package scala.lms.tutorial
import scala.lms.common._
object query_staged0 {
trait QueryCompiler extends Dsl with StagedQueryProcessor
with ScannerBase {
override def version = "query_staged0"
type Fields = Vector[Rep[String]]
case class Record(fields: Fields, schema: Schema) {
def apply(key: String): Rep[String] = fields(schema indexOf key)
def apply(keys: Schema): Fields = keys.map(this apply _)
}
def processCSV(filename: Rep[String], schema: Schema, fieldDelimiter: Char, externalSchema: Boolean)(yld: Record => Rep[Unit]): Rep[Unit] = {
val s = newScanner(filename)
val last = schema.last
def nextRecord = Record(schema.map{x => s.next(if (x==last) '\n' else fieldDelimiter)}, schema)
if (!externalSchema) {
// the right thing would be to dynamically re-check the schema,
// but it clutters the generated code
// schema.foreach(f => if (s.next != f) println("ERROR: schema mismatch"))
nextRecord // ignore csv header
}
while (s.hasNext) yld(nextRecord)
s.close
}
def printSchema(schema: Schema) = println(schema.mkString(defaultFieldDelimiter.toString))
def printFields(fields: Fields) = printf(fields.map{_ => "%s"}.mkString("", defaultFieldDelimiter.toString, "\n"), fields: _*)
def fieldsEqual(a: Fields, b: Fields) = (a zip b).foldLeft(unit(true)) { (a,b) => a && b._1 == b._2 }
def evalPred(p: Predicate)(rec: Record): Rep[Boolean] = p match {
case Eq(a1, a2) => evalRef(a1)(rec) == evalRef(a2)(rec)
}
def evalRef(r: Ref)(rec: Record): Rep[String] = r match {
case Field(name) => rec(name)
case Value(x) => x.toString
}
def resultSchema(o: Operator): Schema = o match {
case Scan(_, schema, _, _) => schema
case Filter(pred, parent) => resultSchema(parent)
case Project(schema, _, _) => schema
case Join(left, right) => resultSchema(left) ++ resultSchema(right)
case Group(keys, agg, parent)=> keys ++ agg
case HashJoin(left, right) => resultSchema(left) ++ resultSchema(right)
case PrintCSV(parent) => Schema()
}
def execOp(o: Operator)(yld: Record => Rep[Unit]): Rep[Unit] = o match {
case Scan(filename, schema, fieldDelimiter, externalSchema) =>
processCSV(filename, schema, fieldDelimiter, externalSchema)(yld)
case Filter(pred, parent) =>
execOp(parent) { rec => if (evalPred(pred)(rec)) yld(rec) }
case Project(newSchema, parentSchema, parent) =>
execOp(parent) { rec => yld(Record(rec(parentSchema), newSchema)) }
case Join(left, right) =>
execOp(left) { rec1 =>
execOp(right) { rec2 =>
val keys = rec1.schema intersect rec2.schema
if (fieldsEqual(rec1(keys), rec2(keys)))
yld(Record(rec1.fields ++ rec2.fields, rec1.schema ++ rec2.schema))
}
}
case Group(keys, agg, parent) => ???
case HashJoin(left, right) => ???
case PrintCSV(parent) =>
val schema = resultSchema(parent)
printSchema(schema)
execOp(parent) { rec => printFields(rec.fields) }
}
def execQuery(q: Operator): Unit = execOp(q) { _ => }
}}
Comments? Suggestions for improvement? View this file on GitHub.