RSQLite is the easiest way to use a database from R because the package itself contains SQLite; no external software is needed. This vignette will walk you through the basics of using a SQLite database.
RSQLite is a DBI-compatible interface which means you primarily use functions defined in the DBI package, so you should always start by loading DBI, not RSQLite:
To create a new SQLite database, you simply supply the filename to dbConnect():
If you just need a temporary database, use either "" (for an on-disk database) or ":memory:" or "file::memory:" (for a in-memory database). This database will be automatically deleted when you disconnect from it.
You can easily copy an R data frame into a SQLite database with dbWriteTable():
Issue a query with dbGetQuery():
dbGetQuery(mydb, 'SELECT * FROM mtcars LIMIT 5')
#> mpg cyl disp hp drat wt qsec vs am gear carb
#> 1 21.0 6 160 110 3.90 2.620 16.46 0 1 4 4
#> 2 21.0 6 160 110 3.90 2.875 17.02 0 1 4 4
#> 3 22.8 4 108 93 3.85 2.320 18.61 1 1 4 1
#> 4 21.4 6 258 110 3.08 3.215 19.44 1 0 3 1
#> 5 18.7 8 360 175 3.15 3.440 17.02 0 0 3 2Not all R variable names are valid SQL variable names, so you may need to escape them with ":
dbGetQuery(mydb, 'SELECT * FROM iris WHERE "Sepal.Length" < 4.6')
#> Sepal.Length Sepal.Width Petal.Length Petal.Width Species
#> 1 4.4 2.9 1.4 0.2 setosa
#> 2 4.3 3.0 1.1 0.1 setosa
#> 3 4.4 3.0 1.3 0.2 setosa
#> 4 4.5 2.3 1.3 0.3 setosa
#> 5 4.4 3.2 1.3 0.2 setosaIf you need to insert the value from a user into a query, don’t use paste()! That makes it easy for a malicious attacker to insert SQL that might damager your database or reveal sensitive information. Instead, use a parameterised query:
dbGetQuery(mydb, 'SELECT * FROM iris WHERE "Sepal.Length" < :x',
params = list(x = 4.6))
#> Sepal.Length Sepal.Width Petal.Length Petal.Width Species
#> 1 4.4 2.9 1.4 0.2 setosa
#> 2 4.3 3.0 1.1 0.1 setosa
#> 3 4.4 3.0 1.3 0.2 setosa
#> 4 4.5 2.3 1.3 0.3 setosa
#> 5 4.4 3.2 1.3 0.2 setosaThis is a little more typing, but much much safer.
If you run a query and the results don’t fit in memory, you can use dbSendQuery(), dbFetch() and dbClearResults() to retrieve the results in batches. By default dbFetch() will retrieve all available rows: use n to set the maximum number of rows to return.
You can use the same approach to run the same parameterised query with different parameters. Call dbBind() to set the parameters:
rs <- dbSendQuery(mydb, 'SELECT * FROM iris WHERE "Sepal.Length" < :x')
dbBind(rs, param = list(x = 4.5))
nrow(dbFetch(rs))
#> [1] 4
dbBind(rs, param = list(x = 4))
nrow(dbFetch(rs))
#> [1] 0
dbClearResult(rs)You can also pass multiple parameters in one call to dbBind():
DBI has new functions dbSendStatement() and dbExecute(), which are the counterparts of dbSendQuery() and dbGetQuery() for SQL statements that do not return a tabular result, such as inserting records into a table, updating a table, or setting engine parameters. It is good practice, although currently not enforced, to use the new functions when you don’t expect a result.