SQL Server connector — Trino 457 Documentation (2024)

Connection security#

The JDBC driver, and therefore the connector, automatically use Transport LayerSecurity (TLS) encryption and certificate validation. This requires a suitableTLS certificate configured on your SQL Server database host.

If you do not have the necessary configuration established, you can disableencryption in the connection string with the encrypt property:

connection-url=jdbc:sqlserver://<host>:<port>;databaseName=<databaseName>;encrypt=false

Further parameters like trustServerCertificate, hostNameInCertificate,trustStore, and trustStorePassword are details in the TLS section ofSQL Server JDBC driver documentation.

Data source authentication#

The connector can provide credentials for the data source connectionin multiple ways:

• inline, in the connector configuration file

• in a separate properties file

• in a key store file

• as extra credentials set when connecting to Trino

You can use secrets to avoid storing sensitivevalues in the catalog properties files.

The following table describes configuration propertiesfor connection credentials:

Multiple SQL Server databases or servers#

The SQL Server connector can only access a single SQL Server databasewithin a single catalog. Thus, if you have multiple SQL Server databases,or want to connect to multiple SQL Server instances, you must configuremultiple instances of the SQL Server connector.

To add another catalog, simply add another properties file to etc/catalogwith a different name, making sure it ends in .properties. For example,if you name the property file sales.properties, Trino creates acatalog named sales using the configured connector.

General configuration properties#

The following table describes general catalog configuration properties for theconnector:

Appending query metadata#

The optional parameter query.comment-format allows you to configure a SQLcomment that is sent to the datasource with each query. The format of thiscomment can contain any characters and the following metadata:

• $QUERY_ID: The identifier of the query.

• $USER: The name of the user who submits the query to Trino.

• $SOURCE: The identifier of the client tool used to submit the query, forexample trino-cli.

• $TRACE_TOKEN: The trace token configured with the client tool.

The comment can provide more context about the query. This additionalinformation is available in the logs of the datasource. To include environmentvariables from the Trino cluster with the comment , use the${ENV:VARIABLE-NAME} syntax.

The following example sets a simple comment that identifies each query sent byTrino:

query.comment-format=Query sent by Trino.

With this configuration, a query such as SELECT * FROM example_table; issent to the datasource with the comment appended:

SELECT * FROM example_table; /*Query sent by Trino.*/

The following example improves on the preceding example by using metadata:

query.comment-format=Query $QUERY_ID sent by user $USER from Trino.

If Jane sent the query with the query identifier20230622_180528_00000_bkizg, the following comment string is sent to thedatasource:

SELECT * FROM example_table; /*Query 20230622_180528_00000_bkizg sent by user Jane from Trino.*/

Domain compaction threshold#

Pushing down a large list of predicates to the data source can compromiseperformance. Trino compacts large predicates into a simpler range predicateby default to ensure a balance between performance and predicate pushdown.If necessary, the threshold for this compaction can be increased to improveperformance when the data source is capable of taking advantage of largepredicates. Increasing this threshold may improve pushdown of largedynamic filters.The domain-compaction-threshold catalog configuration property or thedomain_compaction_threshold catalog session property can be used to adjust the default value of32 for this threshold.

Specific configuration properties#

The SQL Server connector supports additional catalog properties to configure thebehavior of the connector and the issues queries to the database.

Case insensitive matching#

When case-insensitive-name-matching is set to true, Trinois able to query non-lowercase schemas and tables by maintaining a mapping ofthe lowercase name to the actual name in the remote system. However, if twoschemas and/or tables have names that differ only in case (such as “customers”and “Customers”) then Trino fails to query them due to ambiguity.

In these cases, use the case-insensitive-name-matching.config-file catalogconfiguration property to specify a configuration file that maps these remoteschemas/tables to their respective Trino schemas/tables:

{ "schemas": [ { "remoteSchema": "CaseSensitiveName", "mapping": "case_insensitive_1" }, { "remoteSchema": "cASEsENSITIVEnAME", "mapping": "case_insensitive_2" }], "tables": [ { "remoteSchema": "CaseSensitiveName", "remoteTable": "tablex", "mapping": "table_1" }, { "remoteSchema": "CaseSensitiveName", "remoteTable": "TABLEX", "mapping": "table_2" }]}

Queries against one of the tables or schemes defined in the mappingattributes are run against the corresponding remote entity. For example, a queryagainst tables in the case_insensitive_1 schema is forwarded to theCaseSensitiveName schema and a query against case_insensitive_2 is forwardedto the cASEsENSITIVEnAME schema.

At the table mapping level, a query on case_insensitive_1.table_1 asconfigured above is forwarded to CaseSensitiveName.tablex, and a query oncase_insensitive_1.table_2 is forwarded to CaseSensitiveName.TABLEX.

By default, when a change is made to the mapping configuration file, Trino mustbe restarted to load the changes. Optionally, you can set thecase-insensitive-name-mapping.refresh-period to have Trino refresh theproperties without requiring a restart:

case-insensitive-name-mapping.refresh-period=30s

Non-transactional INSERT#

The connector supports adding rows using INSERT statements.By default, data insertion is performed by writing data to a temporary table.You can skip this step to improve performance and write directly to the targettable. Set the insert.non-transactional-insert.enabled catalog propertyor the corresponding non_transactional_insert catalog session property totrue.

