dhis2-users team mailing list archive

[Jason Pickering <jason.p.pickering@xxxxxxxxx>]

Hi Bob,

Yes, I suspect that most R users would probably want to do things
their own way. It has a rather steep learning curve. :)

As for canned R scripts, the best way would probably with with PL/R, a
procedural Postgresql language which utilizes R.

http://www.joeconway.com/plr/doc/index.html

I have done some very basic testing and it seems to work just fine on
the server side.

I think they are two separate problems really, but I totally agree, C
is likely going to be faster than Java for big operations. However, I
do think (as all of you know) that the use of stored procedures (with
the wrapper facade type of approach) for certain functions (like
aggregation and heavy cross tab operations) would be much better to be
executed on the database server as a native stored procedure.

Regards,
Jason




On Thu, May 27, 2010 at 11:45 AM, Bob Jolliffe <bobjolliffe@xxxxxxxxx> wrote:
> We've talked before about integrating scripting engine (such as R)
> into dhis : http://www.rforge.net/rscript/
>
> But my guess is that most R users are going to be of a level of
> sophistication that they would be most comfortable doing the kind of
> thing you describe - conecting directly to db with r client and doing
> their stuff.
>
> OTOH if there were sufficiently useful "canned" dhis R scripts which
> could take some number crunching load off the jvm and produce canned
> useful analysis then that would be different.
>
> Sadly I don't know sufficient about R to know.  But I sense it ...
>
> Regards
> Bob
>
> On 27 May 2010 10:08, Jason Pickering <jason.p.pickering@xxxxxxxxx> wrote:
>> Hi everyone. I have had a recent question from a user about how DHIS2
>> can be used with R. I am including a trivial example here about how to
>> use R as as a client to access data and produce a graph in DHIS2.
>>
>> Just get a copy of R  and install the DBI and RPostregSQL packages with
>>
>>>install.packages()
>>
>>
>> After that, just connect to the DB, retrieve your data (in this case
>> from a report table) and produce a graph.
>>
>>>library(DBI)
>>
>>>library(RPostgreSQL)
>>
>>>drv <- dbDriver("PostgreSQL")
>>
>>>con <- dbConnect(drv, dbname="dhis2_zm_prod2", user="postgres", password="postgres")
>>
>>>rs <- dbSendQuery(con, "SELECT * FROM _report_malaria_indicators_district where
>> organisationunitid = 3904")
>>
>>>data <- fetch(rs,n=-1)
>>
>>>barplot(data$malaria_confirm_incidence, names.arg=as.character(data$periodname), main=as.character(data$organisationunitname[1]),las=2)
>>
>>>dev.print(png, file="/home/jason/test.png")
>>
>> Regards,
>> Jason
>>
>> ---
>> Jason P. Pickering
>> email: jason.p.pickering@xxxxxxxxx
>> tel:+260968395190
>>
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>



-- 
--
Jason P. Pickering
email: jason.p.pickering@xxxxxxxxx
tel:+260968395190