SQL Server connector#

The SQL Server connector allows querying and creating tables in an external Microsoft SQL Server database. This can be used to join data between different systems like SQL Server and Hive, or between two different SQL Server instances.

Requirements#

To connect to SQL Server, you need:

  • SQL Server 2012 or higher, or Azure SQL Database.

  • Network access from the Trino coordinator and workers to SQL Server. Port 1433 is the default port.

Configuration#

The connector can query a single database on a given SQL Server instance. Create a catalog properties file that specifies the SQL server connector by setting the connector.name to sqlserver.

For example, to access a database as sqlserver, create the file etc/catalog/sqlserver.properties. Replace the connection properties as appropriate for your setup:

connector.name=sqlserver
connection-url=jdbc:sqlserver://<host>:<port>;database=<database>;encrypt=false
connection-user=root
connection-password=secret

The connection-url defines the connection information and parameters to pass to the SQL Server JDBC driver. The supported parameters for the URL are available in the SQL Server JDBC driver documentation.

The connection-user and connection-password are typically required and determine the user credentials for the connection, often a service user. You can use secrets to avoid actual values in the catalog properties files.

Connection security#

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

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

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

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

Multiple SQL Server databases or servers#

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

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

General configuration properties#

The following table describes general catalog configuration properties for the connector:

Property name

Description

Default value

case-insensitive-name-matching

Support case insensitive schema and table names.

false

case-insensitive-name-matching.cache-ttl

1m

case-insensitive-name-matching.config-file

Path to a name mapping configuration file in JSON format that allows Trino to disambiguate between schemas and tables with similar names in different cases.

null

case-insensitive-name-matching.refresh-period

Frequency with which Trino checks the name matching configuration file for changes.

0 (refresh disabled)

metadata.cache-ttl

Duration for which metadata, including table and column statistics, is cached.

0 (caching disabled)

metadata.cache-missing

Cache the fact that metadata, including table and column statistics, is not available

false

metadata.cache-maximum-size

Maximum number of objects stored in the metadata cache

10000

write.batch-size

Maximum number of statements in a batched execution. Do not change this setting from the default. Non-default values may negatively impact performance.

1000

dynamic-filtering.enabled

Push down dynamic filters into JDBC queries

true

dynamic-filtering.wait-timeout

Maximum duration for which Trino will wait for dynamic filters to be collected from the build side of joins before starting a JDBC query. Using a large timeout can potentially result in more detailed dynamic filters. However, it can also increase latency for some queries.

20s

Domain compaction threshold#

Pushing down a large list of predicates to the data source can compromise performance. Trino compacts large predicates into a simpler range predicate by default to ensure a balance between performance and predicate pushdown. If necessary, the threshold for this compaction can be increased to improve performance when the data source is capable of taking advantage of large predicates. Increasing this threshold may improve pushdown of large dynamic filters. The domain-compaction-threshold catalog configuration property or the domain_compaction_threshold catalog session property can be used to adjust the default value of 32 for this threshold.

Specific configuration properties#

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

Property name

Description

sqlserver.snapshot-isolation.disabled

Control the automatic use of snapshot isolation for transactions issued by Trino in SQL Server. Defaults to false, which means that snapshot isolation is enabled.

Procedures#

  • system.flush_metadata_cache()

    Flush JDBC metadata caches. For example, the following system call flushes the metadata caches for all schemas in the example catalog

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

Case insensitive matching#

When case-insensitive-name-matching is set to true, Trino is able to query non-lowercase schemas and tables by maintaining a mapping of the lowercase name to the actual name in the remote system. However, if two schemas 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 catalog configuration property to specify a configuration file that maps these remote schemas/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 mapping attributes are run against the corresponding remote entity. For example, a query against tables in the case_insensitive_1 schema is forwarded to the CaseSensitiveName schema and a query against case_insensitive_2 is forwarded to the cASEsENSITIVEnAME schema.

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

By default, when a change is made to the mapping configuration file, Trino must be restarted to load the changes. Optionally, you can set the case-insensitive-name-mapping.refresh-period to have Trino refresh the properties 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 target table. Set the insert.non-transactional-insert.enabled catalog property or the corresponding non_transactional_insert catalog session property to true.

Note that with this property enabled, data can be corrupted in rare cases where exceptions occur during the insert operation. With transactions disabled, no rollback can be performed.

Querying SQL Server#

The SQL Server connector provides access to all schemas visible to the specified user in the configured database. For the following examples, assume the SQL Server catalog is sqlserver.

You can see the available schemas by running SHOW SCHEMAS:

SHOW SCHEMAS FROM sqlserver;

If you have a schema named web, you can view the tables in this schema by running SHOW TABLES:

SHOW TABLES FROM sqlserver.web;

You can see a list of the columns in the clicks table in the web database using either of the following:

DESCRIBE sqlserver.web.clicks;
SHOW COLUMNS FROM sqlserver.web.clicks;

Finally, you can query the clicks table in the web schema:

SELECT * FROM sqlserver.web.clicks;

If you used a different name for your catalog properties file, use that catalog name instead of sqlserver in the above examples.

Type mapping#

Because Trino and SQL Server each support types that the other does not, this connector modifies some types when reading or writing data. Data types may not map the same way in both directions between Trino and the data source. Refer to the following sections for type mapping in each direction.

