Question

我有一个数据集，我想提取在x和y之间有（评论/时间）的那些（评论/文本），例如（1183334400＆lt; time＆lt; 1185926400），

这是我数据的一部分：

product/productId: B000278ADA
product/title: Jobst Ultrasheer 15-20 Knee-High Silky Beige Large
product/price: 46.34
review/userId: A17KXW1PCUAIIN
review/profileName: Mark Anthony "Mark"
review/helpfulness: 4/4
review/score: 5.0
review/time: 1174435200
review/summary: Jobst UltraSheer Knee High Stockings
review/text: Does a very good job of relieving fatigue.

product/productId: B000278ADB
product/title: Jobst Ultrasheer 15-20 Knee-High Silky Beige Large
product/price: 46.34
review/userId: A9Q3932GX4FX8
review/profileName: Trina Wehle
review/helpfulness: 1/1
review/score: 3.0
review/time: 1352505600
review/summary: Delivery was very long wait.....
review/text: It took almost 3 weeks to recieve the two pairs of stockings .

product/productId: B000278ADB
product/title: Jobst Ultrasheer 15-20 Knee-High Silky Beige Large
product/price: 46.34
review/userId: AUIZ1GNBTG5OB
review/profileName: dgodoy
review/helpfulness: 1/1
review/score: 2.0
review/time: 1287014400
review/summary: sizes recomended in the size chart are not real
review/text: sizes are much smaller than what is recomended in the chart. I tried to put it and sheer it!.

我的Spark-Scala代码：

import org.apache.hadoop.conf.Configuration
import org.apache.hadoop.io.{LongWritable, Text}
import org.apache.hadoop.mapreduce.lib.input.TextInputFormat
import org.apache.spark.{SparkConf, SparkContext}

object test1 {
  def main(args: Array[String]): Unit = {
    val conf1 = new SparkConf().setAppName("golabi1").setMaster("local")
    val sc = new SparkContext(conf1)
    val conf: Configuration = new Configuration
    conf.set("textinputformat.record.delimiter", "product/title:")
    val input1=sc.newAPIHadoopFile("data/Electronics.txt",     classOf[TextInputFormat], classOf[LongWritable], classOf[Text], conf)
    val lines = input1.map { text => text._2}
    val filt = lines.filter(text=>(text.toString.contains(tt => tt in (startdate until enddate))))
    filt.saveAsTextFile("data/filter1")
  }
}

但我的代码效果不好，

如何过滤这些线？

Answer 1

比那简单得多。试试这个：

object test1 
{
  def main(args: Array[String]): Unit = 
  {
    val conf1 = new SparkConf().setAppName("golabi1").setMaster("local")
    val sc = new SparkContext(conf1)

    def extractDateAndCompare(line: String): Boolean=
    {
        val from = line.indexOf("/time: ") + 7
        val to = line.indexOf("review/text: ") -1
        val date = line.substring(from, to).toLong
        date > startDate && date < endDate
    }

    sc.textFile("data/Electronics.txt")
        .filter(extractDateAndCompare)
        .saveAsTextFile("data/filter1")
  }
}

我通常会找到那些使事情更清晰的中间辅助方法。当然，这假设边界日期是在某处定义的，输入文件包含格式问题。我故意这样做是为了保持这个简单，但添加一个try，返回一个Option子句并使用flatMap（）可以帮助你避免错误，如果你有它们。

此外，您的原始文本有点麻烦，您可能想要探索Json，TSV文件或其他一些替代的，更简单的格式。

scala spark中的RDD过滤器

1 个答案: