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Magnitude Simba Google BigQuery ODBC Data Connector Release Notes
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The release notes provide details of enhancements, features, known issues, and
workflow changes in Simba Google BigQuery ODBC Connector 2.4.1, as well as the
version history. 


2.4.1 ========================================================================

Released 2021-08-26

Enhancements & New Features
   
 * [GAUSS-1279] Multi-statement transactions support
 
   The connector now supports multi-statement transactions. For more 
   information, see: https://cloud.google.com/bigquery/docs/reference/standard-sql/transactions.
   
 * [GAUSS-1315] Updated gRPC support

   The connector now uses gRPC version 1.37.1 for the High-Throughput API.

 * [GAUSS-1316] Retrieve data through High-Throughput API proxy

   The High-Throughput API can now be configured to use a proxy to retrieve 
   data. For more information on how to configure a proxy, see the 
   Installation and Configuration Guide. 

 * [GAUSS-1344] Data control language support

   The connector now supports data control language. For more information, 
   see: https://cloud.google.com/bigquery/docs/reference/standard-sql/data-control-language.


Resolved Issues
The following issues have been resolved in Simba Google BigQuery ODBC 
Connector 2.4.1.

 * [GAUSS-1308] SQLDescribeParam does not return the correct value for 
   NUMERIC data types in the DecimalDigits field.
 
   This issue has been resolved. The connector now reports precision and scale
   for NUMERIC parameters through SQLDescribeParam.
 
 * [GAUSS-1340] In some cases, while retrieving data due to erroneous thread 
   handling in multi-threaded environments, the connector becomes 
   unresponsive. 

 * [GAUSS-1341] The connector does not correctly bind all parameters based on 
   the BigQuery type for the respective column.

 * [GAUSS-1360] In some cases, the connector successfully executes a script 
   query with DML operations but fails to return the correct number of 
   affected rows.


Known Issues
The following are known issues that you may encounter due to limitations in
the data source, the connector, or an application.

 * [GAUSS-1350] The INTERVAL data type is not supported.

 * The connector does not support parameterized types for Resultset and 
   Parameter metadata 

   This is a limitation of the Google BigQuery server. 

 * The connector does not support parameters in the exception block.
 
   This is a limitation of the Google BigQuery server discovered on Mar 2021.
   
 * On macOS or Linux platforms, when the connector converts SQL_DOUBLE data to 
   SQL_C_CHAR or SQL_C_WCHAR, data which is small or large enough to require 
   representation in scientific notation may prepend a 0 to the exponent. 

   This is a limitation of Google BigQuery. For a list of BigQuery data types 
   that the connector maps to the SQL_DOUBLE ODBC type, see the Installation 
   and Configuration Guide.

 * When casting data, you must specify the data type according to Google 
   BigQuery standards.

   When casting data to a specific data type, you must use the corresponding 
   data type name shown in the "Casting" section of the Query Reference: 
   https://cloud.google.com/bigquery/sql-reference/functions-and-operators#cas
   ting 

   For example, to cast the "salary" column to the INTEGER type, you must 
   specify INT64 instead of INTEGER: 

      SELECT position, CAST(salary AS INT64) from Employee

 * When using the Standard SQL dialect, the connector's ODBC escape 
   functionality is subject to the following limitations:
   
   - Standard SQL does not support the seed in the RAND([seed]) scalar
     function. As a result, the connector maps RAND() and RAND(6) to RAND().

   - For the following scalar functions, BigQuery only returns values in UTC,
     but ODBC expects the values in local time:
     - CURDATE()
     - CURRENT_DATE()
     - CURRENT_TIME[(TIME_PRECISION)]
     - CURRENT_TIMESTAMP[(TIME_PRECISION)]
     - CURTIME()
     - NOW()

   - Time precision values are not supported for the 
     CURRENT_TIME[(TIME_PRECISION)] and CURRENT_TIMESTAMP[(TIME_PRECISION)]
     scalar functions.

   - TIME data types are not supported for the following scalar functions:
     - EXTRACT(interval FROM datetime)
     - TIMESTAMPADD(interval,integer_exp,timestamp_exp
     - TIMESTAMPDIFF(interval,timestamp_exp1,timestamp_exp2)
     For TIMESTAMPADD and TIMESTAMPDIFF, only the TIMESTAMP and DATE data 
     types are supported.

   - When calling the TIMESTAMPADD() scalar function to work with DAY, WEEK, 
     MONTH, QUARTER, or YEAR intervals, the connector escapes the function and 
     calls DATE_ADD() instead. DATE_ADD() only supports DATE types, so time
     information is lost if the function is called on TIMESTAMP data.

   - When calling the TIMESTAMPDIFF() scalar function to work with DAY, MONTH, 
     QUARTER, or YEAR intervals, the connector escapes the function and calls 
     DATE_DIFF() instead. DATE_DIFF() only supports DATE types, so time 
     information is lost if the function is called on TIMESTAMP data.

   - For the BIT_LENGTH scalar function, only the STRING and BYTES data types 
     are supported. This behavior aligns with the SQL-92 specification, but 
     not the ODBC specification.

 * When using the Legacy SQL dialect, the connector's ODBC escape 
   functionality is subject to the following limitations:

   - For the following scalar functions, BigQuery only returns values in UTC,
     but ODBC expects the values in local time:
     - CURDATE()
     - CURRENT_DATE()
     - CURRENT_TIME[(TIME_PRECISION)]
     - CURRENT_TIMESTAMP[(TIME_PRECISION)]
     - CURTIME()

   - Time precision values are not supported for the 
     CURRENT_TIME[(TIME_PRECISION)] and CURRENT_TIMESTAMP[(TIME_PRECISION)]
     scalar functions. 

   - For the following scalar functions, TIME data types are not supported.
     Only the TIMESTAMP and DATE data types are supported.
     - TIMESTAMPADD(interval,integer_exp,timestamp_exp
     - TIMESTAMPDIFF(interval,timestamp_exp1,timestamp_exp2)


Workflow Changes =============================================================

The following changes may disrupt established workflows for the connector.


2.3.5 -----------------------------------------------------------------------
 
 * [GAUSS-1246] Removed support for macOS earlier than 10.14

   Beginning with this release, the connector no longer supports macOS
   versions earlier than 10.14. For a list of supported macOS versions, see 
   the Installation and Configuration Guide.


2.2.4 ------------------------------------------------------------------------

 * [GAUSS-980] Removed support for the Visual C++ Redistributable for Visual
   Studio 2013
  
   Beginning with this release, the driver no longer supports this version
   of the dependency, and requires Visual C++ Redistributable for Visual
   Studio 2015 instead.
   

2.2.2 ------------------------------------------------------------------------

 * [GAUSS-875] New service endpoints

   The driver now uses a new set of service endpoints to connect to the 
   Google BigQuery API. The previous service endpoints have been deprecated. 
   For a list of the new endpoints, see the "Service Endpoints" section of 
   the Installation and Configuration Guide. 

 * [GAUSS-897] Precedence for default large result dataset

   If the Use Default _bqodbc_temp_tables Large Results Dataset check box is 
   selected (the UseDefaultLargeResultsDataset property is set to 1) and a 
   dataset is specified in the Dataset Name For Large Result Sets field (the 
   LargeResultsDataSetID property), the driver now uses the default 
   _bqodbc_temp_tables dataset. For more information, see the Installation 
   and Configuration Guide.


2.2.0 ------------------------------------------------------------------------

 * Linux support changes

   Beginning with this release, the Linux version of the driver now requires 
   glibc 2.17 or later to be installed on the target machine.
   
   As a result, the driver no longer supports CentOS 6 or RedHat Enterprise 
   Linux (RHEL) 6. Only CentOS 7, RHEL 7, and SUSE Linux Enterprise Server 
   (SLES) 11 and 12 are supported.


2.1.22 -----------------------------------------------------------------------

 * [GAUSS-653] Updated large result set behavior

   The driver's behavior for handling large result sets with legacy SQL has
   been changed. When the driver sends a query, it checks whether the "Allow
   Large Results" option is enabled and if there is a dataset name specified.
   If the option is enabled, it requests a temporary large result set for
   your data. This data storage has cost implications for your Big Query
   account, consult the Big Query service documentation for details.


2.1.14 -----------------------------------------------------------------------

 * Minimum TLS Version

   Beginning with this release, the driver requires a minimum version of TLS 
   for encrypting the data store connection. By default, the driver requires 
   TLS version 1.2. This requirement may cause existing DSNs and connection 
   strings to stop working, if they are used to connect to data stores that 
   use a TLS version earlier than 1.2.

   To resolve this, in your DSN or connection string, set the Minimum TLS 
   option (the Min_TLS property) to the appropriate version of TLS for your 
   server. For more information, see the Installation and Configuration Guide.

 * Large result set handling
 
   If you have a default destination set for large datasets but have not
   enabled the Allow Large Result Sets option (the AllowLargeResults property) 
   the driver reports an error.
   
   To resolve this, enable the Allow Large Result Sets option (the 
   AllowLargeResults property).


Version History ==============================================================

2.4.0 ------------------------------------------------------------------------

Released 2021-06-30

Enhancements & New Features
   
 * [GAUSS-1227][GAUSS-1239][GAUSS-1240][GAUSS-1241] Improved performance for
   metadata functions

   Improvements in parallelization and new design have been made to the 
   following metadata functions: 
   - SQLColumns
   - SQLProcedures
   - SQLProcedureColumns
   - SQLTables

 * [GAUSS-1218] New MaxThreads connector-wide property 
   
   You can now control the size of the threadpool used by statements to 
   execute concurrently. To do this, set the MaxThreads connector-wide 
   property to the maximum number of threads. For more information on how to 
   set connector-wide properties, see the Installation and Configuration 
   Guide.

 * [GAUSS-1290] Updated routine argument type support

   The routine argument type now supports ANY_TYPE. ANY_TYPE can be considered
   as SQL_UNKNOWN_TYPE when listing the argument in the SQLProcedureColumns 
   metadata. The type name would be ANY_TYPE. 
   
 * [GAUSS-1303] Parameterized data types support

   The connector now supports parameterized data types. For metadata 
   functions, SQLColumns returns the size, length, precision, and scale 
   related to these types.

   Due to current limitations of the BigQuery server on providing metadata for
   Resultset and Parameter, the connector does not provide specific 
   information (size, scale, etc.) on these parametrized data types when 
   retrieving metadata for them. In these cases, the connector returns the 
   default value.

   For example:
   CREATE TABLE Test(str STRING(100));

   The SQLColumn function returns the correct value of 100 for the size and 
   buffer length. SQLDescribeCol which is used for retrieving metadata of 
   Resultset, returns the default string length that has been set for the
   connector. Due to ODBC limitations, the connector only returns string 
   and byte lengths up to INT32_MAX. 


Resolved Issues
The following issue has been resolved in Simba Google BigQuery ODBC Connector 
2.4.0.

 * [GAUSS-1255] When a table or view has user only permissions, the connector
   returns 0 rows. 
   
   This issue has been resolved. When using the HTAPI, the user must ensure 
   that their account has the following permissions:
   - bigquery.readsessions.create
   - bigquery.readsessions.getData
   - bigquery.readsessions.update

   These permissions are included in the following predefined roles:
   - roles/bigquery.admin
   - roles/bigquery.user
   - roles/bigquery.readSessionUser


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