SQL blocks
Execute SQL commands directly in your database, data warehouse, etc.
Credentials
Before starting, you need to add credentials so Mage can execute your SQL commands.
Follow the steps for the database or data warehouse of your choice:
Add SQL block to pipeline
- Create a new pipeline or open an existing pipeline.
- Add a data loader, transformer, or data exporter block.
- Select
SQL
.
Configure SQL block
There are 4 - 5 fields that must be configured for each SQL block:
Field | Required | Description |
---|---|---|
Data provider | Yes | The database or data warehouse you want to execute your SQL commands in. |
Profile | Yes | When you add your credentials to the io_config.yaml file, you added them under a key. That key is called the profile. Choose which set of credentials you want this SQL block to use. |
Use raw SQL | No | You can write raw SQL and it’ll be executed as written in your data provider. |
Database | Depends on data provider | Some data warehouses require that we explicitly state the name of the database we want to write to. If this is present, it’s required. The name of the table that is created follows this convention: [database].[schema].[pipeline UUID]_[block UUID] . |
Schema to save | Yes | Every SQL block will save data to your data provider. The name of the table that is created follows this convention: [schema].[pipeline UUID]_[block UUID] . |
Table | No | SQL blocks will automatically name your table for you using a naming convention (see the section Automatic naming of tables for more information). You can override this automatic naming convention by filling in a value in this field. |
Write policy | Yes | How do you want to handle existing data with the same database, schema, and table name? See below for more information. |
Write policies
Policy | Description |
---|---|
Append | Add rows to the existing table. |
Replace | Delete the existing data. |
Fail | Raise an error during execution. |
YAML configuration
You can also modify block configuration in pipeline’s metadata.yaml
file. Each block has a configuration
field.
Example configuration
configuration:
data_provider: sqlserver
data_provider_profile: default
data_provider_schema: ''
export_write_policy: append
limit: 1000
limit_in_pipeline_run: 1
use_raw_sql: false
In addition to the fields mentioned in the table above. Here are some extra fields that can be included in the configuration:
Field | Required | Description |
---|---|---|
limit | No | The maximum number of rows to return in notebook. |
limit_in_pipeline_run | No | The maximum number of rows to return when running the block in the pipeline run. |
Automatically created tables
Each SQL block will create a table in the data provider of your choice.
When you run a block, it’ll execute your SQL command, then store the results in a table created in your database or data warehouse.
Using raw SQL
If you’re using version 0.9.69
or less and interpolating a SQL command from an upstream block that uses raw SQL:
if the downstream block’s SQL command is referencing the upstream block using a variable such as {{ df_1 }}
and ends the statement with a semi-colon (;
), there is an interpolation error.
To work around the error, remove the semi-colon ;
.
A fix will be available in 0.9.70
.
If you toggle this setting, you’re responsible for writing the CREATE TABLE
command and the
INSERT
command.
For example, if a table already exists then you can write the INSERT
statement:
INSERT INTO mage.users
SELECT 1 AS id, 'Urza' AS username;
If the table doesn’t exist yet, you can write both the CREATE TABLE
statement
and the INSERT
statement:
CREATE TABLE IF NOT EXISTS mage.users (
id BIGINT
, username VARCHAR(255)
);
WITH users AS (
SELECT
1 AS id
, 'Urza' AS username
)
INSERT INTO mage.users
SELECT
*
FROM users;
This SQL query will create a table named mage.users
with 2 columns: id
as a BIGINT
and username
as a VARCHAR(255)
.
Then, it’ll insert a single row into that table.
Required SQL statements
When writing raw SQL, you must at least 1 of the following statements:
SELECT
SELECT 1;
INSERT
INSERT INTO some_table SELECT 1;
CREATE TABLE
CREATE TABLE some_table (id BIGINT);
DROP TABLE
DROP TABLE some_table;
UPDATE
UPDATE some_table SET col1 = 'value1' WHERE col2 = 'value2'
Multiple SQL statements
You can execute multiple SQL statements in a SQL block. Separate your SQL statements using a semi-colon (;
).
Automatic naming of tables
If you don’t choose the setting for using raw SQL, the name of this automatically created table follows these conventions:
- If
Database
field is configured:[database].[schema].[pipeline UUID]_[block UUID]
- If no
Database
field is configured:[schema].[pipeline UUID]_[block UUID]
Where pipeline UUID is the name of the current pipeline you’re editing.
Where block UUID is the name of the SQL block you are running.
Upstream blocks
If your SQL block depends on upstream blocks that aren’t SQL blocks (e.g. Python code blocks), then those blocks will also automatically create tables.
