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Filters

Field filters can be attached to objects in several contexts. They can be used on fields (measures, dimensions, dimension groups), and dashboards (at the whole-dashboard level or the element level).

Their syntax is not entirely straightforward but is quite powerful.


Properties#

Field filters have only two (2) properties, with an optional third:

field: (Required) The name of the field to reference. If you reference this field inside a view, you do not need to use the syntax view_name.field_name but otherwise you will need to use that syntax to disambiguate the field. Note: for dimension groups, you will also need to include the extension in your reference (e.g. if your dimension group has name order_at and has an option date in its timeframes property, a valid reference would be order_at_date, NOT order_at)

value: (Required) This is the value used to determine the comparison the filter will use (equal to, greater than, etc) and the value tom compare against. The syntax is discussed in depth below.

Syntax + Examples#

If you've used LookML before this syntax will feel familiar to you, and you may be able to get by without even reading this guide. We'll go in more detail based on the type of filter.

Anytime when using the Zenlytic UI you can replicate this behavior using the matches option in the dropdown for filter comparison type.

String (or text)#

ExampleDescription
FooEquals "Foo" exactly, field_name = 'Foo'
Foo,BarEquals "Foo" or "Bar" exactly, field_name in ('Foo', 'Bar')
%Foo%Matches any string that contains "Foo" (not case sensitive), e.g. matches 'fast food', field_name ilike '%Foo%'
Foo%Matches any string that starts with "Foo" (not case sensitive), e.g. matches 'food' does not match 'fast food', field_name ilike 'Foo%'
%FooMatches any string that ends with "Foo" (not case sensitive), e.g. matches 'tofoo' does not match 'food', field_name ilike '%Foo'
NULLValue is null, field_name is null
-FooNot equal to "Foo" exactly, field_name <> 'Foo'
-Foo,-BarNot equal to "Foo" or "Bar" exactly, field_name not in ('Foo', 'Bar')
-NULLValue is not null, field_name is not null
-%Foo%Does not match any string that contains "Foo" (not case sensitive), field_name not ilike '%Foo%'
-Foo%Does not match any string that starts with "Foo" (not case sensitive), field_name not ilike 'Foo%'
-%FooDoes not match any string that ends with "Foo" (not case sensitive), field_name not ilike '%Foo'

Numeric#

ExampleDescription
"=100"Equals 100 exactly, field_name = 100
"!=100","<>100"Not equal to 100 exactly, field_name &lt;&gt; 100
">=100"Greater than or equal to 100 exactly, field_name &gt;= 100
"<=100"Less than or equal to 100 exactly, field_name &lt;= 100
">100"Greater than 100 exactly, field_name &gt; 100
"<100"Less than 100 exactly, field_name &lt; 100
NULLValue is null, field_name is null
-NULLValue is not null, field_name is not null

Boolean (True or False)#

ExampleDescription
TRUEThe value evaluates to true, field_name
FALSEThe value evaluates to false, not field_name

Dates#

These are by far the most complicated, but also some of the most powerful expressions for filtering.

Examples for all of these patterns will be given below in a table.

To start with the simplest pattern, you can make sure data is all before or after a explicit date.

Moving to a more complex pattern, you can say this {interval} or last {interval} or {n} {interval} or {n} {interval} ago when interval is one of these: "week", "month", "quarter", "year", and n can be any integer.

You can also use the above patterns and append "to date" to get rolling historic date windows. You can say {interval} to date or last {interval} to date or {n} {interval} ago to date.

Finally, you can also say {n} {interval} ago for {n} {interval} to have a extremely fine-grained filter for historical dates.

ExampleDescription
"after 2021-02-03"This is any date on or after 2021-02-03
"before 2021-02-03"This is any date on or before 2021-02-03
"today"This is any date that has the same day as current_date in your warehouse
"yesterday"This is any date that has the same day as the day before current_date in your warehouse
"this week"This is any date from the start of the current week (as defined in your model) to now
"this month"This is any date from the start of the current month to now
"this quarter"This is any date from the start of the current quarter to now
"this year"This is any date from the start of the current year to now
"last week"This is any date from the start of the last complete week to the beginning of the current week
"last month"This is any date from the start of the last complete month to the beginning of the current month
"last quarter"This is any date from the start of the last complete quarter to the beginning of the current quarter
"last year"This is any date from the start of the last complete year to the beginning of the current year
"week to date"This is any date from the start of the current week (as defined in your model) to now
"month to date"This is any date from the start of the current month to now
"quarter to date"This is any date from the start of the current quarter to now
"year to date"This is any date from the start of the current year to now
"last week to date"This is any date from the start of the last complete week to same number of complete days from the start of that week that have been completed in the current week
"52 weeks ago to date"This is any date from the start of 52 weeks ago to same number of complete days from the start of that week that have been completed in the current week
"12 months ago to date"This is any date from the start of the 12 months ago to same number of complete days from the start of that month that have been completed in the current month
"1 year ago to date"This is any date from the start of the 1 year ago to same number of complete days from the start of that year that have been completed in the current year
"1 year ago for 3 months"This is any date from the start of the 1 year ago to the end of 3 months from the start of that year
"1 year ago for 30 days"This is any date from the start of the 1 year ago to the end of 30 days from the start of that year
"2 years ago"2 years ago from the start of the current year until one year after that date
"3 months ago"3 months ago from the start of the current month until one month after that date
"3 months"3 months ago from the start of the current month to now
"30 days"30 days ago from the start of the current day to now

Examples#

In a field you can optionally apply one or more of these filters. We see three filters applied here.

The first filter sets the numeric order_number equal to 1. The second filter sets the string first_order_source_category not equal to 'Paid'. The third filter sets the order_date to be in the month to date range.

- field_type: measure  name: number_of_organic_new_orders  type: count  sql: ${id}  description: The total number of orders that are new and organic  value_format_name: decimal_0  filters:    - field: order_number      value: =1    - field: first_order_source_category      value: -Paid    - field: order_date      value: month to date