Pre-aggregations

Pre-aggregations are materialized query results persisted as tables. Cube.js has an ability to analyze queries against a defined set of pre-aggregation rules in order to choose the optimal one that will be used to create pre-aggregation table.

If Cube.js finds a suitable pre-aggregation rule, database querying becomes a multi-stage process:

1. Cube.js checks if an up-to-date copy of the pre-aggregation exists.

2. Cube.js will execute a query against the pre-aggregated tables instead of the raw data.

Pre-aggregations can be defined in the preAggregations available on each cube. A more in-depth diagram detailing how pre-aggregations are selected can be found here.

Naming

Pre-aggregations must have, at minimum, a name and a type. This name, along with the name of the cube will be used as a prefix for pre-aggregation tables created in the database.

Pre-aggregation names should:

• Be unique within a cube
• Start with a lowercase letter
• Consist of numbers, letters and _

cube(`Orders`, {
  sql: `SELECT * FROM orders`,

  ...,

  preAggregations: {
    ordersByStatus: {
      dimensions: [CUBE.status],
      measures: [CUBE.count],
    },
  },
});

Pre-aggregations must include all dimensions, measures, and filters you will query with.

Parameters

type

Cube supports three types of pre-aggregations:

• rollup
• originalSql
• rollupJoin

The default type is rollup.

rollup

Rollup pre-aggregations are the most effective way to boost performance of any analytical application. The blazing fast performance of tools like Google Analytics or Mixpanel are backed by a similar concept. The theory behind it lies in multi-dimensional analysis, and a rollup pre-aggregation is the result of a roll-up operation on an OLAP cube. A rollup pre-aggregation is essentially the summarized data of the original cube grouped by any selected dimensions of interest.

The most performant kind of rollup pre-aggregation is an additive rollup: all measures of which are based on decomposable aggregate functions. Additive measure types are: count, sum, min, max or countDistinctApprox. The performance boost in this case is based on two main properties of additive rollup pre-aggregations:

1. A rollup pre-aggregation table usually contains many fewer rows than its' corresponding original fact table. The fewer dimensions that are selected for roll-up means fewer rows in the materialized result. A smaller number of rows therefore means less time to query rollup pre-aggregation tables.

2. If your query is a subset of dimensions and measures of an additive rollup, then it can be used to calculate a query without accessing the raw data. The more dimensions and measures are selected for roll-up, the more queries can use this particular rollup.

Rollup definitions can contain members from a single cube as well as from multiple cubes. In case of multiple cubes being involved, the join query will be built according to the standard rules of cubes joining.

Rollups are selected for querying based on properties found in queries made to the Cube.js REST API. A thorough explanation can be found under Getting Started with Pre-Aggregations.

cube(`Orders`, {
  sql: `SELECT * FROM orders`,

  ...,

  preAggregations: {
    ordersByCompany: {
      measures: [CUBE.count],
      dimensions: [CUBE.status],
    },
  },
});

originalSql

As the name suggests, it persists the results of the sql property of the cube. Pre-aggregations of type originalSql should only be used when the cube's sql is a complex query (i.e. nested, window functions and/or multiple joins). We strongly recommend only persisting results of originalSql back to the source database. They often do not provide much in the way of performance directly, but there are two specific applications:

1. They can be used in tandem with the useOriginalSqlPreAggregations option in other rollup pre-aggregations.

2. Situations where it is not possible to use a rollup pre-aggregations, such as funnels.

For example, to pre-aggregate all completed orders, you could do the following:

cube(`CompletedOrders`, {
  sql: `SELECT * FROM orders WHERE completed = true`,

  ...,

  preAggregations: {
    main: {
      type: `originalSql`
    },
  },
});

rollupJoin

Cube is capable of performing joins between pre-aggregations from different data sources to avoid making excessive queries to them.

