[jira] [Commented] (SPARK-12932) Bad error message with trying to create Dataset from RDD of Java objects that are not bean-compliant

["Reynold Xin (JIRA)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/SPARK-12932?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15109386#comment-15109386 ] 

Reynold Xin commented on SPARK-12932:
-------------------------------------

Ah ok. This makes sense.

[~andygrove] would you like to submit a patch for this?


> Bad error message with trying to create Dataset from RDD of Java objects that are not bean-compliant
> ----------------------------------------------------------------------------------------------------
>
>                 Key: SPARK-12932
>                 URL: https://issues.apache.org/jira/browse/SPARK-12932
>             Project: Spark
>          Issue Type: Bug
>          Components: Java API
>    Affects Versions: 1.6.0
>         Environment: Ubuntu 15.10 / Java 8
>            Reporter: Andy Grove
>
> When trying to create a Dataset from an RDD of Person (all using the Java API), I got the error "java.lang.UnsupportedOperationException: no encoder found for example_java.dataset.Person". This is not a very helpful error and no other logging information was apparent to help troubleshoot this.
> It turned out that the problem was that my Person class did not have a default constructor and also did not have setter methods and that was the root cause.
> This JIRA is for implementing a more usful error message to help Java developers who are trying out the Dataset API for the first time.
> The full stack trace is:
> {{Exception in thread "main" java.lang.UnsupportedOperationException: no encoder found for example_java.common.Person
> 	at org.apache.spark.sql.catalyst.JavaTypeInference$.org$apache$spark$sql$catalyst$JavaTypeInference$$extractorFor(JavaTypeInference.scala:403)
> 	at org.apache.spark.sql.catalyst.JavaTypeInference$.extractorsFor(JavaTypeInference.scala:314)
> 	at org.apache.spark.sql.catalyst.encoders.ExpressionEncoder$.javaBean(ExpressionEncoder.scala:75)
> 	at org.apache.spark.sql.Encoders$.bean(Encoder.scala:176)
> 	at org.apache.spark.sql.Encoders.bean(Encoder.scala)
> }}
> NOTE that if I do provide EITHER the default constructor OR the setters, but not both, then I get a stack trace with much more useful information, but omitting BOTH causes this issue.
> The original source is below.
> {code:title=Example.java}
> public class JavaDatasetExample {
>     public static void main(String[] args) throws Exception {
>         SparkConf sparkConf = new SparkConf()
>                 .setAppName("Example")
>                 .setMaster("local[*]");
>         JavaSparkContext sc = new JavaSparkContext(sparkConf);
>         SQLContext sqlContext = new SQLContext(sc);
>         List<Person> people = ImmutableList.of(
>                 new Person("Joe", "Bloggs", 21, "NY")
>         );
>         Dataset<Person> dataset = sqlContext.createDataset(people, Encoders.bean(Person.class));
> {code}
> {code:title=Person.java}
> class Person implements Serializable {
>     String first;
>     String last;
>     int age;
>     String state;
>     public Person() {
>     }
>     public Person(String first, String last, int age, String state) {
>         this.first = first;
>         this.last = last;
>         this.age = age;
>         this.state = state;
>     }
>     public String getFirst() {
>         return first;
>     }
>     public String getLast() {
>         return last;
>     }
>     public int getAge() {
>         return age;
>     }
>     public String getState() {
>         return state;
>     }
> }
> {code}



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