data from existing data files, and
supports weighting. It is XML based (sorry, folks) and lets you say things like:
<pick distribute="20,80" >
<datafile file="femalenames.dat"/>
<datafile file="malenames.dat"/>
<pick/>
to select female names about 20% of the time and male names 80% of the time.
But the purpose of this question is not to describe my product but to get info on other tools.
Latest: If anyone is interested, they can get the alpha of my data generator at http://code.google.com/p/csvtest
That can be a one-liner in R where I use the littler scripting front-end:
# generate the data as a one-liner from the command-line
# we set the RNG seed, and draw from a bunch of distributions
# indented just to fit the box here
edd#ron:~$ r -e'set.seed(42); write.csv(data.frame(y=runif(10), x1=rnorm(10),
x2=rt(10,4), x3=rpois(10, 0.4)), file="/tmp/neil.csv",
quote=FALSE, row.names=FALSE)'
edd#ron:~$ cat /tmp/neil.csv
y,x1,x2,x3
0.914806043496355,-0.106124516091484,0.830735621223563,0
0.937075413297862,1.51152199743894,1.6707628713402,0
0.286139534786344,-0.0946590384130976,-0.282485683052060,0
0.830447626067325,2.01842371387704,0.714442314565005,0
0.641745518893003,-0.062714099052421,-1.08008578470128,0
0.519095949130133,1.30486965422349,2.28674786332467,0
0.736588314641267,2.28664539270111,-0.73270267483628,1
0.134666597237810,-1.38886070111234,-1.45317770550920,1
0.656992290401831,-0.278788766817371,-1.01676025893376,1
0.70506478403695,-0.133321336393658,0.404860813371462,0
edd#ron:~$
You have not said anything about your data-generating process, but rest assured that R can probably cope with just about any requirement, including multivariate normal, t, skew-t, and more. The (six different) random-number generators in R are also of very high quality.
R can also write to DBs, or read parameters from it, and if it needs to be on Windoze then the Rscript front-end could be used instead of littler.
I asked a similar question some months ago:
Tools for Generating Mock Data?
I got some sincere suggestions, but most were not suitable for my needs. Either expensive (non-free) software, or else not flexible enough w.r.t. data types and database structure, or range of mock data, or way too slow (e.g. the Rails ActiveRecord solution).
Features I was looking for were:
Generate mock data to fill existing database tables
Quick to generate > 1 million rows
Produce either SQL script format or flat file suitable for importing
Scriptable command-line interface, not a GUI
Not dependent on Microsoft Windows environment
Nice-to-have features:
Extensible/configurable
Open-source, free license
Written in a dynamic language like Perl/PHP/Python
Point it at a database and let it "discover" the metadata
Integrated with testing tools (e.g. DbUnit)
Option to fill directly into the database as it generates data
The answer I accepted as Databene Benerator. Though since asking the question, I admit I haven't used it very much.
I was surprised that even when asking the community, the range of tools for generating mock data was so thin. This seems like a niche waiting to be filled! I'll be interested to see what you release.
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I am interested in learning how a database engine works (i.e. the internals of it). I know most of the basic data structures taught in CS (trees, hash tables, lists, etc.) as well as a pretty good understanding of compiler theory (and have implemented a very simple interpreter) but I don't understand how to go about writing a database engine. I have searched for tutorials on the subject and I couldn't find any, so I am hoping someone else can point me in the right direction. Basically, I would like information on the following:
How the data is stored internally (i.e. how tables are represented, etc.)
How the engine finds data that it needs (e.g. run a SELECT query)
How data is inserted in a way that is fast and efficient
And any other topics that may be relevant to this. It doesn't have to be an on-disk database - even an in-memory database is fine (if it is easier) because I just want to learn the principals behind it.
Many thanks for your help.
If you're good at reading code, studying SQLite will teach you a whole boatload about database design. It's small, so it's easier to wrap your head around. But it's also professionally written.
