diff --git a/src/.vuepress/sidebar/V2.0.x/en-Table.ts b/src/.vuepress/sidebar/V2.0.x/en-Table.ts index 2093e570e..4352cedf4 100644 --- a/src/.vuepress/sidebar/V2.0.x/en-Table.ts +++ b/src/.vuepress/sidebar/V2.0.x/en-Table.ts @@ -155,6 +155,7 @@ export const enSidebar = { { text: 'FILL Clause', link: 'Fill-Clause' }, { text: 'ORDER BY Clause', link: 'OrderBy-Clause' }, { text: 'LIMIT&OFFSET Clause', link: 'Limit-Offset-Clause' }, + { text: 'Nested Queries', link: 'Nested-Queries' }, ], }, { @@ -165,6 +166,7 @@ export const enSidebar = { { text: 'Featured Functions', link: 'Featured-Functions' }, ], }, + ], }, { diff --git a/src/.vuepress/sidebar/V2.0.x/zh-Table.ts b/src/.vuepress/sidebar/V2.0.x/zh-Table.ts index aad81b998..f44c9136a 100644 --- a/src/.vuepress/sidebar/V2.0.x/zh-Table.ts +++ b/src/.vuepress/sidebar/V2.0.x/zh-Table.ts @@ -147,6 +147,7 @@ export const zhSidebar = { { text: 'FILL子句', link: 'Fill-Clause' }, { text: 'ORDER BY子句', link: 'OrderBy-Clause' }, { text: 'LIMIT&OFFSET子句', link: 'Limit-Offset-Clause' }, + { text: '嵌套查询', link: 'Nested-Queries' }, ], }, { @@ -157,6 +158,7 @@ export const zhSidebar = { { text: '特色函数', link: 'Featured-Functions' }, ], }, + ], }, { diff --git a/src/.vuepress/sidebar_timecho/V2.0.x/en-Table.ts b/src/.vuepress/sidebar_timecho/V2.0.x/en-Table.ts index e34adcdf3..2395ba3c6 100644 --- a/src/.vuepress/sidebar_timecho/V2.0.x/en-Table.ts +++ b/src/.vuepress/sidebar_timecho/V2.0.x/en-Table.ts @@ -160,6 +160,7 @@ export const enSidebar = { { text: 'FILL Clause', link: 'Fill-Clause' }, { text: 'ORDER BY Clause', link: 'OrderBy-Clause' }, { text: 'LIMIT&OFFSET Clause', link: 'Limit-Offset-Clause' }, + { text: 'Nested Queries', link: 'Nested-Queries' }, ], }, { @@ -170,6 +171,7 @@ export const enSidebar = { { text: 'Featured Functions', link: 'Featured-Functions' }, ], }, + ], }, { diff --git a/src/.vuepress/sidebar_timecho/V2.0.x/zh-Table.ts b/src/.vuepress/sidebar_timecho/V2.0.x/zh-Table.ts index 058d1ba58..f2106c84f 100644 --- a/src/.vuepress/sidebar_timecho/V2.0.x/zh-Table.ts +++ b/src/.vuepress/sidebar_timecho/V2.0.x/zh-Table.ts @@ -151,6 +151,7 @@ export const zhSidebar = { { text: 'FILL子句', link: 'Fill-Clause' }, { text: 'ORDER BY子句', link: 'OrderBy-Clause' }, { text: 'LIMIT&OFFSET子句', link: 'Limit-Offset-Clause' }, + { text: '嵌套查询', link: 'Nested-Queries' }, ], }, { @@ -161,6 +162,7 @@ export const zhSidebar = { { text: '特色函数', link: 'Featured-Functions' }, ], }, + ], }, { diff --git a/src/UserGuide/Master/Table/SQL-Manual/Nested-Queries.md b/src/UserGuide/Master/Table/SQL-Manual/Nested-Queries.md new file mode 100644 index 000000000..031134efa --- /dev/null +++ b/src/UserGuide/Master/Table/SQL-Manual/Nested-Queries.md @@ -0,0 +1,876 @@ + + +# Nested Queries + +## 1. Overview + +Nested queries, also known as subqueries, refer to query statements that contain one or more other query statements within them. A nested query consists of an inner query and an outer query. + +## 2. Classification of Nested Queries + +Nested queries can be classified based on two criteria: whether they reference the outer query and the dimensionality of the result set. + +* **Classification by Reference to Outer Query:** + + + + + + + + + + + + + + + + + + + + +
Classification BasisNested Query TypeDescriptionIoTDB Support
Whether to Reference Outer QueryNon-Correlated SubqueryThe execution of the inner query is independent of the outer query. The inner query executes only once, and its result is used as a condition for the outer query.Supported
Correlated SubqueryThe inner query references columns from the outer query's table, requiring the outer query to execute first, followed by the inner query.Not Supported
+ +* **Classification by Result Set Dimensionality:** + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
Classification BasisSubquery TypeDescriptionUsable ClausesIoTDB Support
Result Set DimensionalityScalar SubqueryReturns a single row and column.select、where、from、havingSupported
Column SubqueryReturns N rows and one column.select、where、from、havingSupported
Row SubqueryReturns one row and N columns. - Not Supported
Table SubqueryReturns N rows and M columns.from Supported
+ +## 3. Functional Definitions + +1. All inner queries must be enclosed in parentheses (subquery). + +2. Non-correlated subqueries cannot reference columns from the outer query. Attempting to do so will result in an error: + + `Msg: org.apache.iotdb.jdbc.IoTDBSQLException： 701: Given correlated subquery is not supported` + +### 3.1 Non-Correlated Scalar Subqueries + +A scalar subquery returns a single scalar value and can be used to replace an operand in an expression. + +**Syntax** + +```SQL +primaryExpression + : literalExpression #Literal + | dateExpression #dateTimeExpression #dateTimeExpression + | '(' expression (',' expression)+ ')' #rowConstructor + | ROW '(' expression (',' expression)* ')' #rowConstructor + | qualifiedName '(' (label=identifier '.')? ASTERISK ')' #functionCall + | qualifiedName '(' (setQuantifier? expression (',' expression)*)?')' #functionCall +​ ​|​ ​'('​ query ​')'​ #subqueryExpression +``` + +**Notes** + +Scalar subqueries can be used as operands in any expression unless the input parameters are explicitly defined as constants. + +Examples where scalar subqueries cannot be used as parameters: + +* The first and third parameters of `date_bin(interval,source,origin)`. +* The first and third parameters of `date_bin_gapfill(interval,source,origin)`. + * `interval` ：Time interval + * `origin`：Starting timestamp +* `Fill` parameters + * `fill previous` + * `fill linear` + * `fill constant` + +### 3.2 Non-Correlated Column Subqueries + +#### 3.2.1 Non-Correlated InPredicate + +An InPredicate is a predicate that returns a column of boolean values. + +**Syntax** + +```SQL +predicate[ParserRuleContext value] + : comparisonOperator right=valueExpression #comparison + | comparisonOperator comparisonQuantifier '(' query ')' #quantifiedComparison + | NOT? BETWEEN lower=valueExpression AND upper=valueExpression #between + | NOT? IN '(' expression (',' expression)* ')' #inList + |​ ​NOT? ​IN​ ​'('​ query ​')'​ #inSubquery + | NOT? LIKE pattern=valueExpression (ESCAPE escape=valueExpression)? #like + | IS NOT? NULL #nullPredicate + | IS NOT? DISTINCT FROM right=valueExpression #distinctFrom + ; +``` + +**Notes** + +Usage: `X [NOT] IN (subquery)` + +* `X` is an expression. +* `NOT` is optional (negation). +* `subquery` returns a result set `Result`with one column and multiple rows. +* For `WHERE X IN (subquery)`, each row where `X` is in `Result` will be retained in the `SELECT` output. + +#### 3.2.2 Non-Correlated Quantified Comparison + +A quantified comparison allows comparing a value to a set of values, typically consisting of: + +1. Comparison operators:`<`， `>`， `=`， `<=`， `>=`， `!=` +2. Quantifiers: + 1. `ALL`: All elements must satisfy the condition. + 2. `ANY` or `SOME`: At least one element must satisfy the condition (ANY and SOME are equivalent). +3. Subquery: Returns a set of values to compare with the main query's value. + +**Syntax** + +```SQL +predicate[ParserRuleContext value] + : comparisonOperator right=valueExpression #comparison + |​ comparisonOperator comparisonQuantifier ​'('​ query ​')'​ #quantifiedComparison + | NOT? BETWEEN lower=valueExpression AND upper=valueExpression #between + | NOT? IN '(' expression (',' expression)* ')' #inList + | NOT? IN '(' query ')' #inSubquery + | NOT? LIKE pattern=valueExpression (ESCAPE escape=valueExpression)? #like + | IS NOT? NULL #nullPredicate + | IS NOT? DISTINCT FROM right=valueExpression #distinctFrom + ; +comparisonQuantifier + : ALL | SOME | ANY + ; +``` + +**Notes** + +Usage: `expression operator ALL/ANY/SOME (subquery)` + +* ALL: The `expression` in the main query must satisfy the condition with every value returned by the subquery. +* ANY/SOME: The `expression` in the main query must satisfy the condition with at least one value returned by the subquery. + +## 4. Usage Examples +### 4.1 Example Data + +s1, s2, s3, s4 are of types INT, LONG, FLOAT, DOUBLE respectively. + +* Table1: + +```SQL +// All data in table1 +IoTDB> select * from