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https://issues.apache.org/jira/browse/SPARK-25199?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16589252#comment-16589252
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Apache Spark commented on SPARK-25199:
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User 'yunjzhang' has created a pull request for this issue:
https://github.com/apache/spark/pull/22177
> InferSchema "all Strings" if one of many CSVs is empty
> ------------------------------------------------------
>
> Key: SPARK-25199
> URL: https://issues.apache.org/jira/browse/SPARK-25199
> Project: Spark
> Issue Type: Bug
> Components: Input/Output
> Affects Versions: 2.2.1
> Environment: I discovered this on AWS Glue, which uses Spark 2.2.1
> Reporter: Neil McGuigan
> Priority: Minor
> Labels: newbie
>
> Spark can load multiple CSV files in one read:
> df = spark.read.format("csv").option("header", "true").option("inferSchema",
> "true").load("/*.csv")
> However, if one of these files is empty (though it has a header), Spark will
> set all column types to "String"
> Spark should skip a file for inference if it contains no (non-header) rows
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