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https://issues.apache.org/jira/browse/SPARK-32582?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17175143#comment-17175143
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Lantao Jin commented on SPARK-32582:
------------------------------------
{code}
files.toIterator.map(file => readSchema(file.getPath, conf,
ignoreCorruptFiles)).collectFirst
{code}
{{collectFirst()}} will break out when its iterator found a matching value.
{code}
def collectFirst[B](pf: PartialFunction[A, B]): Option[B] = {
for (x <- self.toIterator) { // make sure to use an iterator or `seq`
if (pf isDefinedAt x)
return Some(pf(x))
}
None
}
{code}
So in most cases, it just reads only one file.
> Spark SQL Infer Schema Performance
> ----------------------------------
>
> Key: SPARK-32582
> URL: https://issues.apache.org/jira/browse/SPARK-32582
> Project: Spark
> Issue Type: Improvement
> Components: SQL
> Affects Versions: 2.4.6, 3.0.0
> Reporter: Jarred Li
> Priority: Major
>
> When infer schema is enabled, it tries to list all the files in the table,
> however only one of the file is used to read schema informaiton. The
> performance is impacted due to list all the files in the table when the
> number of partitions is larger.
>
> See the code in
> "[https://github.com/apache/spark/blob/master/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/orc/OrcUtils.scala#88]";,
> all the files in the table are input, however only one of the file's schema
> is used to infer schema.
>
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