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https://issues.apache.org/jira/browse/SPARK-40624?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=17611803#comment-17611803
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Bruce Robbins commented on SPARK-40624:
---
That's not a Spark API throwing that exception. Instead,
{{scala.math.BigDecimal#apply}} (which you call via {{BigDecimal("1.0/0")}}) is
throwing the exception.
In a plain Scala REPL (no Spark), I can reproduce:
{noformat}
bash-3.2$ bin/scala
Welcome to Scala 2.12.4 (Java HotSpot(TM) 64-Bit Server VM, Java 1.8.0_311).
Type in expressions for evaluation. Or try :help.
scala> BigDecimal("1.0/0")
java.lang.NumberFormatException
at java.math.BigDecimal.(BigDecimal.java:497)
at java.math.BigDecimal.(BigDecimal.java:383)
at java.math.BigDecimal.(BigDecimal.java:809)
at scala.math.BigDecimal$.exact(BigDecimal.scala:124)
at scala.math.BigDecimal$.apply(BigDecimal.scala:282)
... 28 elided
scala>
{noformat}
My guess is that {{BigDecimal#apply(x: String)}} was not written to expect an x
representing an expression, just representing a number. Even "2/1" fails:
{noformat}
scala> BigDecimal("2/1")
java.lang.NumberFormatException
at java.math.BigDecimal.(BigDecimal.java:497)
at java.math.BigDecimal.(BigDecimal.java:383)
at java.math.BigDecimal.(BigDecimal.java:809)
at scala.math.BigDecimal$.exact(BigDecimal.scala:124)
at scala.math.BigDecimal$.apply(BigDecimal.scala:282)
... 28 elided
scala> scala> BigDecimal("2.3")
res7: scala.math.BigDecimal = 2.3
scala>
{noformat}
> A DECIMAL value with division by 0 errors in DataFrame but evaluates to NULL
> in SparkSQL
>
>
> Key: SPARK-40624
> URL: https://issues.apache.org/jira/browse/SPARK-40624
> Project: Spark
> Issue Type: Bug
> Components: Spark Shell
>Affects Versions: 3.2.1
>Reporter: xsys
>Priority: Major
>
> h3. Describe the bug
> Storing an invalid value (e.g. {{{}BigDecimal("1.0/0"){}}}) via
> {{spark-shell}} errors out during RDD creation. However, {{1.0/0}} evaluates
> to {{NULL}} if the value is inserted into a {{DECIMAL(20,10)}} column of a
> table via {{{}spark-sql{}}}.
> h3. To Reproduce
> On Spark 3.2.1 (commit {{{}4f25b3f712{}}}), using {{{}spark-sql{}}}:
> {code:java}
> $SPARK_HOME/bin/spark-sql{code}
> Execute the following: (evaluated to {{{}NULL{}}})
> {code:java}
> spark-sql> create table decimal_vals(c1 DECIMAL(20,10)) stored as ORC;
> spark-sql> insert into decimal_vals 1.0/0;
> spark-sql> select * from ws71;
> 71 NULL{code}
> Using {{{}spark-shell{}}}:
> {code:java}
> $SPARK_HOME/bin/spark-shell{code}
> Execute the following: (errors out during RDD creation)
> {code:java}
> scala> val rdd = sc.parallelize(Seq(Row(BigDecimal("1.0/0"
> java.lang.NumberFormatException
> at java.math.BigDecimal.(BigDecimal.java:497)
> at java.math.BigDecimal.(BigDecimal.java:383)
> at java.math.BigDecimal.(BigDecimal.java:809)
> at scala.math.BigDecimal$.exact(BigDecimal.scala:126)
> at scala.math.BigDecimal$.apply(BigDecimal.scala:284)
> ... 49 elided{code}
> h3. Expected behavior
> We expect the two Spark interfaces ({{{}spark-sql{}}} & {{{}spark-shell{}}})
> to behave consistently for the same data type & input combination
> ({{{}BigDecimal{}}}/{{{}DECIMAL(20,10){}}} and {{{}1.0/0{}}}).
>
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