[jira] [Commented] (SPARK-1849) Broken UTF-8 encoded data gets character replacements and thus can't be "fixed"

["Sean Owen (JIRA)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/SPARK-1849?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14169549#comment-14169549 ] 

Sean Owen commented on SPARK-1849:
----------------------------------

Yes, I think there isn't a 'fix' here short of a quite different implementation. Hadoop's text support pretty deeply assumes UTF-8 (partly for speed) and the Spark implementation is just Hadoop's. This would have to justify rewriting all that. I think you have to treat this as binary data for now.

> Broken UTF-8 encoded data gets character replacements and thus can't be "fixed"
> -------------------------------------------------------------------------------
>
>                 Key: SPARK-1849
>                 URL: https://issues.apache.org/jira/browse/SPARK-1849
>             Project: Spark
>          Issue Type: Bug
>            Reporter: Harry Brundage
>         Attachments: encoding_test
>
>
> I'm trying to process a file which isn't valid UTF-8 data inside hadoop using Spark via {{sc.textFile()}}. Is this possible, and if not, is this a bug that we should fix? It looks like {{HadoopRDD}} uses {{org.apache.hadoop.io.Text.toString}} on all the data it ever reads, which I believe replaces invalid UTF-8 byte sequences with the UTF-8 replacement character, \uFFFD. Some example code mimicking what {{sc.textFile}} does underneath:
> {code}
> scala> sc.textFile(path).collect()(0)
> res8: String = ?pple
> scala> sc.hadoopFile(path, classOf[TextInputFormat], classOf[LongWritable], classOf[Text]).map(pair => pair._2.toString).collect()(0).getBytes()
> res9: Array[Byte] = Array(-17, -65, -67, 112, 112, 108, 101)
> scala> sc.hadoopFile(path, classOf[TextInputFormat], classOf[LongWritable], classOf[Text]).map(pair => pair._2.getBytes).collect()(0)
> res10: Array[Byte] = Array(-60, 112, 112, 108, 101)
> {code}
> In the above example, the first two snippets show the string representation and byte representation of the example line of text. The string shows a question mark for the replacement character and the bytes reveal the replacement character has been swapped in by {{Text.toString}}. The third snippet shows what happens if you call {{getBytes}} on the {{Text}} object which comes back from hadoop land: we get the real bytes in the file out.
> Now, I think this is a bug, though you may disagree. The text inside my file is perfectly valid iso-8859-1 encoded bytes, which I would like to be able to rescue and re-encode into UTF-8, because I want my application to be smart like that. I think Spark should give me the raw broken string so I can re-encode, but I can't get at the original bytes in order to guess at what the source encoding might be, as they have already been replaced. I'm dealing with data from some CDN access logs which are to put it nicely diversely encoded, but I think a use case Spark should fully support. So, my suggested fix, which I'd like some guidance, is to change {{textFile}} to spit out broken strings by not using {{Text}}'s UTF-8 encoding.
> Further compounding this issue is that my application is actually in PySpark, but we can talk about how bytes fly through to Scala land after this if we agree that this is an issue at all. 



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