This page lists SQLMesh configuration options and their parameters. Learn more about SQLMesh configuration in the configuration guide.
Configuration options for model definitions are listed in the model configuration reference page.
A SQLMesh project configuration consists of root level parameters within which other parameters are defined.
Two important root level parameters are gateways and gateway/connection defaults, which have their own sections below.
This section describes the other root level configuration parameters.
Configuration options for SQLMesh project directories.
| Option | Description | Type | Required |
|---|---|---|---|
ignore_patterns |
Files that match glob patterns specified in this list are ignored when scanning the project folder (Default: []) |
list[string] | N |
project |
The project name of this config. Used for multi-repo setups. | string | N |
Configuration options for SQLMesh environment creation and promotion.
| Option | Description | Type | Required |
|---|---|---|---|
snapshot_ttl |
The period of time that a model snapshot not a part of any environment should exist before being deleted. This is defined as a string with the default in 1 week. Other relative dates can be used, such as in 30 days. (Default: in 1 week) |
string | N |
environment_ttl |
The period of time that a development environment should exist before being deleted. This is defined as a string with the default in 1 week. Other relative dates can be used, such as in 30 days. (Default: in 1 week) |
string | N |
pinned_environments |
The list of development environments that are exempt from deletion due to expiration | list[string] | N |
time_column_format |
The default format to use for all model time columns. This time format uses python format codes (Default: %Y-%m-%d) |
string | N |
default_target_environment |
The name of the environment that will be the default target for the sqlmesh plan and sqlmesh run commands. (Default: prod) |
string | N |
physical_schema_override |
(Deprecated) Use physical_schema_mapping instead. A mapping from model schema names to names of schemas in which physical tables for the corresponding models will be placed. |
dict[string, string] | N |
physical_schema_mapping |
A mapping from regular expressions to names of schemas in which physical tables for the corresponding models will be placed. (Default physical schema name: sqlmesh__[model schema]) |
dict[string, string] | N |
environment_suffix_target |
Whether SQLMesh views should append their environment name to the schema or table - additional details. (Default: schema) |
string | N |
environment_catalog_mapping |
A mapping from regular expressions to catalog names. The catalog name is used to determine the target catalog for a given environment. | dict[string, string] | N |
log_limit |
The default number of logs to keep (Default: 20) |
int | N |
The model_defaults key is required and must contain a value for the dialect key.
See all the keys allowed in model_defaults at the model configuration reference page.
The variables key can be used to provide values for user-defined variables, accessed using the @VAR macro function in SQL model definitions, context.var method in Python model definitions, and evaluator.var method in Python macro functions.
The variables key consists of a mapping of variable names to their values - see an example on the SQLMesh macros concepts page. Note that keys are case insensitive.
Global variable values may be any of the data types in the table below or lists or dictionaries containing those types.
| Option | Description | Type | Required |
|---|---|---|---|
variables |
Mapping of variable names to values | dict[string, int | float | bool | string | list | dict] | N |
The before_all and after_all keys can be used to specify lists of SQL statements and/or SQLMesh macros that are executed at the start and end, respectively, of the sqlmesh plan and sqlmesh run commands. For more information and examples, see the configuration guide.
| Option | Description | Type | Required |
|---|---|---|---|
before_all |
List of SQL statements to be executed at the start of the plan and run commands. |
list[string] | N |
after_all |
List of SQL statements to be executed at the end of the plan and run commands. |
list[string] | N |
Configuration for the sqlmesh plan command.
| Option | Description | Type | Required |
|---|---|---|---|
auto_categorize_changes |
Indicates whether SQLMesh should attempt to automatically categorize model changes during plan creation per each model source type (additional details) | dict[string, string] | N |
include_unmodified |
Indicates whether to create views for all models in the target development environment or only for modified ones (Default: False) | boolean | N |
auto_apply |
Indicates whether to automatically apply a new plan after creation (Default: False) | boolean | N |
forward_only |
Indicates whether the plan should be forward-only (Default: False) | boolean | N |
enable_preview |
Indicates whether to enable data preview for forward-only models when targeting a development environment (Default: True, except for dbt projects where the target engine does not support cloning) | Boolean | N |
no_diff |
Don't show diffs for changed models (Default: False) | boolean | N |
no_prompts |
Disables interactive prompts in CLI (Default: True) | boolean | N |
Configuration for the sqlmesh run command. Please note that this is only applicable when configured with the builtin scheduler.
| Option | Description | Type | Required |
|---|---|---|---|
environment_check_interval |
The number of seconds to wait between attempts to check the target environment for readiness (Default: 30 seconds) | int | N |
environment_check_max_wait |
The maximum number of seconds to wait for the target environment to be ready (Default: 6 hours) | int | N |
Formatting settings for the sqlmesh format command and UI.
