本文整理汇总了Scala中org.apache.parquet.hadoop.api.ReadSupport类的典型用法代码示例。如果您正苦于以下问题：Scala ReadSupport类的具体用法？Scala ReadSupport怎么用？Scala ReadSupport使用的例子？那么恭喜您, 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ReadSupport类的2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: ScalaPBReadSupport
//设置package包名称以及导入依赖的类
package com.trueaccord.scalapb.parquet
import java.util
import com.trueaccord.scalapb.{GeneratedMessage, GeneratedMessageCompanion, Message}
import org.apache.hadoop.conf.Configuration
import org.apache.parquet.hadoop.api.{InitContext, ReadSupport}
import org.apache.parquet.hadoop.api.ReadSupport.ReadContext
import org.apache.parquet.io.api.{GroupConverter, RecordMaterializer}
import org.apache.parquet.schema.MessageType
class ScalaPBReadSupport[T <: GeneratedMessage with Message[T]] extends ReadSupport[T] {
override def prepareForRead(
configuration: Configuration,
keyValueMetaData: util.Map[String, String],
fileSchema: MessageType,
readContext: ReadContext): RecordMaterializer[T] = {
val protoClass = Option(keyValueMetaData.get(ScalaPBReadSupport.PB_CLASS)).getOrElse(throw new RuntimeException(s"Value for ${ScalaPBReadSupport.PB_CLASS} not found."))
val cmp = {
import scala.reflect.runtime.universe
val runtimeMirror = universe.runtimeMirror(getClass.getClassLoader)
val module = runtimeMirror.staticModule(protoClass)
val obj = runtimeMirror.reflectModule(module)
obj.instance.asInstanceOf[GeneratedMessageCompanion[T]]
}
new RecordMaterializer[T] {
val root = new ProtoMessageConverter[T](cmp, fileSchema, onEnd = _ => ())
override def getRootConverter: GroupConverter = root
override def getCurrentRecord: T = root.getCurrentRecord
}
}
override def init(context: InitContext): ReadContext = {
new ReadContext(context.getFileSchema)
}
}
object ScalaPBReadSupport {
val PB_CLASS = "parquet.scalapb.class"
} 示例2: apply
//设置package包名称以及导入依赖的类
package io.eels.component.parquet
import com.sksamuel.exts.Logging
import io.eels.{Predicate, Row}
import org.apache.hadoop.conf.Configuration
import org.apache.hadoop.fs.Path
import org.apache.parquet.filter2.compat.FilterCompat
import org.apache.parquet.hadoop.api.ReadSupport
import org.apache.parquet.hadoop.{ParquetInputFormat, ParquetReader}
import org.apache.parquet.schema.Type
def apply(path: Path,
predicate: Option[Predicate],
readSchema: Option[Type],
dictionaryFiltering: Boolean)(implicit conf: Configuration): ParquetReader[Row] = {
logger.debug(s"Opening parquet reader for $path")
// The parquet reader can use a projection by setting a projected schema onto the supplied conf object
def configuration(): Configuration = {
val newconf = new Configuration(conf)
readSchema.foreach { it =>
newconf.set(ReadSupport.PARQUET_READ_SCHEMA, it.toString)
}
newconf.set(ParquetInputFormat.DICTIONARY_FILTERING_ENABLED, dictionaryFiltering.toString)
newconf.set(org.apache.parquet.hadoop.ParquetFileReader.PARQUET_READ_PARALLELISM, config.parallelism.toString)
newconf
}
// a filter is set when we have a predicate for the read
def filter(): FilterCompat.Filter = predicate.map(ParquetPredicateBuilder.build)
.map(FilterCompat.get)
.getOrElse(FilterCompat.NOOP)
ParquetReader.builder(new RowReadSupport, path)
.withConf(configuration())
.withFilter(filter())
.build()
}
}