本文整理汇总了Scala中org.apache.spark.sql.catalyst.ScalaReflection类的典型用法代码示例。如果您正苦于以下问题：Scala ScalaReflection类的具体用法？Scala ScalaReflection怎么用？Scala ScalaReflection使用的例子？那么, 这里精选的类代码示例或许可以为您提供帮助。
在下文中一共展示了ScalaReflection类的3个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Scala代码示例。
示例1: DatabaseBackup
//设置package包名称以及导入依赖的类
package unus.stage
import unus.helpers.Conf
import org.apache.spark.sql.catalyst.ScalaReflection
import org.apache.spark.sql.types.StructType
import scala.reflect.runtime.universe._
import org.apache.spark.sql.SaveMode
class DatabaseBackup[T: TypeTag](table: String) {
private lazy val schema = ScalaReflection.schemaFor[T].dataType.asInstanceOf[StructType]
def save(): Unit = {
Conf.spark.read
.format("jdbc")
.option("url", Conf.dbUrl)
.option("dbtable", s""""$table"""")
.option("user", Conf.dbUsername)
.option("password", Conf.dbPassword)
.option("jdbcdriver","org.postgresql.Driver")
.load()
.write
.format("csv")
.option("header", "true")
.save(Conf.dataDir + "/" + table + ".csv")
}
def load(): Unit = {
Conf.spark.read
.format("csv")
.option("header", "true")
.schema(schema)
.load(Conf.dataDir + "/" + table + ".csv.gz")
.write
.format("jdbc")
.option("url", Conf.dbUrl)
.option("dbtable", s""""$table"""")
.option("user", Conf.dbUsername)
.option("password", Conf.dbPassword)
.option("jdbcdriver","org.postgresql.Driver")
.mode(SaveMode.Append)
.save()
}
} 示例2: SchemaConverter
//设置package包名称以及导入依赖的类
import org.apache.spark.sql.types._
import org.apache.spark.sql.catalyst.ScalaReflection
import org.apache.spark.sql.catalyst.ScalaReflection.universe._
/**
* Convert schema to case class and case class to schema
*
* Created by swadhin on 27/01/17.
*/
object SchemaConverter {
type TypeConverter = (DataType) => String
def schemaToCaseClass(schema: StructType, className: String)(implicit tc: TypeConverter): String = {
def genField(s: StructField): String = {
val f = tc(s.dataType)
s match {
case x if x.nullable => s" ${s.name}:Option[$f] = None"
case _ => s" ${s.name}:$f"
}
}
val fieldsStr = schema.map(genField).mkString(",\n ")
s"""
|case class $className (
| $fieldsStr
|)
""".stripMargin
}
def caseClassToSchema[T: TypeTag] = {
ScalaReflection.schemaFor[T].dataType.asInstanceOf[StructType]
}
implicit val defaultTypeConverter: TypeConverter = {
case _: ByteType => "Byte"
case _: ShortType => "Short"
case _: IntegerType => "Int"
case _: LongType => "Long"
case _: FloatType => "Float"
case _: DoubleType => "Double"
case _: DecimalType => "BigDecimal"
case _: StringType => "String"
case _: BinaryType => "Array[Byte]"
case _: BooleanType => "Boolean"
case _: TimestampType => "java.sql.Timestamp"
case _: DateType => "java.sql.Date"
case _: ArrayType => "Seq[Int]"
case _: MapType => "scala.collection.Map"
case _: StructType => "org.apache.spark.sql.Row"
case _ => "String"
}
} 示例3: PatientCacher
//设置package包名称以及导入依赖的类
package unus.stage
import unus.helpers.Conf
import unus.db.{Patient, Repository}
import unus.helpers.Cacher
import org.apache.spark.rdd.RDD
import org.apache.spark.sql.catalyst.ScalaReflection
import org.apache.spark.sql.types.StructType
class PatientCacher extends Cacher[Patient] {
override protected val name: String = "patient"
override protected def build(): RDD[Patient] = {
val schema = ScalaReflection.schemaFor[Patient].dataType.asInstanceOf[StructType]
import Conf.spark.implicits._
Conf.spark.read.format("csv")
.schema(schema)
.option("header", "true")
.load(Conf.dataDir + "/FInalDataset.csv")
.as[Patient]
.rdd
}
}