[jira] [Commented] (SPARK-1849) Broken UTF-8 encoded data gets character replacements and thus can't be fixed
[
https://issues.apache.org/jira/browse/SPARK-1849?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanelfocusedCommentId=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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[jira] [Commented] (SPARK-1849) Broken UTF-8 encoded data gets character replacements and thus can't be fixed
[
https://issues.apache.org/jira/browse/SPARK-1849?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanelfocusedCommentId=14000460#comment-14000460
]
Harry Brundage commented on SPARK-1849:
---
I disagree - the data isn't badly encoded, just not UTF-8 encoded, which when
we're talking about data from the internet really isn't all that uncommon. You
could extend my specific problem of some lines in the source file being a
different encoding to a file entirely encoded in iso-8859-1, which is likely
something Spark should deal with considering all the effort put into supporting
Windows. I don't think asking users to drop down to writing custom
{{InputFormat}}s to deal with the realities of large data is a good move if
Spark wants to become the fast and general data processing engine for large
scale data.
I could certainly use {{sc.hadoopFile}} to load in my data and work with the
{{org.apache.hadoop.io.Text}} objects myself, but A) why force everyone dealing
with this issue to go through the pain of figuring that out, and B) I'm in
PySpark where I can't actually do that without fancy Py4J trickery. I think
encoding issues should be in your face.
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
Fix For: 1.0.0, 0.9.1
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 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.
--
This message was sent by Atlassian JIRA
(v6.2#6252)
[jira] [Commented] (SPARK-1849) Broken UTF-8 encoded data gets character replacements and thus can't be fixed
[
https://issues.apache.org/jira/browse/SPARK-1849?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanelfocusedCommentId=14000397#comment-14000397
]
Mridul Muralidharan commented on SPARK-1849:
Looks like textFile is probably the wrong api to use.
You cannot recover from badly encoded data ... Better would be to write your
own InputFormat which does what you need.
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
Fix For: 1.0.0, 0.9.1
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 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.
--
This message was sent by Atlassian JIRA
(v6.2#6252)
