Cubes
A cube represents a table of data in Cube.
Cubes are typically declared in separate files with one cube per file. Within each cube are definitions of measures, dimensions, hierarchies, segments, joins between cubes, pre-aggregations, and data access policies.
cubes:
- name: users
sql_table: users
joins:
- name: organizations
relationship: many_to_one
sql: "{CUBE.organization_id} = {organizations.id}"
measures:
- name: count
type: count
sql: id
dimensions:
- name: organization_id
sql: organization_id
type: number
primary_key: true
- name: created_at
sql: created_at
type: time
- name: country
sql: country
type: stringParameters
name
The name parameter serves as the identifier of a cube. It must be unique among
all cubes and views within a deployment and follow the naming
conventions.
cubes:
- name: orders
sql_table: orderssql_alias
Use sql_alias when auto-generated cube alias prefix is too long and truncated
by databases such as Postgres:
cubes:
- name: order_facts_about_literally_everything_in_the_world
sql_table: orders
sql_alias: order_factsIt'll generate aliases for members such as order_facts__count. sql_alias affects
all member names including pre-aggregation table names.
extends
You can use the extends parameter to extend cubes in order to reuse
all declared members of a cube.
In the example below, extended_order_facts will reuse the sql and count measures
from order_facts:
cubes:
- name: order_facts
sql_table: orders
measures:
- name: count
type: count
sql: id
- name: extended_order_facts
extends: order_facts
measures:
- name: double_count
type: number
sql: "{count} * 2"You can also omit the cube name while defining a cube in JavaScript. This way,
Cube doesn't register this cube globally; instead it returns a reference which
you can use while combining cubes. It makes sense to use it for dynamic data
model generation and reusing with extends. Previous example without defining
order_facts cube globally:
const order_facts = cube({
sql: `orders`,
measures: {
count: {
type: `count`,
sql: `id`
}
}
})
cube(`extended_order_facts`, {
extends: order_facts,
measures: {
double_count: {
type: `number`,
sql: `${count} * 2`
}
}
})data_source
Each cube can have its own data_source name to support scenarios where data
should be fetched from multiple databases. The value of the data_source
parameter will be passed to the driverFactory()
function as part of the context parameter. By default, each cube has a
default value for its data_source; to override it you can use:
cubes:
- name: order_facts
data_source: prod_db
sql_table: orderssql
The sql parameter specifies the SQL that will be used to generate a table that
will be queried by a cube. It can be any valid SQL query, but usually it takes
the form of a SELECT * FROM my_table query. Please note that you don't need to
use GROUP BY in a SQL query on the cube level. This query should return a
plain table, without aggregations.
cubes:
- name: orders
sql: SELECT * FROM ordersYou can also reference other cubes' SQL statements for code reuse using the
{cube.sql()} function:
cubes:
- name: companies
sql:
SELECT
users.company_name,
users.company_id
FROM {users.sql()} AS usersIt is recommended to prefer the sql_table parameter
over the sql parameter for all cubes that are supposed to use queries like
this: SELECT * FROM table.
sql_table
The sql_table parameter is used as a concise way for defining a cube that uses
a query like this: SELECT * FROM table. Instead of using the
sql parameter, use sql_table with the table name that this
cube will query.
cubes:
- name: orders
sql_table: public.orderstitle
Use the title parameter to change the display name of the cube.
By default, Cube will humanize the cube's name, so for instance, users_orders
would become Users Orders. If default humanizing doesn't work in your case,
please use the title parameter. It is highly recommended to give human readable
names to your cubes. It will help everyone on a team better understand the data
structure and will help maintain a consistent set of definitions across an
organization.
cubes:
- name: orders
sql_table: orders
title: Product Ordersdescription
This parameter provides a human-readable description of a cube. When applicable, it will be displayed in Playground and exposed to data consumers via APIs and integrations.
