Feng Liu created SPARK-22003:
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Summary: 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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