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Posted to issues@spark.apache.org by "kondziolka9ld (Jira)" <ji...@apache.org> on 2021/03/01 09:51:00 UTC
[jira] [Commented] (SPARK-34564) DateTimeUtils.fromJavaDate fails
for very late dates during casting to Int
[ https://issues.apache.org/jira/browse/SPARK-34564?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17292786#comment-17292786 ]
kondziolka9ld commented on SPARK-34564:
---------------------------------------
> We changed the behaviour intentionally because we do believe that it is better to return an error instead of an incorrect result silently
Great!
> How? What would you like to see?
I would rather got `IllegalArgumentException` or some another more verbose exception.
Please note that for
```
scala> org.apache.spark.sql.catalyst.util.DateTimeUtils.fromJavaTimestamp(new java.sql.Timestamp(Long.MaxValue))
java.lang.ArithmeticException: long overflow
at java.lang.Math.multiplyExact(Math.java:892)
at org.apache.spark.sql.catalyst.util.DateTimeUtils$.fromMillis(DateTimeUtils.scala:227)
at org.apache.spark.sql.catalyst.util.DateTimeUtils$.fromJavaTimestamp(DateTimeUtils.scala:184)
... 47 elided
```
it is very similar issue.
> DateTimeUtils.fromJavaDate fails for very late dates during casting to Int
> --------------------------------------------------------------------------
>
> Key: SPARK-34564
> URL: https://issues.apache.org/jira/browse/SPARK-34564
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 3.0.1, 3.2.0, 3.1.2
> Reporter: kondziolka9ld
> Priority: Major
>
> Please consider a following scenario on *spark-3.0.1*:
> {code:java}
> scala> List(("some date", new Date(Int.MaxValue)), ("some corner case date", new Date(Long.MaxValue))).toDF
> java.lang.RuntimeException: Error while encoding: java.lang.ArithmeticException: integer overflow
> staticinvoke(class org.apache.spark.unsafe.types.UTF8String, StringType, fromString, knownnotnull(assertnotnull(input[0, scala.Tuple2, true]))._1, true, false) AS _1#0
> staticinvoke(class org.apache.spark.sql.catalyst.util.DateTimeUtils$, DateType, fromJavaDate, knownnotnull(assertnotnull(input[0, scala.Tuple2, true]))._2, true, false) AS _2#1
> at org.apache.spark.sql.catalyst.encoders.ExpressionEncoder$Serializer.apply(ExpressionEncoder.scala:215)
> at org.apache.spark.sql.SparkSession.$anonfun$createDataset$1(SparkSession.scala:466)
> at scala.collection.TraversableLike.$anonfun$map$1(TraversableLike.scala:238)
> at scala.collection.immutable.List.foreach(List.scala:392)
> at scala.collection.TraversableLike.map(TraversableLike.scala:238)
> at scala.collection.TraversableLike.map$(TraversableLike.scala:231)
> at scala.collection.immutable.List.map(List.scala:298)
> at org.apache.spark.sql.SparkSession.createDataset(SparkSession.scala:466)
> at org.apache.spark.sql.SQLContext.createDataset(SQLContext.scala:353)
> at org.apache.spark.sql.SQLImplicits.localSeqToDatasetHolder(SQLImplicits.scala:231)
> ... 51 elided
> Caused by: java.lang.ArithmeticException: integer overflow
> at java.lang.Math.toIntExact(Math.java:1011)
> at org.apache.spark.sql.catalyst.util.DateTimeUtils$.fromJavaDate(DateTimeUtils.scala:111)
> at org.apache.spark.sql.catalyst.util.DateTimeUtils.fromJavaDate(DateTimeUtils.scala)
> at org.apache.spark.sql.catalyst.expressions.GeneratedClass$SpecificUnsafeProjection.apply(Unknown Source)
> at org.apache.spark.sql.catalyst.encoders.ExpressionEncoder$Serializer.apply(ExpressionEncoder.scala:211)
> ... 60 more
> {code}
> In opposition to *spark-2.4.7* where it is possible to create dataframe with such values:
> {code:java}
> scala> val df = List(("some date", new Date(Int.MaxValue)), ("some corner case date", new Date(Long.MaxValue))).toDF
> df: org.apache.spark.sql.DataFrame = [_1: string, _2: date]scala> df.show
> +--------------------+-------------+
> | _1| _2|
> +--------------------+-------------+
> | some date| 1970-01-25|
> |some corner case ...|1701498-03-18|
> +--------------------+-------------+
> {code}
> Anyway, I am aware of the fact that during collecting these data I will got another result:
> {code:java}
> scala> df.collect
> res10: Array[org.apache.spark.sql.Row] = Array([some date,1970-01-25], [some corner case date,?498-03-18])
> {code}
> what seems to be natural because of behaviour of *java.sql.Date*:
> {code:java}
> scala> new java.sql.Date(Long.MaxValue)
> res1: java.sql.Date = ?994-08-17
> {code}
>
> ----
> When it comes to easier reproduction, please consider:
> {code:java}
> scala> org.apache.spark.sql.catalyst.util.DateTimeUtils.fromJavaDate(new java.sql.Date(Long.MaxValue))
> java.lang.ArithmeticException: integer overflow
> at java.lang.Math.toIntExact(Math.java:1011)
> at org.apache.spark.sql.catalyst.util.DateTimeUtils$.fromJavaDate(DateTimeUtils.scala:111)
> ... 47 elided
> {code}
> However, the question is even if such late dates are not supported, could it fail in more gentle way?
>
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