Major Description
The MS SQL JDBC driver introduced support for spatial types since version 7.0. The JDBC data source lacks mappings for these types which results in an exception below. It seems that a mapping in MsSqlServerDialect.getCatalystType that maps -157 and -158 typecode to VARBINARY should address the issue.
java.sql.SQLException: Unrecognized SQL type -157 at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$.getCatalystType(JdbcUtils.scala:251) at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$.$anonfun$getSchema$1(JdbcUtils.scala:321) at scala.Option.getOrElse(Option.scala:189) at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$.getSchema(JdbcUtils.scala:321) 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:226) at org.apache.spark.sql.execution.datasources.jdbc.JdbcRelationProvider.createRelation(JdbcRelationProvider.scala:35) at org.apache.spark.sql.execution.datasources.DataSource.resolveRelation(DataSource.scala:364) at org.apache.spark.sql.DataFrameReader.loadV1Source(DataFrameReader.scala:366) at org.apache.spark.sql.DataFrameReader.$anonfun$load$2(DataFrameReader.scala:355) at scala.Option.getOrElse(Option.scala:189) at org.apache.spark.sql.DataFrameReader.load(DataFrameReader.scala:355) at org.apache.spark.sql.DataFrameReader.load(DataFrameReader.scala:240) at org.apache.spark.sql.DataFrameReader.jdbc(DataFrameReader.scala:381)