table1; ++-----------------------------+--------+--------+--------+---------+------+----------------+----+-----+----+----+-----+--------------------------------+--------------------------------+------------+-----------------------------+----------+ +| time|province| city| region|device_id| color| type| s1| s2| s3| s4| s5| s6| s7| s8| s9| s10| ++-----------------------------+--------+--------+--------+---------+------+----------------+----+-----+----+----+-----+--------------------------------+--------------------------------+------------+-----------------------------+----------+ +|2024-09-24T14:15:30.000+08:00|shanghai|shanghai| pudong| d05| red| A| 30| null|30.0|null| null| shanghai_pudong_red_A_d05_30| null|0xcafebabe30|2024-09-24T14:15:30.000+08:00| null| +|2024-09-24T14:15:35.000+08:00|shanghai|shanghai| pudong| d05| red| A|null|35000|35.0|35.0| null| shanghai_pudong_red_A_d05_35| shanghai_pudong_red_A_d05_35| null|2024-09-24T14:15:35.000+08:00|2024-09-24| +|2024-09-24T14:15:40.000+08:00|shanghai|shanghai| pudong| d05| red| A| 40| null|40.0|null| true| null| shanghai_pudong_red_A_d05_40| null|2024-09-24T14:15:40.000+08:00| null| +|2024-09-24T14:15:50.000+08:00|shanghai|shanghai| pudong| d05| red| A|null|50000|null|null|false| null| null| null|2024-09-24T14:15:50.000+08:00|2024-09-24| +|2024-09-24T14:15:55.000+08:00|shanghai|shanghai| pudong| d05| red| A| 55| null|null|55.0| null| null| null|0xcafebabe55|2024-09-24T14:15:55.000+08:00| null| +|2024-09-24T14:15:31.000+08:00|shanghai|shanghai| pudong| d07|yellow| A|null|31000|null|null| null| null| null|0xcafebabe31|2024-09-24T14:15:31.000+08:00| null| +|2024-09-24T14:15:36.000+08:00|shanghai|shanghai| pudong| d07|yellow| A| 36| null|null|36.0| null| null| shanghai_pudong_yellow_A_d07_36| null|2024-09-24T14:15:36.000+08:00|2024-09-24| +|2024-09-24T14:15:41.000+08:00|shanghai|shanghai| pudong| d07|yellow| A| 41| null|41.0|null|false| shanghai_pudong_yellow_A_d07_41| null|0xcafebabe41|2024-09-24T14:15:41.000+08:00| null| +|2024-09-24T14:15:46.000+08:00|shanghai|shanghai| pudong| d07|yellow| A|null|46000|null|46.0| null| null| shanghai_pudong_yellow_A_d07_46| null|2024-09-24T14:15:46.000+08:00| null| +|2024-09-24T14:15:51.000+08:00|shanghai|shanghai| pudong| d07|yellow| A|null| null|51.0|null| null| shanghai_pudong_yellow_A_d07_51| null| null|2024-09-24T14:15:51.000+08:00| null| +|2024-09-24T14:13:30.000+08:00|shanghai|shanghai| huangpu| d01| red| A| 30| 30|30.0|30.0| true| shanghai_huangpu_red_A_d01_30| shanghai_huangpu_red_A_d01_30|0xcafebabe30|2024-09-24T14:13:00.000+08:00|2024-09-23| +|2024-09-24T14:14:30.000+08:00|shanghai|shanghai| huangpu| d01| red| A| 40| 40|40.0|40.0|false| shanghai_huangpu_red_A_d01_40| shanghai_huangpu_red_A_d01_40|0xcafebabe40|2024-09-24T14:14:00.000+08:00|2024-09-24| +|2024-09-24T14:15:30.000+08:00|shanghai|shanghai| huangpu| d01| red| A| 50| 50|50.0|50.0| true| shanghai_huangpu_red_A_d01_50| shanghai_huangpu_red_A_d01_50|0xcafebabe50|2024-09-24T14:15:00.000+08:00|2024-09-25| +|2024-09-24T14:16:30.000+08:00|shanghai|shanghai| huangpu| d01| red| A| 60| 60|60.0|60.0|false| shanghai_huangpu_red_A_d01_60| shanghai_huangpu_red_A_d01_60|0xcafebabe60|2024-09-24T14:16:00.000+08:00|2024-09-26| +|2024-09-24T14:17:30.000+08:00|shanghai|shanghai| huangpu| d01| red| A| 70| 70|70.0|70.0| true| shanghai_huangpu_red_A_d01_70| shanghai_huangpu_red_A_d01_70|0xcafebabe70|2024-09-24T14:17:00.000+08:00|2024-09-27| +|2024-09-24T14:15:31.000+08:00|shanghai|shanghai| huangpu| d03|yellow| A|null|31000|null|null| null| null| null|0xcafebabe31|2024-09-24T14:15:31.000+08:00| null| +|2024-09-24T14:15:36.000+08:00|shanghai|shanghai| huangpu| d03|yellow| A| 36| null|null|36.0| null| null|shanghai_huangpu_yellow_A_d03_36| null|2024-09-24T14:15:36.000+08:00|2024-09-24| +|2024-09-24T14:15:41.000+08:00|shanghai|shanghai| huangpu| d03|yellow| A| 41| null|41.0|null|false|shanghai_huangpu_yellow_A_d03_41| null|0xcafebabe41|2024-09-24T14:15:41.000+08:00| null| +|2024-09-24T14:15:46.000+08:00|shanghai|shanghai| huangpu| d03|yellow| A|null|46000|null|46.0| null| null|shanghai_huangpu_yellow_A_d03_46| null|2024-09-24T14:15:46.000+08:00| null| +|2024-09-24T14:15:51.000+08:00|shanghai|shanghai| huangpu| d03|yellow| A|null| null|51.0|null| null|shanghai_huangpu_yellow_A_d03_51| null| null|2024-09-24T14:15:51.000+08:00| null| +|2024-09-24T14:15:31.000+08:00| beijing| beijing|chaoyang| d11|yellow| A|null|31000|null|null| null| null| null|0xcafebabe31|2024-09-24T14:15:31.000+08:00| null| +|2024-09-24T14:15:36.000+08:00| beijing| beijing|chaoyang| d11|yellow| A| 36| null|null|36.0| null| null|beijing_chaoyang_yellow_A_d11_36| null|2024-09-24T14:15:36.000+08:00|2024-09-24| +|2024-09-24T14:15:41.000+08:00| beijing| beijing|chaoyang| d11|yellow| A| 41| null|41.0|null|false|beijing_chaoyang_yellow_A_d11_41| null|0xcafebabe41|2024-09-24T14:15:41.000+08:00| null| +|2024-09-24T14:15:46.000+08:00| beijing| beijing|chaoyang| d11|yellow| A|null|46000|null|46.0| null| null|beijing_chaoyang_yellow_A_d11_46| null|2024-09-24T14:15:46.000+08:00| null| +|2024-09-24T14:15:51.000+08:00| beijing| beijing|chaoyang| d11|yellow| A|null| null|51.0|null| null|beijing_chaoyang_yellow_A_d11_51| null| null|2024-09-24T14:15:51.000+08:00| null| +|2024-09-24T14:15:30.000+08:00| beijing| beijing|chaoyang| d09| red| A| 30| null|30.0|null| null| beijing_chaoyang_red_A_d09_30| null|0xcafebabe30|2024-09-24T14:15:30.000+08:00| null| +|2024-09-24T14:15:35.000+08:00| beijing| beijing|chaoyang| d09| red| A|null|35000|35.0|35.0| null| beijing_chaoyang_red_A_d09_35| beijing_chaoyang_red_A_d09_35| null|2024-09-24T14:15:35.000+08:00|2024-09-24| +|2024-09-24T14:15:40.000+08:00| beijing| beijing|chaoyang| d09| red| A| 40| null|40.0|null| true| null| beijing_chaoyang_red_A_d09_40| null|2024-09-24T14:15:40.000+08:00| null| +|2024-09-24T14:15:50.000+08:00| beijing| beijing|chaoyang| d09| red| A|null|50000|null|null|false| null| null| null|2024-09-24T14:15:50.000+08:00|2024-09-24| +|2024-09-24T14:15:55.000+08:00| beijing| beijing|chaoyang| d09| red| A| 55| null|null|55.0| null| null| null|0xcafebabe55|2024-09-24T14:15:55.000+08:00| null| +|2024-09-24T14:15:30.000+08:00| beijing| beijing| haidian| d13| red| A| 30| null|30.0|null| null| beijing_haidian_red_A_d13_30| null|0xcafebabe30|2024-09-24T14:15:30.000+08:00| null| +|2024-09-24T14:15:35.000+08:00| beijing| beijing| haidian| d13| red| A|null|35000|35.0|35.0| null| beijing_haidian_red_A_d13_35| beijing_haidian_red_A_d13_35| null|2024-09-24T14:15:35.000+08:00|2024-09-24| +|2024-09-24T14:15:40.000+08:00| beijing| beijing| haidian| d13| red| A| 40| null|40.0|null| true| null| beijing_haidian_red_A_d13_40| null|2024-09-24T14:15:40.000+08:00| null| +|2024-09-24T14:15:50.000+08:00| beijing| beijing| haidian| d13| red| A|null|50000|null|null|false| null| null| null|2024-09-24T14:15:50.000+08:00|2024-09-24| +|2024-09-24T14:15:55.000+08:00| beijing| beijing| haidian| d13| red| A| 55| null|null|55.0| null| null| null|0xcafebabe55|2024-09-24T14:15:55.000+08:00| null| +|2024-09-24T14:15:31.000+08:00| beijing| beijing| haidian| d15|yellow| A|null|31000|null|null| null| null| null|0xcafebabe31|2024-09-24T14:15:31.000+08:00| null| +|2024-09-24T14:15:36.000+08:00| beijing| beijing| haidian| d15|yellow| A| 36| null|null|36.0| null| null| beijing_haidian_yellow_A_d15_36| null|2024-09-24T14:15:36.000+08:00|2024-09-24| +|2024-09-24T14:15:41.000+08:00| beijing| beijing| haidian| d15|yellow| A| 41| null|41.0|null|false| beijing_haidian_yellow_A_d15_41| null|0xcafebabe41|2024-09-24T14:15:41.000+08:00| null| +|2024-09-24T14:15:46.000+08:00| beijing| beijing| haidian| d15|yellow| A|null|46000|null|46.0| null| null| beijing_haidian_yellow_A_d15_46| null|2024-09-24T14:15:46.000+08:00| null| +|2024-09-24T14:15:51.000+08:00| beijing| beijing| haidian| d15|yellow| A|null| null|51.0|null| null| beijing_haidian_yellow_A_d15_51| null| null|2024-09-24T14:15:51.000+08:00| null| +|2024-09-24T14:15:36.000+08:00|shanghai|shanghai| pudong| d06| red|BBBBBBBBBBBBBBBB| 36| null|null|null| true| shanghai_pudong_red_B_d06_36| shanghai_pudong_red_B_d06_36| null|2024-09-24T14:15:36.000+08:00| null| +|2024-09-24T14:15:40.000+08:00|shanghai|shanghai| pudong| d06| red|BBBBBBBBBBBBBBBB| 