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https://issues.apache.org/jira/browse/SPARK-45424?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17772365#comment-17772365
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Andy Grove commented on SPARK-45424:
------------------------------------
The regression seems to have been introduced in
https://issues.apache.org/jira/browse/SPARK-39280 and/or
https://issues.apache.org/jira/browse/SPARK-39281
Commits:
[https://github.com/apache/spark/commit/b1c0d599ba32a4562ae1697e3f488264f1d03c76]
[https://github.com/apache/spark/commit/3192bbd29585607d43d0819c6c2d3ac00180261a]
[~fanjia] Do you understand why this behavior has changed?
> Regression in CSV schema inference when timestamps do not match specified
> timestampFormat
> -----------------------------------------------------------------------------------------
>
> Key: SPARK-45424
> URL: https://issues.apache.org/jira/browse/SPARK-45424
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 3.5.0
> Reporter: Andy Grove
> Priority: Major
>
> There is a regression in Spark 3.5.0 when inferring the schema of CSV files
> containing timestamps, where a column will be inferred as a timestamp even if
> the contents do not match the specified timestampFormat.
> *Test Data*
> I have the following CSV file:
> {code:java}
> 2884-06-24T02:45:51.138
> 2884-06-24T02:45:51.138
> 2884-06-24T02:45:51.138
> {code}
> *Spark 3.4.0 Behavior (correct)*
> In Spark 3.4.0, if I specify the correct timestamp format, then the schema is
> inferred as timestamp:
> {code:java}
> scala> val df = spark.read.option("timestampFormat",
> "yyyy-MM-dd'T'HH:mm:ss.SSS").option("inferSchema",
> true).csv("/tmp/timestamps.csv")
> df: org.apache.spark.sql.DataFrame = [_c0: timestamp]
> {code}
> If I specify an incompatible timestampFormat, then the schema is inferred as
> string:
> {code:java}
> scala> val df = spark.read.option("timestampFormat",
> "yyyy-MM-dd'T'HH:mm:ss").option("inferSchema",
> true).csv("/tmp/timestamps.csv")
> df: org.apache.spark.sql.DataFrame = [_c0: string]
> {code}
> *Spark 3.5.0*
> In Spark 3.5.0, the column will be inferred as timestamp even if the data
> does not match the specified timestampFormat.
> {code:java}
> scala> val df = spark.read.option("timestampFormat",
> "yyyy-MM-dd'T'HH:mm:ss").option("inferSchema",
> true).csv("/tmp/timestamps.csv")
> df: org.apache.spark.sql.DataFrame = [_c0: timestamp]
> {code}
> Reading the DataFrame then results in an error:
> {code:java}
> Caused by: java.time.format.DateTimeParseException: Text
> '2884-06-24T02:45:51.138' could not be parsed, unparsed text found at index 19
> {code}
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