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https://issues.apache.org/jira/browse/SPARK-15856?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15326065#comment-15326065
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Reynold Xin commented on SPARK-15856:
-------------------------------------
Note that we have decided to only revert the SQLContext.range API in this
ticket.
> Revert API breaking changes made in SQLContext.range
> ----------------------------------------------------
>
> Key: SPARK-15856
> URL: https://issues.apache.org/jira/browse/SPARK-15856
> Project: Spark
> Issue Type: Sub-task
> Components: SQL
> Reporter: Cheng Lian
> Assignee: Wenchen Fan
> Fix For: 2.0.0
>
>
> In Spark 2.0, after unifying Datasets and DataFrames, we made two API
> breaking changes:
> # {{DataFrameReader.text()}} now returns {{Dataset\[String\]}} instead of
> {{DataFrame}}
> # {{SQLContext.range()}} now returns {{Dataset\[java.lang.Long\]}} instead of
> {{DataFrame}}
> However, these two changes introduced several inconsistencies and problems:
> # {{spark.read.text()}} silently discards partitioned columns when reading a
> partitioned table in text format since {{Dataset\[String\]}} only contains a
> single field. Users have to use {{spark.read.format("text").load()}} to
> workaround this, which is pretty confusing and error-prone.
> # All data source shortcut methods in `DataFrameReader` return {{DataFrame}}
> (aka {{Dataset\[Row\]}}) except for {{DataFrameReader.text()}}.
> # When applying typed operations over Datasets returned by {{spark.range()}},
> weird schema changes may happen. Please refer to SPARK-15632 for more details.
> Due to these reasons, we decided to revert these two changes.
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