[jira] [Commented] (SPARK-17041) Columns in schema are no longer case sensitive when reading csv file
[
https://issues.apache.org/jira/browse/SPARK-17041?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16152745#comment-16152745
]
Alexandre Dupriez commented on SPARK-17041:
---
I would advocate for a message which highlights the problem is case-related,
since it may not be obvious from a message like {{Reference 'Output' is
ambiguous, could be: Output#1263, Output#1295.;}} (in fact it seems the
column's header name provided in the message can be taken from either of the
colliding columns - and thus contain capital letters, which can be misleading
w.r.t. case sensitivity).
> Columns in schema are no longer case sensitive when reading csv file
>
>
> Key: SPARK-17041
> URL: https://issues.apache.org/jira/browse/SPARK-17041
> Project: Spark
> Issue Type: Bug
> Components: Input/Output
>Affects Versions: 2.0.0
>Reporter: Barry Becker
>
> It used to be (in spark 1.6.2) that I could read a csv file that had columns
> with names that differed only by case. For example, one column may be
> "output" and another called "Output". Now (with spark 2.0.0) if I try to read
> such a file, I get an error like this:
> {code}
> org.apache.spark.sql.AnalysisException: Reference 'Output' is ambiguous,
> could be: Output#1263, Output#1295.;
> {code}
> The schema (dfSchema below) that I pass to the csv read looks like this:
> {code}
> StructType( StructField(Output,StringType,true), ...
> StructField(output,StringType,true), ...)
> {code}
> The code that does the read is this
> {code}
> sqlContext.read
> .format("csv")
> .option("header", "false") // Use first line of all files as header
> .option("inferSchema", "false") // Automatically infer data types
> .schema(dfSchema)
> .csv(dataFile)
> {code}
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[jira] [Commented] (SPARK-17041) Columns in schema are no longer case sensitive when reading csv file
[
https://issues.apache.org/jira/browse/SPARK-17041?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15443779#comment-15443779
]
koert kuipers commented on SPARK-17041:
---
note that the docs say:
"It is highly discouraged to turn on case sensitive mode."
which seems to suggest one shouldn't have files like this. that is not very
realistic. i feel like this is a case where a bad idea (sql lack of case
sensitivity) is being pushed upon us.
if only we could ignore the bad sql ideas a bit more and be inspired by R
data.frame or pandas.
> Columns in schema are no longer case sensitive when reading csv file
>
>
> Key: SPARK-17041
> URL: https://issues.apache.org/jira/browse/SPARK-17041
> Project: Spark
> Issue Type: Bug
> Components: Input/Output
>Affects Versions: 2.0.0
>Reporter: Barry Becker
>
> It used to be (in spark 1.6.2) that I could read a csv file that had columns
> with names that differed only by case. For example, one column may be
> "output" and another called "Output". Now (with spark 2.0.0) if I try to read
> such a file, I get an error like this:
> {code}
> org.apache.spark.sql.AnalysisException: Reference 'Output' is ambiguous,
> could be: Output#1263, Output#1295.;
> {code}
> The schema (dfSchema below) that I pass to the csv read looks like this:
> {code}
> StructType( StructField(Output,StringType,true), ...
> StructField(output,StringType,true), ...)
> {code}
> The code that does the read is this
> {code}
> sqlContext.read
> .format("csv")
> .option("header", "false") // Use first line of all files as header
> .option("inferSchema", "false") // Automatically infer data types
> .schema(dfSchema)
> .csv(dataFile)
> {code}
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[jira] [Commented] (SPARK-17041) Columns in schema are no longer case sensitive when reading csv file
[
https://issues.apache.org/jira/browse/SPARK-17041?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15420994#comment-15420994
]
Dongjoon Hyun commented on SPARK-17041:
---
Great! Thank you for confirming.
> Columns in schema are no longer case sensitive when reading csv file
>
>
> Key: SPARK-17041
> URL: https://issues.apache.org/jira/browse/SPARK-17041
> Project: Spark
> Issue Type: Bug
> Components: Input/Output
>Affects Versions: 2.0.0
>Reporter: Barry Becker
>
> It used to be (in spark 1.6.2) that I could read a csv file that had columns
> with names that differed only by case. For example, one column may be
> "output" and another called "Output". Now (with spark 2.0.0) if I try to read
> such a file, I get an error like this:
> {code}
> org.apache.spark.sql.AnalysisException: Reference 'Output' is ambiguous,
> could be: Output#1263, Output#1295.;
> {code}
> The schema (dfSchema below) that I pass to the csv read looks like this:
> {code}
> StructType( StructField(Output,StringType,true), ...
> StructField(output,StringType,true), ...)
> {code}
> The code that does the read is this
> {code}
> sqlContext.read
> .format("csv")
> .option("header", "false") // Use first line of all files as header
> .option("inferSchema", "false") // Automatically infer data types
> .schema(dfSchema)
> .csv(dataFile)
> {code}
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[jira] [Commented] (SPARK-17041) Columns in schema are no longer case sensitive when reading csv file
[
https://issues.apache.org/jira/browse/SPARK-17041?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15420952#comment-15420952
]
Barry Becker commented on SPARK-17041:
--
Yes, that suggestion worked. I added
{code}
sqlContext.sql("set spark.sql.caseSensitive=true")
{code}
Right before the read and I can now read the file with columns that only differ
by case.
