kondziolka9ld created SPARK-34564: ------------------------------------- Summary: 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: Question Components: SQL Affects Versions: 3.0.1 Reporter: kondziolka9ld
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$Serializer.apply(ExpressionEncoder.scala:211) ... 60 more {code} In opposition to *spark-2.4.7* where it is possible to create dataframe with such values: {code:java} scala> val df = List(("some date", new Date(Int.MaxValue)), ("some corner case date", new Date(Long.MaxValue))).toDF df: org.apache.spark.sql.DataFrame = [_1: string, _2: date]scala> df.show +--------------------+-------------+ | _1| _2| +--------------------+-------------+ | some date| 1970-01-25| |some corner case ...|1701498-03-18| +--------------------+-------------+ {code} Anyway, I am aware of the fact that during collecting these data I will got another result: {code:java} scala> df.collect res10: Array[org.apache.spark.sql.Row] = Array([some date,1970-01-25], [some corner case date,?498-03-18]) {code} what seems to be natural as: {code:java} scala> new java.sql.Date(Long.MaxValue) res1: java.sql.Date = ?994-08-17 {code} ---- When it comes to easier reproduction, please consider: {code:java} scala> org.apache.spark.sql.catalyst.util.DateTimeUtils.fromJavaDate(new java.sql.Date(Long.MaxValue)) java.lang.ArithmeticException: integer overflow at java.lang.Math.toIntExact(Math.java:1011) at org.apache.spark.sql.catalyst.util.DateTimeUtils$.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? -- This message was sent by Atlassian Jira (v8.3.4#803005) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org