本文整理汇总了Scala中org.apache.spark.sql.sources.Filter类的典型用法代码示例。如果您正苦于以下问题：Scala Filter类的具体用法？Scala Filter怎么用？Scala Filter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Filter类的1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: DefaultSource
//设置package包名称以及导入依赖的类
package pl.jborkowskijmartin.spark.mf
import org.apache.hadoop.conf.Configuration
import org.apache.hadoop.fs.FileStatus
import org.apache.hadoop.mapreduce.Job
import org.apache.spark.sql.SparkSession
import org.apache.spark.sql.catalyst.InternalRow
import org.apache.spark.sql.execution.datasources.{FileFormat, OutputWriterFactory, PartitionedFile}
import org.apache.spark.sql.sources.Filter
import org.apache.spark.sql.types.{StringType, StructField, StructType}
import org.apache.spark.unsafe.types.UTF8String
class DefaultSource extends FileFormat {
override def inferSchema(sparkSession: SparkSession, options: Map[String, String], files: Seq[FileStatus]):
Option[StructType] = {
println(">>>InferSchema")
Some(StructType(
StructField("line", StringType, nullable = true) :: Nil
))
}
override def prepareWrite(sparkSession: SparkSession, job: Job, options: Map[String, String], dataSchema: StructType):
OutputWriterFactory = {
println(">>> prepareWrite")
null
}
override def buildReader(sparkSession: SparkSession, dataSchema: StructType, partitionSchema: StructType,
requiredSchema: StructType, filters: Seq[Filter], options: Map[String, String],
hadoopConf: Configuration): (PartitionedFile) => Iterator[InternalRow] = {
pf => Iterator(InternalRow(UTF8String.fromString("hello")))
}
}