approximate

Usage

view: view_name {
  measure: field_name {
    approximate: yes 
  }
}
Hierarchy
approximate
Possible Field Types
Measure

Accepts
A Boolean (yes or no)

Definition

See the Dialect support for approximate section on this page for the list of dialects that support indexes.

The approximate parameter lets you use approximate counting with measures of type: count and type: count_distinct. With large datasets, approximate counts can be much faster than exact counts and are typically within a few percent of the actual value. Please check your SQL dialect's documentation to understand the speed and accuracy tradeoffs of this method.

measure: apx_unique_count {
  type: count_distinct
  approximate: yes   # default value is no
  sql: ${id} ;;
}

-

Turning on approximate with a measure of type: count might seem unnecessary, because the approximate counting feature applies only to distinct counts. However, there are some situations when Looker automatically turns measures of type: count into a distinct count of a primary key to provide accurate results for joined views. In those situations, approximate counting may be useful.

Dialect support for approximate

The ability to use approximate depends on the database dialect your Looker connection is using. In the latest version of Looker, the following dialects support approximate:

Dialect Supported?
Actian Avalanche
No
Amazon Athena
Yes
Amazon Aurora MySQL
No
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+
No
ClickHouse
No
Cloudera Impala 3.1+
Yes
Cloudera Impala 3.1+ with Native Driver
Yes
Cloudera Impala with Native Driver
Yes
DataVirtuality
No
Databricks
No
Denodo 7
No
Denodo 8
No
Dremio
No
Dremio 11+
No
Exasol
No
Firebolt
No
Google BigQuery Legacy SQL
Yes
Google BigQuery Standard SQL
Yes
Google Cloud PostgreSQL
No
Google Cloud SQL
No
Google Spanner
No
Greenplum
No
HyperSQL
No
IBM Netezza
No
MariaDB
No
Microsoft Azure PostgreSQL
No
Microsoft Azure SQL Database
No
Microsoft Azure Synapse Analytics
No
Microsoft SQL Server 2008+
No
Microsoft SQL Server 2012+
No
Microsoft SQL Server 2016
No
Microsoft SQL Server 2017+
No
MongoBI
No
MySQL
No
MySQL 8.0.12+
No
Oracle
No
Oracle ADWC
No
PostgreSQL 9.5+
No
PostgreSQL pre-9.5
No
PrestoDB
Yes
PrestoSQL
Yes
SAP HANA
No
SAP HANA 2+
No
SingleStore
No
SingleStore 7+
No
Snowflake
No
Teradata
No
Trino
Yes
Vector
No
Vertica
No