# RSQLite

#### Hadley Wickham

#### 2016-11-25

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:

    library(DBI)

## Creating a new database

To create a new SQLite database, you simply supply the filename to `dbConnect()`:

    mydb <- dbConnect(RSQLite::SQLite(), "my-db.sqlite")
    dbDisconnect(mydb)
    #> [1] TRUE
    unlink("my-db.sqlite")

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.

    mydb <- dbConnect(RSQLite::SQLite(), "")
    dbDisconnect(mydb)
    #> [1] TRUE

## Loading data

You can easily copy an R data frame into a SQLite database with `dbWriteTable()`:

    mydb <- dbConnect(RSQLite::SQLite(), "")
    dbWriteTable(mydb, "mtcars", mtcars)
    #> [1] TRUE
    dbWriteTable(mydb, "iris", iris)
    #> [1] TRUE
    dbListTables(mydb)
    #> [1] "iris"   "mtcars"

## Queries

Issue a query with `dbGetQuery()`:

    dbGetQuery(mydb, 'SELECT * FROM mtcars LIMIT 5')
    #>                    mpg cyl disp  hp drat    wt  qsec vs am gear carb
    #> Mazda RX4         21.0   6  160 110 3.90 2.620 16.46  0  1    4    4
    #> Mazda RX4 Wag     21.0   6  160 110 3.90 2.875 17.02  0  1    4    4
    #> Datsun 710        22.8   4  108  93 3.85 2.320 18.61  1  1    4    1
    #> Hornet 4 Drive    21.4   6  258 110 3.08 3.215 19.44  1  0    3    1
    #> Hornet Sportabout 18.7   8  360 175 3.15 3.440 17.02  0  0    3    2

Not 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  setosa

If 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  setosa

This is a little more typing, but much much safer.

## Batched queries

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.

    rs <- dbSendQuery(mydb, 'SELECT * FROM mtcars')
    while (!dbHasCompleted(rs)) {
      df <- dbFetch(rs, n = 10)
      print(nrow(df))
    }
    #> [1] 10
    #> [1] 10
    #> [1] 10
    #> [1] 2
    dbClearResult(rs)
    #> [1] TRUE

## Multiple parameterised queries

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)
    #> [1] TRUE

You can also pass multiple parameters in one call to `dbBind()`:

    rs <- dbSendQuery(mydb, 'SELECT * FROM iris WHERE "Sepal.Length" = :x')
    dbBind(rs, param = list(x = seq(4, 4.4, by = 0.1)))
    nrow(dbFetch(rs))
    #> [1] 4
    dbClearResult(rs)
    #> [1] TRUE

## Statements

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.

    dbExecute(mydb, 'DELETE FROM iris WHERE "Sepal.Length" < 4')
    #> [1] 0
    rs <- dbSendStatement(mydb, 'DELETE FROM iris WHERE "Sepal.Length" < :x')
    dbBind(rs, param = list(x = 4.5))
    dbGetRowsAffected(rs)
    #> [1] 4
    dbClearResult(rs)
    #> [1] TRUE