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https://issues.apache.org/jira/browse/SPARK-14463?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15240640#comment-15240640
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Cheng Lian commented on SPARK-14463:
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Should we simply throw an exception when text data source is used together with
partitioning?
> read.text broken for partitioned tables
> ---------------------------------------
>
> Key: SPARK-14463
> URL: https://issues.apache.org/jira/browse/SPARK-14463
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Reporter: Michael Armbrust
> Priority: Critical
>
> Strongly typing the return values of {{read.text}} as {{Dataset\[String]}}
> breaks when trying to load a partitioned table (or any table where the path
> looks partitioned)
> {code}
> Seq((1, "test"))
> .toDF("a", "b")
> .write
> .format("text")
> .partitionBy("a")
> .save("/home/michael/text-part-bug")
> sqlContext.read.text("/home/michael/text-part-bug")
> {code}
> {code}
> org.apache.spark.sql.AnalysisException: Try to map struct<value:string,a:int>
> to Tuple1, but failed as the number of fields does not line up.
> - Input schema: struct<value:string,a:int>
> - Target schema: struct<value:string>;
> at
> org.apache.spark.sql.catalyst.encoders.ExpressionEncoder.org$apache$spark$sql$catalyst$encoders$ExpressionEncoder$$fail$1(ExpressionEncoder.scala:265)
> at
> org.apache.spark.sql.catalyst.encoders.ExpressionEncoder.validate(ExpressionEncoder.scala:279)
> at org.apache.spark.sql.Dataset.<init>(Dataset.scala:197)
> at org.apache.spark.sql.Dataset.<init>(Dataset.scala:168)
> at org.apache.spark.sql.Dataset$.apply(Dataset.scala:57)
> at org.apache.spark.sql.Dataset.as(Dataset.scala:357)
> at org.apache.spark.sql.DataFrameReader.text(DataFrameReader.scala:450)
> {code}
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