I would prefer that that be the default behavior, but at least this is no
longer a block for me. Thanks!
> Columns in schema are no longer case sensitive when reading csv file
>
>
> Key: SPARK-17041
> URL: https://issues.apache.org/jira/browse/SPARK-17041
> Project: Spark
> Issue Type: Bug
> Components: Input/Output
>Affects Versions: 2.0.0
>Reporter: Barry Becker
>
> It used to be (in spark 1.6.2) that I could read a csv file that had columns
> with names that differed only by case. For example, one column may be
> "output" and another called "Output". Now (with spark 2.0.0) if I try to read
> such a file, I get an error like this:
> {code}
> org.apache.spark.sql.AnalysisException: Reference 'Output' is ambiguous,
> could be: Output#1263, Output#1295.;
> {code}
> The schema (dfSchema below) that I pass to the csv read looks like this:
> {code}
> StructType( StructField(Output,StringType,true), ...
> StructField(output,StringType,true), ...)
> {code}
> The code that does the read is this
> {code}
> sqlContext.read
> .format("csv")
> .option("header", "false") // Use first line of all files as header
> .option("inferSchema", "false") // Automatically infer data types
> .schema(dfSchema)
> .csv(dataFile)
> {code}
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[jira] [Commented] (SPARK-17041) Columns in schema are no longer case sensitive when reading csv file
[
https://issues.apache.org/jira/browse/SPARK-17041?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15420106#comment-15420106
]
Dongjoon Hyun commented on SPARK-17041:
---
Since I don't have the exact script of your situation, it might be different.
But, Spark 2.0 supports `case sensitive` of course with SQL configuration. In
the above, `sql("set spark.sql.caseSensitive=true")`.
Could you confirm on your site, [~barrybecker4]?
> Columns in schema are no longer case sensitive when reading csv file
>
>
> Key: SPARK-17041
> URL: https://issues.apache.org/jira/browse/SPARK-17041
> Project: Spark
> Issue Type: Bug
> Components: Input/Output
>Affects Versions: 2.0.0
>Reporter: Barry Becker
>
> It used to be (in spark 1.6.2) that I could read a csv file that had columns
> with names that differed only by case. For example, one column may be
> "output" and another called "Output". Now (with spark 2.0.0) if I try to read
> such a file, I get an error like this:
> {code}
> org.apache.spark.sql.AnalysisException: Reference 'Output' is ambiguous,
> could be: Output#1263, Output#1295.;
> {code}
> The schema (dfSchema below) that I pass to the csv read looks like this:
> {code}
> StructType( StructField(Output,StringType,true), ...
> StructField(output,StringType,true), ...)
> {code}
> The code that does the read is this
> {code}
> sqlContext.read
> .format("csv")
> .option("header", "false") // Use first line of all files as header
> .option("inferSchema", "false") // Automatically infer data types
> .schema(dfSchema)
> .csv(dataFile)
> {code}
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[jira] [Commented] (SPARK-17041) Columns in schema are no longer case sensitive when reading csv file
[
https://issues.apache.org/jira/browse/SPARK-17041?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15420105#comment-15420105
]
Dongjoon Hyun commented on SPARK-17041:
---
Hi, [~barrybecker4]
I reproduced your problems and I think I can give you the solution.
{code}
scala> spark.read.format("csv").option("header", "false").option("inferSchema",
"false").schema(StructType(Seq(StructField("c", StringType, false),
StructField("C", StringType, false.csv("/tmp/csv_caseSensitive").show
org.apache.spark.sql.AnalysisException: Reference 'c' is ambiguous, could be:
c#45, c#46.;
...
scala> sql("set spark.sql.caseSensitive=true")
res9: org.apache.spark.sql.DataFrame = [key: string, value: string]
scala> spark.read.format("csv").option("header", "false").option("inferSchema",
"false").schema(StructType(Seq(StructField("c", StringType, false),
StructField("C", StringType, false.csv("/tmp/csv_caseSensitive").show
+---+---+
| c| C|
+---+---+
| c1| C1|
| 1| 2|
+---+---+
{code}
> Columns in schema are no longer case sensitive when reading csv file
>
>
> Key: SPARK-17041
> URL: https://issues.apache.org/jira/browse/SPARK-17041
> Project: Spark
> Issue Type: Bug
> Components: Input/Output
>Affects Versions: 2.0.0
>Reporter: Barry Becker
>
> It used to be (in spark 1.6.2) that I could read a csv file that had columns
> with names that differed only by case. For example, one column may be
> "output" and another called "Output". Now (with spark 2.0.0) if I try to read
> such a file, I get an error like this:
> {code}
> org.apache.spark.sql.AnalysisException: Reference 'Output' is ambiguous,
> could be: Output#1263, Output#1295.;
> {code}
> The schema (dfSchema below) that I pass to the csv read looks like this:
> {code}
> StructType( StructField(Output,StringType,true), ...
