Read error with spark.read against SQL Server table (via JDBC Connection)

user_12262123 0
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I have a problem in Zeppelin when I try to create a dataframe reading directly from a SQL table. The problem is that I dont know how to read a SQL column with the geography type.

SQL table

This is the code that I am using, and the error that I obtain.

Create JDBC connection

import org.apache.spark.sql.SaveMode
import java.util.Properties

val jdbcHostname = "XX.XX.XX.XX"
val jdbcDatabase = "databasename"
val jdbcUsername = "user"
val jdbcPassword = "XXXXXXXX"

// Create the JDBC URL without passing in the user and password parameters.
val jdbcUrl = s"jdbc:sqlserver://${jdbcHostname};database=${jdbcDatabase}"

// Create a Properties() object to hold the parameters.
val connectionProperties = new Properties()
connectionProperties.put("user", s"${jdbcUsername}")
connectionProperties.put("password", s"${jdbcPassword}")
connectionProperties.setProperty("Driver", "com.microsoft.sqlserver.jdbc.SQLServerDriver")

Read from SQL

import spark.implicits._

val table = "tablename"

val postcode_polygons = spark.
    read.
    jdbc(jdbcUrl, table, connectionProperties)

Error

import spark.implicits._
table: String = Lookup.Postcode50m_Lookup
java.sql.SQLException: Unsupported type -158
  at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$.org$apache$spark$sql$execution$datasources$jdbc$JdbcUtils$$getCatalystType(JdbcUtils.scala:233)
  at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$$anonfun$8.apply(JdbcUtils.scala:290)
  at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$$anonfun$8.apply(JdbcUtils.scala:290)
  at scala.Option.getOrElse(Option.scala:121)
  at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$.getSchema(JdbcUtils.scala:289)
  at org.apache.spark.sql.execution.datasources.jdbc.JDBCRDD$.resolveTable(JDBCRDD.scala:64)
  at org.apache.spark.sql.execution.datasources.jdbc.JDBCRelation.<init>(JDBCRelation.scala:114)
  at org.apache.spark.sql.execution.datasources.jdbc.JdbcRelationProvider.createRelation(JdbcRelationProvider.scala:52)
  at org.apache.spark.sql.execution.datasources.DataSource.resolveRelation(DataSource.scala:307)
  at org.apache.spark.sql.DataFrameReader.load(DataFrameReader.scala:178)
  at org.apache.spark.sql.DataFrameReader.load(DataFrameReader.scala:146)
  at org.apache.spark.sql.DataFrameReader.jdbc(DataFrameReader.scala:193)
apache-zeppelin apache-spark sql-server
2 Answers

Adding to thebluephantom answer have you tried changing the type to string as below and loading the table. 

val jdbcDF = spark.read.format("jdbc")
  .option("dbtable" -> "(select toString(SData) as s_sdata,toString(CentroidSData) as s_centroidSdata from table) t")
  .option("user", "user_name")
  .option("other options")
  .load()
user_17621050

This is the final solution in my case, the idea of moasifk is correct, but in my code I cannot use the function "toString". I have applied the same idea but with another sintaxis.

import spark.implicits._

val tablename = "Lookup.Postcode50m_Lookup"

val postcode_polygons = spark.
    read.
    jdbc(jdbcUrl, table=s"(select PostcodeNoSpaces, cast(SData as nvarchar(4000)) as SData from $tablename) as postcode_table", connectionProperties)
user_122621230
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