[
https://issues.apache.org/jira/browse/SPARK-21246?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Hyukjin Kwon resolved SPARK-21246.
----------------------------------
Resolution: Invalid
Of course, it follows the schema an user specified.
{code}
scala> peopleDF.schema == schema
res9: Boolean = true
{code}
and this throws an exception as the schema is mismatched. I don't think at
least the same schema is not an issue here. I am resolving this.
> Unexpected Data Type conversion from LONG to BIGINT
> ---------------------------------------------------
>
> Key: SPARK-21246
> URL: https://issues.apache.org/jira/browse/SPARK-21246
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 1.6.1
> Environment: Using Zeppelin Notebook or Spark Shell
> Reporter: Monica Raj
>
> The unexpected conversion occurred when creating a data frame out of an
> existing data collection. The following code can be run in zeppelin notebook
> to reproduce the bug:
> import org.apache.spark.sql.types._
> import org.apache.spark.sql.Row
> val schemaString = "name"
> val lstVals = Seq(3)
> val rowRdd = sc.parallelize(lstVals).map(x => Row( x ))
> rowRdd.collect()
> // Generate the schema based on the string of schema
> val fields = schemaString.split(" ")
> .map(fieldName => StructField(fieldName, LongType, nullable = true))
> val schema = StructType(fields)
> print(schema)
> val peopleDF = sqlContext.createDataFrame(rowRdd, schema)
--
This message was sent by Atlassian JIRA
(v6.4.14#64029)
---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org
For additional commands, e-mail: issues-h...@spark.apache.org
