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spark sc.textfile如何详细工作?

[英]How does spark sc.textfile work in detail?

I want to find how sc.textfile works in detail. 我想找到sc.textfile工作原理。
I have found the textfile source code in SparkContext.scala but they contain so much infomation about scheduler, stage and task submitted. 我在SparkContext.scala中找到了文本文件源代码,但它们包含有关调度程序,阶段和任务提交的大量信息。 What I want is how sc.textfile reads files from hdfs and how sc.textfile uses wildcard to match multiple files. 我想要的是sc.textfile如何从hdfs读取文件以及sc.textfile如何使用通配符来匹配多个文件。
Where can I find the source code? 在哪里可以找到源代码?

textFile is a method of a org.apache.spark.SparkContext class that reads a text file from HDFS, a local file system (available on all nodes), or any Hadoop-supported file system URI, and return it as an RDD of Strings. textFileorg.apache.spark.SparkContext类的方法,该方法从HDFS,本地文件系统(在所有节点上都可用)或任何Hadoop支持的文件系统URI中读取文本文件,并将其作为字符串的RDD返回。

sc.textFile(path,minpartions)

> @param path path to the text file on a supported file system  
> @param minPartitions suggested minimum number of partitions for the resulting RDD
> @return RDD of lines of the text file

It internally uses hadoopRDD (An RDD that provides core functionality for reading data stored in Hadoop ) 它在内部使用hadoopRDD(RDD提供了用于读取Hadoop中存储的数据的核心功能)

Hadoop Rdd looks like this Hadoop Rdd看起来像这样

HadoopRDD(
      sc, //Sparkcontext
      confBroadcast, //A general Hadoop Configuration, or a subclass of it
      Some(setInputPathsFunc),//Optional closure used to initialize any JobConf that HadoopRDD creates.       inputFormatClass,
      keyClass,
      valueClass,
      minPartitions)

In the textFile method we call create a hadoopRDD with some hardcoded value: 在textFile方法中,我们调用创建带有一些硬编码值的hadoopRDD:

HadoopRDD(
      sc, //Sparkcontext
      confBroadcast, //A general Hadoop Configuration, or a subclass of it
      Some(setInputPathsFunc),//Optional closure used to initialize any JobConf that HadoopRDD creates. 
      classOf[TextInputFormat],
      classOf[LongWritable],
      classOf[Text],
      minPartitions)

Because of these hard coded values we are only able to read textfiles , so if we want to read any other type of file we use HadoopRdd . 由于这些硬编码值,我们只能读取文本文件,因此,如果要读取任何其他类型的文件,请使用HadoopRdd。

the compute function in core\\src\\main\\scala\\org\\apache\\spark\\rdd\\HadoopRDD.scala 核心\\ src \\ main \\ scala \\ org \\ apache \\ spark \\ rdd \\ HadoopRDD.scala中的计算功能

here are some code in the function below 这是下面函数中的一些代码

  var reader: RecordReader[K, V] = null
  val inputFormat = getInputFormat(jobConf)
  HadoopRDD.addLocalConfiguration(new SimpleDateFormat("yyyyMMddHHmm").format(createTime),
   context.stageId, theSplit.index, context.attemptNumber, jobConf)
  reader = inputFormat.getRecordReader(split.inputSplit.value, jobConf, Reporter.NULL)

  // Register an on-task-completion callback to close the input stream.
  context.addTaskCompletionListener{ context => closeIfNeeded() }
  val key: K = reader.createKey()
  val value: V = reader.createValue()

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