SQL Server type to Trino type mapping#

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

SQL Server type to Trino type mapping#

SQL Server database type

Trino type

Notes

BIT

BOOLEAN

TINYINT

SMALLINT

SQL Server TINYINT is actually unsigned tinyint

SMALLINT

SMALLINT

INTEGER

INTEGER

BIGINT

BIGINT

DOUBLE PRECISION

DOUBLE

FLOAT[(n)]

REAL or DOUBLE

See Numeric type mapping

REAL

REAL

DECIMAL[(p[, s])], NUMERIC[(p[, s])]

DECIMAL(p, s)

CHAR[(n)]

CHAR(n)

1 <= n <= 8000

NCHAR[(n)]

CHAR(n)

1 <= n <= 4000

VARCHAR[(n | max)], NVARCHAR[(n | max)]

VARCHAR(n)

1 <= n <= 8000, max = 2147483647

TEXT

VARCHAR(2147483647)

NTEXT

VARCHAR(1073741823)

VARBINARY[(n | max)]

VARBINARY

1 <= n <= 8000, max = 2147483647

DATE

DATE

TIME[(n)]

TIME(n)

0 <= n <= 7

DATETIME2[(n)]

TIMESTAMP(n)

0 <= n <= 7

SMALLDATETIME

TIMESTAMP(0)

DATETIMEOFFSET[(n)]

TIMESTAMP(n) WITH TIME ZONE

0 <= n <= 7

Trino type to SQL Server type mapping#

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

Trino type to SQL Server type mapping#

Trino type

SQL Server type

Notes

BOOLEAN

BIT

TINYINT

TINYINT

Trino only supports writing values belonging to [0, 127]

SMALLINT

SMALLINT

INTEGER

INTEGER

BIGINT

BIGINT

REAL

REAL

DOUBLE

DOUBLE PRECISION

DECIMAL(p, s)

DECIMAL(p, s)

CHAR(n)

NCHAR(n) or NVARCHAR(max)

See Character type mapping

VARCHAR(n)

NVARCHAR(n) or NVARCHAR(max)

See Character type mapping

VARBINARY

VARBINARY(max)

DATE

DATE

TIME(n)

TIME(n)

0 <= n <= 7

TIMESTAMP(n)

DATETIME2(n)

0 <= n <= 7

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 the connected data source are mapped to Trino data types and how the metadata is cached in Trino.

Property name

Description

Default value

unsupported-type-handling

Configure how unsupported column data types are handled:

  • IGNORE, column is not accessible.

  • CONVERT_TO_VARCHAR, column is converted to unbounded VARCHAR.

The respective catalog session property is unsupported_type_handling.

IGNORE

jdbc-types-mapped-to-varchar

Allow forced mapping of comma separated lists of data types to convert to unbounded VARCHAR

SQL support#

The connector provides read access and write access to data and metadata in SQL Server. In addition to the globally available and read operation statements, the connector supports the following features:

SQL DELETE#

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

ALTER TABLE#

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

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

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

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

Table functions#

The connector provides specific table functions to access SQL Server.

query(varchar) -> table#

The query function allows you to query the underlying database directly. It requires syntax native to SQL Server, because the full query is pushed down and processed in SQL Server. This can be useful for accessing native features which are not implemented in Trino or for improving query performance in situations where running a query natively may be faster.

Note

Polymorphic table functions may not preserve the order of the query result. If the table function contains a query with an ORDER BY clause, the function result may not be ordered as expected.

For example, select the top 10 percent of nations by population:

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

Performance#

The connector includes a number of performance improvements, detailed in the following sections.

Table statistics#

The SQL Server connector can use table and column statistics for cost based optimizations, to improve query processing performance based 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 Server Database can automatically create column statistics for certain columns. If column statistics are not created automatically for a certain column, you can create them by executing the following statement in SQL Server Database.

CREATE STATISTICS my_statistics_name ON table_schema.table_name (column_name);

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

UPDATE STATISTICS table_schema.table_name;

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

Pushdown#

The connector supports pushdown for a number of operations:

Aggregate pushdown for the following functions:

Cost-based join pushdown#

The connector supports cost-based Join pushdown to make intelligent decisions about whether to push down a join operation to the data source.

When cost-based join pushdown is enabled, the connector only pushes down join operations if the available Table statistics suggest that doing so improves performance. Note that if no table statistics are available, join operation pushdown does not occur to avoid a potential decrease in query performance.

The following table describes catalog configuration properties for join pushdown:

Property name

Description

Default value

join-pushdown.enabled

Enable join pushdown. Equivalent catalog session property is join_pushdown_enabled.

true

join-pushdown.strategy

Strategy used to evaluate whether join operations are pushed down. Set to AUTOMATIC to enable cost-based join pushdown, or EAGER to push down joins whenever possible. Note that EAGER can push down joins even when table statistics are unavailable, which may result in degraded query performance. Because of this, EAGER is only recommended for testing and troubleshooting purposes.

AUTOMATIC

Predicate pushdown support#

The connector does not support pushdown of any predicates on columns with textual types like CHAR or VARCHAR. This ensures correctness of results since the data source may compare strings case-insensitively.

In the following example, the predicate is not pushed down for either query since name is a column of type VARCHAR:

SELECT * FROM nation WHERE name > 'CANADA';
SELECT * FROM nation WHERE name = 'CANADA';

Bulk insert#

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

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

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

Bulk load properties#

Property name

Description

Default

sqlserver.bulk-copy-for-write.enabled

Use the SQL Server bulk copy API for writes. The corresponding catalog session property is bulk_copy_for_write.

false

sqlserver.bulk-copy-for-write.lock-destination-table

Obtain a bulk update lock on the destination table for write operations. The corresponding catalog session property is bulk_copy_for_write_lock_destination_table. Setting is only used when bulk-copy-for-write.enabled=true.

false

Limitations:

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

Data compression#

You can specify the data compression policy for SQL Server tables with the data_compression table property. Valid policies are NONE, ROW or PAGE.

Example:

CREATE TABLE myschema.scientists (
  recordkey VARCHAR,
  name VARCHAR,
  age BIGINT,
  birthday DATE
)
WITH (
  data_compression = 'ROW'
);