some impala built-in function can't work in spark data source reader

[#1]

I want to get subquery from impala table as one dataset.

Code like this:

String subQuery = "(select to_timestamp(unix_timestamp(now())) as ts from my_table) t"
Dataset<Row> ds = spark.read().jdbc(myImpalaUrl, subQuery, prop);

But result is error:

Caused by: java.sql.SQLDataException: [Cloudera][JDBC](10140) Error converting value to Timestamp.

to_timestmap() function failed ,but unix_timestmap() , now() work fine.

ps. I found another problem, when I use hive udf in the "jdbc" api still failed. 

Can anyone help me?

[#2]

Getting same conversion issues for below schema. 

root
 |-- instance: string (nullable = true)
 |-- count(*): long (nullable = true)

Error Message:

java.sql.SQLDataException: [Simba][JDBC](10140) Error converting value to long.
	at com.cloudera.exceptions.ExceptionConverter.toSQLException(Unknown Source)
	at com.cloudera.utilities.conversion.TypeConverter.toLong(Unknown Source)
	at com.cloudera.jdbc.common.SForwardResultSet.getLong(Unknown Source)
	at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$$anonfun$org$apache$spark$sql$execution$datasources$jdbc$JdbcUtils$$makeGetter$8.apply(JdbcUtils.scala:409)
	at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$$anonfun$org$apache$spark$sql$execution$datasources$jdbc$JdbcUtils$$makeGetter$8.apply(JdbcUtils.scala:408)
	at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$$anon$1.getNext(JdbcUtils.scala:330)
	at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$$anon$1.getNext(JdbcUtils.scala:312)

Can anyone please help on resolving this issue in spark java. 

[#3]

Hey cloudera, @Nathan @Shushruth @is this issue addressed getting the same issue with python3 and pyspark2.3 while fetching data from Impala using spark jdbc.

[#4]

Hello,

Are you trying to connect impala from spark via JDBC?

if yes, we don't support this feature yet. please refer to the below document.

https://docs.cloudera.com/documentation/enterprise/6/release-notes/topics/rg_cdh_621_unsupported_fea...

[#5]

@ShankerSharma is cloudera planning to include this functionality anytime soon. If not, what other ways do we have to read tables from Impala using pyspark 2.3.