[R] RMySQL - Bulk loading data and creating FK links

Gabor Grothendieck ggrothendieck at gmail.com
Thu Jan 28 17:55:25 CET 2010 

I think one would only be concerned about such internals if one were
primarily interested in performance; otherwise, one would be more
interested in ease of specification and part of that ease is having it
independent of implementation and separating implementation from
specification activities.  An example of separation of specification
and implementation is that by simply specifying a disk-based database
rather than an in-memory database SQL can perform queries that take
more space than memory.  The query itself need not be modified.

I think the viewpoint you are discussing is primarily one of
performance whereas the viewpoint I was discussing is primarily ease
of use and that accounts for the difference.

I believe your performance comparison is comparing a sequence of
operations that include building a database, transferring data to it,
performing the operation, reading it back in and destroying the
database to an internal manipulation.  I would expect the internal
manipulation, particular one done primarily in C code as is the case
with data.table, to be faster although some benchmarks of the database
approach found that it compared surprisingly well to straight R code
-- some users of sqldf found that for an 8000 row data frame sqldf
actually ran faster than aggregate and also faster than tapply.  The
News section on the sqldf home page provides links to their
benchmarks.  Thus if R is fast enough then its likely that the
database approach is fast enough too since its even faster.

On Thu, Jan 28, 2010 at 8:52 AM, Matthew Dowle <mdowle at mdowle.plus.com> wrote:
> Are you claiming that SQL is that utopia?  SQL is a row store.  It cannot
> give the user the benefits of column store.
>
> For example, why does SQL take 113 seconds in the example in this thread :
> http://tolstoy.newcastle.edu.au/R/e9/help/10/01/1872.html
> but data.table takes 5 seconds to get the same result ? How come the high
> level language SQL doesn't appear to hide the user from this detail ?
>
> If you are just describing utopia, then of course I agree.  It would be
> great to have a language which hid us from this.  In the meantime the user
> has choices, and the best choice depends on the task and the real goal.
>
> "Gabor Grothendieck" <ggrothendieck at gmail.com> wrote in message
> news:971536df1001280428p345f8ff4v5f3a80c13f96dd15 at mail.gmail.com...
> Its only important internally.  Externally its undesirable that the
> user have to get involved in it.  The idea of making software easy to
> write and use is to hide the implementation and focus on the problem.
> That is why we use high level languages, object orientation, etc.
>
> On Thu, Jan 28, 2010 at 4:37 AM, Matthew Dowle <mdowle at mdowle.plus.com>
> wrote:
>> How it represents data internally is very important, depending on the real
>> goal :
>> http://en.wikipedia.org/wiki/Column-oriented_DBMS
>>
>>
>> "Gabor Grothendieck" <ggrothendieck at gmail.com> wrote in message
>> news:971536df1001271710o4ea62333l7f1230b860114c7e at mail.gmail.com...
>> How it represents data internally should not be important as long as
>> you can do what you want. SQL is declarative so you just specify what
>> you want rather than how to get it and invisibly to the user it
>> automatically draws up a query plan and then uses that plan to get the
>> result.
>>
>> On Wed, Jan 27, 2010 at 12:48 PM, Matthew Dowle <mdowle at mdowle.plus.com>
>> wrote:
>>>
>>>> sqldf("select * from BOD order by Time desc limit 3")
>>> Exactly. SQL requires use of order by. It knows the order, but it isn't
>>> ordered. Thats not good, but might be fine, depending on what the real
>>> goal
>>> is.
>>>
>>>
>>> "Gabor Grothendieck" <ggrothendieck at gmail.com> wrote in message
>>> news:971536df1001270629w4795da89vb7d77af6e4e8be7f at mail.gmail.com...
>>> On Wed, Jan 27, 2010 at 8:56 AM, Matthew Dowle <mdowle at mdowle.plus.com>
>>> wrote:
>>>> How many columns, and of what type are the columns ? As Olga asked too,
>>>> it
>>>> would be useful to know more about what you're really trying to do.
>>>>
>>>> 3.5m rows is not actually that many rows, even for 32bit R. Its depends
>>>> on
>>>> the columns and what you want to do with those columns.
>>>>
>>>> At the risk of suggesting something before we know the full facts, one
>>>> possibility is to load the data from flat file into data.table. Use
>>>> setkey()
>>>> to set your keys. Use tables() to summarise your various tables. Then do
>>>> your joins etc all-in-R. data.table has fast ways to do those sorts of
>>>> joins (but we need more info about your task).
>>>>
