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DS-15755: Document LIKE and HAVING support in Analytics Engine SQL reference (#27200)
* DS-15755: Document `LIKE` pattern matching operators in Analytics Engine SQL reference `LIKE`, `ILIKE`, `NOT LIKE`, `NOT ILIKE` are all now supported by Workers Analytics Engine. Add docs. * DS-15385: Add SQL `HAVING` documentation to Analytics Engine SQL reference `HAVING` has been supported for a few weeks and soft-announced. This commit documents it. * DS-15385: Add WAE changelog entry for `HAVING` and `LIKE` support I'm combining the changelogs for these two small additions because they have a lot in common and are too small to justify multiple posts at once.
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Miki Mokrysz
GitHub
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3 changed files with 162 additions and 3 deletions
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---
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title: Workers Analytics Engine SQL now supports filtering using HAVING and LIKE
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description: Workers Analytics Engine's SQL API now supports SQL's HAVING and LIKE features
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date: 2026-01-07
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products:
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- workers-analytics-engine
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---
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You can now use the `HAVING` clause and `LIKE` pattern matching operators in [Workers Analytics Engine](https://developers.cloudflare.com/analytics/analytics-engine/).
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Workers Analytics Engine allows you to ingest and store high-cardinality data at scale and query your data through a simple SQL API.
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## Filtering using `HAVING`
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The `HAVING` clause complements the `WHERE` clause by enabling you to filter groups based on aggregate values. While `WHERE` filters rows before aggregation, `HAVING` filters groups after aggregation is complete.
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You can use `HAVING` to filter groups where the average exceeds a threshold:
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```sql
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SELECT
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blob1 AS probe_name,
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avg(double1) AS average_temp
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FROM temperature_readings
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GROUP BY probe_name
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HAVING average_temp > 10
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```
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You can also filter groups based on aggregates such as the number of items in the group:
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```sql
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SELECT
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blob1 AS probe_name,
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count() AS num_readings
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FROM temperature_readings
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GROUP BY probe_name
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HAVING num_readings > 100
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```
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## Pattern matching using `LIKE`
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The new pattern matching operators enable you to search for strings that match specific patterns using wildcard characters:
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- `LIKE` - case-sensitive pattern matching
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- `NOT LIKE` - case-sensitive pattern exclusion
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- `ILIKE` - case-insensitive pattern matching
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- `NOT ILIKE` - case-insensitive pattern exclusion
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Pattern matching supports two wildcard characters: `%` (matches zero or more characters) and `_` (matches exactly one character).
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You can match strings starting with a prefix:
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```sql
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SELECT *
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FROM logs
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WHERE blob1 LIKE 'error%'
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```
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You can also match file extensions (case-insensitive):
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```sql
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SELECT *
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FROM requests
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WHERE blob2 ILIKE '%.jpg'
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```
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Another example is excluding strings containing specific text:
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```sql
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SELECT *
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FROM events
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WHERE blob3 NOT ILIKE '%debug%'
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```
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## Ready to get started?
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Learn more about the [`HAVING` clause](/analytics/analytics-engine/sql-reference/statements/#having-clause) or [pattern matching operators](/analytics/analytics-engine/sql-reference/operators/#pattern-matching-operators) in the Workers Analytics Engine SQL reference documentation.
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@ -6,9 +6,10 @@ sidebar:
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head:
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- tag: title
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content: Workers Analytics Engine SQL Reference
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---
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import { Badge } from "~/components";
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The following operators are supported:
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## Arithmetic operators
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@ -36,6 +37,39 @@ The following operators are supported:
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We also support the `BETWEEN` operator for checking a value is in an inclusive range: `a [NOT] BETWEEN b AND c`.
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### Pattern matching operators <Badge text="New" variant="tip" size="small" />
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| Operator | Description |
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| ----------- | -------------------------------------------------------------------------------------------------- |
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| `LIKE` | true if the string matches the pattern (case-sensitive)<br/>`column LIKE 'pattern%'` |
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| `NOT LIKE` | true if the string does not match the pattern (case-sensitive)<br/>`column NOT LIKE 'pattern%'` |
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| `ILIKE` | true if the string matches the pattern (case-insensitive)<br/>`column ILIKE 'pattern%'` |
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| `NOT ILIKE` | true if the string does not match the pattern (case-insensitive)<br/>`column NOT ILIKE 'pattern%'` |
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Pattern matching supports two wildcard characters:
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- `%` matches any sequence of zero or more characters
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- `_` matches any single character
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Examples:
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```sql
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-- Match strings starting with "error"
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WHERE blob1 LIKE 'error%'
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-- Match strings ending with ".jpg" (case-insensitive)
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WHERE blob2 ILIKE '%.jpg'
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-- Match strings containing "test" anywhere
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WHERE blob3 LIKE '%test%'
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-- Match exactly 5 characters starting with "log"
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WHERE blob4 LIKE 'log__'
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-- Exclude strings containing "debug" (case-insensitive)
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WHERE blob5 NOT ILIKE '%debug%'
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```
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## Boolean operators
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| Operator | Description |
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@ -6,9 +6,10 @@ sidebar:
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head:
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- tag: title
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content: Workers Analytics Engine SQL Reference
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---
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import { Badge } from "~/components";
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## SHOW TABLES statement
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`SHOW TABLES` can be used to list the tables on your account. The table name is the name you specified as `dataset` when configuring the workers binding (refer to [Get started with Workers Analytics Engine](/analytics/analytics-engine/get-started/), for more information). The table is automatically created when you write event data in your worker.
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@ -49,6 +50,7 @@ SELECT <expression_list>
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[FROM <table>|(<subquery>)]
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[WHERE <expression>]
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[GROUP BY <expression>, ...]
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[HAVING <expression>]
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[ORDER BY <expression_list>]
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[LIMIT <n>|ALL]
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[FORMAT <format>]
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@ -131,7 +133,7 @@ Note that queries can only operate on a single table. `UNION`, `JOIN` etc. are n
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### WHERE clause
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`WHERE` is used to filter the rows returned by a query.
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`WHERE` is used to filter the rows returned by a query before grouping and aggregation.
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Usage:
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@ -145,6 +147,8 @@ WHERE <condition>
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Expressions containing functions and [operators](/analytics/analytics-engine/sql-reference/operators/#supported-operators) are supported.
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To filter results after grouping and aggregation, use the [`HAVING` clause](#having-clause) instead.
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Examples:
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```sql
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In the usual case the `<expression>` can just be a column name but it is also possible to supply a complex expression here. Multiple expressions or column names can be supplied separated by commas.
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### HAVING clause <Badge text="New" variant="tip" size="small" />
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`HAVING` is used to filter the results after grouping and aggregation.
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Usage:
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```sql
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HAVING <condition>
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```
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`<condition>` can be any expression that evaluates to a boolean, and can reference aggregate functions or grouped columns.
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Unlike `WHERE`, which filters rows before grouping, `HAVING` filters groups after aggregation. This allows you to filter based on aggregate values.
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[Comparison operators](/analytics/analytics-engine/sql-reference/operators/#comparison-operators) can be used to compare values and [boolean operators](/analytics/analytics-engine/sql-reference/operators/#boolean-operators) can be used to combine conditions.
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Examples:
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```sql
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-- filter groups where the average is greater than 10
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SELECT
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blob1 AS probe_name,
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avg(double1) AS average_temp
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FROM temperature_readings
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GROUP BY probe_name
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HAVING average_temp > 10
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-- filter groups with more than 100 readings
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SELECT
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blob1 AS probe_name,
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count() AS num_readings
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FROM temperature_readings
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GROUP BY probe_name
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HAVING num_readings > 100
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-- combine multiple conditions
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SELECT
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blob1 AS city,
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avg(double1) AS avg_temp,
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count() AS readings
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FROM weather_data
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GROUP BY city
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HAVING avg_temp > 20 AND readings >= 50
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```
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### ORDER BY clause
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`ORDER BY` can be used to control the order in which rows are returned.
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