How to make Spark DataFrameReader jdbc accept Postgres Array of custom type

Question

Got Unsupported type ARRAY when read table with DataFrameReader jdbc() function:

java.sql.SQLException: Unsupported type ARRAY
    at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$.org$apache$spark$sql$execution$datasources$jdbc$JdbcUtils$$getCatalystType(JdbcUtils.scala:251)
    at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$$anonfun$8.apply(JdbcUtils.scala:316)
    at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$$anonfun$8.apply(JdbcUtils.scala:316)
    at scala.Option.getOrElse(Option.scala:121)
    at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$.getSchema(JdbcUtils.scala:315)
    at org.apache.spark.sql.execution.datasources.jdbc.JDBCRDD$.resolveTable(JDBCRDD.scala:63)
    at org.apache.spark.sql.execution.datasources.jdbc.JDBCRelation$.getSchema(JDBCRelation.scala:210)
    at org.apache.spark.sql.execution.datasources.jdbc.JDBCRelation$.apply(JDBCRelation.scala:225)
    at org.apache.spark.sql.DataFrameReader.jdbc(DataFrameReader.scala:313)

The table is like:

mydb=> \d check_type;
              Table "public.check_type"
 Column |   Type    | Collation | Nullable | Default
--------+-----------+-----------+----------+---------
 id     | integer   |           |          |
 types  | my_type[] |           |          |

mydb=> \d my_type;
          Composite type "public.my_type"
 Column |  Type   | Collation | Nullable | Default
--------+---------+-----------+----------+---------
 id     | integer |           |          |

Is there a workaround for that? Or is it an expected behavior?

Spark version:

Spark-core = 2.4.0;
Spark-sql = 2.4.0;