Enhancements & New Features
[SPARKO-1408] Process Name as Default UserAgentEntry
The driver will now use the process name as the UserAgentEntry if
the UserAgentEntry is not set.
[SPARKO-1472] Upgraded LTS support
The driver now uses LTS versions 11.3 through 15.4. For supported versions,
see the Installation and Configuration Guide.
[SPARKO-1482][05221097] Databricks domains support
The driver now supports cloud.databricks.us and cloud.databricks.mil
domains.
[SPARKO-1325][SPARKO-1435] Timestamp_NTZ support
The driver now recognizes timestamp_ntz columns in the following data
source tables:
- SQLGetTypeInfo (SQL_ALL_TYPES) now lists timestamp_ntz as an available
type.
- SQLGetTypeInfo (SQL_TIMESTAMP) now lists timestamp_ntz as one of the
types that map to SQL timestamps.
- SQLColumns now identifies timestamp_ntz columns correctly.
- If UseNativeQuery is set to 0, SQLColAttribute (SQL_DESC_TYPE_NAME)
identifies timestamp_ntz columns correctly.
[SPARKO-1384][SPARKO-1405][SPARKO-1411] CRL cache support
On Windows, the driver supports the CRL cache when UseSystemTruststore is
enabled (set to 1).
[SPARKO-1399][SPARKO-1417] Updated third-party libraries
The connector now uses the following third-party libraries:
- OpenSSL 3.0.16 (previously 3.0.15)
- libcURL 8.12.1 (previously 8.11.0)
- Expat 2.7.1 (previously 2.6.3)
[SPARKO-1404] VOID type support
The driver now supports VOID columns and lists them correctly in
SQLGetColumns calls.
[SPARKO-1419][SPARKO-1420] OAuth Token exchange support
The driver now supports OAuth Token exchange feature for IDP different
from the host. In these cases, OAuth access token (including BYOT) will be
exchanged for a Databricks in-house access token. For more information, see
the Installation and Configuration Guide.
[SPARKO-1474] Upgraded Windows Server support
The connector now supports Windows Server 2025. For a list of supported
versions, see the Installation and Configuration Guide.
Resolved Issues
The following issues have been resolved in Simba Apache Spark ODBC Connector
2.9.2.
- [SPARKO-1516][SPARKO-1518] A memory leak is resolved.
Known Issues
The following are known issues that you may encounter due to limitations in
the data source, the connector, or an application.
[SPARKO-1404] When querying tables that contain VOID columns, the server
returns an error.
[SPARKO-1101] When the Auth_AccessToken line length is longer than the
maximum limit of 1000, the connector returns an authentication error. For
more information, see the Installation and Configuration Guide.
[SPARKO-879] When connecting to a server that supports multiple catalogs,
the connector no longer reports the catalog for schemas and tables as
SPARK.
The Spark server now reports the catalog.
[SPARKO-670] In some cases, when retrieving timestamp data, the connector
returns an error.
In some cases, when connecting to certain distributions of
Apache Spark, the connector returns the following error: "Conversion from
number to string failed due to undersized character buffer". This issue
affects versions 2.6.12 to 2.6.14 of the Spark ODBC connector.
As a workaround, set EnableArrow=0 in the connection string or DSN.
[SPARKO-620] Issue with date and timestamp before the beginning of the
Gregorian calendar when connecting to Spark 2.4.4 or later, or versions
previous to 3.0, with Arrow result set serialization.
When using Spark 2.4.4 or later, or versions previous to Spark 3.0, DATE
and TIMESTAMP data before October 15, 1582 may be returned incorrectly if
the server supports serializing query results using Apache Arrow. This
issue should not impact most distributions of Apache Spark.
To confirm if your distribution of Spark 2.4.4 or later has been impacted
by this issue, you can execute the following query:
SELECT DATE '1581-10-14'
If the result returned by the connector is 1581-10-24, then you are
impacted by the issue. In this case, if your data set contains date and/or
timestamp data earlier than October 15, 1582, you can work around this
issue by adding EnableArrow=0 in your DSN or connection string to disable
the Arrow result set serialization feature.
When retrieving data from a BINARY column, a ClassCastException error
occurs.
In Spark 1.6.3 or earlier, the server sometimes returns a
ClassCastException error when attempting to retrieve data from a BINARY
column.
This issue is fixed as of Spark 2.0.0.
For more information, see the JIRA issue posted by Apache named "When
column type is binary, select occurs ClassCastException in Beeline" at
https://issues.apache.org/jira/browse/SPARK-12143.