Note that with this property enabled, data can be corrupted in rare cases whereexceptions occur during the insert operation. With transactions disabled, norollback can be performed.

Fault-tolerant execution support#

The connector supports Fault-tolerant execution of queryprocessing. Read and write operations are both supported with any retry policy.

SQL Server type to Trino type mapping#

The connector maps SQL Server types to the corresponding Trino types following this table:

Trino type to SQL Server type mapping#

The connector maps Trino types to the corresponding SQL Server types following this table:

Complete list of SQL Server data types.

Numeric type mapping#

For SQL Server FLOAT[(n)]:

• If n is not specified maps to Trino Double

• If 1 <= n <= 24 maps to Trino REAL

• If 24 < n <= 53 maps to Trino DOUBLE

Character type mapping#

For Trino CHAR(n):

• If 1 <= n <= 4000 maps SQL Server NCHAR(n)

• If n > 4000 maps SQL Server NVARCHAR(max)

For Trino VARCHAR(n):

• If 1 <= n <= 4000 maps SQL Server NVARCHAR(n)

• If n > 4000 maps SQL Server NVARCHAR(max)

Type mapping configuration properties#

The following properties can be used to configure how data types from theconnected data source are mapped to Trino data types and how the metadata iscached in Trino.

UPDATE#

Only UPDATE statements with constant assignments and predicates aresupported. For example, the following statement is supported because the valuesassigned are constants:

UPDATE table SET col1 = 1 WHERE col3 = 1

Arithmetic expressions, function calls, and other non-constant UPDATEstatements are not supported. For example, the following statement is notsupported because arithmetic expressions cannot be used with the SETcommand:

UPDATE table SET col1 = col2 + 2 WHERE col3 = 1

All column values of a table row cannot be updated simultaneously. For a threecolumn table, the following statement is not supported:

UPDATE table SET col1 = 1, col2 = 2, col3 = 3 WHERE col3 = 1

SQL DELETE#

If a WHERE clause is specified, the DELETE operation only works if thepredicate in the clause can be fully pushed down to the data source.

ALTER TABLE RENAME TO#

The connector does not support renaming tables across multiple schemas. Forexample, the following statement is supported:

ALTER TABLE example.schema_one.table_one RENAME TO example.schema_one.table_two

The following statement attempts to rename a table across schemas, and thereforeis not supported:

ALTER TABLE example.schema_one.table_one RENAME TO example.schema_two.table_two

Procedures#

USE example.example_schema;CALL system.flush_metadata_cache();

USE example.example_schema;CALL system.execute(query => 'ALTER TABLE your_table ALTER COLUMN your_column DROP DEFAULT');

Table functions#

The connector provides specific table functions toaccess SQL Server.

SELECT *FROM TABLE( example.system.query( query => 'SELECT TOP(10) PERCENT * FROM tpch.nation ORDER BY population DESC' ) );

procedure(varchar) -> table#

The procedure function allows you to run stored procedures on the underlyingdatabase directly. It requires syntax native to SQL Server, because the full queryis pushed down and processed in SQL Server. In order to use this table function setsqlserver.experimental.stored-procedure-table-function-enabled to true.

The follow example runs the stored procedure employee_sp in the example catalog and theexample_schema schema in the underlying SQL Server database:

SELECT *FROM TABLE( example.system.procedure( query => 'EXECUTE example_schema.employee_sp' ) );

If the stored procedure employee_sp requires any inputappend the parameter value to the procedure statement:

SELECT *FROM TABLE( example.system.procedure( query => 'EXECUTE example_schema.employee_sp 0' ) );

Table statistics#

The SQL Server connector can use table and column statistics for cost based optimizations, to improve query processing performancebased on the actual data in the data source.

The statistics are collected by SQL Server and retrieved by the connector.

The connector can use information stored in single-column statistics. SQL ServerDatabase can automatically create column statistics for certain columns. Ifcolumn statistics are not created automatically for a certain column, you cancreate them by executing the following statement in SQL Server Database.

CREATE STATISTICS example_statistics_name ON table_schema.table_name (column_name);

SQL Server Database routinely updates the statistics. In some cases, you maywant to force statistics update (e.g. after defining new column statistics orafter changing data in the table). You can do that by executing the followingstatement in SQL Server Database.

UPDATE STATISTICS table_schema.table_name;

Refer to SQL Server documentation for information about options, limitations andadditional considerations.

Pushdown#

The connector supports pushdown for a number of operations:

• Join pushdown

• Limit pushdown

• Top-N pushdown

Aggregate pushdown for the following functions:

• avg()

• count()

• max()

• min()

• sum()

• stddev()

• stddev_pop()

• stddev_samp()

• variance()

• var_pop()

• var_samp()

Bulk insert#

You can optionally use the bulk copy APIto drastically speed up write operations.

Enable bulk copying and a lock on the destination table to meet minimallogging requirements.

The following table shows the relevant catalog configuration properties andtheir default values:

Limitations:

• Column names with leading and trailing spaces are not supported.