Re: [MonetDB-users] loading RDF data in MonetDB

On Tue, Oct 06, 2009 at 08:43:46PM -0400, Medha Atre wrote:

I tried installing MonetDB-SQL-xx.tar.gz from sources.

Make fails giving error -lMapi not found.

I was wondering why does it need Mapi library when all I want to do is simply build a database and load some data and query it!!

Can someone help please? The READMEs in the sources are of no help and there is no step-by-step setup procedure given on the web-documentation.

On http://monetdb.cwi.nl/ "Download" leads to http://monetdb.cwi.nl/Download/ from where "Installation" leads to http://monetdb.cwi.nl/Download/Packages/ which explains to how to install pre-built binary packages, build from the super source ball, and point to the "documentation" about how to build from individual source tarballs at http://monetdb.cwi.nl/MonetDB/Documentation/Experts.html I hope this provides sufficent choices and information ... Stefan

Thanks in anticipation.

Medha

On Tue, Oct 6, 2009 at 8:26 PM, Medha Atre wrote:

...

OK. I figured that must be the command after digging through the manuals. But for the vertically partitioned approach demonstrated in various research papers, I believe the end user has to manually load the RDF data split according to the predicates into different tables, which also requires that the SQL query being issued specifies these tables and joins across these tables as opposed to one big triple table.

Correct me if I am wrong.

Thanks.

Medha

On Tue, Oct 6, 2009 at 5:06 PM, Sjoerd Mullender wrote:

...

On 2009-10-06 17:59, Medha Atre wrote:

...

Hi,

Thanks for the reply.

At this point, all I am looking for is to load RDF NTriples data -- treated as a 3 column table -- into MonetDB using "vertical partitioning" to index the data nicely (as I read about MonetDB being used for the same in different research papers recently.. e.g. http://portal.acm.org/citation.cfm?id=1453856.1453927 RDF-3X etc). I am not really looking for a great support for different RDF formats (as the data has already been cleaned into NTriples format using rdflib), I want to check the correctness of the results generated using my own querying tool.

So can you please suggest me a method of treating the given RDF NTriples file as a simple "space separated" 3-column data file from which I can load the data into MonetDB creating the required indexes or "vertical partitions"?

Perhaps something like COPY <n> RECORDS INTO <table> FROM <file> USING DELIMITERS ' ','\n'; where <n> is the number of tuples, <table> is the name of a table that you created for this, and <file> is the full path name of the file (in single quotes).

...

Querying with SQL front end is fine with me!

Looking forward to your help.

Medha

...

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Message: 5 Date: Tue, 6 Oct 2009 10:19:57 +0200 From: Lefteris Subject: Re: [MonetDB-users] loading RDF data in MonetDB To: Communication channel for MonetDB users         Message-ID:         <852badbc0910060119x4f125a06qd5fc7ed0c56035c@mail.gmail.com> Content-Type: text/plain; charset=ISO-8859-1

Hi,

there is a highly experimental module for MonetDB to load RDF data. This is not activated in the stable release, and in order to use it you will need to do some compilation on your own and possible report back any problems you have. If you are willing to jump deeper in the MonetDB experience I can guide you on how to do this. The module will read any RDF format supported by the rdflib library and create a triple store with appropriate indices. However, the only way to query the triple store at this point is through the SQL front-end.

regrads,

lefteris

On Tue, Oct 6, 2009 at 8:59 AM, Medha Atre  wrote:

...

Hi,

I intend to use MonetDB for some of my experimental work using RDF data. I was wondering if there is an easy way to load RDF data (in NTriples format) in MonetDB making use of the column-wise vertical partitioning of the RDF data, based on properties/predicates in the RDF data.

Some pointers or help regarding this is much appreciated.

I am sorry if this is not the correct forum to post this message.

Thanks. Medha

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