40| null|null|40.0| null| null| shanghai_pudong_red_B_d06_40| null|2024-09-24T14:15:40.000+08:00|2024-09-24| +|2024-09-24T14:15:50.000+08:00|shanghai|shanghai| pudong| d06| red|BBBBBBBBBBBBBBBB|null|50000|null|null| null| null| shanghai_pudong_red_B_d06_50|0xcafebabe50|2024-09-24T14:15:50.000+08:00| null| +|2024-09-24T14:15:30.000+08:00|shanghai|shanghai| pudong| d08|yellow|BBBBBBBBBBBBBBBB|null| null|30.0|null| true| null| shanghai_pudong_yellow_B_d08_30| null|2024-09-24T14:15:30.000+08:00|2024-09-24| +|2024-09-24T14:15:40.000+08:00|shanghai|shanghai| pudong| d08|yellow|BBBBBBBBBBBBBBBB|null|40000|null|null| null| null| null| null|2024-09-24T14:15:40.000+08:00| null| +|2024-09-24T14:15:55.000+08:00|shanghai|shanghai| pudong| d08|yellow|BBBBBBBBBBBBBBBB| 55| null|null|55.0| null| shanghai_pudong_yellow_B_d08_55| null|0xcafebabe55|2024-09-24T14:15:55.000+08:00| null| +|2024-09-24T14:15:36.000+08:00|shanghai|shanghai| huangpu| d02| red|BBBBBBBBBBBBBBBB| 36| null|null|null| true| shanghai_huangpu_red_B_d02_36| shanghai_huangpu_red_B_d02_36| null|2024-09-24T14:15:36.000+08:00| null| +|2024-09-24T14:15:40.000+08:00|shanghai|shanghai| huangpu| d02| red|BBBBBBBBBBBBBBBB| 40| null|null|40.0| null| null| shanghai_huangpu_red_B_d02_40| null|2024-09-24T14:15:40.000+08:00|2024-09-24| +|2024-09-24T14:15:50.000+08:00|shanghai|shanghai| huangpu| d02| red|BBBBBBBBBBBBBBBB|null|50000|null|null| null| null| shanghai_huangpu_red_B_d02_50|0xcafebabe50|2024-09-24T14:15:50.000+08:00| null| +|2024-09-24T14:15:30.000+08:00|shanghai|shanghai| huangpu| d04|yellow|BBBBBBBBBBBBBBBB|null| null|30.0|null| true| null|shanghai_huangpu_yellow_B_d04_30| null|2024-09-24T14:15:30.000+08:00|2024-09-24| +|2024-09-24T14:15:40.000+08:00|shanghai|shanghai| huangpu| d04|yellow|BBBBBBBBBBBBBBBB|null|40000|null|null| null| null| null| null|2024-09-24T14:15:40.000+08:00| null| +|2024-09-24T14:15:55.000+08:00|shanghai|shanghai| huangpu| d04|yellow|BBBBBBBBBBBBBBBB| 55| null|null|55.0| null|shanghai_huangpu_yellow_B_d04_55| null|0xcafebabe55|2024-09-24T14:15:55.000+08:00| null| +|2024-09-24T14:15:36.000+08:00| beijing| beijing|chaoyang| d10| red|BBBBBBBBBBBBBBBB| 36| null|null|null| true| beijing_chaoyang_red_B_d10_36| beijing_chaoyang_red_B_d10_36| null|2024-09-24T14:15:36.000+08:00| null| +|2024-09-24T14:15:40.000+08:00| beijing| beijing|chaoyang| d10| red|BBBBBBBBBBBBBBBB| 40| null|null|40.0| null| null| beijing_chaoyang_red_B_d10_40| null|2024-09-24T14:15:40.000+08:00|2024-09-24| +|2024-09-24T14:15:50.000+08:00| beijing| beijing|chaoyang| d10| red|BBBBBBBBBBBBBBBB|null|50000|null|null| null| null| beijing_chaoyang_red_B_d10_50|0xcafebabe50|2024-09-24T14:15:50.000+08:00| null| +|2024-09-24T14:15:30.000+08:00| beijing| beijing|chaoyang| d12|yellow|BBBBBBBBBBBBBBBB|null| null|30.0|null| true| null|beijing_chaoyang_yellow_B_d12_30| null|2024-09-24T14:15:30.000+08:00|2024-09-24| +|2024-09-24T14:15:40.000+08:00| beijing| beijing|chaoyang| d12|yellow|BBBBBBBBBBBBBBBB|null|40000|null|null| null| null| null| null|2024-09-24T14:15:40.000+08:00| null| +|2024-09-24T14:15:55.000+08:00| beijing| beijing|chaoyang| d12|yellow|BBBBBBBBBBBBBBBB| 55| null|null|55.0| null|beijing_chaoyang_yellow_B_d12_55| null|0xcafebabe55|2024-09-24T14:15:55.000+08:00| null| +|2024-09-24T14:15:36.000+08:00| beijing| beijing| haidian| d14| red|BBBBBBBBBBBBBBBB| 36| null|null|null| true| beijing_haidian_red_B_d14_36| beijing_haidian_red_B_d14_36| null|2024-09-24T14:15:36.000+08:00| null| +|2024-09-24T14:15:40.000+08:00| beijing| beijing| haidian| d14| red|BBBBBBBBBBBBBBBB| 40| null|null|40.0| null| null| beijing_haidian_red_B_d14_40| null|2024-09-24T14:15:40.000+08:00|2024-09-24| +|2024-09-24T14:15:50.000+08:00| beijing| beijing| haidian| d14| red|BBBBBBBBBBBBBBBB|null|50000|null|null| null| null| beijing_haidian_red_B_d14_50|0xcafebabe50|2024-09-24T14:15:50.000+08:00| null| +|2024-09-24T14:15:30.000+08:00| beijing| beijing| haidian| d16|yellow|BBBBBBBBBBBBBBBB|null| null|30.0|null| true| null| beijing_haidian_yellow_B_d16_30| null|2024-09-24T14:15:30.000+08:00|2024-09-24| +|2024-09-24T14:15:40.000+08:00| beijing| beijing| haidian| d16|yellow|BBBBBBBBBBBBBBBB|null|40000|null|null| null| null| null| null|2024-09-24T14:15:40.000+08:00| null| +|2024-09-24T14:15:55.000+08:00| beijing| beijing| haidian| d16|yellow|BBBBBBBBBBBBBBBB| 55| null|null|55.0| null| beijing_haidian_yellow_B_d16_55| null|0xcafebabe55|2024-09-24T14:15:55.000+08:00| null| ++-----------------------------+--------+--------+--------+---------+------+----------------+----+-----+----+----+-----+--------------------------------+--------------------------------+------------+-----------------------------+----------+ +Total line number = 64 +``` + +* Table2: + +```SQL +IoTDB> select * from table2 ++-----------------------------+---------+----+----+----+----+-----+-----+-------+------------+-----------------------------+----------+ +| time|device_id| s1| s2| s3| s4| s5| s6| s7| s8| s9| s10| ++-----------------------------+---------+----+----+----+----+-----+-----+-------+------------+-----------------------------+----------+ +|1970-01-01T08:00:00.001+08:00| d1| 1| 11| 1.1|11.1| true|text1|string1|0xcafebabe01|1970-01-01T08:00:00.001+08:00|2024-10-01| +|1970-01-01T08:00:00.002+08:00| d1| 2| 22| 2.2|22.2|false| null| null| null| null| null| +|1970-01-01T08:00:00.003+08:00| d1|null|null|null|null| null|text3|string3|0xcafebabe03|1970-01-01T08:00:00.003+08:00|2024-10-03| +|1970-01-01T08:00:00.004+08:00| d1|null|null|null|null| null|text4|string4|0xcafebabe04|1970-01-01T08:00:00.004+08:00|2024-10-04| +|1970-01-01T08:00:00.005+08:00| d1| 5| 55| 5.5|55.5|false| null| null| null| null| null| ++-----------------------------+---------+----+----+----+----+-----+-----+-------+------------+-----------------------------+----------+ +Total line number = 5 +``` + +* Table 3: Contains Null Values + +```SQL +IoTDB> select device_id, s1 from table3; ++---------+----+ +|device_id| s1| ++---------+----+ +| d_null| 30| +| d_null|null| +| d01| 30| +| d01| 40| ++---------+----+ +Total line number = 4 +``` + +> Examples of subquery usage in the FROM clause can be referenced in [FROM & JOIN Clause](../SQL-Manual/From-Join-Clause.md). The following text primarily introduces examples of usage in the WHERE, HAVING, and SELECT clauses. + + +### 4.2 Non-Correlated Scalar Subquery Examples + +**Where Clause** + +Find records in table1 where `device_id = 'd01'` and s1 is greater than or equal to the average s1 value for the same device. + +SQL: + +```SQL +IoTDB> SELECT s1 FROM table1 + WHERE device_id = 'd01' + and s1 >= (SELECT avg(s1) from table1 WHERE device_id = 'd01'); +``` + +Result: + +```SQL ++--+ +|s1| ++--+ +|50| +|60| +|70| ++--+ +Total line number = 3 +``` + +**Having Clause** + +Group table1 by `device_id` and count records, filtering groups where the count is not less than the count of records for device `d1` in table2. + +SQL: + +```SQL +IoTDB> SELECT device_id, count(*) + from table1 group by device_id + having count(*) >= (SELECT count(*) from table2 where device_id = 'd1'); +``` + +Result: + +```SQL ++---------+-----+ +|device_id|_col1| ++---------+-----+ +| d01| 5| +| d03| 5| +| d05| 5| +| d07| 5| +| d09| 5| +| d11| 5| +| d13| 5| +| d15| 5| ++---------+-----+ +Total line number = 8 +``` + +**Select Clause** + +For each record in table1 where `device_id = 'd01'`, add its s1 value to the maximum s2 value for the same device (from a subquery). + +SQL: + +```SQL +IoTDB> SELECT s1 + + (SELECT max(s2) from table1 where device_id = 'd01') + from table1 where device_id = 'd01'; +``` + +Result: + +```SQL ++-----+ +|_col0| ++-----+ +| 100| +| 110| +| 120| +| 130| +| 140| ++-----+ +Total line number = 5 +``` + +**Special Cases** + +* If a non-aggregate subquery returns exactly one row of results, it can also be treated as a scalar subquery: + +```SQL +// The subquery returns a value of 1, resulting in an empty result set +IoTDB> SELECT s1 FROM table1 + WHERE device_id = 'd01' and + s1 = (SELECT s1 FROM table2 limit 1); +``` + +> If the subquery returns more than one row, an error will be thrown. + +* When used as a standalone column in the SELECT clause, it can be considered equivalent to selecting a constant column. The