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https://issues.apache.org/jira/browse/SPARK-15840?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15322147#comment-15322147
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Hyukjin Kwon commented on SPARK-15840:
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For custom dateFormat, here there are,
https://github.com/apache/spark/blob/32f2f95dbdfb21491e46d4b608fd4e8ac7ab8973/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/csv/CSVSuite.scala#L450-L496
and for inferring type...
https://github.com/apache/spark/blob/32f2f95dbdfb21491e46d4b608fd4e8ac7ab8973/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/csv/CSVSuite.scala#L116-L151
> New csv reader does not "determine the input schema"
> ----------------------------------------------------
>
> Key: SPARK-15840
> URL: https://issues.apache.org/jira/browse/SPARK-15840
> Project: Spark
> Issue Type: Bug
> Components: PySpark, SQL
> Affects Versions: 2.0.0
> Reporter: Ernst Sjöstrand
>
> When testing the new csv reader I found that it would not determine the input
> schema as is stated in the documentation.
> (I used this documentation:
> https://people.apache.org/~pwendell/spark-nightly/spark-master-docs/latest/api/python/pyspark.sql.html#pyspark.sql.SQLContext
> )
> So either there is a bug in the implementation or in the documentation.
> This also means that things like dateFormat are ignore it seems like.
> Here's a quick test in pyspark (using Python3):
> a = spark.read.csv("/home/ernst/test.csv")
> a.printSchema()
> print(a.dtypes)
> a.show()
> {noformat}
> root
> |-- _c0: string (nullable = true)
> [('_c0', 'string')]
> +---+
> |_c0|
> +---+
> | 1|
> | 2|
> | 3|
> | 4|
> +---+
> {noformat}
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