In the following example, we have a Users cube with a usersRollup pre-aggregation, and an Orders cube with an ordersRollup pre-aggregation, and an ordersWithUsersRollup pre-aggregation. Note the following:

• Both cubes have different values for dataSource.
• The type of ordersWithUsersRollup is rollupJoin.
• This pre-aggregation has a special property rollups which is an array containing references to both "source" rollups.

cube(`Users`, {
  dataSource: 'postgres',
  sql: `SELECT * FROM public.users`,

  preAggregations: {
    usersRollup: {
      dimensions: [CUBE.id, CUBE.name],
    },
  },

  measures: {
    count: {
      type: `count`,
    },
  },

  dimensions: {
    id: {
      sql: `id`,
      type: `number`,
      // We need to set this field as the primary key for joins to work
      primaryKey: true,
    },
    name: {
      sql: `first_name || last_name`,
      type: `string`,
    },
  },
});

cube('Orders', {
  dataSource: 'mssql',
  sql: `SELECT * FROM orders`,

  preAggregations: {
    ordersRollup: {
      measures: [CUBE.count],
      dimensions: [CUBE.userId, CUBE.status],
      timeDimension: CUBE.createdAt,
      granularity: `day`,
    },
    // Here we add a new pre-aggregation of type `rollupJoin`
    ordersWithUsersRollup: {
      type: `rollupJoin`,
      measures: [CUBE.count],
      dimensions: [Users.name],
      rollups: [Users.usersRollup, CUBE.ordersRollup],
    },
  },

  joins: {
    Users: {
      relationship: `belongsTo`,
      // Make sure the join uses dimensions on the cube, rather than
      // the column names from the underlying SQL
      sql: `${CUBE.userId} = ${Users.id}`,
    },
  },

  measures: {
    count: {
      type: `count`,
    },
  },

  dimensions: {
    id: {
      sql: `id`,
      type: `number`,
      primaryKey: true,
    },
    userId: {
      sql: `user_id`,
      type: `number`,
    },
    status: {
      sql: `status`,
      type: `string`,
    },
    createdAt: {
      sql: `created_at`,
      type: `time`,
    },
  },
});

cube('Orders', {
  sql: `SELECT * FROM orders`,

  preAggregations: {
    ordersRollup: {
      measures: [CUBE.count],
      dimensions: [Users.name, CUBE.status],
      timeDimension: CUBE.createdAt,
      granularity: `day`,
    },
  },
});

measures

The measures property is an array of measures from the cube that should be included in the pre-aggregation:

cube('Orders', {
  sql: `SELECT * FROM orders`,

  measures: {
    count: {
      type: `count`,
    },
  },

  preAggregations: {
    usersRollup: {
      measures: [CUBE.count],
    },
  },
});

dimensions

The dimensions property is an array of dimensions from the cube that should be included in the pre-aggregation:

cube('Orders', {
  sql: `SELECT * FROM orders`,

  dimensions: {
    status: {
      type: `string`,
      sql: `status`,
    },
  },

  preAggregations: {
    usersRollup: {
      dimensions: [CUBE.status],
    },
  },
});

timeDimension

The timeDimension property can be any dimension of type time. All other measures and dimensions in the schema are aggregated This property is an extremely useful tool for improving performance with massive datasets.

cube('Orders', {
  sql: `SELECT * FROM orders`,

  measures: {
    count: {
      type: `count`,
    },
  },

  dimensions: {
    status: {
      type: `string`,
      sql: `status`,
    },
    createdAt: {
      type: `time`,
      sql: `created_at`,
    },
  },

  preAggregations: {
    ordersByStatus: {
      measures: [CUBE.count],
      dimensions: [CUBE.status],
      timeDimension: CUBE.createdAt,
      granularity: `day`,
    },
  },
});

A granularity must also be included in the pre-aggregation definition.

granularity

The granularity property defines the granularity of data within the pre-aggregation. If set to week, for example, then Cube.js will pre-aggregate the data by week and persist it to Cube Store.

cube('Orders', {
  sql: `SELECT * FROM orders`,

  ...,

  preAggregations: {
    usersRollupByWeek: {
      measures: [CUBE.count],
      dimensions: [CUBE.status],
      timeDimension: CUBE.createdAt,
      granularity: `week`,
    },
  },
});

The value can be one of second, minute, hour, day, week, month, quarter or year. This property is required when using timeDimension.