result set will repeat the scalar subquery result X times, where X equals the number of rows in the outer query's result set. + +SQL: + +```SQL +// The outer query is: SELECT xx FROM table1 WHERE device_id = 'd01' +// And SELECT count(*) FROM table1 WHERE device_id = 'd01' returns 5, meaning the result set contains five rows + +IoTDB> SELECT + (SELECT max(s1) from table1 where device_id = 'd01') + from table1 where device_id = 'd01'; +``` + +Result: + +```SQL ++-----+ +|_col0| ++-----+ +| 70| +| 70| +| 70| +| 70| +| 70| ++-----+ +Total line number = 5 +``` + +### 4.3 Non-Correlated Column Subquery Examples + +#### 4.3.1 Non-Correlated InPredicate + +**Where Clause** + +Find records in `table1` where `device_id = 'd01'` and `s1` values exist in `table3` for the same device. + +SQL: + +```SQL +IoTDB> SELECT s1 FROM table1 + WHERE device_id = 'd01' and + s1 in (SELECT s1 from table3 WHERE device_id = 'd01'); +``` + +Result: + +```SQL ++--+ +|s1| ++--+ +|30| +|40| ++--+ +Total line number = 2 +``` + +**Having Clause** + +From the `table1` table, group by `device_id`, calculate the record count for each device ID, and find all device IDs and their corresponding record counts where the result of adding 25 to the grouped record count appears in the s1 field values of records with device ID `'d01'` in the `table3` table. + +SQL: + +```SQL +IoTDB> SELECT device_id, count(*) from table1 + group by device_id + having count(*) + 25 + in (SELECT cast(s1 as INT64) from table3 where device_id = 'd01'); +``` + +Result: + +```SQL ++---------+-----+ +|device_id|_col1| ++---------+-----+ +| d01| 5| +| d03| 5| +| d05| 5| +| d07| 5| +| d09| 5| +| d11| 5| +| d13| 5| +| d15| 5| ++---------+-----+ +Total line number = 8 +``` + +**Select Clause** + +From `table1`, select records where `device_id = 'd01'` and check whether their `s1` field values exist in the `s1` field values of records with the same device ID (`d01`) in `table3`. + +SQL: + +```SQL +IoTDB> SELECT + s1 in (SELECT s1 from table3 WHERE device_id = 'd01') + from table1 where device_id = 'd01'; +``` + +Result: + +```SQL ++-----+ +|_col0| ++-----+ +| true| +| true| +|false| +|false| +|false| ++-----+ +Total line number = 5 +``` + +**Special Cases** + +When using InPredicate in the SELECT clause (SELECT x [NOT] IN (subquery) FROM table), the result rules are summarized as follows: + +* If the current row's x is null, the result is null +* If the current row's x is not null: + * Without NOT: + * If x exists in the subquery result set, the current row result is True + * If x does not exist in the subquery result set: + * If the subquery result set contains null, the current row result is null; otherwise, it's False + * With NOT: + * If x exists in the subquery result set, the current row result is False + * If x does not exist in the subquery result set: + * If the subquery result set contains null, the current row result is null; otherwise, it's True + +Example 1: When X result set contains null + +```SQL +IoTDB> select s1 from table3; ++----+ +| s1| ++----+ +| 30| +|null| +| 30| +| 40| ++----+ +Total line number = 4 + +IoTDB> select s1 from table3 where s1 in (select s1 from table3); ++--+ +|s1| ++--+ +|30| +|30| +|40| ++--+ +Total line number = 3 +``` + +Example 2: When used in the SELECT clause, the corresponding row's result is null + +```SQL +IoTDB> select device_id, s1 in (select s1 from table1 where device_id = 'd01'), s1 from table3 ; ++---------+-----+----+ +|device_id|_col1| s1| ++---------+-----+----+ +| d_null| true| 30| +| d01| true| 30| +| d01| true| 40| +| d_null| null|null| ++---------+-----+----+ +``` + +Example 3: When the subquery result set contains null values + +```SQL +IoTDB> select s1 from table1 where device_id = 'd02' ++----+ +| s1| ++----+ +| 36| +| 40| +|null| ++----+ +Total line number = 3 + +IoTDB> select s1 from table3; ++----+ +| s1| ++----+ +| 30| +|null| +| 30| +| 40| ++----+ +Total line number = 4 +``` + +Example 4: Use in the where clause, that is, where s1 in (subquery). The result set only contains one row of 40. + +```SQL +IoTDB> select s1 from table1 where device_id = 'd02' and s1 in (select s1 from table3); ++--+ +|s1| ++--+ +|40| ++--+ +Total line number = 1 +``` + +Example 5: Use it in the select clause. The result set of s1 is (36, 40, null), and the result set of subquery is (30, 40, null). Since 36 is not equal to the two non-null results 30 and 40, and the result set of subquery contains null, the corresponding result is null. + +```SQL +IoTDB> SELECT +> s1 in (SELECT s1 from table3) from table1 +> where device_id = 'd02' ++-----+ +|_col0| ++-----+ +| null| +| true| +| null| ++-----+ +Total line number = 3 +``` + +#### 4.3.2 Non-Correlated Quantified Comparison + +**WHERE Clause** + +* ALL + +Find the records with the equipment number `d01` from the `table1`, and the value of the `s1` field must be greater than all the `s1` field values of the same equipment number in the `table3`. + +SQL: + +```SQL +IoTDB> SELECT s1 FROM table1 + WHERE device_id = 'd01' and + s1 > all (SELECT s1 FROM table3 WHERE device_id = 'd01'); +``` + +Result: + +```SQL ++--+ +|s1| ++--+ +|50| +|60| +|70| ++--+ +Total line number = 3 +``` + +* ANY/SOME + +Find the records with the equipment number `d01` from the `table1`, and the value of the `s1` field must be greater than the `s1` field value of any record with the same equipment number in the `table3`. + +SQL: + +```SQL +IoTDB> SELECT s1 FROM table1 + WHERE device_id = 'd01' and + s1 > any (SELECT s1 FROM table1 WHERE device_id = 'd01'); +``` + +Result: + +```SQL ++--+ +|s1| ++--+ +|40| +|50| +|60| +|70| ++--+ +Total line number = 4 +``` + +**HAVING Clause** + +* ALL + +Group the records in `table1` by `device_id` (equipment number), calculate the number of records for each equipment number. Then, find the equipment numbers and their corresponding record counts such that the sum of the group record count and 35 is greater than or equal to all the `s1` field values (converted to the integer type) of the equipment number `d01` in `table3`. + +SQL: + +```SQL +IoTDB> SELECT device_id, count(*) from table1 + group by device_id + having count(*) + 35 >= + all(SELECT cast(s1 as INT64) from table3 where device_id = 'd01'); +``` + +Result: + +```SQL ++---------+-----+ +|device_id|_col1| ++---------+-----+ +| d01| 5| +| d03| 5| +| d05| 5| +| d07| 5| +| d09| 5| +| d11| 5| +| d13| 5| +| d15| 5| ++---------+-----+ +Total line number = 8 +``` + +* ANY/SOME + +Group the records in `table1` by `device_id` (equipment number), calculate the number of records for each equipment number. Then, find the equipment numbers and their corresponding record counts such that the sum of the group record count and 35 is greater than or equal to any one of the `s1` field values (converted to the integer type) of the equipment number `d01` in `table3`. + +SQL: + +```SQL +IoTDB> SELECT device_id, count(*) + from table1 group by device_id + having count(*) + 25 >= + any(SELECT cast(s1 as INT64) from table3 where device_id = 'd01'); +``` + +Result: + +```SQL ++---------+-----+ +|device_id|_col1| ++---------+-----+ +| d01| 5| +| d03| 5| +| d05| 5| +| d07| 5| +| d09| 5| +| d11| 5| +| d13| 5| +| d15| 5| ++---------+-----+ +Total line number = 8 +``` + +**SELECT Clause** + +* ALL + +Select the records with the equipment number `d01` from `table1`, and the value of the `s1` field must be greater than all the `s1` field values of the equipment number `d01` in `table3`. + +SQL: + +```SQL +IoTDB> SELECT s1 > + all(SELECT (s1) from table3 WHERE device_id = 'd01') + from table1 where device_id = 'd01'; +``` + +Result: + +```SQL ++-----+ +|_col0| ++-----+ +|false| +|false| +| true| +| true| +| true| ++-----+ +Total line number = 5 +``` + +* ANY/SOME + +Select the records with the equipment number `d01` from `table1`, and the value of the `s1` field must be greater than any one of the `s1` field values of the equipment number `d01` in `table3`. + +SQL: + +```SQL +IoTDB> SELECT s1 > + any(SELECT (s1) from table3 WHERE device_id = 'd01') + from table1 where device_id = 'd01'; +``` + +Result: + +```SQL ++-----+ +|_col0| ++-----+ +|false| +| true| +| true| +| true| +| true| ++-----+ +Total line