GROUP BY Clause

reference

The GROUP BY clause arranges aggregate values into groups, based on one or more fields.

Purpose

Use the GROUP BY clause to arrange aggregate values into groups of one or more fields. This GROUP BY clause follows the WHERE clause and precedes the optional LETTING, HAVING, and ORDER BY clauses.

Syntax

group-by-clause ::= 'GROUP' 'BY' group-term ( ',' group-term )*
                    letting-clause? having-clause? | letting-clause

group-term	Group Term
letting-clause	LETTING Clause
having-clause	HAVING Clause

Group Term

group-term ::= expr ( ('AS')? alias )?

At least one group term is required.

expr: String or expression representing an aggregate function or field to group together.
alias: Assigns another name to the group term. For details, see AS Clause.

Assigning an alias to the group term is optional. If you assign an alias, the AS keyword may be omitted.

LETTING Clause

letting-clause ::= 'LETTING' alias '=' expr ( ',' alias '=' expr )*

[Optional] Stores the result of a sub-expression in order to use it in subsequent clauses.

alias: String or expression representing the name of the clause to be referred to.
expr: String or expression representing the value of the LETTING alias variable.

HAVING Clause

having-clause ::= 'HAVING' cond

[Optional] To return items where aggregate values meet the specified conditions.

cond: String or expression representing the clause of aggregate values.

Limitations

GROUP BY works only on a group key or aggregate function.

A query needs a predicate on a leading index key to ensure that the optimizer can select a secondary index for the query. Without a matching predicate, the query will use the primary index. The simplest predicate is WHERE leading-index-key IS NOT MISSING. This is usually only necessary in queries which do not otherwise have a WHERE clause; for example, some GROUP BY and aggregate queries. For more details, refer to Index Selection.

Examples

Example 1. Group the unique landmarks by city and list the top 4 cities with the most landmarks in descending order

SELECT city City, COUNT(DISTINCT name) LandmarkCount
FROM `travel-sample`.inventory.landmark
GROUP BY city
ORDER BY LandmarkCount DESC
LIMIT 4;

Results

[
  {
    "City": "San Francisco",
    "LandmarkCount": 797
  },
  {
    "City": "London",
    "LandmarkCount": 443
  },
  {
    "City": "Los Angeles",
    "LandmarkCount": 284
  },
  {
    "City": "San Diego",
    "LandmarkCount": 197
  }
]

Example 2. Use LETTING to find cities that have a minimum number of things to see

SELECT city City, COUNT(DISTINCT name) LandmarkCount
FROM `travel-sample`.inventory.landmark
GROUP BY city
LETTING MinimumThingsToSee = 400
HAVING COUNT(DISTINCT name) > MinimumThingsToSee;

Results

[
  {
    "City": "London",
    "LandmarkCount": 443
  },
  {
    "City": "San Francisco",
    "LandmarkCount": 797
  }
]

Example 3. Use HAVING to specify cities that have more than 180 landmarks

SELECT city City, COUNT(DISTINCT name) LandmarkCount
FROM `travel-sample`.inventory.landmark
GROUP BY city
HAVING COUNT(DISTINCT name) > 180;

Results

[
  {
    "City": "London",
    "LandmarkCount": 443
  },
  {
    "City": "Los Angeles",
    "LandmarkCount": 284
  },
  {
    "City": "San Francisco",
    "LandmarkCount": 797
  },
  {
    "City": "San Diego",
    "LandmarkCount": 197
  }
]

The above HAVING clause must use the aggregate function COUNT instead of its alias LandmarkCount.

Example 4. Use HAVING to specify landmarks that begin with an "S" or higher

SELECT city City, COUNT(DISTINCT name) LandmarkCount
FROM `travel-sample`.inventory.landmark
GROUP BY city
HAVING city > "S"
ORDER BY city;

Results

[
  {
    "City": "Sacramento",
    "LandmarkCount": 2
  },
  {
    "City": "Saint Albans",
    "LandmarkCount": 5
  },
  {
    "City": "Saint Andrews",
    "LandmarkCount": 13
  },
  {
    "City": "Saint Annes Head",
    "LandmarkCount": 1
  },
// ...

(execution: 1s docs: 138)

Example 5. Using WHERE yields the same results as HAVING, however, WHERE is faster

SELECT city City, COUNT(DISTINCT name) LandmarkCount
FROM `travel-sample`.inventory.landmark
WHERE city > "S"
GROUP BY city
ORDER BY city;

Results

[
  {
    "City": "Sacramento",
    "LandmarkCount": 2
  },
  {
    "City": "Saint Albans",
    "LandmarkCount": 5
  },
  {
    "City": "Saint Andrews",
    "LandmarkCount": 13
  },
  {
    "City": "Saint Annes Head",
    "LandmarkCount": 1
  },
// ...

(execution: 480.2ms docs: 138)

The WHERE clause is faster because WHERE gets processed before any GROUP BY and doesn’t have access to aggregated values. HAVING gets processed after GROUP BY and is used to constrain the resultset to only those with aggregated values.

Example 6. Using an alias for a group term

SELECT Hemisphere, COUNT(DISTINCT name) AS LandmarkCount
FROM `travel-sample`.inventory.landmark AS l
GROUP BY CASE
  WHEN l.geo.lon <0 THEN "West"
  ELSE "East"
END AS Hemisphere;

Results

[
  {
    "Hemisphere": "East",
    "LandmarkCount": 459
  },
  {
    "Hemisphere": "West",
    "LandmarkCount": 3885
  }
]

The CASE expression categorizes each landmark into the Western hemisphere if its longitude is negative, or the Eastern hemisphere otherwise. The alias in the GROUP BY clause enables you to refer to the CASE expression in the SELECT clause.

For further examples, refer to Group By and Aggregate Performance.

GROUP BY Clause

Purpose

Syntax

Group Term

LETTING Clause

HAVING Clause

Limitations

Examples

Related Links