| Option | Description | Type | Required |
|---|---|---|---|
normalize |
Whether to normalize SQL (Default: False) | boolean | N |
pad |
The number of spaces to use for padding (Default: 2) | int | N |
indent |
The number of spaces to use for indentation (Default: 2) | int | N |
normalize_functions |
Whether to normalize function names. Supported values are: 'upper' and 'lower' (Default: None) | string | N |
leading_comma |
Whether to use leading commas (Default: False) | boolean | N |
max_text_width |
The maximum text width in a segment before creating new lines (Default: 80) | int | N |
append_newline |
Whether to append a newline to the end of the file (Default: False) | boolean | N |
no_rewrite_casts |
Preserve the existing casts, without rewriting them to use the :: syntax. (Default: False) | boolean | N |
SQLMesh UI settings.
| Option | Description | Type | Required |
|---|---|---|---|
format_on_save |
Whether to automatically format model definitions upon saving them to a file (Default: False) | boolean | N |
The gateways dictionary defines how SQLMesh should connect to the data warehouse, state backend, test backend, and scheduler.
It takes one or more named gateway configuration keys, each of which can define its own connections. A named gateway does not need to specify all four components and will use defaults if any are omitted - more information is provided about gateway defaults below.
For example, a project might configure the gate1 and gate2 gateways:
gateways:
gate1:
connection:
...
state_connection: # defaults to `connection` if omitted and not using airflow or google cloud composer scheduler
...
test_connection: # defaults to `connection` if omitted
...
scheduler: # defaults to `builtin` if omitted
...
gate2:
connection:
...Find additional information about gateways in the configuration guide gateways section.
Configuration for each named gateway.
A named gateway key may define any or all of a data warehouse connection, state backend connection, state schema name, test backend connection, and scheduler.
Some connections use default values if not specified:
- The
connectionkey may be omitted if adefault_connectionis specified. - The state connection defaults to
connectionunless the configuration uses an Airflow or Google Cloud Composer scheduler. If using one of those schedulers, the state connection defaults to the scheduler's database. - The test connection defaults to
connectionif omitted.
NOTE: Spark and Trino engines may not be used for the state connection.
| Option | Description | Type | Required |
|---|---|---|---|
connection |
The data warehouse connection for core SQLMesh functions. | connection configuration | N (if default_connection specified) |
state_connection |
The data warehouse connection where SQLMesh will store internal information about the project. (Default: connection if using builtin scheduler, otherwise scheduler database) |
connection configuration | N |
state_schema |
The name of the schema where state information should be stored. (Default: sqlmesh) |
string | N |
test_connection |
The data warehouse connection SQLMesh will use to execute tests. (Default: connection) |
connection configuration | N |
scheduler |
The scheduler SQLMesh will use to execute tests. (Default: builtin) |
scheduler configuration | N |
variables |
The gateway-specific variables which override the root-level variables by key. | dict[string, int | float | bool | string | list | dict] | N |
Configuration for a data warehouse connection.
Most parameters are specific to the connection engine type - see below. The default data warehouse connection type is an in-memory DuckDB database.
| Option | Description | Type | Required |
|---|---|---|---|
type |
The engine type name, listed in engine-specific configuration pages below. | str | Y |
concurrent_tasks |
The maximum number of concurrent tasks that will be run by SQLMesh. (Default: 4 for engines that support concurrent tasks.) | int | N |
register_comments |
Whether SQLMesh should register model comments with the SQL engine (if the engine supports it). (Default: true.) |
bool | N |
pre_ping |
Whether or not to pre-ping the connection before starting a new transaction to ensure it is still alive. This can only be enabled for engines with transaction support. | bool | N |
pretty_sql |
If SQL should be formatted before being executed, not recommended in a production setting. (Default: false.) |
bool | N |
These pages describe the connection configuration options for each execution engine.
- Athena
- BigQuery
- ClickHouse
- Databricks
- DuckDB
- MotherDuck
- MySQL
- MSSQL
- Postgres
- GCP Postgres
- Redshift
- Snowflake
- Spark
- Trino
Identifies which scheduler backend to use. The scheduler backend is used both for storing metadata and for executing plans.
By default, the scheduler type is set to builtin and uses the gateway's connection to store metadata. Use the airflow type to integrate with Airflow.
Below is the list of configuration options specific to each corresponding scheduler type. Find additional details in the configuration overview scheduler section.
Type: builtin
No configuration options are supported by this scheduler type.