number = 5 +``` + +**Special Cases** + +ALL requires all comparisons to be True for the result to be True. + +ANY/SOME requires any comparison to be True for the result to be True. + +Example 1: ALL + +```SQL +IoTDB> select s1 from table1 where device_id = 'd01' ++--+ +|s1| ++--+ +|30| +|40| +|50| +|60| +|70| ++--+ +Total line number = 5 + +IoTDB> select s1 from table3; ++----+ +| s1| ++----+ +| 30| +|null| +| 30| +| 40| ++----+ + +IoTDB> select (s1 > all(select s1 from table3)) from table1 where device_id = 'd01'; ++-----+ +|_col0| ++-----+ +|false| +|false| +| null| +| null| +| null| ++-----+ +``` + +Note: + +* For the two rows of 30 and 40 in `table1s1`, since the non-`null` result set (30, 40) of `table3 s1` makes 30 > 40 / 40 > 40 evaluate to `False`, that is, short-circuit evaluation occurs, and the result is `false`. +* For the three values of 50, 60, and 70, since ALL requires all comparison results to be `True` for the final result to be `True`, the comparisons of 50, 60, and 70 with `null` are all `null`, and the result is `null`. + +Example 2: ANY/SOME + +```SQL +IoTDB> SELECT s1 <= + any(SELECT (s1) from table3), s1 <= any(SELECT (s1) from table3 where s1 is not NULL) + from table1 where device_id = 'd01' ++-----+-----+ +|_col0|_col1| ++-----+-----+ +| true| true| +| true| true| +| null|false| +| null|false| +| null|false| ++-----+-----+ +``` + +Note: + +* For 30 and 40 in `table1`, because of the non-null result set (30, 40) of `table3 s1`, the comparison results are `true` (valid). +* For 50, 60, and 70, since `ANY` requires at least one comparison result to be `true` for the overall result to be `true`, and the comparison results with `null` are `null`, these results are `null`. +* In the second query, because we have excluded null values, for 50, 60, and 70, there are no larger non-null values in `table3`, so the comparison results are `false`. + diff --git a/src/UserGuide/latest-Table/SQL-Manual/Nested-Queries.md b/src/UserGuide/latest-Table/SQL-Manual/Nested-Queries.md new file mode 100644 index 000000000..031134efa --- /dev/null +++ b/src/UserGuide/latest-Table/SQL-Manual/Nested-Queries.md @@ -0,0 +1,876 @@ + + +# Nested Queries + +## 1. Overview + +Nested queries, also known as subqueries, refer to query statements that contain one or more other query statements within them. A nested query consists of an inner query and an outer query. + +## 2. Classification of Nested Queries + +Nested queries can be classified based on two criteria: whether they reference the outer query and the dimensionality of the result set. + +* **Classification by Reference to Outer Query:** + + + + + + + + + + + + + + + + + + + + +
Classification BasisNested Query TypeDescriptionIoTDB Support
Whether to Reference Outer QueryNon-Correlated SubqueryThe execution of the inner query is independent of the outer query. The inner query executes only once, and its result is used as a condition for the outer query.Supported
Correlated SubqueryThe inner query references columns from the outer query's table, requiring the outer query to execute first, followed by the inner query.Not Supported
+ +* **Classification by Result Set Dimensionality:** + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
Classification BasisSubquery TypeDescriptionUsable ClausesIoTDB Support
Result Set DimensionalityScalar SubqueryReturns a single row and column.select、where、from、havingSupported
Column SubqueryReturns N rows and one column.select、where、from、havingSupported
Row SubqueryReturns one row and N columns. - Not Supported
Table SubqueryReturns N rows and M columns.from Supported
+ +## 3. Functional Definitions + +1. All inner queries must be enclosed in parentheses (subquery). + +2. Non-correlated subqueries cannot reference columns from the outer query. Attempting to do so will result in an error: + + `Msg: org.apache.iotdb.jdbc.IoTDBSQLException： 701: Given correlated subquery is not supported` + +### 3.1 Non-Correlated Scalar Subqueries + +A scalar subquery returns a single scalar value and can be used to replace an operand in an expression. + +**Syntax** + +```SQL +primaryExpression + : literalExpression #Literal + | dateExpression #dateTimeExpression #dateTimeExpression + | '(' expression (',' expression)+ ')' #rowConstructor + | ROW '(' expression (',' expression)* ')' #rowConstructor + | qualifiedName '(' (label=identifier '.')? ASTERISK ')' #functionCall + | qualifiedName '(' (setQuantifier? expression (',' expression)*)?')' #functionCall +​ ​|​ ​'('​ query ​')'​ #subqueryExpression +``` + +**Notes** + +Scalar subqueries can be used as operands in any expression unless the input parameters are explicitly defined as constants. + +Examples where scalar subqueries cannot be used as parameters: + +* The first and third parameters of `date_bin(interval,source,origin)`. +* The first and third parameters of `date_bin_gapfill(interval,source,origin)`. + * `interval` ：Time interval + * `origin`：Starting timestamp +* `Fill` parameters + * `fill previous` + * `fill linear` + * `fill constant` + +### 3.2 Non-Correlated Column Subqueries + +#### 3.2.1 Non-Correlated InPredicate + +An InPredicate is a predicate that returns a column of boolean values. + +**Syntax** + +```SQL +predicate[ParserRuleContext value] + : comparisonOperator right=valueExpression #comparison + | comparisonOperator comparisonQuantifier '(' query ')' #quantifiedComparison + | NOT? BETWEEN lower=valueExpression AND upper=valueExpression #between + | NOT? IN '(' expression (',' expression)* ')' #inList + |​ ​NOT? ​IN​ ​'('​ query ​')'​ #inSubquery + | NOT? LIKE pattern=valueExpression (ESCAPE escape=valueExpression)? #like + | IS NOT? NULL #nullPredicate + | IS NOT? DISTINCT FROM right=valueExpression #distinctFrom + ; +``` + +**Notes** + +Usage: `X [NOT] IN (subquery)` + +* `X` is an expression. +* `NOT` is optional (negation). +* `subquery` returns a result set `Result`with one column and multiple rows. +* For `WHERE X IN (subquery)`, each row where `X` is in `Result` will be retained in the `SELECT` output. + +#### 3.2.2 Non-Correlated Quantified Comparison + +A quantified comparison allows comparing a value to a set of values, typically consisting of: + +1. Comparison operators:`<`， `>`， `=`， `<=`， `>=`， `!=` +2. Quantifiers: + 1. `ALL`: All elements must satisfy the condition. + 2. `ANY` or `SOME`: At least one element must satisfy the condition (ANY and SOME are equivalent). +3. Subquery: Returns a set of values to compare with the main query's value. + +**Syntax** + +```SQL +predicate[ParserRuleContext value] + : comparisonOperator right=valueExpression #comparison + |​ comparisonOperator comparisonQuantifier ​'('​ query ​')'​ #quantifiedComparison + | NOT? BETWEEN lower=valueExpression AND upper=valueExpression #between + | NOT? IN '(' expression (',' expression)* ')' #inList + | NOT? IN '(' query ')' #inSubquery + | NOT? LIKE pattern=valueExpression (ESCAPE escape=valueExpression)? #like + | IS NOT? NULL #nullPredicate + | IS NOT? DISTINCT FROM right=valueExpression #distinctFrom + ; +comparisonQuantifier + : ALL | SOME | ANY + ; +``` + +**Notes** + +Usage: `expression operator ALL/ANY/SOME (subquery)` + +* ALL: The `expression` in the main query must satisfy the condition with every value returned by the subquery. +* ANY/SOME: The `expression` in the main query must satisfy the condition with at least one value returned by the subquery. + +## 4. Usage Examples +### 4.1 Example Data + +s1, s2, s3, s4 are of types INT, LONG, FLOAT, DOUBLE respectively. + +* Table1: + +```SQL +// All data in table1 +IoTDB> select * from table1; ++-----------------------------+--------+--------+--------+---------+------+----------------+----+-----+----+----+-----+--------------------------------+--------------------------------+------------+-----------------------------+----------+ +| time|province| city| region|device_id| color| type| s1| s2| s3| s4| s5| s6| s7| s8| s9| s10| ++-----------------------------+--------+--------+--------+---------+------+----------------+----+-----+----+----+-----+--------------------------------+--------------------------------+------------+-----------------------------+----------+ +|2024-09-24T14:15:30.000+08:00|shanghai|shanghai| pudong| d05| red| A| 30| null|30.0|null| null| shanghai_pudong_red_A_d05_30| null|0xcafebabe30|2024-09-24T14:15:30.000+08:00| null| +|2024-09-24T14:15:35.000+08:00|shanghai|shanghai| pudong| d05| red| A|null|35000|35.0|35.0| null| shanghai_pudong_red_A_d05_35| shanghai_pudong_red_A_d05_35| null|2024-09-24T14:15:35.000+08:00|2024-09-24| +|2024-09-24T14:15:40.000+08:00|shanghai|shanghai| pudong| d05| red| A| 40| null|40.0|null| true| null| shanghai_pudong_red_A_d05_40| null|2024-09-24T14:15:40.000+08:00| null| +|2024-09-24T14:15:50.000+08:00|shanghai|shanghai| pudong| d05| red| A|null|50000|null|null|false| null| null| null|2024-09-24T14:15:50.000+08:00|2024-09-24| +|2024-09-24T14:15:55.000+08:00|shanghai|shanghai| pudong| d05| red| A| 55| null|null|55.0| null| null| null|0xcafebabe55|2024-09-24T14:15:55.000+08:00| null| +|2024-09-24T14:15:31.000+08:00|shanghai|shanghai| pudong| d07|yellow| A|null|31000|null|null| null| null| null|0xcafebabe31|2024-09-24T14:15:31.000+08:00| null| +|2024-09-24T14:15:36.000+08:00|shanghai|shanghai| pudong| d07|yellow| A| 36| null|null|36.0| null| null| shanghai_pudong_yellow_A_d07_36| null|2024-09-24T14:15:36.000+08:00|2024-09-24| +|2024-09-24T14:15:41.000+08:00|shanghai|shanghai| pudong| d07|yellow| A| 41| null|41.0|null|false| shanghai_pudong_yellow_A_d07_41| null|0xcafebabe41|2024-09-24T14:15:41.000+08:00| null| +|2024-09-24T14:15:46.000+08:00|shanghai|shanghai| pudong| d07|yellow| A|null|46000|null|46.0| null| null| shanghai_pudong_yellow_A_d07_46| null|2024-09-24T14:15:46.000+08:00| null| +|2024-09-24T14:15:51.000+08:00|shanghai|shanghai| pudong| d07|yellow| A|null| null|51.0|null| null| shanghai_pudong_yellow_A_d07_51| null| null|2024-09-24T14:15:51.000+08:00| null| +|2024-09-24T14:13:30.000+08:00|shanghai|shanghai| huangpu| d01| red| A| 30| 30|30.0|30.0| true| shanghai_huangpu_red_A_d01_30| shanghai_huangpu_red_A_d01_30|0xcafebabe30|2024-09-24T14:13:00.000+08:00|2024-09-23| +|2024-09-24T14:14:30.000+08:00|shanghai|shanghai| huangpu| d01| red| A| 40| 40|40.0|40.0|false| shanghai_huangpu_red_A_d01_40| shanghai_huangpu_red_A_d01_40|0xcafebabe40|2024-09-24T14:14:00.000+08:00|2024-09-24| +|2024-09-24T14:15:30.000+08:00|shanghai|shanghai| huangpu| d01| red| A| 50| 50|50.0|50.0| true| shanghai_huangpu_red_A_d01_50| shanghai_huangpu_red_A_d01_50|0xcafebabe50|2024-09-24T14:15:00.000+08:00|2024-09-25| +|2024-09-24T14:16:30.000+08:00|shanghai|shanghai| huangpu| d01| red| A| 60| 60|60.0|60.0|false| shanghai_huangpu_red_A_d01_60| shanghai_huangpu_red_A_d01_60|0xcafebabe60|2024-09-24T14:16:00.000+08:00|2024-09-26| +|2024-09-24T14:17:30.000+08:00|shanghai|shanghai| huangpu| d01| red| A| 70| 70|70.0|70.0| true| shanghai_huangpu_red_A_d01_70| shanghai_huangpu_red_A_d01_70|0xcafebabe70|2024-09-24T14:17:00.000+08:00|2024-09-27| +|2024-09-24T14:15:31.000+08:00|shanghai|shanghai| huangpu| d03|yellow| A|null|31000|null|null| null| null| null|0xcafebabe31|2024-09-24T14:15:31.000+08:00| null| +|2024-09-24T14:15:36.000+08:00|shanghai|shanghai| huangpu| d03|yellow| A| 36| null|null|36.0| null| null|shanghai_huangpu_yellow_A_d03_36| null|2024-09-24T14:15:36.000+08:00|2024-09-24| +|2024-09-24T14:15:41.000+08:00|shanghai|shanghai| huangpu| d03|yellow| A| 41| null|41.0|null|false|shanghai_huangpu_yellow_A_d03_41| null|0xcafebabe41|2024-09-24T14:15:41.000+08:00| null| +|2024-09-24T14:15:46.000+08:00|shanghai|shanghai| huangpu| d03|yellow| A|null|46000|null|46.0| null| null|shanghai_huangpu_yellow_A_d03_46| null|2024-09-24T14:15:46.000+08:00| null| +|2024-09-24T14:15:51.000+08:00|shanghai|shanghai| huangpu| d03|yellow| A|null| null|51.0|null| null|shanghai_huangpu_yellow_A_d03_51| null| null|2024-09-24T14:15:51.000+08:00| null| +|2024-09-24T14:15:31.000+08:00| beijing| beijing|chaoyang| d11|yellow| A|null|31000|null|null| null| null| null|0xcafebabe31|2024-09-24T14:15:31.000+08:00| null| +|2024-09-24T14:15:36.000+08:00| beijing| beijing|chaoyang| d11|yellow| A| 36| null|null|36.0| null| null|beijing_chaoyang_yellow_A_d11_36| null|2024-09-24T14:15:36.000+08:00|2024-09-24| +|2024-09-24T14:15:41.000+08:00| beijing| beijing|chaoyang| d11|yellow| A| 41| null|41.0|null|false|beijing_chaoyang_yellow_A_d11_41| null|0xcafebabe41|2024-09-24T14:15:41.000+08:00| null| +|2024-09-24T14:15:46.000+08:00| beijing| beijing|chaoyang| d11|yellow| A|null|46000|null|46.0| null| null|beijing_chaoyang_yellow_A_d11_46| null|2024-09-24T14:15:46.000+08:00| null| +|2024-09-24T14:15:51.000+08:00| beijing| beijing|chaoyang| d11|yellow| A|null| null|51.0|null| null|beijing_chaoyang_yellow_A_d11_51| null| null|2024-09-24T14:15:51.000+08:00| null| +|2024-09-24T14:15:30.000+08:00| beijing| beijing|chaoyang| d09| red| A| 30| null|30.0|null| null| beijing_chaoyang_red_A_d09_30| null|0xcafebabe30|2024-09-24T14:15:30.000+08:00| null| +|2024-09-24T14:15:35.000+08:00| beijing| beijing|chaoyang| d09| red| A|null|35000|35.0|35.0| null| beijing_chaoyang_red_A_d09_35| beijing_chaoyang_red_A_d09_35| null|2024-09-24T14:15:35.000+08:00|2024-09-24| +|2024-09-24T14:15:40.000+08:00| beijing| beijing|chaoyang| d09| red| A| 40| null|40.0|null| true| null| beijing_chaoyang_red_A_d09_40| null|2024-09-24T14:15:40.000+08:00| null| +|2024-09-24T14:15:50.000+08:00| beijing| beijing|chaoyang| d09| red| A|null|50000|null|null|false| null| null| null|2024-09-24T14:15:50.000+08:00|2024-09-24| +|2024-09-24T14:15:55.000+08:00| beijing| beijing|chaoyang| d09| red| A| 55| null|null|55.0| null| null| null|0xcafebabe55|2024-09-24T14:15:55.000+08:00| null| +|2024-09-24T14:15:30.000+08:00| beijing| beijing| haidian| d13| red| A| 30| null|30.0|null| null| beijing_haidian_red_A_d13_30| null|0xcafebabe30|2024-09-24T14:15:30.000+08:00| null| +|2024-09-24T14:15:35.000+08:00| beijing| beijing| haidian| d13| red| A|null|35000|35.0|35.0| null| beijing_haidian_red_A_d13_35| beijing_haidian_red_A_d13_35| null|2024-09-24T14:15:35.000+08:00|2024-09-24| +|2024-09-24T14:15:40.000+08:00| beijing| beijing| haidian| d13| red| A| 40| null|40.0|null| true| null| beijing_haidian_red_A_d13_40| null|2024-09-24T14:15:40.000+08:00| null| +|2024-09-24T14:15:50.000+08:00| beijing| beijing| haidian| d13| red| A|null|50000|null|null|false| null| null| null|2024-09-24T14:15:50.000+08:00|2024-09-24| +|2024-09-24T14:15:55.000+08:00| beijing| beijing| haidian| d13| red| A| 55| null|null|55.0| null| null| null|0xcafebabe55|2024-09-24T14:15:55.000+08:00| null| +|2024-09-24T14:15:31.000+08:00| beijing| beijing| haidian| d15|yellow| A|null|31000|null|null| null| null| null|0xcafebabe31|2024-09-24T14:15:31.000+08:00| null| +|2024-09-24T14:15:36.000+08:00| beijing| beijing| haidian| d15|yellow| A| 36| null|null|36.0| null| null| beijing_haidian_yellow_A_d15_36| null|2024-09-24T14:15:36.000+08:00|2024-09-24| +|2024-09-24T14:15:41.000+08:00| beijing| beijing| haidian| d15|yellow| A| 41| null|41.0|null|false| beijing_haidian_yellow_A_d15_41| null|0xcafebabe41|2024-09-24T14:15:41.000+08:00| null| +|2024-09-24T14:15:46.000+08:00| beijing| beijing| haidian| d15|yellow| A|null|46000|null|46.0| null| null| beijing_haidian_yellow_A_d15_46| null|2024-09-24T14:15:46.000+08:00| null| +|2024-09-24T14:15:51.000+08:00| beijing| beijing| haidian| d15|yellow| A|null| null|51.0|null| null| beijing_haidian_yellow_A_d15_51| null| null|2024-09-24T14:15:51.000+08:00| null| +|2024-09-24T14:15:36.000+08:00|shanghai|shanghai| pudong| d06| red|BBBBBBBBBBBBBBBB| 36| null|null|null| true| shanghai_pudong_red_B_d06_36| shanghai_pudong_red_B_d06_36| null|2024-09-24T14:15:36.000+08:00| null| +|2024-09-24T14:15:40.000+08:00|shanghai|shanghai| pudong| d06| red|BBBBBBBBBBBBBBBB| 40| null|null|40.0| null| null| shanghai_pudong_red_B_d06_40| null|2024-09-24T14:15:40.000+08:00|2024-09-24| +|2024-09-24T14:15:50.000+08:00|shanghai|shanghai| pudong| d06| red|BBBBBBBBBBBBBBBB|null|50000|null|null| null| null| shanghai_pudong_red_B_d06_50|0xcafebabe50|2024-09-24T14:15:50.000+08:00| null| +|2024-09-24T14:15:30.000+08:00|shanghai|shanghai| pudong| d08|yellow|BBBBBBBBBBBBBBBB|null| null|30.0|null| true| null| shanghai_pudong_yellow_B_d08_30| null|2024-09-24T14:15:30.000+08:00|2024-09-24| +|2024-09-24T14:15:40.000+08:00|shanghai|shanghai| pudong| d08|yellow|BBBBBBBBBBBBBBBB|null|40000|null|null| null| null| null| null|2024-09-24T14:15:40.000+08:00| null| +|2024-09-24T14:15:55.000+08:00|shanghai|shanghai| pudong| d08|yellow|BBBBBBBBBBBBBBBB| 