You can use the UPDATE STATISTICS statement to gather statistics for an index key expression.
Purpose
The UPDATE STATISTICS
statement provides a syntax which enables you to gather statistics for an index key expression.
When you use an index with a query, you typically create the index on the fields which the query uses to filter. To use the cost-based optimizer with that query, you must collect statistics on the same fields that you used to create the index.
A query may have predicates on non-indexed fields, and you can collect statistics on those fields also to help the optimizer.
For a query which filters on an array or array of objects, you must collect the statistics using exactly the same expression that you used to create the index.
Syntax
update-statistics-expr ::= ( 'UPDATE' 'STATISTICS' 'FOR'? |
'ANALYZE' ( 'KEYSPACE' | 'COLLECTION')? )
keyspace-ref '(' index-key ( ',' index-key )* ')' index-with?
For this syntax, UPDATE STATISTICS
and ANALYZE
are synonyms.
The statement must begin with one of these alternatives.
When using the UPDATE STATISTICS
keywords, the FOR
keyword is optional.
Including this keyword makes no difference to the operation of the statement.
When using the ANALYZE
keyword, the COLLECTION
or KEYSPACE
keywords are optional.
Including either of these keywords makes no difference to the operation of the statement.
keyspace-ref | |
index-key | |
index-with |
Keyspace Reference
keyspace-ref ::= keyspace-path | keyspace-partial
keyspace-path ::= ( namespace ':' )? bucket ( '.' scope '.' collection )?
keyspace-partial ::= collection
The simple name or fully-qualified name of the keyspace for which you want to gather statistics. Refer to the CREATE INDEX statement for details of the syntax.
Index Expression
The expression for which you want to gather statistics. This may be any expression that is supported as an index key, including, but not limited to:
-
A SQL++ expression over any fields in the document, as used in a secondary index.
-
An array expression, as used when creating an array index.
-
An expression with the META() function, as used in a metadata index.
WITH Clause
index-with ::= 'WITH' expr
Use the WITH
clause to specify additional options.
expr |
An object with the following properties:
|
Refer to Distribution Statistics for more information on sample size and resolution.
Examples
To try the examples in this section, set the query context to the inventory
scope in the travel sample dataset.
For more information, see Query Context.
CREATE INDEX idx_country_city ON hotel(country, city);
CREATE INDEX idx_city_country ON hotel(city, country);
UPDATE STATISTICS FOR hotel(city, country);
EXPLAIN
SELECT COUNT(*) FROM hotel WHERE country = 'France';
[
{
"cardinality": 1, (1)
"cost": 36.39093947963759, (2)
"plan": {
"#operator": "Sequence",
"~children": [
{
"#operator": "IndexScan3",
"bucket": "travel-sample",
"covers": [
"cover ((`hotel`.`country`))",
"cover ((`hotel`.`city`))",
"cover ((meta(`hotel`).`id`))",
"cover (count(*))"
],
"index": "idx_country_city",
"index_group_aggs": {
"aggregates": [
{
"aggregate": "COUNT",
"expr": "1",
"id": 3,
"keypos": -1
}
]
},
"index_id": "9071bf247db9d656",
"index_projection": {
"entry_keys": [
3
]
},
"keyspace": "hotel",
"namespace": "default",
"optimizer_estimates": { (3)
"cardinality": 1,
"cost": 36.386580580694044,
"fr_cost": 12.314601064983428,
"size": 19
},
"scope": "inventory",
"spans": [
{
"exact": true,
"range": [
{
"high": "\"France\"",
"inclusion": 3,
"low": "\"France\""
}
]
}
],
"using": "gsi"
},
{
"#operator": "Parallel",
"~child": {
"#operator": "Sequence",
"~children": [
{
"#operator": "InitialProject",
"optimizer_estimates": { (4)
"cardinality": 1,
"cost": 36.39093947963759,
"fr_cost": 12.318959963926968,
"size": 19
},
"result_terms": [
{
"expr": "cover (count(*))"
}
]
}
]
}
}
]
},
"text": "SELECT COUNT(*) FROM `travel-sample`.inventory.hotel WHERE country = 'France';"
}
]
1 | The overall cardinality estimate for the query. |
2 | The overall cost estimate for the query. |
3 | Cardinality and cost estimates for the index scan operator. |
4 | Cardinality and cost estimates for the initial project operator. |
This example uses the same indexes as Example 1.
UPDATE STATISTICS FOR hotel(city, country, free_breakfast);
There is no index on the free_breakfast
field.
However, the query below refers to this field as a predicate, so we collect statistics on this field also.
