Usage
explore: explore_name {
symmetric_aggregates: yes
}
|
Hierarchy
symmetric_aggregates |
Default Value
yes
Accepts
A Boolean (yes or no)
|
Definition
The symmetric_aggregates parameter determines whether or not symmetric aggregates will be applied within a given Explore. When symmetric_aggregates is on, aggregate functions return correct results, even when joins result in a fanout. Symmetric aggregates are described in more detail on the Understanding symmetric aggregates Best Practices page, and the fanout problem they solve is explained in The problem of SQL fanouts Community post.
By default, symmetric aggregates are turned on for every Explore within Looker. This means that if your SQL dialect supports symmetric aggregates, you need to include the symmetric_aggregates parameter only if you'd like to disable that functionality for an Explore.
Examples
Turn on symmetric aggregates for the product Explore:
explore: product {
symmetric_aggregates: yes # the default value, could be excluded
}
Turn off symmetric aggregates for the customer Explore:
explore: customer {
symmetric_aggregates: no
}
Things to consider
Create joins carefully when symmetric aggregates are off
Symmetric aggregates protect certain calculations from giving incorrect results when a join results in a fanout. Therefore, if your dialect does not support symmetric aggregates, or if you choose to turn them off, you will need to be careful when you execute joins in Looker. This problem and the workarounds for it are described in great detail in the Community post The problem of SQL fanouts.
Not all database dialects support median and percentile measure types with symmetric aggregates
When symmetric aggregates are enabled, Looker automatically converts the percentile and median measure types to percentile_distinct and median_distinct when a join involves a fanout. Not all database dialects that support symmetric aggregates support the percentile_distinct and median_distinct measure types. You can see whether your database dialect supports the percentile_distinct and median_distinct measure types on the Measure types documentation page.
If you receive an error similar to SQL dialect doesn't support Symmetric Aggregates with percentiles, field ignored., this indicates that your database dialect does not support the percentile_distinct and median_distinct measure types. To work around this, change the measure type to type: number and then specify the aggregate function with sql: median(${dimension}). This disables symmetric aggregates, however.
Dialect support for symmetric aggregates
The ability to use symmetric aggregates depends on the database dialect your Looker connection is using. In the latest release of Looker, the following dialects support aggregate awareness:
| Dialect | Supported? |
|---|---|
| Actian Avalanche | Yes |
| Amazon Athena | Yes |
| Amazon Aurora MySQL | Yes |
| Amazon Redshift | Yes |
| Apache Druid | No |
| Apache Druid 0.13+ | No |
| Apache Druid 0.18+ | No |
| Apache Hive 2.3+ | No |
| Apache Hive 3.1.2+ | No |
| Apache Spark 3+ | Yes |
| ClickHouse | No |
| Cloudera Impala 3.1+ | Yes |
| Cloudera Impala 3.1+ with Native Driver | Yes |
| Cloudera Impala with Native Driver | No |
| DataVirtuality | Yes |
| Databricks | Yes |
| Denodo 7 | Yes |
| Denodo 8 | Yes |
| Dremio | No |
| Dremio 11+ | Yes |
| Exasol | Yes |
| Firebolt | Yes |
| Google BigQuery Legacy SQL | Yes |
| Google BigQuery Standard SQL | Yes |
| Google Cloud PostgreSQL | Yes |
| Google Cloud SQL | Yes |
| Google Spanner | Yes |
| Greenplum | Yes |
| HyperSQL | No |
| IBM Netezza | Yes |
| MariaDB | Yes |
| Microsoft Azure PostgreSQL | Yes |
| Microsoft Azure SQL Database | Yes |
| Microsoft Azure Synapse Analytics | Yes |
| Microsoft SQL Server 2008+ | Yes |
| Microsoft SQL Server 2012+ | Yes |
| Microsoft SQL Server 2016 | Yes |
| Microsoft SQL Server 2017+ | Yes |
| MongoBI | No |
| MySQL | Yes |
| MySQL 8.0.12+ | Yes |
| Oracle | Yes |
| Oracle ADWC | Yes |
| PostgreSQL 9.5+ | Yes |
| PostgreSQL pre-9.5 | Yes |
| PrestoDB | Yes |
| PrestoSQL | Yes |
| SAP HANA 2+ | Yes |
| SingleStore | Yes |
| SingleStore 7+ | Yes |
| Snowflake | Yes |
| Teradata | Yes |
| Trino | Yes |
| Vector | Yes |
| Vertica | Yes |