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package ru.circumflex
package orm
/*!# Criteria API
The `Criteria` class provides simplified API for querying records in neat
object-oriented notation with the ability to fetch the whole hierarchy of
records in one query via _prefetching_.
Criteria API is designed to operate specifically on `Record` instances. If
you need different projections, use `Select` instead.
*/
class Criteria[PK, R <: Record[PK, R]](val rootNode: RelationNode[PK, R])
extends SQLable with Cloneable {
protected var _executionTime = 0l
def executionTime = _executionTime
private var _counter = 0
protected def nextCounter(): Int = {
_counter += 1
_counter
}
protected var _rootTree: RelationNode[PK, R] = rootNode
protected var _joinTree: RelationNode[PK, R] = rootNode
protected var _prefetchSeq: Seq[Association[_, _, _]] = Nil
protected var _projections: Seq[RecordProjection[_, _]] = List(rootNode.*)
protected var _restrictions: Seq[Predicate] = Nil
protected var _orders: Seq[Order] = Nil
// Process the `prefetchSeq` of root relation
rootNode.relation.prefetchSeq.foreach(prefetch(_))
protected def resetProjection(projection: Projection[_]) {
projection match {
case a: AtomicProjection[_] => a.AS("p_" + nextCounter)
case c: CompositeProjection[_] => c.subProjections.foreach(p => resetProjection(p))
}
}
protected def replaceLeft(join: JoinNode[PK, R, _, _],
node: RelationNode[PK, R]): RelationNode[PK, R] =
join.left match {
case j: JoinNode[PK, R, _, _] => replaceLeft(j, node)
case r: RelationNode[PK, R] => join.replaceLeft(node)
}
protected def updateRootTree[PKN, N <: Record[PKN, N]](
node: RelationNode[PKN, N], association: Association[_, _, _]): RelationNode[PKN, N] =
node match {
// we don't actually care about types here, since type annotations are eliminated by erasure
case j: JoinNode[PKN, N, PKN, N] =>
j.replaceLeft(updateRootTree(j.left, association))
.replaceRight(updateRootTree(j.right, association))
case node: RelationNode[PKN, N] =>
val a = association.asInstanceOf[Association[PKN, N, N]]
if (node.relation == a.field.record.relation) { // N == C
new ManyToOneJoin[PKN, N, PKN, N](node, preparePf(a.parentRelation, a), a, LEFT)
} else if (node.relation == a.parentRelation) { // N == P
new OneToManyJoin[PKN, N, PKN, N](node, preparePf(a.field.record.relation, a), a, LEFT)
} else node
}
protected def preparePf[PKN, N <: Record[PKN, N]](
relation: Relation[PKN, N], association: Association[_, _, _]): RelationNode[PKN, N] = {
val node = relation.AS("pf_" + nextCounter)
_projections ++= List(node.*)
_prefetchSeq ++= List[Association[_, _, _]](association)
node
}
protected def updateJoinTree[PKN, N <: Record[PKN, N]](
node: RelationNode[PKN, N], tree: RelationNode[PK, R]): RelationNode[PK, R] =
tree match {
// outra vez, types are not really important here
case j: JoinNode[PK, R, PK, R] => try { // try the left side
j.replaceLeft(updateJoinTree(node, j.left))
j.replaceRight(updateJoinTree(node, j.right))
} catch {
case e: Exception => // try the right side
j.replaceRight(updateJoinTree(node, j.right))
}
case rel: RelationNode[PK, R] => rel.JOIN(node)
}
protected def processTupleTree[PKN, N <: Record[PKN, N]](
tuple: Array[_], tree: RelationNode[PKN, N]) {
tree match {
case j: OneToManyJoin[PKN, N, PKN, N] =>
val pNode = j.left
val cNode = j.right
val a = j.association
val pIndex = _projections.indexWhere(_.node.alias == pNode.alias)
val cIndex = _projections.indexWhere(_.node.alias == cNode.alias)
if (pIndex == -1 || cIndex == -1) return
tuple(pIndex).asInstanceOf[Option[N]] map { parent =>
val children = a.inverseCache.get(parent.PRIMARY_KEY().toString, new InverseSeq[N])
tuple(cIndex).asInstanceOf[Option[N]] map { child =>
if (!children.records.contains(child))
children.add(child)
}
}
processTupleTree(tuple, j.left)
processTupleTree(tuple, j.right)
case j: JoinNode[_, _, _, _] =>
processTupleTree(tuple, j.left)
processTupleTree(tuple, j.right)
case _ =>
}
}
def add(predicates: Predicate*): Criteria[PK, R] = {
_restrictions ++= predicates.toList
this
}
def add(expression: String, params: Pair[String, Any]*): Criteria[PK, R] =
add(prepareExpr(expression, params: _*))
def addOrder(orders: Order*): Criteria[PK, R] = {
_orders ++= orders.toList
this
}
def prefetch(association: Association[_, _, _]): Criteria[PK, R] = {
val a = association.asInstanceOf[Association[PK, R, R]]
if (!_prefetchSeq.contains(a)) {
// The depth-search is used to update query plan if possible.
_rootTree = updateRootTree(_rootTree, a)
// Also process `prefetchSeq` of parent and child relations
a.parentRelation.prefetchSeq.foreach(prefetch(_))
a.record.relation.prefetchSeq.foreach(prefetch(_))
}
this
}
def addJoin[PKN, N <: Record[PKN, N]](node: RelationNode[PKN, N]): Criteria[PK, R] = {
_joinTree = updateJoinTree(node, _joinTree)
this
}
/*!## Limits & offsets
Use methods `limit` and `offset` to provide paging/scrolling on the result set
of the select query produced by `mkSelect`. Note that these clauses interfere
with one-to-many joins or prefetches, which typically require larger result sets.
