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Marc Le Bihan edited comment on SPARK-45311 at 11/12/23 10:55 AM: ------------------------------------------------------------------ The problem *java.util.NoSuchElementException: None.get* happens in `{color:#0033b3} {color}{color:#000000}JavaBeanEncoder{color}({color:#000000}tag{color}, {color:#000000}fields{color})` case of `deserializerFor` method in `ScalaReflexion` (sorry for the indentation that I had to change due to a bad copy-paste) ```scala {color:#0033b3}case {color}{color:#000000}JavaBeanEncoder{color}({color:#000000}tag{color}, {color:#000000}fields{color}) => {color:#0033b3}val {color}{color:#000000}setters {color}= {color:#000000}fields{color}.map { f => {color:#0033b3}val {color}{color:#000000}newTypePath {color}= walkedTypePath.recordField( f.enc.clsTag.runtimeClass.getName, f.name) {color:#0033b3} val {color}{color:#000000}setter {color}= expressionWithNullSafety( deserializerFor( f.enc, addToPath(path, f.name, f.enc.dataType, {color:#000000}newTypePath{color}), {color:#000000}newTypePath{color}), nullable = f.nullable, {color:#000000}newTypePath{color}) f.writeMethod.get -> {color:#000000}setter{color} \{color}} ``` `f.writeMethod` is valued with `None` if it happens that the method observed, a `getSomething()` or `isSomething()` doesn't have a correspondant setter method `setSomething(...)`. I cannot tell if it's the new wished behavior for Spark after the `3.4.x` or if it's a regression. But until `3.3.x`, it was possible to have class having `isSomething()` methods, in order to do some checkings, without the need of having a setter. — The workaround is to rename a method not having a setter to `something()` only, without `get` or `is` prefix. Then Spark will skip it. was (Author: mlebihan): The problem *java.util.NoSuchElementException: None.get* happens in `{color:#0033b3} {color}{color:#000000}JavaBeanEncoder{color}({color:#000000}tag{color}, {color:#000000}fields{color})` case of `deserializerFor` method in `ScalaReflexion` (sorry for the indentation that I had to change due to a bad copy-paste) ```scala {color:#0033b3}case {color}{color:#000000}JavaBeanEncoder{color}({color:#000000}tag{color}, {color:#000000}fields{color}) => {color:#0033b3}val {color}{color:#000000}setters {color}= {color:#000000}fields{color}.map { f => {color:#0033b3}val {color}{color:#000000}newTypePath {color}= walkedTypePath.recordField( f.enc.clsTag.runtimeClass.getName, f.name) {color:#0033b3} val {color}{color:#000000}setter {color}= expressionWithNullSafety( deserializerFor( f.enc, addToPath(path, f.name, f.enc.dataType, {color:#000000}newTypePath{color}), {color:#000000}newTypePath{color}), nullable = f.nullable, {color:#000000}newTypePath{color}) f.writeMethod.get -> {color:#000000}setter {color}{color:#000000} {color}} ``` `f.writeMethod` is valued with `None` if it happens that the method observed, a `getSomething()` or `isSomething()` doesn't have a correspondant setter method `setSomething(...)`. I cannot tell if it's the new wished behavior for Spark after the `3.4.x` or if it's a regression. But until `3.3.x`, it was possible to have class having `isSomething()` methods, in order to do some checkings, without the need of having a setter. --- The workaround is to rename a method not having a setter to `something()` only, without `get` or `is` prefix. Then Spark will skip it. > Encoder fails on many "NoSuchElementException: None.get" since 3.4.x, search > for an encoder for a generic type, and since 3.5.x isn't "an expression > encoder" > ------------------------------------------------------------------------------------------------------------------------------------------------------------- > > Key: SPARK-45311 > URL: https://issues.apache.org/jira/browse/SPARK-45311 > Project: Spark > Issue Type: Bug > Components: Spark Core > Affects Versions: 3.4.0, 3.4.1, 3.5.0 > Environment: Debian 12 > Java 17 > Underlying Spring-Boot 2.7.14 > Reporter: Marc Le Bihan > Priority: Major > > If you find it convenient, you might clone the > [https://gitlab.com/territoirevif/minimal-tests-spark-issue] project (that > does many operations around cities, local authorities and accounting with > open data) where I've extracted from my work what's necessary to make a set > of 35 tests that run correctly with Spark 3.3.x, and show the troubles > encountered with 3.4.x and 3.5.x. > > It is working well with Spark 3.2.x, 3.3.x. But as soon as I selec{*}t Spark > 3.4.x{*}, where the encoder seems to have deeply changed, the encoder fails > with two problems: > > *1)* It throws *java.util.NoSuchElementException: None.get* messages > everywhere. > Asking over the Internet, I wasn't alone facing this problem. Reading it, > you'll see that I've attempted a debug but my Scala skills are low. > [https://stackoverflow.com/questions/76036349/encoders-bean-doesnt-work-anymore-on-a-java-pojo-with-spark-3-4-0] > {color:#172b4d}by the way, if possible, the encoder and decoder functions > should forward a parameter as soon as the name of the field being handled is > known, and then all the long of their process, so that when the encoder is at > any point where it has to throw an exception, it knows the field it is > handling in its specific call and can send a message like:{color} > {color:#00875a}_java.util.NoSuchElementException: None.get when encoding [the > method or field it was targeting]_{color} > > *2)* *Not found an encoder of the type RS to Spark SQL internal > representation.* Consider to change the input type to one of supported at > (...) > Or : Not found an encoder of the type *OMI_ID* to Spark SQL internal > representation (...) > > where *RS* and *OMI_ID* are generic types. > This is strange. > [https://stackoverflow.com/questions/76045255/encoders-bean-attempts-to-check-the-validity-of-a-return-type-considering-its-ge] > > *3)* When I switch to the *Spark 3.5.0* version, the same problems remain, > but another add itself to the list: > "{*}Only expression encoders are supported for now{*}" on what was accepted > and working before. > -- This message was sent by Atlassian Jira (v8.20.10#820010) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org