Cheng Lian created SPARK-12371:
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Summary: Make sure Dataset nullability conforms to its underlying
logical plan
Key: SPARK-12371
URL: https://issues.apache.org/jira/browse/SPARK-12371
Project: Spark
Issue Type: Sub-task
Components: SQL
Affects Versions: 1.6.0, 2.0.0
Reporter: Cheng Lian
Assignee: Cheng Lian
Currently it's possible to construct a Dataset with different nullability from
its underlying logical plan, which should be caught during analysis phase:
{code}
val rowRDD = sqlContext.sparkContext.parallelize(Seq(Row("hello"), Row(null)))
val schema = StructType(Seq(StructField("_1", StringType, nullable = false)))
val df = sqlContext.createDataFrame(rowRDD, schema)
df.as[Tuple1[String]].collect().foreach(println)
// Output:
//
// (hello)
// (null)
{code}
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