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  1. Spark
  2. SPARK-19980

Basic Dataset transformation on POJOs does not preserves nulls.

    Details

    • Type: Bug
    • Status: Resolved
    • Priority: Major
    • Resolution: Fixed
    • Affects Version/s: 2.1.0
    • Fix Version/s: 2.1.1, 2.2.0
    • Component/s: SQL
    • Labels:
      None

      Description

      Applying an identity map transformation on a statically typed Dataset with a POJO produces an unexpected result.

      Given POJOs:

      public class Stuff implements Serializable {
          private String name;
          public void setName(String name) { this.name = name; }
          public String getName() { return name; }
      }
      
      public class Outer implements Serializable {
          private String name;
          private Stuff stuff;
          public void setName(String name) { this.name = name; }
          public String getName() { return name; }
          public void setStuff(Stuff stuff) { this.stuff = stuff; }
          public Stuff getStuff() { return stuff; }
      }
      

      Produces the result:

      scala> val encoder = Encoders.bean(classOf[Outer])
      encoder: org.apache.spark.sql.Encoder[pojos.Outer] = class[name[0]: string, stuff[0]: struct<name:string>]
      
      scala> val schema = encoder.schema
      schema: org.apache.spark.sql.types.StructType = StructType(StructField(name,StringType,true), StructField(stuff,StructType(StructField(name,StringType,true)),true))
      
      scala> schema.printTreeString
      root
       |-- name: string (nullable = true)
       |-- stuff: struct (nullable = true)
       |    |-- name: string (nullable = true)
      
      
      scala> val df = spark.read.schema(schema).json("stuff.json").as[Outer](encoder)
      df: org.apache.spark.sql.Dataset[pojos.Outer] = [name: string, stuff: struct<name: string>]
      
      scala> df.show()
      +----+-----+
      |name|stuff|
      +----+-----+
      |  v1| null|
      +----+-----+
      
      scala> df.map(x => x)(encoder).show()
      +----+------+
      |name| stuff|
      +----+------+
      |  v1|[null]|
      +----+------+
      

      After identity transformation, `stuff` becomes an object with null values inside it instead of staying null itself.

      Doing the same with case classes preserves the nulls:

      scala> case class ScalaStuff(name: String)
      defined class ScalaStuff
      
      scala> case class ScalaOuter(name: String, stuff: ScalaStuff)
      defined class ScalaOuter
      
      scala> val encoder2 = Encoders.product[ScalaOuter]
      encoder2: org.apache.spark.sql.Encoder[ScalaOuter] = class[name[0]: string, stuff[0]: struct<name:string>]
      
      scala> val schema2 = encoder2.schema
      schema2: org.apache.spark.sql.types.StructType = StructType(StructField(name,StringType,true), StructField(stuff,StructType(StructField(name,StringType,true)),true))
      
      scala> schema2.printTreeString
      root
       |-- name: string (nullable = true)
       |-- stuff: struct (nullable = true)
       |    |-- name: string (nullable = true)
      
      
      scala>
      
      scala> val df2 = spark.read.schema(schema2).json("stuff.json").as[ScalaOuter]
      df2: org.apache.spark.sql.Dataset[ScalaOuter] = [name: string, stuff: struct<name: string>]
      
      scala> df2.show()
      +----+-----+
      |name|stuff|
      +----+-----+
      |  v1| null|
      +----+-----+
      
      
      scala> df2.map(x => x).show()
      +----+-----+
      |name|stuff|
      +----+-----+
      |  v1| null|
      +----+-----+
      

      stuff.json:

      {"name":"v1", "stuff":null }
      

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            • Assignee:
              maropu Takeshi Yamamuro
              Reporter:
              FlamingMike Michel Lemay
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              Dates

              • Created:
                Updated:
                Resolved: