Purpose

The QueryNamespace class is designed to be a convenient way to write (and re-write) SQL queries for packages with defined result model specifications. The convenience is that only passed parameters must be set in the query - any table names or other pre-defined variables can be set once in a result spec and reused if table prefixes are applied to the tables. The intention is to save time and limit bugs. This also builds on the SqlRender/DatabaseConnector principle of “Write sql once, use anywhere” principle across ohdsi packages. This is not intended to replace usage of dbplyr style operations which are expressive and allow use of sql. However, many find that writing SQL strings is often more convenient and portable to other programming language than dplyr calls allow.

Basic usage

The most basic usage is to create a specification with a single table that conforms to a valid data model specification

library(ResultModelManager)

## Loading required package: R6

## Loading required package: DatabaseConnector

## 
## Attaching package: 'ResultModelManager'

## The following object is masked _by_ '.GlobalEnv':
## 
##     DataMigrationManager

tableSpecification <- data.frame(
  tableName = "cohort_definition",
  columnName = c("cohort_definition_id", "cohort_name", "json", "sql"),
  primaryKey = c("yes", "no", "no", "no"),
  dataType = c("bigint", "varchar", "varchar", "varchar")
)

Note, that generally we would save these tables to a csv file that can be loaded.

We then load a QueryNamespace instance with this table:

connectionDetails <- DatabaseConnector::createConnectionDetails("sqlite", server = tempfile())
qns <- createQueryNamespace(
  connectionDetails = connectionDetails,
  usePooledConnection = FALSE,
  tableSpecification = tableSpecification,
  tablePrefix = "rwe_study_99_",
  snakeCaseToCamelCase = TRUE,
  database_schema = "main"
)

## Connecting using SQLite driver

# Create our schema within the namespace
sql <- generateSqlSchema(schemaDefinition = tableSpecification)
# note - the table prefix and schema parameters are not neeeded
qns$executeSql(sql)

##   |                                                                              |                                                                      |   0%  |                                                                              |======================================================================| 100%

## Executing SQL took 0.0127 secs

We can then query the table with sql that automatically replaces the table names:

qns$queryDb("SELECT * FROM @database_schema.@cohort_definition")

## [1] cohortDefinitionId cohortName         json               sql               
## <0 rows> (or 0-length row.names)

Note that the underlying query is already handling our tablePrefix for us, so we don’t need to add it:

qns$queryDb("SELECT * FROM @database_schema.@cohort_definition")

## [1] cohortDefinitionId cohortName         json               sql               
## <0 rows> (or 0-length row.names)

Adding replacement variables at runtime

Variables can naturally be added at runtime, for example, in a query:

qns$queryDb("SELECT * FROM @database_schema.@cohort_definition WHERE cohort_definition_id = @id",
  id = 5
)

## [1] cohortDefinitionId cohortName         json               sql               
## <0 rows> (or 0-length row.names)

Alternatively we can persist the id in the object for use in all queries.

qns$addReplacementVariable("database_id", "my_cdm")

Note that replacing the same variable will result in an error

qns$addReplacementVariable("database_id", "my_cdm")

We can also add to the table specification

tableSpecification2 <- data.frame(
  tableName = "database_info",
  columnName = c("database_id", "database_name"),
  primaryKey = c("yes", "no"),
  dataType = c("varchar", "varchar")
)
qns$addTableSpecification(tableSpecification2)