calasql-operations_3.0.1.6.source-code.DbApiOps.scala Maven / Gradle / Ivy
package scalasql.operations
import scalasql.core.SqlStr.SqlStringSyntax
import scalasql.core._
class DbApiOps(dialect: DialectTypeMappers) {
import dialect._
/**
* Creates a SQL `CASE`/`WHEN`/`ELSE` clause
*/
def caseWhen[T: TypeMapper](values: (Expr[Boolean], Expr[T])*) =
new scalasql.operations.CaseWhen(values)
/**
* The row_number() of the first peer in each group - the rank of the current row
* with gaps. If there is no ORDER BY clause, then all rows are considered peers and
* this function always returns 1.
*/
def rank(): Expr[Int] = Expr { _ => sql"RANK()" }
/**
* The number of the row within the current partition. Rows are numbered starting
* from 1 in the order defined by the ORDER BY clause in the window definition, or
* in arbitrary order otherwise.
*/
def rowNumber(): Expr[Int] = Expr { _ => sql"ROW_NUMBER()" }
/**
* The number of the current row's peer group within its partition - the rank of the
* current row without gaps. Rows are numbered starting from 1 in the order defined
* by the ORDER BY clause in the window definition. If there is no ORDER BY clause,
* then all rows are considered peers and this function always returns 1.
*/
def denseRank(): Expr[Int] = Expr { _ => sql"DENSE_RANK()" }
/**
* Despite the name, this function always returns a value between 0.0 and 1.0 equal to
* (rank - 1)/(partition-rows - 1), where rank is the value returned by built-in window
* function rank() and partition-rows is the total number of rows in the partition. If
* the partition contains only one row, this function returns 0.0.
*/
def percentRank(): Expr[Double] = Expr { _ => sql"PERCENT_RANK()" }
/**
* The cumulative distribution. Calculated as row-number/partition-rows, where row-number
* is the value returned by row_number() for the last peer in the group and partition-rows
* the number of rows in the partition.
*/
def cumeDist(): Expr[Double] = Expr { _ => sql"CUME_DIST()" }
/**
* Argument N is handled as an integer. This function divides the partition into N groups
* as evenly as possible and assigns an integer between 1 and N to each group, in the order
* defined by the ORDER BY clause, or in arbitrary order otherwise. If necessary, larger
* groups occur first. This function returns the integer value assigned to the group that
* the current row is a part of.
*/
def ntile(n: Int): Expr[Int] = Expr { _ => sql"NTILE($n)" }
private def lagLead[T](prefix: SqlStr, e: Expr[T], offset: Int, default: Expr[T]): Expr[T] =
Expr { implicit ctx =>
val args = SqlStr.join(
Seq(
Some(sql"$e"),
Some(offset).filter(_ != -1).map(o => sql"$o"),
Option(default).map(d => sql"$d")
).flatten,
SqlStr.commaSep
)
sql"$prefix($args)"
}
/**
* The lag() function returns the result of evaluating expression expr against the
* previous row in the partition. Or, if there is no previous row (because the current
* row is the first), NULL.
*
* If the offset argument is provided, then it must be a non-negative integer. In this
* case the value returned is the result of evaluating expr against the row offset rows
* before the current row within the partition. If offset is 0, then expr is evaluated
* against the current row. If there is no row offset rows before the current row, NULL
* is returned.
*
* If default is also provided, then it is returned instead of NULL if the row identified
* by offset does not exist.
*/
def lag[T](e: Expr[T], offset: Int = -1, default: Expr[T] = null): Expr[T] =
lagLead(sql"LAG", e, offset, default)
/**
* The lead() function returns the result of evaluating expression expr against the next
* row in the partition. Or, if there is no next row (because the current row is the last),
* NULL.
*
* If the offset argument is provided, then it must be a non-negative integer. In this
* case the value returned is the result of evaluating expr against the row offset rows
* after the current row within the partition. If offset is 0, then expr is evaluated
* against the current row. If there is no row offset rows after the current row, NULL
* is returned.
*
* If default is also provided, then it is returned instead of NULL if the row identified
* by offset does not exist.
*/
def lead[T](e: Expr[T], offset: Int = -1, default: Expr[T] = null): Expr[T] =
lagLead(sql"LEAD", e, offset, default)
/**
* Calculates the window frame for each row in the same way as an aggregate window
* function. It returns the value of expr evaluated against the first row in the window
* frame for each row.
*/
def firstValue[T](e: Expr[T]): Expr[T] = Expr { implicit ctx => sql"FIRST_VALUE($e)" }
/**
* Calculates the window frame for each row in the same way as an aggregate window
* function. It returns the value of expr evaluated against the last row in the window
* frame for each row.
*/
def lastValue[T](e: Expr[T]): Expr[T] = Expr { implicit ctx => sql"LAST_VALUE($e)" }
/**
* Calculates the window frame for each row in the same way as an aggregate window
* function. It returns the value of expr evaluated against the row N of the window
* frame. Rows are numbered within the window frame starting from 1 in the order
* defined by the ORDER BY clause if one is present, or in arbitrary order otherwise.
* If there is no Nth row in the partition, then NULL is returned.
*/
def nthValue[T](e: Expr[T], n: Int): Expr[T] = Expr { implicit ctx => sql"NTH_VALUE($e, $n)" }
}