A description can give a hint both to your team and end users, making sure they interpret the data correctly.
cubes:
- name: orders
sql_table: orders
title: Product Orders
description: All orders-related informationpublic
The public parameter is used to manage the visibility of a cube. Valid values
for public are true and false. When set to false, this cube cannot
be queried through the API. Defaults to true.
cubes:
- name: orders
sql_table: public.orders
public: falseTo learn more about using public to control visibility based on security
context, read the Controlling access to cubes and views
recipe.
refresh_key
Cube's caching layer uses refresh_key queries to get the current version of
content for a specific cube. If a query result changes, Cube will invalidate all
queries that rely on that cube.
The default values for refresh_key are
every: '2 minute'for BigQuery, Athena, Snowflake, and Presto.every: '10 second'for all other databases.
Refresh key of a query is a concatenation of all cubes refresh keys involved in query. For rollup queries pre-aggregation table name is used as a refresh key.
You can set up a custom refresh check SQL by changing the refresh_key parameter.
Often, a MAX(updated_at_timestamp) for OLTP data is a viable option, or
examining a metadata table for whatever system is managing the data to see when
it last ran. timestamp in that case.
cubes:
- name: order_facts
sql_table: orders
refresh_key:
sql: SELECT MAX(updated_at_timestamp) FROM ordersYou can use interval-based refresh_key. For example:
cubes:
- name: order_facts
sql_table: orders
refresh_key:
every: 1 hourevery - can be set as an interval with granularities second, minute,
hour, day, and week or accept CRON string with some limitations. If you
set every as CRON string, you can use the timezone parameter. It takes
precedence over the query timezone.
For example:
cubes:
- name: order_facts
sql_table: orders
refresh_key:
every: 30 5 * * 5
timezone: America/Los_Angelesevery can accept only equal time intervals - so "Day of month" and "month"
intervals in CRON expressions are not supported.
Cube supports two different formats of CRON expressions: standard and advanced with support for seconds.
Such refresh_key is just a syntactic sugar over refresh_key SQL. It's
guaranteed that refresh_key change it's value at least once during every
interval. It will be converted to appropriate SQL select which value will change
over time based on interval value. Values of interval based refresh_key are
tried to be checked ten times within defined interval but not more than once per
1 second and not less than once per 5 minute. For example if interval is
10 minute it's refreshKeyRenewalThreshold will be 60 seconds and generated
refresh_key SQL (Postgres) would be:
SELECT FLOOR(EXTRACT(EPOCH FROM NOW()) / 600)For 5 second interval refreshKeyRenewalThreshold will be just 1 second and
SQL will be:
SELECT FLOOR(EXTRACT(EPOCH FROM NOW()) / 5)Supported cron formats
- Standard cron syntax
* * * * *
┬ ┬ ┬ ┬ ┬
│ │ │ │ |
│ │ │ │ └ day of week (0 - 7) (0 or 7 is Sun)
│ │ │ └───── month (1 - 12)
│ │ └────────── day of month (1 - 31, L)
│ └─────────────── hour (0 - 23)
└──────────────────── minute (0 - 59)- Advanced cron format with support for seconds
* * * * * *
┬ ┬ ┬ ┬ ┬ ┬
│ │ │ │ │ |
│ │ │ │ │ └ day of week (0 - 7) (0 or 7 is Sun)
│ │ │ │ └───── month (1 - 12)
│ │ │ └────────── day of month (1 - 31, L)
│ │ └─────────────── hour (0 - 23)
│ └──────────────────── minute (0 - 59)
└───────────────────────── second (0 - 59, optional)meta
Custom metadata. Can be used to pass any information to the frontend.
cubes:
- name: orders
sql_table: orders
title: Product Orders
meta:
any: value
calendar
The calendar parameter is used to mark calendar cubes.
It's set to false by default.
When set to true, Cube will treat this cube as a calendar cube and allow to
override time-shifts and granularities
on its time dimensions. This can be useful for time-shift
calculations with a custom calendar.
pre_aggregations
The pre_aggregations parameter is used to configure pre-aggregations.
joins
The joins parameter is used to configure joins.
dimensions
The dimensions parameter is used to configure dimensions.
hierarchies
The hierarchies parameter is used to configure hierarchies.
segments
The segments parameter is used to configure segments.
measures
The measures parameter is used to configure measures.
access_policy
The access_policy parameter is used to configure data access policies.