If you find yourself in the situation where you are required to use one-to-many
prefetching or joins, simulate result set limiting using subqueries in the `WHERE`
clause.
*/
protected var _limit: Int = -1
def limit: Int = _limit
def limit(l: Int): this.type = {
_limit = l
this
}
protected var _offset: Int = 0
def offset: Int = _offset
def offset(o: Int): this.type = {
_offset = o
this
}
// Querying
def mkSelect(): SQLQuery[Array[Option[Any]]] =
SELECT(new UntypedTupleProjection(projections: _*))
.FROM(queryPlan)
.WHERE(predicate)
.ORDER_BY(_orders: _*)
.LIMIT(limit)
.OFFSET(offset)
def mkUpdate(): Update[PK, R] = UPDATE(rootNode).WHERE(predicate)
def mkDelete(): Delete[PK, R] = DELETE(rootNode).WHERE(predicate)
def projections: Seq[Projection[_]] = {
_projections.foreach(p => resetProjection(p))
_projections
}
def predicate: Predicate = _restrictions.size match {
case 0 => EmptyPredicate
case 1 => _restrictions(0)
case _ => orm.AND(_restrictions: _*)
}
def queryPlan: RelationNode[PK, R] = _joinTree match {
case j: JoinNode[PK, R, _, _] => replaceLeft(j.clone(), _rootTree)
case r: RelationNode[PK, R] => _rootTree
}
def list(): Seq[R] = {
val q = mkSelect()
val result = q.resultSet { rs =>
var result: Seq[R] = Nil
while (rs.next) q.read(rs) map { tuple =>
processTupleTree(tuple, _rootTree)
val root = tuple(0).asInstanceOf[Option[R]].get
if (!result.contains(root))
result ++= List(root)
}
result
}
_executionTime = q.executionTime
result
}
def unique(): Option[R] = {
val q = mkSelect()
val result = q.resultSet { rs =>
if (!rs.next) None // none records found
// Okay, let's grab the first one. This would be the result eventually.
else q.read(rs) map { firstTuple =>
processTupleTree(firstTuple, _rootTree)
val result = firstTuple(0).asInstanceOf[Option[R]].get
// We don't want to screw prefetches up so let's walk till the end,
// but make sure that no other root records appear in result set.
while (rs.next) {
q.read(rs) map { tuple =>
processTupleTree(tuple, _rootTree)
val root = tuple(0).asInstanceOf[Option[Any]].get
if (root != result) // Wow, this thingy shouldn't be here, call the police!
throw new ORMException("Unique result expected, but multiple records found.")
}
}
result
}
}
_executionTime = q.executionTime
result
}
def toSql = mkSelect().toSql
override def toString = queryPlan.toString
/*!## Criteria Merging
Several `Criteria` objects can be merged using `AND` and `OR` operators.
Merging implies following actions:
* this criteria object is shallowly cloned prior to merging so that the
source is not modified;
* the root aliases of both criteria must match or `ORMException` will
be thrown;
* alias counters are summed to prevent collisions;
* every association from specified `criteria` prefetch sequence is added to
the result criteria prefetch sequence, thus updating it's query plan;
* next, the join tree of specified `criteria` is merged with the join tree of
the result criteria;
* finally, restrictions and order specificators are copied from specified
`criteria` to the result criteria, specified `operator` is applied to
restrictions.
Note, however, that alias collision can occur while merging criteria with
joins. It is a best practice to assign join aliases manually.
*/
protected def merge(criteria: Criteria[PK, R], operator: String): Criteria[PK, R] = {
val result = this.clone.asInstanceOf[Criteria[PK, R]]
// compare aliases
if (result.rootNode.alias != criteria.rootNode.alias)
throw new ORMException("Criteria root aliases must match for successful merging.")
// ensure counter integrity
result._counter += criteria._counter
// add prefetches
criteria._prefetchSeq.foreach(a => result.prefetch(a))
// update join tree
result._joinTree = criteria._joinTree match {
case j: JoinNode[PK, R, _, _] => result.replaceLeft(j.clone(), result._joinTree)
case _ => result._joinTree
}
// copy restrictions
result._restrictions = List(new AggregatePredicate(
operator, List(result.predicate, criteria.predicate)))
// copy order specificators
criteria._orders.foreach { o =>
if (!result._orders.contains(o))
result.addOrder(o)
}
result
}
def AND(criteria: Criteria[PK, R]): Criteria[PK, R] = merge(criteria, ormConf.dialect.AND)
def OR(criteria: Criteria[PK, R]): Criteria[PK, R] = merge(criteria, ormConf.dialect.OR)
/*! Criteria can be merged with inverse associations to create logical scopes. Same
rules are applied as with criteria merging, except that the criteria object with
proper restrictions is created from the inverse association implicitly.
*/
protected def merge(inverse: InverseAssociation[_, R, _, _], operator: String): Criteria[PK, R] = {
val criteria = new Criteria[PK, R](rootNode)
aliasStack.push(rootNode.alias)
criteria.add(inverse.association.asInstanceOf[Association[_, _, R]] IS inverse.record.asInstanceOf[R])
merge(criteria, operator)
}
def AND(inverse: InverseAssociation[_, R, _, _]): Criteria[PK, R] = merge(inverse, ormConf.dialect.AND)
def OR(inverse: InverseAssociation[_, R, _, _]): Criteria[PK, R] = merge(inverse, ormConf.dialect.OR)
}
