[jira] [Assigned] (SPARK-22003) vectorized reader does not work with UDF when the column is array

["Apache Spark (JIRA)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/SPARK-22003?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Apache Spark reassigned SPARK-22003:
------------------------------------

    Assignee:     (was: Apache Spark)

> vectorized reader does not work with UDF when the column is array
> -----------------------------------------------------------------
>
>                 Key: SPARK-22003
>                 URL: https://issues.apache.org/jira/browse/SPARK-22003
>             Project: Spark
>          Issue Type: Improvement
>          Components: SQL
>    Affects Versions: 2.2.0
>            Reporter: Feng Liu
>
> The UDF needs to deserialize the UnsafeRow. When the column type is Array, the `get` method from the ColumnVector, which is used by the vectorized reader, is called, but this method is not implemented, unfortunately. 
> Code to reproduce the issue:
> {code:java}
> val fileName = "testfile"
> val str = """{ "choices": ["key1", "key2", "key3"] }"""
> val rdd = sc.parallelize(Seq(str))
> val df = spark.read.json(rdd)
> df.write.mode("overwrite").parquet(s"file:///tmp/$fileName ")
> import org.apache.spark.sql._
> import org.apache.spark.sql.functions._
> spark.udf.register("acf", (rows: Seq[Row]) => Option[String](null))
> spark.read.parquet(s"file:///tmp/$fileName ").select(expr("""acf(choices)""")).show
> {code}



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