>>>> Alternatively, you could check out the sqldf website. There is an
>>>> sqlread.csv (or similar name) which can read your files directly into
>>>> SQL
>>>
>>> read.csv.sql
>>>
>>>> instead of going via R. Gabor has some nice examples there about that
>>>> and
>>>> its faster.
>>>>
>>>> You use some buzzwords which makes me think that SQL may not be
>>>> appropriate
>>>> for your task though. Can't say for sure (because we don't have enough
>>>> information) but its possible you are struggling because SQL has no row
>>>> ordering concept built in. That might be why you've created an increment
>>>
>>> In the SQLite database it automatically assigns a self incrementing
>>> hidden column called rowid to each row. e.g. using SQLite via the
>>> sqldf package on CRAN and the BOD data frame which is built into R we
>>> can display the rowid column explicitly by referring to it in our
>>> select statement:
>>>
>>>> library(sqldf)
>>>> BOD
>>> Time demand
>>> 1 1 8.3
>>> 2 2 10.3
>>> 3 3 19.0
>>> 4 4 16.0
>>> 5 5 15.6
>>> 6 7 19.8
>>>> sqldf("select rowid, * from BOD")
>>> rowid Time demand
>>> 1 1 1 8.3
>>> 2 2 2 10.3
>>> 3 3 3 19.0
>>> 4 4 4 16.0
>>> 5 5 5 15.6
>>> 6 6 7 19.8
>>>
>>>
>>>> field? Do your queries include "order by incrementing field"? SQL is not
>>>> good at "first" and "last" type logic. An all-in-R solution may well be
>>>
>>> In SQLite you can get the top 3 values, say, like this (continuing the
>>> prior example):
>>>
>>>> sqldf("select * from BOD order by Time desc limit 3")
>>> Time demand
>>> 1 7 19.8
>>> 2 5 15.6
>>> 3 4 16.0
>>>
>>>> better, since R is very good with ordered vectors. A 1GB data.table (or
>>>> data.frame) for example, at 3.5m rows, could have 76 integer columns, or
>>>> 38 double columns. 1GB is well within 32bit and allows some space for
>>>> working copies, depending on what you want to do with the data. If you
>>>> have
>>>> 38 or less columns, or you have 64bit, then an all-in-R solution *might*
>>>> get your task done quicker, depending on what your real goal is.
>>>>
>>>> If this sounds plausible, you could post more details and, if its
>>>> appropriate, and luck is on your side, someone might even sketch out how
>>>> to
>>>> do an all-in-R solution.
>>>>
>>>>
>>>> "Nathan S. Watson-Haigh" <nathan.watson-haigh at csiro.au> wrote in message
>>>> news:4B5FDE1B.10806 at csiro.au...
>>>>>I have a table (contact) with several fields and it's PK is an auto
>>>>>increment field. I'm bulk loading data to this table from files which if
>>>>>successful will be about 3.5million rows (approx 16000 rows per file).
>>>>>However, I have a linking table (an_contact) to resolve a m:m
>>>>>relationship
>>>>>between the an and contact tables. How can I retrieve the PK's for the
>>>>>data
>>>>>bulk loaded into contact so I can insert the relevant data into
>>>>>an_contact.
>>>>>
>>>>> I currently load the data into contact using:
>>>>> dbWriteTable(con, "contact", dat, append=TRUE, row.names=FALSE)
>>>>>
>>>>> But I then need to get all the PK's which this dbWriteTable() appended
>>>>> to
>>>>> the contact table so I can load the data into my an_contact link table.
>>>>> I
>>>>> don't want to issue a separate INSERT query for each row in dat and
>>>>> then
>>>>> use MySQLs LAST_INSERT_ID() function....not when I have 3.5million rows
>>>>> to
>>>>> insert!
>>>>>
>>>>> Any pointers welcome,
>>>>> Nathan
>>>>>
>>>>> --
>>>>> --------------------------------------------------------
>>>>> Dr. Nathan S. Watson-Haigh
>>>>> OCE Post Doctoral Fellow
>>>>> CSIRO Livestock Industries
>>>>> University Drive
>>>>> Townsville, QLD 4810
>>>>> Australia
>>>>>
>>>>> Tel: +61 (0)7 4753 8548
>>>>> Fax: +61 (0)7 4753 8600
>>>>> Web: http://www.csiro.au/people/Nathan.Watson-Haigh.html
>>>>>
>>>>
>>>> ______________________________________________
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>>>> http://www.R-project.org/posting-guide.html
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>>>>
>>>
>>> ______________________________________________
>>> R-help at r-project.org mailing list
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>>> PLEASE do read the posting guide
>>> http://www.R-project.org/posting-guide.html
>>> and provide commented, minimal, self-contained, reproducible code.
>>>
>>
>> ______________________________________________
>> R-help at r-project.org mailing list
>> https://stat.ethz.ch/mailman/listinfo/r-help
>> PLEASE do read the posting guide
>> http://www.R-project.org/posting-guide.html
>> and provide commented, minimal, self-contained, reproducible code.
>>
>
> ______________________________________________
> R-help at r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>

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