Akh*_*laV 3 scala apache-spark rdd
我的阅读文本文件的示例代码是
val text = sc.hadoopFile(path, classOf[TextInputFormat], classOf[LongWritable], classOf[Text], sc.defaultMinPartitions)
var rddwithPath = text.asInstanceOf[HadoopRDD[LongWritable, Text]].mapPartitionsWithInputSplit { (inputSplit, iterator) ?
val file = inputSplit.asInstanceOf[FileSplit]
iterator.map { tpl ? (file.getPath.toString, tpl._2.toString) }
}.reduceByKey((a,b) => a)
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这样我怎么能使用PDF和Xml文件
可以使用Tika解析PDF和XML:
看看Apache Tika - 一个内容分析工具包
看看 - https://tika.apache.org/1.9/api/org/apache/tika/parser/xml/
- http://tika.apache.org/0.7/api/org/apache/tika/parser/ pdf/PDFParser.html
- https://tika.apache.org/1.9/api/org/apache/tika/parser/AutoDetectParser.html
以下是Spark与Tika的示例集成:
import org.apache.spark.SparkContext
import org.apache.spark.SparkContext._
import org.apache.spark.SparkConf
import org.apache.spark.input.PortableDataStream
import org.apache.tika.metadata._
import org.apache.tika.parser._
import org.apache.tika.sax.WriteOutContentHandler
import java.io._
object TikaFileParser {
def tikaFunc (a: (String, PortableDataStream)) = {
val file : File = new File(a._1.drop(5))
val myparser : AutoDetectParser = new AutoDetectParser()
val stream : InputStream = new FileInputStream(file)
val handler : WriteOutContentHandler = new WriteOutContentHandler(-1)
val metadata : Metadata = new Metadata()
val context : ParseContext = new ParseContext()
myparser.parse(stream, handler, metadata, context)
stream.close
println(handler.toString())
println("------------------------------------------------")
}
def main(args: Array[String]) {
val filesPath = "/home/user/documents/*"
val conf = new SparkConf().setAppName("TikaFileParser")
val sc = new SparkContext(conf)
val fileData = sc.binaryFiles(filesPath)
fileData.foreach( x => tikaFunc(x))
}
}
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