Spark:使用与新行不同的分隔符读取文件

您可以使用textinputformat.record.delimiter设置分隔符TextInputFormat,例如,

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

val conf = new Configuration(sc.hadoopConfiguration)
conf.set("textinputformat.record.delimiter", "X")
val input = sc.newAPIHadoopFile("file_path", classOf[TextInputFormat], classOf[LongWritable], classOf[Text], conf)
val lines = input.map { case (_, text) => text.toString}
println(lines.collect)

例如,我的输入是一个包含一行的文件aXbXcXd.上面的代码将输出

Array(a, b, c, d)

在Spark shell中,我根据spark中的Settinginputformat.record.delimiter提取数据:

$ spark-shell
...
scala> import org.apache.hadoop.io.LongWritable
import org.apache.hadoop.io.LongWritable

scala> import org.apache.hadoop.io.Text
import org.apache.hadoop.io.Text

scala> import org.apache.hadoop.conf.Configuration
import org.apache.hadoop.conf.Configuration

scala> import org.apache.hadoop.mapreduce.lib.input.TextInputFormat
import org.apache.hadoop.mapreduce.lib.input.TextInputFormat

scala> val conf = new Configuration
conf: org.apache.hadoop.conf.Configuration = Configuration: core-default.xml, core-site.xml, mapred-default.xml, mapred-site.xml, yarn-default.xml, yarn-site.xml

scala> conf.set("textinputformat.record.delimiter", "\u0001")

scala> val data = sc.newAPIHadoopFile("mydata.txt", classOf[TextInputFormat], classOf[LongWritable], classOf[Text], conf).map(_._2.toString)
data: org.apache.spark.rdd.RDD[(org.apache.hadoop.io.LongWritable, org.apache.hadoop.io.Text)] = NewHadoopRDD[0] at newAPIHadoopFile at <console>:19

sc.newAPIHadoopFile("mydata.txt", ...)是a RDD[(LongWritable, Text)],其中元素的第一部分是起始字符索引,第二部分是由分隔的实际文本"\u0001".

在python中,这可以通过以下方式实现:

rdd = sc.newAPIHadoopFile(YOUR_FILE, "org.apache.hadoop.mapreduce.lib.input.TextInputFormat",
            "org.apache.hadoop.io.LongWritable", "org.apache.hadoop.io.Text",
            conf={"textinputformat.record.delimiter": YOUR_DELIMITER}).map(lambda l:l[1])