segments

The segments property is an array of segments from the cube that can target the pre-aggregation:

cube(`Orders`, {
  sql: `SELECT * FROM orders`,

  measures: {
    count: {
      type: `count`,
    },
  },

  segments: {
    onlyComplete: {
      sql: `${CUBE}.status = 'completed'`,
    },
  },

  preAggregations: {
    main: {
      measures: [CUBE.count],
      segments: [CUBE.onlyComplete],
    },
  },
});

partitionGranularity

The partitionGranularity defines the granularity for each partition of the pre-aggregation:

cube('Orders', {
  sql: `SELECT * FROM orders`,

  ...,

  preAggregations: {
    usersRollup: {
      measures: [CUBE.count],
      dimensions: [CUBE.status],
      timeDimension: CUBE.createdAt,
      granularity: `day`,
      partitionGranularity: `month`,
    },
  },
});

The value can be one of hour, day, week, month, quarter, year. A timeDimension and granularity must also be included in the pre-aggregation definition. This property is required when using partitioned pre-aggregations.

refreshKey

Cube.js can also take care of keeping pre-aggregations up to date with the refreshKey property. By default, it is set to every: '1 hour'.

sql

You can set up a custom refresh check strategy by using the sql property:

cube(`Orders`, {
  sql: `SELECT * FROM orders`,

  preAggregations: {
    main: {
      measures: [CUBE.count],
      refreshKey: {
        sql: `SELECT MAX(created_at) FROM orders`,
      },
    },
  },
});

In the above example, the refresh key SQL will be executed every 10 seconds, as every is not defined. If the results of the SQL refresh key differ from the last execution, then the pre-aggregation will be refreshed.

every

The refreshKey can define an every property which can be used to refresh pre-aggregations based on a time interval. By default, it is set to 1 hour unless the sql property is also defined, in which case it is set to 10 seconds. For example:

cube(`Orders`, {
  sql: `SELECT * FROM orders`,

  preAggregations: {
    main: {
      measures: [CUBE.count],
      refreshKey: {
        every: `1 day`,
      },
    },
  },
});

For possible every parameter values please refer to refreshKey documentation.

You can also use every with sql:

cube(`Orders`, {
  sql: `SELECT * FROM orders`,

  preAggregations: {
    main: {
      measures: [CUBE.count],
      refreshKey: {
        every: `1 hour`,
        sql: `SELECT MAX(created_at) FROM orders`,
      },
    },
  },
});

In the above example, the refresh key SQL will be executed every hour. If the results of the SQL refresh key differ from the last execution, then the pre-aggregation will be refreshed.

incremental

You can incrementally refresh partitioned rollups by setting incremental: true. This option defaults to false.

cube(`Orders`, {
  sql: `SELECT * FROM orders`,

  ...,

  preAggregations: {
    main: {
      measure: [CUBE.count],
      timeDimension: CUBE.createdAt,
      granularity: `day`,
      partitionGranularity: `day`,
      refreshKey: {
        every: `1 day`,
        incremental: true,
      },
    },
  },
});

updateWindow

The incremental: true flag generates a special refreshKey SQL query which triggers a refresh for partitions where the end date lies within the updateWindow from the current time.

In the example below, it will refresh today's and the last 7 days of partitions once a day. Partitions before the 7 day interval will not be refreshed once they are built unless the rollup SQL is changed.

cube(`Orders`, {
  sql: `SELECT * FROM orders`,

  ...,

  preAggregations: {
    main: {
      measure: [CUBE.count],
      timeDimension: CUBE.createdAt,
      granularity: `day`,
      partitionGranularity: `day`,
      refreshKey: {
        every: `1 day`,
        incremental: true,
        updateWindow: `7 day`,
      },
    },
  },
});

This property is required when using incremental refreshes.

allowNonStrictDateRangeMatch

The allowNonStrictDateRangeMatch property can be used to allow queries to match this pre-aggregation when using non-strict date ranges. This is useful when using a visualization tools such as Apache Superset that use loose date ranges by default.

cube(`Orders`, {
  sql: `SELECT * FROM orders`,

  ...,

  preAggregations: {
    main: {
      measure: [CUBE.count],
      timeDimension: CUBE.createdAt,
      granularity: `day`,
      partitionGranularity: `day`,
      allowNonStrictDateRangeMatch: true,
    },
  },
});

useOriginalSqlPreAggregations

Cube.js supports multi-stage pre-aggregations by reusing original SQL pre-aggregations in rollups through the useOriginalSqlPreAggregations property. It is helpful in cases where you want to re-use a heavy SQL query calculation in multiple rollup pre-aggregations. Without useOriginalSqlPreAggregations enabled, Cube.js will always re-execute all underlying SQL calculations every time it builds new rollup tables.