The name of those tables follows the same naming convention mentioned above.
Variables
All SQL blocks have the following variables they can access in their query:
{{ execution_date }}
The date and time the block is ran.
Example
SELECT '{{ execution_date }}' AS today
Result
today |
---|
2022-09-24 23:01:08.376057 |
If a SQL block has 1 or more upstream blocks, then they have access to their parent blocks’ output using the following variable:
{{ df_1 }}
Depending on how many upstream blocks there are, the variable name changes. For example, if there are 3 upstream blocks then there are 3 variables that can be accessed:
{{ df_1 }}
{{ df_2 }}
{{ df_3 }}
The SQL block UI will display which variable maps to which upstream block. By
convention, the 1st added upstream block will be {{ df_1 }}
, and every
upstream block added after that will have an incrementing number in the variable
name after the prefix df_
.
Example
SELECT a.id , b.username FROM {{ df_1 }} AS a LEFT JOIN {{ df_2 }} AS b ON
a.id = b.user_id LIMIT 1
Result
id | username |
---|---|
1 | Sorcerer supreme |
Variable interpolation
Available in versions >= 0.9.59
Interpolate values in the block’s code using data from:
- Upstream block output
- Variables
- Global variables
- Pipeline variables
- Runtime variables
- Environment variables
Upstream block output
Use the data from 1 or more upstream block’s output by using the block_output
function.
block_uuid
The UUID of the upstream block to get data from. If argument isn’t present, data from all upstream blocks will be fetched.
Optional | ✅ |
Type | str |
Example | 'data_loader_block' |
parse
A lambda function to parse the data from an upstream block’s output.
If the parse
argument isn’t present, then the fetched data from the upstream block’s output
will be interpolated as is.
Optional | ✅ |
Type | function |
Example | lambda data, variables: data['runtime'] * variables['tries'] |
-
data
If the
block_uuid
argument isn’t present, then the 1st argument in the lambda function is a list of objects.The list of objects contain the data from an upstream block’s output. The positional order of the data in the list corresponds to the current block’s upstream blocks order.
For example, if the current block has the following upstream blocks with the following output:
load_api_data
:[1, 2, 3]
load_users_data
:{ 'mage': 'powerful' }
Then the 1st argument in the lambda function will be the following list:
[ [1, 2, 3], { 'mage': 'powerful' }, ]
Optional ❌ Type If block_uuid
argument is present, then the type depends on the output from that block. Ifblock_uuid
isn’t present, then the type islist
.Example { 'mage': 'powerful' }
-
variables
A dictionary containing pipeline variables and runtime variables.Optional ❌ Type dict
Example { 'fire': 40 }
Example
With block_uuid
SELECT
'{{ block_output("magic_config", parse=lambda data, _vars: data["power"]) }}' AS power
, '{{ block_output("magic_config", parse=lambda data, _vars: data["spell"]) }}' AS spell
FROM mage.core_spells
SELECT
'{{ block_output("data_loader_block", parse=lambda data, variables: data["runtime"] * variables["tries"]) }}' AS data
FROM mage.core_spells
SELECT
'{{ block_output("load_recent_user", parse=lambda user, _variables: user["id"]) }}'
FROM mage.core_spells
Without block_uuid
SELECT
'{{ block_output(parse=lambda data, _vars: data[0]["power"]) }}' AS power
, '{{ block_output(parse=lambda data, _vars: data[0]["spell"]) }}' AS spell
FROM mage.core_spells
SELECT
'{{ block_output(parse=lambda data, variables: data[0]["runtime"] * variables[0]["tries"]) }}' AS data
FROM mage.core_spells
SELECT
'{{ block_output(parse=lambda user, _variables: user[0]["id"]) }}'
FROM mage.core_spells
Variables
Interpolate values from a dictionary containing keys and values from:
- Global variables
- Pipeline variables
- Runtime variables
Example
SELECT
'{{ variables("mana") }}' AS mana
FROM mage.dual_lands
Environment variables
Interpolate values from the environment variables.
Example
SELECT
'{{ env_var("ALLOW_POWER_9") }}' AS vintage
FROM mage.mox
Executing pure SQL
Available in versions >= 0.9.59
Mage automatically pre-processes your SQL command before sending it to the final destination.
The pre-process extracts and structures the command so that Mage can build upstream tables and properly display preview data.
However, there are scenarios where the SQL command you write must be executed as is. You can disable Mage’s pre-processing by opening a SQL block and checking the box labeled Use raw SQL and Disable query preprocessing.
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