EXPLAIN
SELECT COUNT(*) FROM hotel
WHERE country = 'United States' AND free_breakfast = true;
[
{
"cardinality": 1, (1)
"cost": 1319.7883498503274,
"plan": {
"#operator": "Sequence",
"~children": [
{
"#operator": "IndexScan3",
"bucket": "travel-sample",
"index": "idx_country_city",
"index_id": "9071bf247db9d656",
"index_projection": {
"primary_key": true
},
"keyspace": "hotel",
"namespace": "default",
"optimizer_estimates": { (2)
"cardinality": 361.00000000000006,
"cost": 74.51787485734917,
"fr_cost": 12.173179708746119,
"size": 11
},
"scope": "inventory",
"spans": [
{
"exact": true,
"range": [
{
"high": "\"United States\"",
"inclusion": 3,
"low": "\"United States\""
}
]
}
],
"using": "gsi"
},
{
"#operator": "Fetch",
"bucket": "travel-sample",
"keyspace": "hotel",
"namespace": "default",
"optimizer_estimates": { (3)
"cardinality": 361.00000000000006,
"cost": 1292.900802248151,
"fr_cost": 27.514960671047508,
"size": 4467
},
"scope": "inventory"
},
{
"#operator": "Parallel",
"~child": {
"#operator": "Sequence",
"~children": [
{
"#operator": "Filter",
"condition": "(((`hotel`.`country`) = \"United States\") and ((`hotel`.`free_breakfast`) = true))",
"optimizer_estimates": { (4)
"cardinality": 267.3053435114504,
"cost": 1317.028460795967,
"fr_cost": 27.605223208379773,
"size": 4467
}
},
{
"#operator": "InitialGroup",
"aggregates": [
"count(*)"
],
"group_keys": [],
"optimizer_estimates": { (5)
"cardinality": 1,
"cost": 1319.7015142310815,
"fr_cost": 1319.7015142310815,
"size": 4467
}
}
]
}
},
{
"#operator": "IntermediateGroup",
"aggregates": [
"count(*)"
],
"group_keys": [],
"optimizer_estimates": { (6)
"cardinality": 1,
"cost": 1319.7115142310815,
"fr_cost": 1319.7115142310815,
"size": 4467
}
},
{
"#operator": "FinalGroup",
"aggregates": [
"count(*)"
],
"group_keys": [],
"optimizer_estimates": { (7)
"cardinality": 1,
"cost": 1319.7215142310815,
"fr_cost": 1319.7215142310815,
"size": 4467
}
},
{
"#operator": "Parallel",
"~child": {
"#operator": "Sequence",
"~children": [
{
"#operator": "InitialProject",
"optimizer_estimates": { (8)
"cardinality": 1,
"cost": 1319.7883498503274,
"fr_cost": 1319.7883498503274,
"size": 4467
},
"result_terms": [
{
"expr": "count(*)"
}
]
}
]
}
}
]
},
"text": "SELECT COUNT(*) FROM `travel-sample`.inventory.hotel\nWHERE country = 'United States' AND free_breakfast = true;"
}
]
1 | Overall cardinality and cost estimates for the query. |
2 | Cardinality and cost estimates for the index scan operator. |
3 | Cardinality and cost estimates for the fetch operator. |
4 | Cardinality and cost estimates for the filter operator. |
5 | Cardinality and cost estimates for the initial group operator. |
6 | Cardinality and cost estimates for the intermediate group operator. |
7 | Cardinality and cost estimates for the final group operator. |
8 | Cardinality and cost estimates for the initial project operator. |
CREATE INDEX idx_public_likes
ON hotel((DISTINCT (`public_likes`)));
UPDATE STATISTICS FOR hotel((DISTINCT (`public_likes`)));
EXPLAIN
SELECT COUNT(1) FROM hotel
WHERE ANY p IN public_likes SATISFIES p LIKE 'A%' END;
[
{
"cardinality": 1,
"cost": 39.80787755862344,
"plan": {
"#operator": "Sequence",
"~children": [
{
"#operator": "DistinctScan",
"optimizer_estimates": {
"cardinality": 105.64354562889939,
"cost": 39.44754768187852,
"fr_cost": 39.44754768187852,
"size": 11
},
"scan": {
"#operator": "IndexScan3",
"bucket": "travel-sample",
"covers": [
"cover ((distinct ((`hotel`.`public_likes`))))",
"cover ((meta(`hotel`).`id`))"
],
"filter": "cover (any `p` in (`hotel`.`public_likes`) satisfies (`p` like \"A%\") end)",
"filter_covers": {
"cover (any `p` in (`hotel`.`public_likes`) satisfies ((\"A\" <= `p`) and (`p` < \"B\")) end)": true,
"cover (any `p` in (`hotel`.`public_likes`) satisfies (`p` like \"A%\") end)": true
},
"index": "idx_public_likes",
// ...
}
},
{
"#operator": "Parallel",
"~child": {
"#operator": "Sequence",
"~children": [
{
"#operator": "InitialGroup",
"aggregates": [
"count(1)"
],
"group_keys": [],
"optimizer_estimates": {
"cardinality": 1,
"cost": 39.797927684252365,
"fr_cost": 39.797927684252365,
"size": 11
}
}
]
}
},
// ...
]
},
"text": "SELECT COUNT(1)\nFROM `travel-sample`.inventory.hotel\nWHERE ANY p IN public_likes SATISFIES p LIKE 'A%' END;"
}
]
CREATE INDEX idx_reviews_ratings_overall
ON hotel(DISTINCT ARRAY r.ratings.Overall
FOR r IN reviews END);
UPDATE STATISTICS
FOR hotel(DISTINCT ARRAY r.ratings.Overall
FOR r IN reviews END);
EXPLAIN
SELECT COUNT(1) FROM hotel
WHERE ANY r IN reviews SATISFIES r.ratings.Overall = 4 END;
[
{
"cardinality": 1,
"cost": 118.0080501905589,
"plan": {
"#operator": "Sequence",
"~children": [
{
"#operator": "IndexScan3",
"bucket": "travel-sample",
"covers": [
"cover ((distinct (array ((`r`.`ratings`).`Overall`) for `r` in (`hotel`.`reviews`) end)))",
"cover ((meta(`hotel`).`id`))",
"cover (count(1))"
],
"filter_covers": {
"cover (any `r` in (`hotel`.`reviews`) satisfies (((`r`.`ratings`).`Overall`) = 4) end)": true
},
"index": "idx_reviews_ratings_overall",
// ...
"optimizer_estimates": {
"cardinality": 1,
"cost": 118.00369129161537,
"fr_cost": 12.312997158401616,
"size": 19
},
// ...
},
// ...
]
},
"text": "SELECT COUNT(1)\nFROM `travel-sample`.inventory.hotel\nWHERE ANY r IN reviews SATISFIES r.ratings.Overall = 4 END;"
}
]