cube(`Orders`, {
  sql: `
    SELECT * FROM orders1
    UNION ALL
    SELECT * FROM orders2
    UNION ALL
    SELECT * FROM orders3
    `,

  ...,

  preAggregations: {
    main: {
      type: `originalSql`,
    },
    statuses: {
      measures: [CUBE.count],
      dimensions: [CUBE.status],
      useOriginalSqlPreAggregations: true,
    },
    completedOrders: {
      measures: [CUBE.count],
      timeDimension: CUBE.completedAt,
      granularity: `day`,
      useOriginalSqlPreAggregations: true,
    },
  },
});

scheduledRefresh

To always keep pre-aggregations up-to-date, you can set scheduledRefresh: true. This option defaults to true. If set to false, pre-aggregations will always be built on-demand. The refreshKey is used to determine if there's a need to update specific pre-aggregations on each scheduled refresh run. For partitioned pre-aggregations, min and max dates for timeDimension are checked to determine range for the refresh.

Each time a scheduled refresh is run, it takes every pre-aggregation partition starting with most recent ones in time and checks if the refreshKey has changed. If a change was detected, then that partition will be refreshed.

In development mode, Cube.js runs the background refresh by default and will refresh all pre-aggregations which have scheduledRefresh: true.

Please consult Production Checklist for best practices on running background refresh in production environments.

cube(`Orders`, {
  sql: `SELECT * FROM orders`,

  // ...

  preAggregations: {
    ordersByStatus: {
      measures: [CUBE.count],
      dimensions: [CUBE.status],
      timeDimension: CUBE.createdAt,
      granularity: `day`,
      partitionGranularity: `month`,
    },
  },
});

buildRangeStart and buildRangeEnd

The build range defines what partitions should be built by a scheduled refresh. Data will never be queried beyond this range. By default, the build range is defined as the minimum and maximum values possible for the timeDimension used in the rollup.

cube(`Orders`, {
  sql: `SELECT * FROM orders`,

  ...,

  preAggregations: {
    main: {
      measures: [CUBE.count],
      timeDimension: CUBE.createdAt,
      granularity: `day`,
      buildRangeStart: {
        sql: `SELECT NOW() - interval '300 day'`,
      },
      buildRangeEnd: {
        sql: `SELECT NOW()`,
      },
    },
  },
});

It can be used together with the pre-aggregation's refreshKey to define granular update settings. Set refreshKey.updateWindow to the interval in which your data can change and buildRangeStart to the earliest point of time when history should be available.

In the following example, refreshKey.updateWindow is 1 week and buildRangeStart is SELECT NOW() - interval '365 day', so the scheduled refresh will build historical partitions for 365 days in the past and will only refresh last week's data.

cube(`Orders`, {
  sql: `SELECT * FROM orders`,

  ...,

  preAggregations: {
    main: {
      measures: [CUBE.count],
      timeDimension: CUBE.createdAt,
      granularity: `day`,
      partitionGranularity: `month`,
      buildRangeStart: {
        sql: `SELECT NOW() - interval '365 day'`,
      },
      buildRangeEnd: {
        sql: `SELECT NOW()`,
      },
      refreshKey: {
        updateWindow: `1 week`,
      },
    },
  },
});

indexes

In case of pre-aggregation tables having significant cardinality, you might want to create indexes for them in databases which support it. This is can be done as follows:

cube(`Orders`, {
  sql: `SELECT * FROM orders`,

  ...,

  preAggregations: {
    categoryAndDate: {
      measures: [CUBE.count],
      dimensions: [CUBE.category],
      timeDimension: CUBE.createdAt,
      granularity: `day`,
      indexes: {
        categoryIndex: {
          columns: [CUBE.category],
        },
      },
    },
  },
});

For originalSql pre-aggregations, the original column names as strings can be used:

cube(`Orders`, {
  sql: `SELECT * FROM orders`,

  ...,

  preAggregations: {
    main: {
      type: `originalSql`,
      indexes: {
        timestampIndex: {
          columns: ['timestamp'],
        },
      },
    },
  },
});