SQLite 2.5.0 for Code Reading
http://sqlite.org/
The answer to this question is a huge one. expect a PHD thesis to have it answered 100% ;)
but we can think of the problems one by one:
How to store the data internally:
you should have a data file containing your database objects and a caching mechanism to load the data in focus and some data around it into RAM
assume you have a table, with some data, we would create a data format to convert this table into a binary file, by agreeing on the definition of a column delimiter and a row delimiter and make sure such pattern of delimiter is never used in your data itself. i.e. if you have selected <*> for example to separate columns, you should validate the data you are placing in this table not to contain this pattern. you could also use a row header and a column header by specifying size of row and some internal indexing number to speed up your search, and at the start of each column to have the length of this column
like "Adam", 1, 11.1, "123 ABC Street POBox 456"
you can have it like
<&RowHeader, 1><&Col1,CHR, 4>Adam<&Col2, num,1,0>1<&Col3, Num,2,1>111<&Col4, CHR, 24>123 ABC Street POBox 456<&RowTrailer>
How to find items quickly
try using hashing and indexing to point at data stored and cached based on different criteria
taking same example above, you could sort the value of the first column and store it in a separate object pointing at row id of items sorted alphabetically, and so on
How to speed insert data
I know from Oracle is that they insert data in a temporary place both in RAM and on disk and do housekeeping on periodic basis, the database engine is busy all the time optimizing its structure but in the same time we do not want to lose data in case of power failure of something like that.
so try to keep data in this temporary place with no sorting, append your original storage, and later on when system is free resort your indexes and clear the temp area when done
good luck, great project.
There are books on the topic a good place to start would be Database Systems: The Complete Book by Garcia-Molina, Ullman, and Widom
SQLite was mentioned before, but I want to add some thing.
I personally learned a lot by studying SQlite. The interesting thing is, that I did not go to the source code (though I just had a short look). I learned much by reading the technical material and specially looking at the internal commands it generates. It has an own stack based interpreter inside and you can read the P-Code it generates internally just by using explain. Thus you can see how various constructs are translated to the low-level engine (that is surprisingly simple -- but that is also the secret of its stability and efficiency).
I would suggest focusing on www.sqlite.org
It's recent, small (source code 1MB), open source (so you can figure it out for yourself)...
Books have been written about how it is implemented:
http://www.sqlite.org/books.html
It runs on a variety of operating systems for both desktop computers and mobile phones so experimenting is easy and learning about it will be useful right now and in the future.
It even has a decent community here: https://stackoverflow.com/questions/tagged/sqlite
Okay, I have found a site which has some information on SQL and implementation - it is a bit hard to link to the page which lists all the tutorials, so I will link them one by one:
http://c2.com/cgi/wiki?CategoryPattern
http://c2.com/cgi/wiki?SliceResultVertically
http://c2.com/cgi/wiki?SqlMyopia
http://c2.com/cgi/wiki?SqlPattern
http://c2.com/cgi/wiki?StructuredQueryLanguage
http://c2.com/cgi/wiki?TemplateTables
http://c2.com/cgi/wiki?ThinkSqlAsConstraintSatisfaction
may be you can learn from HSQLDB. I think they offers small and simple database for learning. you can look at the codes since it is open source.
If MySQL interests you, I would also suggest this wiki page, which has got some information about how MySQL works. Also, you might want to take a look at Understanding MySQL Internals.
You might also consider looking at a non-SQL interface for your Database engine. Please take a look at Apache CouchDB. Its what you would call, a document oriented database system.
Good Luck!
I am not sure whether it would fit to your requirements but I had implemented a simple file oriented database with support for simple (SELECT, INSERT , UPDATE ) using perl.
What I did was I stored each table as a file on disk and entries with a well defined pattern and manipulated the data using in built linux tools like awk and sed. for improving efficiency, frequently accessed data were cached.