55| null|null|55.0| null| shanghai_pudong_yellow_B_d08_55| null|0xcafebabe55|2024-09-24T14:15:55.000+08:00| null| +|2024-09-24T14:15:36.000+08:00|shanghai|shanghai| huangpu| d02| red|BBBBBBBBBBBBBBBB| 36| null|null|null| true| shanghai_huangpu_red_B_d02_36| shanghai_huangpu_red_B_d02_36| null|2024-09-24T14:15:36.000+08:00| null| +|2024-09-24T14:15:40.000+08:00|shanghai|shanghai| huangpu| d02| red|BBBBBBBBBBBBBBBB| 40| null|null|40.0| null| null| shanghai_huangpu_red_B_d02_40| null|2024-09-24T14:15:40.000+08:00|2024-09-24| +|2024-09-24T14:15:50.000+08:00|shanghai|shanghai| huangpu| d02| red|BBBBBBBBBBBBBBBB|null|50000|null|null| null| null| shanghai_huangpu_red_B_d02_50|0xcafebabe50|2024-09-24T14:15:50.000+08:00| null| +|2024-09-24T14:15:30.000+08:00|shanghai|shanghai| huangpu| d04|yellow|BBBBBBBBBBBBBBBB|null| null|30.0|null| true| null|shanghai_huangpu_yellow_B_d04_30| null|2024-09-24T14:15:30.000+08:00|2024-09-24| +|2024-09-24T14:15:40.000+08:00|shanghai|shanghai| huangpu| d04|yellow|BBBBBBBBBBBBBBBB|null|40000|null|null| null| null| null| null|2024-09-24T14:15:40.000+08:00| null| +|2024-09-24T14:15:55.000+08:00|shanghai|shanghai| huangpu| d04|yellow|BBBBBBBBBBBBBBBB| 55| null|null|55.0| null|shanghai_huangpu_yellow_B_d04_55| null|0xcafebabe55|2024-09-24T14:15:55.000+08:00| null| +|2024-09-24T14:15:36.000+08:00| beijing| beijing|chaoyang| d10| red|BBBBBBBBBBBBBBBB| 36| null|null|null| true| beijing_chaoyang_red_B_d10_36| beijing_chaoyang_red_B_d10_36| null|2024-09-24T14:15:36.000+08:00| null| +|2024-09-24T14:15:40.000+08:00| beijing| beijing|chaoyang| d10| red|BBBBBBBBBBBBBBBB| 40| null|null|40.0| null| null| beijing_chaoyang_red_B_d10_40| null|2024-09-24T14:15:40.000+08:00|2024-09-24| +|2024-09-24T14:15:50.000+08:00| beijing| beijing|chaoyang| d10| red|BBBBBBBBBBBBBBBB|null|50000|null|null| null| null| beijing_chaoyang_red_B_d10_50|0xcafebabe50|2024-09-24T14:15:50.000+08:00| null| +|2024-09-24T14:15:30.000+08:00| beijing| beijing|chaoyang| d12|yellow|BBBBBBBBBBBBBBBB|null| null|30.0|null| true| null|beijing_chaoyang_yellow_B_d12_30| null|2024-09-24T14:15:30.000+08:00|2024-09-24| +|2024-09-24T14:15:40.000+08:00| beijing| beijing|chaoyang| d12|yellow|BBBBBBBBBBBBBBBB|null|40000|null|null| null| null| null| null|2024-09-24T14:15:40.000+08:00| null| +|2024-09-24T14:15:55.000+08:00| beijing| beijing|chaoyang| d12|yellow|BBBBBBBBBBBBBBBB| 55| null|null|55.0| null|beijing_chaoyang_yellow_B_d12_55| null|0xcafebabe55|2024-09-24T14:15:55.000+08:00| null| +|2024-09-24T14:15:36.000+08:00| beijing| beijing| haidian| d14| red|BBBBBBBBBBBBBBBB| 36| null|null|null| true| beijing_haidian_red_B_d14_36| beijing_haidian_red_B_d14_36| null|2024-09-24T14:15:36.000+08:00| null| +|2024-09-24T14:15:40.000+08:00| beijing| beijing| haidian| d14| red|BBBBBBBBBBBBBBBB| 40| null|null|40.0| null| null| beijing_haidian_red_B_d14_40| null|2024-09-24T14:15:40.000+08:00|2024-09-24| +|2024-09-24T14:15:50.000+08:00| beijing| beijing| haidian| d14| red|BBBBBBBBBBBBBBBB|null|50000|null|null| null| null| beijing_haidian_red_B_d14_50|0xcafebabe50|2024-09-24T14:15:50.000+08:00| null| +|2024-09-24T14:15:30.000+08:00| beijing| beijing| haidian| d16|yellow|BBBBBBBBBBBBBBBB|null| null|30.0|null| true| null| beijing_haidian_yellow_B_d16_30| null|2024-09-24T14:15:30.000+08:00|2024-09-24| +|2024-09-24T14:15:40.000+08:00| beijing| beijing| haidian| d16|yellow|BBBBBBBBBBBBBBBB|null|40000|null|null| null| null| null| null|2024-09-24T14:15:40.000+08:00| null| +|2024-09-24T14:15:55.000+08:00| beijing| beijing| haidian| d16|yellow|BBBBBBBBBBBBBBBB| 55| null|null|55.0| null| beijing_haidian_yellow_B_d16_55| null|0xcafebabe55|2024-09-24T14:15:55.000+08:00| null| ++-----------------------------+--------+--------+--------+---------+------+----------------+----+-----+----+----+-----+--------------------------------+--------------------------------+------------+-----------------------------+----------+ +Total line number = 64 +``` + +* Table2: + +```SQL +IoTDB> select * from table2 ++-----------------------------+---------+----+----+----+----+-----+-----+-------+------------+-----------------------------+----------+ +| time|device_id| s1| s2| s3| s4| s5| s6| s7| s8| s9| s10| ++-----------------------------+---------+----+----+----+----+-----+-----+-------+------------+-----------------------------+----------+ +|1970-01-01T08:00:00.001+08:00| d1| 1| 11| 1.1|11.1| true|text1|string1|0xcafebabe01|1970-01-01T08:00:00.001+08:00|2024-10-01| +|1970-01-01T08:00:00.002+08:00| d1| 2| 22| 2.2|22.2|false| null| null| null| null| null| +|1970-01-01T08:00:00.003+08:00| d1|null|null|null|null| null|text3|string3|0xcafebabe03|1970-01-01T08:00:00.003+08:00|2024-10-03| +|1970-01-01T08:00:00.004+08:00| d1|null|null|null|null| null|text4|string4|0xcafebabe04|1970-01-01T08:00:00.004+08:00|2024-10-04| +|1970-01-01T08:00:00.005+08:00| d1| 5| 55| 5.5|55.5|false| null| null| null| null| null| ++-----------------------------+---------+----+----+----+----+-----+-----+-------+------------+-----------------------------+----------+ +Total line number = 5 +``` + +* Table 3: Contains Null Values + +```SQL +IoTDB> select device_id, s1 from table3; ++---------+----+ +|device_id| s1| ++---------+----+ +| d_null| 30| +| d_null|null| +| d01| 30| +| d01| 40| ++---------+----+ +Total line number = 4 +``` + +> Examples of subquery usage in the FROM clause can be referenced in [FROM & JOIN Clause](../SQL-Manual/From-Join-Clause.md). The following text primarily introduces examples of usage in the WHERE, HAVING, and SELECT clauses. + + +### 4.2 Non-Correlated Scalar Subquery Examples + +**Where Clause** + +Find records in table1 where `device_id = 'd01'` and s1 is greater than or equal to the average s1 value for the same device. + +SQL: + +```SQL +IoTDB> SELECT s1 FROM table1 + WHERE device_id = 'd01' + and s1 >= (SELECT avg(s1) from table1 WHERE device_id = 'd01'); +``` + +Result: + +```SQL ++--+ +|s1| ++--+ +|50| +|60| +|70| ++--+ +Total line number = 3 +``` + +**Having Clause** + +Group table1 by `device_id` and count records, filtering groups where the count is not less than the count of records for device `d1` in table2. + +SQL: + +```SQL +IoTDB> SELECT device_id, count(*) + from table1 group by device_id + having count(*) >= (SELECT count(*) from table2 where device_id = 'd1'); +``` + +Result: + +```SQL ++---------+-----+ +|device_id|_col1| ++---------+-----+ +| d01| 5| +| d03| 5| +| d05| 5| +| d07| 5| +| d09| 5| +| d11| 5| +| d13| 5| +| d15| 5| ++---------+-----+ +Total line number = 8 +``` + +**Select Clause** + +For each record in table1 where `device_id = 'd01'`, add its s1 value to the maximum s2 value for the same device (from a subquery). + +SQL: + +```SQL +IoTDB> SELECT s1 + + (SELECT max(s2) from table1 where device_id = 'd01') + from table1 where device_id = 'd01'; +``` + +Result: + +```SQL ++-----+ +|_col0| ++-----+ +| 100| +| 110| +| 120| +| 130| +| 140| ++-----+ +Total line number = 5 +``` + +**Special Cases** + +* If a non-aggregate subquery returns exactly one row of results, it can also be treated as a scalar subquery: + +```SQL +// The subquery returns a value of 1, resulting in an empty result set +IoTDB> SELECT s1 FROM table1 + WHERE device_id = 'd01' and + s1 = (SELECT s1 FROM table2 limit 1); +``` + +> If the subquery returns more than one row, an error will be thrown. + +* When used as a standalone column in the SELECT clause, it can be considered equivalent to selecting a constant column. The result set will repeat the scalar subquery result X times, where X equals the number of rows in the outer query's result set. + +SQL: + +```SQL +// The outer query is: SELECT xx FROM table1 WHERE device_id = 'd01' +// And SELECT count(*) FROM table1 WHERE device_id = 'd01' returns 5, meaning the result set contains five rows + +IoTDB> SELECT + (SELECT max(s1) from table1 where device_id = 'd01') + from table1 where device_id = 'd01'; +``` + +Result: + +```SQL ++-----+ +|_col0| ++-----+ +| 70| +| 70| +| 70| +| 70| +| 70| ++-----+ +Total line number = 5 +``` + +### 