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https://issues.apache.org/jira/browse/SPARK-39910?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Wenchen Fan resolved SPARK-39910.
---------------------------------
Fix Version/s: 3.5.1
4.0.0
Resolution: Fixed
Issue resolved by pull request 43463
[https://github.com/apache/spark/pull/43463]
> DataFrameReader API cannot read files from hadoop archives (.har)
> -----------------------------------------------------------------
>
> Key: SPARK-39910
> URL: https://issues.apache.org/jira/browse/SPARK-39910
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 3.0.3, 3.1.3, 3.3.0, 3.2.2
> Reporter: Christophe Préaud
> Assignee: Christophe Préaud
> Priority: Minor
> Labels: DataFrameReader, pull-request-available
> Fix For: 3.5.1, 4.0.0
>
>
> Reading a file from an hadoop archive using the DataFrameReader API returns
> an empty Dataset:
> {code:java}
> scala> val df =
> spark.read.textFile("har:///user/preaudc/logs/lead/jp/2022/202207.har/20220719")
> df: org.apache.spark.sql.Dataset[String] = [value: string]
> scala> df.count
> res7: Long = 0 {code}
>
> On the other hand, reading the same file, from the same hadoop archive, but
> using the RDD API yields the correct result:
> {code:java}
> scala> val df =
> sc.textFile("har:///user/preaudc/logs/lead/jp/2022/202207.har/20220719").toDF("value")
> df: org.apache.spark.sql.DataFrame = [value: string]
> scala> df.count
> res8: Long = 5589 {code}
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