> StructField(output,StringType,true), ...)
> {code}
> The code that does the read is this
> {code}
> sqlContext.read
> .format("csv")
> .option("header", "false") // Use first line of all files as header
> .option("inferSchema", "false") // Automatically infer data types
> .schema(dfSchema)
> .csv(dataFile)
> {code}
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[jira] [Commented] (SPARK-17041) Columns in schema are no longer case sensitive when reading csv file
[
https://issues.apache.org/jira/browse/SPARK-17041?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15420100#comment-15420100
]
Dongjoon Hyun commented on SPARK-17041:
---
Hi, [~barrybecker4].
Could you give us more reproducible example?
> Columns in schema are no longer case sensitive when reading csv file
>
>
> Key: SPARK-17041
> URL: https://issues.apache.org/jira/browse/SPARK-17041
> Project: Spark
> Issue Type: Bug
> Components: Input/Output
>Affects Versions: 2.0.0
>Reporter: Barry Becker
>
> It used to be (in spark 1.6.2) that I could read a csv file that had columns
> with names that differed only by case. For example, one column may be
> "output" and another called "Output". Now (with spark 2.0.0) if I try to read
> such a file, I get an error like this:
> {code}
> org.apache.spark.sql.AnalysisException: Reference 'Output' is ambiguous,
> could be: Output#1263, Output#1295.;
> {code}
> The schema (dfSchema below) that I pass to the csv read looks like this:
> {code}
> StructType( StructField(Output,StringType,true), ...
> StructField(output,StringType,true), ...)
> {code}
> The code that does the read is this
> {code}
> sqlContext.read
> .format("csv")
> .option("header", "false") // Use first line of all files as header
> .option("inferSchema", "false") // Automatically infer data types
> .schema(dfSchema)
> .csv(dataFile)
> {code}
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[jira] [Commented] (SPARK-17041) Columns in schema are no longer case sensitive when reading csv file
[
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]
Barry Becker commented on SPARK-17041:
--
I'm not sure either. How can we find out? I think it would be better if columns
were case sensitive. Was the change intentional? This was a dataset from a
client, and for whatever reason, they thought it was reasonable to have columns
that varied only by case. Since it was something that worked before, I thought
it might be considered a regression, but maybe it should be a feature request.
In our product, someone may rename a column from "output" to "Output". If the
column names are not case sensitive, I'm not sure what problems this might
cause. At a minimum, the rename will probably not work.
> Columns in schema are no longer case sensitive when reading csv file
>
>
> Key: SPARK-17041
> URL: https://issues.apache.org/jira/browse/SPARK-17041
> Project: Spark
> Issue Type: Bug
> Components: Input/Output
>Affects Versions: 2.0.0
>Reporter: Barry Becker
>
> It used to be (in spark 1.6.2) that I could read a csv file that had columns
> with names that differed only by case. For example, one column may be
> "output" and another called "Output". Now (with spark 2.0.0) if I try to read
> such a file, I get an error like this:
> {code}
> org.apache.spark.sql.AnalysisException: Reference 'Output' is ambiguous,
> could be: Output#1263, Output#1295.;
> {code}
> The schema (dfSchema below) that I pass to the csv read looks like this:
> {code}
> StructType( StructField(Output,StringType,true), ...
> StructField(output,StringType,true), ...)
> {code}
> The code that does the read is this
> {code}
> sqlContext.read
> .format("csv")
> .option("header", "false") // Use first line of all files as header
> .option("inferSchema", "false") // Automatically infer data types
> .schema(dfSchema)
> .csv(dataFile)
> {code}
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[jira] [Commented] (SPARK-17041) Columns in schema are no longer case sensitive when reading csv file
[
https://issues.apache.org/jira/browse/SPARK-17041?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15419133#comment-15419133
]
Sean Owen commented on SPARK-17041:
---
Behavior changes across major versions. I'm not sure this is a bug just because
behavior is different.
> Columns in schema are no longer case sensitive when reading csv file
>
>
> Key: SPARK-17041
> URL: https://issues.apache.org/jira/browse/SPARK-17041
> Project: Spark
> Issue Type: Bug
> Components: Input/Output
>Affects Versions: 2.0.0
>Reporter: Barry Becker
>
> It used to be (in spark 1.6.2) that I could read a csv file that had columns
> with names that differed only by case. For example, one column may be
> "output" and another called "Output". Now (with spark 2.0.0) if I try to read
> such a file, I get an error like this:
> {code}
> org.apache.spark.sql.AnalysisException: Reference 'Output' is ambiguous,
> could be: Output#1263, Output#1295.;
> {code}
> The schema (dfSchema below) that I pass to the csv read looks like this:
> {code}
> StructType( StructField(Output,StringType,true), ...
> StructField(output,StringType,true), ...)
> {code}
> The code that does the read is this
> {code}
> sqlContext.read
> .format("csv")
> .option("header", "false") // Use first line of all files as header
> .option("inferSchema", "false") // Automatically infer data types
> .schema(dfSchema)
> .csv(dataFile)
> {code}
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