While executing the below command
StructType obs = Encoders.bean(Test.class).schema();
I am getting the below error
java.lang.UnsupportedOperationException: Cannot have circular references in bean class, but got the circular reference of class class java.time.ZoneOffset
class Test has OffsetDateTime
field, which is causing the error. If I remove this field the error also goes away.
Is there a way by which I can avoid this circular reference error and also use OffsetDateTime?
java.lang.UnsupportedOperationException: Cannot have circular references in bean class, but got the circular reference of class class java.time.ZoneOffset
at org.apache.spark.sql.errors.QueryExecutionErrors$.cannotHaveCircularReferencesInBeanClassError(QueryExecutionErrors.scala:984)
at org.apache.spark.sql.catalyst.JavaTypeInference$.inferDataType(JavaTypeInference.scala:148)
at org.apache.spark.sql.catalyst.JavaTypeInference$.$anonfun$inferDataType$1(JavaTypeInference.scala:156)
at scala.collection.TraversableLike.$anonfun$map$1(TraversableLike.scala:286)
at scala.collection.IndexedSeqOptimized.foreach(IndexedSeqOptimized.scala:36)
at scala.collection.IndexedSeqOptimized.foreach$(IndexedSeqOptimized.scala:33)
at scala.collection.mutable.ArrayOps$ofRef.foreach(ArrayOps.scala:198)
at scala.collection.TraversableLike.map(TraversableLike.scala:286)
at scala.collection.TraversableLike.map$(TraversableLike.scala:279)
at scala.collection.mutable.ArrayOps$ofRef.map(ArrayOps.scala:198)
at org.apache.spark.sql.catalyst.JavaTypeInference$.inferDataType(JavaTypeInference.scala:154)
at org.apache.spark.sql.catalyst.JavaTypeInference$.inferDataType(JavaTypeInference.scala:134)
at org.apache.spark.sql.catalyst.JavaTypeInference$.$anonfun$inferDataType$1(JavaTypeInference.scala:156)
at scala.collection.TraversableLike.$anonfun$map$1(TraversableLike.scala:286)
at scala.collection.IndexedSeqOptimized.foreach(IndexedSeqOptimized.scala:36)
at scala.collection.IndexedSeqOptimized.foreach$(IndexedSeqOptimized.scala:33)
at scala.collection.mutable.ArrayOps$ofRef.foreach(ArrayOps.scala:198)
at scala.collection.TraversableLike.map(TraversableLike.scala:286)
at scala.collection.TraversableLike.map$(TraversableLike.scala:279)
at scala.collection.mutable.ArrayOps$ofRef.map(ArrayOps.scala:198)
at org.apache.spark.sql.catalyst.JavaTypeInference$.inferDataType(JavaTypeInference.scala:154)
at org.apache.spark.sql.catalyst.JavaTypeInference$.$anonfun$inferDataType$1(JavaTypeInference.scala:156)
at scala.collection.TraversableLike.$anonfun$map$1(TraversableLike.scala:286)
at scala.collection.IndexedSeqOptimized.foreach(IndexedSeqOptimized.scala:36)
at scala.collection.IndexedSeqOptimized.foreach$(IndexedSeqOptimized.scala:33)
at scala.collection.mutable.ArrayOps$ofRef.foreach(ArrayOps.scala:198)
at scala.collection.TraversableLike.map(TraversableLike.scala:286)
at scala.collection.TraversableLike.map$(TraversableLike.scala:279)
at scala.collection.mutable.ArrayOps$ofRef.map(ArrayOps.scala:198)
at org.apache.spark.sql.catalyst.JavaTypeInference$.inferDataType(JavaTypeInference.scala:154)
at org.apache.spark.sql.catalyst.JavaTypeInference$.$anonfun$inferDataType$1(JavaTypeInference.scala:156)
at scala.collection.TraversableLike.$anonfun$map$1(TraversableLike.scala:286)
at scala.collection.IndexedSeqOptimized.foreach(IndexedSeqOptimized.scala:36)
at scala.collection.IndexedSeqOptimized.foreach$(IndexedSeqOptimized.scala:33)
at scala.collection.mutable.ArrayOps$ofRef.foreach(ArrayOps.scala:198)
at scala.collection.TraversableLike.map(TraversableLike.scala:286)
at scala.collection.TraversableLike.map$(TraversableLike.scala:279)
at scala.collection.mutable.ArrayOps$ofRef.map(ArrayOps.scala:198)
at org.apache.spark.sql.catalyst.JavaTypeInference$.inferDataType(JavaTypeInference.scala:154)
at org.apache.spark.sql.catalyst.JavaTypeInference$.$anonfun$inferDataType$1(JavaTypeInference.scala:156)
at scala.collection.TraversableLike.$anonfun$map$1(TraversableLike.scala:286)
at scala.collection.IndexedSeqOptimized.foreach(IndexedSeqOptimized.scala:36)
at scala.collection.IndexedSeqOptimized.foreach$(IndexedSeqOptimized.scala:33)
at scala.collection.mutable.ArrayOps$ofRef.foreach(ArrayOps.scala:198)
at scala.collection.TraversableLike.map(TraversableLike.scala:286)
at scala.collection.TraversableLike.map$(TraversableLike.scala:279)
at scala.collection.mutable.ArrayOps$ofRef.map(ArrayOps.scala:198)
at org.apache.spark.sql.catalyst.JavaTypeInference$.inferDataType(JavaTypeInference.scala:154)
at org.apache.spark.sql.catalyst.JavaTypeInference$.inferDataType(JavaTypeInference.scala:70)
at org.apache.spark.sql.catalyst.encoders.ExpressionEncoder$.javaBean(ExpressionEncoder.scala:66)
at org.apache.spark.sql.Encoders$.bean(Encoders.scala:171)
at org.apache.spark.sql.Encoders.bean(Encoders.scala)```
CodePudding user response:
OffsetDateTime
not supported by Encoders
As per Encoder
doc, supported type for bean fields are:
supported types for java bean field: - primitive types: boolean, int, double, etc. - boxed types: Boolean, Integer, Double, etc. - String - java.math.BigDecimal, java.math.BigInteger - time related: java.sql.Date, java.sql.Timestamp, java.time.LocalDate, java.time.Instant - collection types: array, java.util.List, and map - nested java bean.
So it looks like it may not be possible to use OffsetDateTime
as far as I can see.
ZoneOffset
is part of OffsetDateTime
field so call Encoders.bean
might be generating code which keeps referring ZoneOffset
in circular manner.
Use Instant
You can convert a OffsetDateTime
object to the more basic class, Instant
.
Instant instant = odt.toInstant() ;
And back again.
ZoneOffset offset = ZoneOffset.ofHours( -8 ) ;
OffsetDateTime odt = instant.atOffset( offset ) ;