options(datatable.print.nrows = 10)
This package abstracts typical patterns used when connecting to and communicating with databases in R. It aims to provide very few, simple and reliable functions for sending queries and data to databases.
devtools::install_github("INWT/dbtools")
We will start with a simple example showing how to use dbtools
to send queries
and data to a database. The example will introduce the main parts of the
package, namely the Credentials class as well as both sendQuery
and
sendData
.
In this example we show how to connect to a database, how to communicate with the database, how to set up a database table, and finally how to send and retrieve data.
To begin with, we have to define an object of class Credentials which will store all necessary information to connect to a database. The driver is mandatory, all other arguments depend on the specific back-end.
library("dbtools") cred <- Credentials(drv = RSQLite::SQLite, dbname = "example.db")
Opposed to the functions available from DBI, functions from dbtools
need a
Credentials instance as argument that takes care of connecting to the
database, communicating with the database and closing the connection.
Now, let's check whether we can actually access the database example.db.
testConnection(cred)
cred
For the remainder of this example, we make use of the USArrests dataset.
Unfortunately, the data contains some information in its row names, namely the
respective state. Since dbtools
does not support row names, we have to convert
them to a variable.
data(USArrests, envir = environment()) USArrests$State <- row.names(USArrests) USArrests <- USArrests[c("State", "Murder", "Assault", "UrbanPop", "Rape")] row.names(USArrests) <- NULL USArrests
Next, we will create the database table by sending a CREATE TABLE
query to
the database.
sendQuery( cred, "CREATE TABLE `USArrests` ( State TEXT PRIMARY KEY, Murder INTEGER, Assault REAL, UrbanPop REAL, Rape INTEGER);" )
Now, we can write the USArrests data to the USArrests database table by using
the sendData
function.
sendData(cred, USArrests)
If we want to read data from the database, we can do this by using sendQuery
,
the same function we used for creating the database table.
dat <- sendQuery(cred, "SELECT * FROM `USArrests`;") dat
Now we will dig a bit deeper into the functionality of dbtools
.
Basically, you already know how to use sendQuery
. In our introductory example
we used it to create a database table and to query some data.
In your normal work-flow you will sometimes want to split up a complex query into more tangible chunks. The approach we take here is to allow for a vector of queries as argument. The result of these queries have to be row-bindable. To make an example lets say we want to query each state separately:
queryFun <- function(state) { paste0("SELECT * FROM USArrests WHERE State = '", state, "';") } sendQuery(cred, queryFun(dat$State))
In such a case sendQuery
will perform all queries on one connection. A
different approach is to fetch the results of the original query in chunks,
which we do not support yet.
As with sendQuery
, you basically already know how to use sendData
. In the
introductory example we used it to send the USArrests data to the USArrests
database table.
When using sendData
you might be interesting in how to handle possible
primary key violations. By default, sendData
will keep old rows and ignore any
duplicates. But you may use the mode argument and set it to "replace" (replace
old rows) or "truncate" (delete old rows from database table before writing
data). If you are using a non MySQL connection, you may notice that this feature
is not available yet.
One of the problems we face on a regular basis are connection problems to
external servers. To address this sendQuery
will evaluate everything in a
'try-catch' handler abstracted in dbtools::reTry
. With this you can state how
many tries a query has, how many seconds should be waited between each iteration
and how the error messages should be logged:
dat <- sendQuery( cred, "SELECT * FROM USArrest;", # wrong name for illustration tries = 2, intSleep = 1 )
Sometimes your data can be distributed on different servers but you want to send
the same query to those servers. What you can do is give sendQuery
a
CredentialsList.
file.copy("example.db", "example1.db")
Now we want to load the data from example1.db
and example.db
which can be
implemented as follows:
cred <- Credentials( RSQLite::SQLite, dbname = c("example.db", "example1.db") ) sendQuery(cred, "SELECT * FROM USArrests;")
It might also be of interest to query your databases in parallel. For that it is possible to supply a apply/map function which in turn can be a parallel lapply like mclapply or something else:
sendQuery( cred, "SELECT * FROM USArrests;", mc.cores = 2, applyFun = parallel::mclapply )
Potentially you can send multiple queries to multiple databases. The results are tried to be simplified by default:
sendQuery(cred, c("SELECT * FROM USArrests;", "SELECT 1 AS x;")) sendQuery(cred, c("SELECT * FROM USArrests;", "SELECT 1 AS x;"), simplify = FALSE)
Both functionalities are available for sendData
, too.
In many applications it is easier and more tangible to separate SQL and R
code. Furthermore we oftentimes paste queries together to have something like
parameterized statements. There are various solutions for this type of problem
but not many for the R language. Hence dbtools
provides an own interface to
what may be understood as template queries. These templates solve two issues
for us:
.sql
file.The use of these features is simple enough. A template is defined as a character and regions in which parameters are substituted are denoted by two curly braces. Users of Liquid templates may be familiar with this idea. Everything inside these regions is interpreted as R-expression and can contain arbitrary operations. The result of the evaluation should be a character of length one.
templateQuery <- "SELECT {{ sqlName(fieldName) }} FROM `someTable`;" Query(templateQuery, fieldName = "someField")
When such a query lives inside a file we can use a connection object and pass it
to Query
.
otherTemplateQuery <- "SELECT `someField` FROM `someTable` WHERE `primaryKey` IN {{ sqlInNums(ids) }};" writeLines(otherTemplateQuery, tmpFile <- tempfile()) Query(file(tmpFile), ids = 1:10)
unlink(c("example.db", "example1.db"))
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