I have a dataset and i want to extract those (review/text) which have (review/time) between x and y, for example ( 1183334400 < time < 1185926400),
here are part of my data:
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!.
my Spark-Scala Code :
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")
}
}
but my code does not work well,
how can i filter these lines?
Is is much simpler than that. Try this:
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")
}
}
I usually find those intermediate auxiliary methods to make things much clearer. Of course, this assumes the boundary dates are defined somewhere and that the input file contain format issues. I did this intentionally to keep this simple, but adding a try, returning an Option clause and using flatMap() can help you avoid errors if you have them.
Also, your raw text is a little cumbersome, you might want to explore Json, TSV files or some other alternative, easier format.
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