Type: airflow
See Airflow Integration Guide for information about how to integrate Airflow with SQLMesh.
| Option | Description | Type | Required |
|---|---|---|---|
airflow_url |
The URL of the Airflow Webserver | string | Y |
username |
The Airflow username | string | Y |
password |
The Airflow password | string | Y |
dag_run_poll_interval_secs |
Determines, in seconds, how often a running DAG can be polled (Default: 10) |
int | N |
dag_creation_poll_interval_secs |
Determines, in seconds, how often SQLMesh should check whether a DAG has been created (Default: 30) |
int | N |
dag_creation_max_retry_attempts |
Determines the maximum number of attempts that SQLMesh will make while checking for whether a DAG has been created (Default: 10) |
int | N |
backfill_concurrent_tasks |
The number of concurrent tasks used for model backfilling during plan application (Default: 4) |
int | N |
ddl_concurrent_tasks |
The number of concurrent tasks used for DDL operations like table/view creation, deletion, and so forth (Default: 4) |
int | N |
max_snapshot_ids_per_request |
The maximum number of snapshot IDs that can be sent in a single HTTP GET request to the Airflow Webserver (Default: None) |
int | N |
use_state_connection |
Whether to use the state_connection configuration to bypass Airflow Webserver and access the SQLMesh state directly (Default: false) |
boolean | N |
default_catalog_override |
Overrides the default catalog value for this project. If specified, this value takes precedence over the default catalog value set on the Airflow side. This only applies in the multi-repo setup when different projects require different default catalog values (Default: None) |
string | N |
Type: cloud_composer
The Google Cloud Composer scheduler type shares the same configuration options as the airflow type, except for username and password. Cloud Composer relies on gcloud authentication, so the username and password options are not required.
Type: yc_airflow
Yandex Managed Airflow shares similar configuration options with the standard airflow type, with the following exceptions:
max_snapshot_ids_per_request: This option is deprecated and not supported.- Authentication: YC Airflow requires additional credentials, including both a
tokenand a combination ofusernameandpassword.
Unlike the airflow type, YC Airflow leverages Yandex Cloud's internal authentication mechanisms. Therefore, all requests to the Airflow API must include a valid Yandex Cloud IAM-token for authentication.
The default gateway and connection keys specify what should happen when gateways or connections are not explicitly specified. Find additional details in the configuration overview page gateway/connection defaults section.
If a configuration contains multiple gateways, SQLMesh will use the first one in the gateways dictionary by default. The default_gateway key is used to specify a different gateway name as the SQLMesh default.
| Option | Description | Type | Required |
|---|---|---|---|
default_gateway |
The name of a gateway to use if one is not provided explicitly (Default: the gateway defined first in the gateways option) |
string | N |
The default_connection, default_test_connection, and default_scheduler keys are used to specify shared defaults across multiple gateways.
For example, you might have a specific connection where your tests should run regardless of which gateway is being used. Instead of duplicating the test connection information in each gateway specification, specify it once in the default_test_connection key.
| Option | Description | Type | Required |
|---|---|---|---|
default_connection |
The default connection to use if one is not specified in a gateway (Default: A DuckDB connection that creates an in-memory database) | connection | N |
default_test_connection |
The default connection to use when running tests if one is not specified in a gateway (Default: A DuckDB connection that creates an in-memory database | connection) | N |
default_scheduler |
The default scheduler configuration to use if one is not specified in a gateway (Default: built-in scheduler) | scheduler | N |
To enable debug mode set the SQLMESH_DEBUG environment variable to one of the following values: "1", "true", "t", "yes" or "y".
Enabling this mode ensures that full backtraces are printed when using CLI. The default log level is set to DEBUG when this mode is enabled.
Example enabling debug mode for the CLI command sqlmesh plan:
=== "Bash"
```bash
$ SQLMESH_DEBUG=1 sqlmesh plan
```
=== "MS Powershell"
```powershell
PS> $env:SQLMESH_DEBUG=1
PS> sqlmesh plan
```
=== "MS CMD"
```cmd
C:\> set SQLMESH_DEBUG=1
C:\> sqlmesh plan
```
We strive to make SQLMesh the best data transformation tool on the market. Part of accomplishing that is continually fixing bugs, adding features, and improving SQLMesh's performance.
We prioritize our development work based on the needs of SQLMesh users. Some users share their needs via our Slack or Github communities, but many do not. We have added some simple anonymized usage information (telemetry) to SQLMesh to ensure the needs of all users are heard.
All information is anonymized with hash functions, so we could not link data to a specific company, user, or project even if we wanted to (which we don't!). No information is related to credentials or authentication.
We collect anonymized information about SQLMesh project complexity and usage - for example, number of models, count of model kinds, project load time, whether an error occurred during a plan/run (no stacktraces or error message), and names (but not values) of the arguments passed to CLI commands.
You can disable collection of anonymized usage information with these methods:
- Set the root
disable_anonymized_analytics: truekey in your SQLMesh project configuration file - Execute SQLMesh commands with an environment variable
SQLMESH__DISABLE_ANONYMIZED_ANALYTICSset to1,true,t,yes, ory
SQLMesh by default uses all of your cores when loading models and snapshots. It takes advantage of fork which is not available on Windows. The default is to use the same number of workers as cores on your machine if fork is available.
You can override this setting by setting the environment variable MAX_FORK_WORKERS. A value of 1 will disable forking and load things sequentially.