4.3 Non-Correlated Column Subquery Examples + +#### 4.3.1 Non-Correlated InPredicate + +**Where Clause** + +Find records in `table1` where `device_id = 'd01'` and `s1` values exist in `table3` for the same device. + +SQL: + +```SQL +IoTDB> SELECT s1 FROM table1 + WHERE device_id = 'd01' and + s1 in (SELECT s1 from table3 WHERE device_id = 'd01'); +``` + +Result: + +```SQL ++--+ +|s1| ++--+ +|30| +|40| ++--+ +Total line number = 2 +``` + +**Having Clause** + +From the `table1` table, group by `device_id`, calculate the record count for each device ID, and find all device IDs and their corresponding record counts where the result of adding 25 to the grouped record count appears in the s1 field values of records with device ID `'d01'` in the `table3` table. + +SQL: + +```SQL +IoTDB> SELECT device_id, count(*) from table1 + group by device_id + having count(*) + 25 + in (SELECT cast(s1 as INT64) from table3 where device_id = 'd01'); +``` + +Result: + +```SQL ++---------+-----+ +|device_id|_col1| ++---------+-----+ +| d01| 5| +| d03| 5| +| d05| 5| +| d07| 5| +| d09| 5| +| d11| 5| +| d13| 5| +| d15| 5| ++---------+-----+ +Total line number = 8 +``` + +**Select Clause** + +From `table1`, select records where `device_id = 'd01'` and check whether their `s1` field values exist in the `s1` field values of records with the same device ID (`d01`) in `table3`. + +SQL: + +```SQL +IoTDB> SELECT + s1 in (SELECT s1 from table3 WHERE device_id = 'd01') + from table1 where device_id = 'd01'; +``` + +Result: + +```SQL ++-----+ +|_col0| ++-----+ +| true| +| true| +|false| +|false| +|false| ++-----+ +Total line number = 5 +``` + +**Special Cases** + +When using InPredicate in the SELECT clause (SELECT x [NOT] IN (subquery) FROM table), the result rules are summarized as follows: + +* If the current row's x is null, the result is null +* If the current row's x is not null: + * Without NOT: + * If x exists in the subquery result set, the current row result is True + * If x does not exist in the subquery result set: + * If the subquery result set contains null, the current row result is null; otherwise, it's False + * With NOT: + * If x exists in the subquery result set, the current row result is False + * If x does not exist in the subquery result set: + * If the subquery result set contains null, the current row result is null; otherwise, it's True + +Example 1: When X result set contains null + +```SQL +IoTDB> select s1 from table3; ++----+ +| s1| ++----+ +| 30| +|null| +| 30| +| 40| ++----+ +Total line number = 4 + +IoTDB> select s1 from table3 where s1 in (select s1 from table3); ++--+ +|s1| ++--+ +|30| +|30| +|40| ++--+ +Total line number = 3 +``` + +Example 2: When used in the SELECT clause, the corresponding row's result is null + +```SQL +IoTDB> select device_id, s1 in (select s1 from table1 where device_id = 'd01'), s1 from table3 ; ++---------+-----+----+ +|device_id|_col1| s1| ++---------+-----+----+ +| d_null| true| 30| +| d01| true| 30| +| d01| true| 40| +| d_null| null|null| ++---------+-----+----+ +``` + +Example 3: When the subquery result set contains null values + +```SQL +IoTDB> select s1 from table1 where device_id = 'd02' ++----+ +| s1| ++----+ +| 36| +| 40| +|null| ++----+ +Total line number = 3 + +IoTDB> select s1 from table3; ++----+ +| s1| ++----+ +| 30| +|null| +| 30| +| 40| ++----+ +Total line number = 4 +``` + +Example 4: Use in the where clause, that is, where s1 in (subquery). The result set only contains one row of 40. + +```SQL +IoTDB> select s1 from table1 where device_id = 'd02' and s1 in (select s1 from table3); ++--+ +|s1| ++--+ +|40| ++--+ +Total line number = 1 +``` + +Example 5: Use it in the select clause. The result set of s1 is (36, 40, null), and the result set of subquery is (30, 40, null). Since 36 is not equal to the two non-null results 30 and 40, and the result set of subquery contains null, the corresponding result is null. + +```SQL +IoTDB> SELECT +> s1 in (SELECT s1 from table3) from table1 +> where device_id = 'd02' ++-----+ +|_col0| ++-----+ +| null| +| true| +| null| ++-----+ +Total line number = 3 +``` + +#### 4.3.2 Non-Correlated Quantified Comparison + +**WHERE Clause** + +* ALL + +Find the records with the equipment number `d01` from the `table1`, and the value of the `s1` field must be greater than all the `s1` field values of the same equipment number in the `table3`. + +SQL: + +```SQL +IoTDB> SELECT s1 FROM table1 + WHERE device_id = 'd01' and + s1 > all (SELECT s1 FROM table3 WHERE device_id = 'd01'); +``` + +Result: + +```SQL ++--+ +|s1| ++--+ +|50| +|60| +|70| ++--+ +Total line number = 3 +``` + +* ANY/SOME + +Find the records with the equipment number `d01` from the `table1`, and the value of the `s1` field must be greater than the `s1` field value of any record with the same equipment number in the `table3`. + +SQL: + +```SQL +IoTDB> SELECT s1 FROM table1 + WHERE device_id = 'd01' and + s1 > any (SELECT s1 FROM table1 WHERE device_id = 'd01'); +``` + +Result: + +```SQL ++--+ +|s1| ++--+ +|40| +|50| +|60| +|70| ++--+ +Total line number = 4 +``` + +**HAVING Clause** + +* ALL + +Group the records in `table1` by `device_id` (equipment number), calculate the number of records for each equipment number. Then, find the equipment numbers and their corresponding record counts such that the sum of the group record count and 35 is greater than or equal to all the `s1` field values (converted to the integer type) of the equipment number `d01` in `table3`. + +SQL: + +```SQL +IoTDB> SELECT device_id, count(*) from table1 + group by device_id + having count(*) + 35 >= + all(SELECT cast(s1 as INT64) from table3 where device_id = 'd01'); +``` + +Result: + +```SQL ++---------+-----+ +|device_id|_col1| ++---------+-----+ +| d01| 5| +| d03| 5| +| d05| 5| +| d07| 5| +| d09| 5| +| d11| 5| +| d13| 5| +| d15| 5| ++---------+-----+ +Total line number = 8 +``` + +* ANY/SOME + +Group the records in `table1` by `device_id` (equipment number), calculate the number of records for each equipment number. Then, find the equipment numbers and their corresponding record counts such that the sum of the group record count and 35 is greater than or equal to any one of the `s1` field values (converted to the integer type) of the equipment number `d01` in `table3`. + +SQL: + +```SQL +IoTDB> SELECT device_id, count(*) + from table1 group by device_id + having count(*) + 25 >= + any(SELECT cast(s1 as INT64) from table3 where device_id = 'd01'); +``` + +Result: + +```SQL ++---------+-----+ +|device_id|_col1| ++---------+-----+ +| d01| 5| +| d03| 5| +| d05| 5| +| d07| 5| +| d09| 5| +| d11| 5| +| d13| 5| +| d15| 5| ++---------+-----+ +Total line number = 8 +``` + +**SELECT Clause** + +* ALL + +Select the records with the equipment number `d01` from `table1`, and the value of the `s1` field must be greater than all the `s1` field values of the equipment number `d01` in `table3`. + +SQL: + +```SQL +IoTDB> SELECT s1 > + all(SELECT (s1) from table3 WHERE device_id = 'd01') + from table1 where device_id = 'd01'; +``` + +Result: + +```SQL ++-----+ +|_col0| ++-----+ +|false| +|false| +| true| +| true| +| true| ++-----+ +Total line number = 5 +``` + +* ANY/SOME + +Select the records with the equipment number `d01` from `table1`, and the value of the `s1` field must be greater than any one of the `s1` field values of the equipment number `d01` in `table3`. + +SQL: + +```SQL +IoTDB> SELECT s1 > + any(SELECT (s1) from table3 WHERE device_id = 'd01') + from table1 where device_id = 'd01'; +``` + +Result: + +```SQL ++-----+ +|_col0| ++-----+ +|false| +| true| +| true| +| true| +| true| ++-----+ +Total line number = 5 +``` + +**Special Cases** + +ALL requires all comparisons to be True for the result to be True. + +ANY/SOME requires any comparison to be True for the result to be True. + +Example 1: ALL + +```SQL +IoTDB> select s1 from table1 where device_id = 'd01' ++--+ +|s1| ++--+ +|30| +|40| +|50| +|60| +|70| ++--+ +Total line number = 5 + +IoTDB> select s1 from table3; ++----+ +| s1| ++----+ +| 30| +|null| +| 30| +| 40| ++----+ + +IoTDB> select (s1 > all(select s1 from table3)) from table1 where device_id = 'd01'; ++-----+ +|_col0| ++-----+ +|false| +|false| +| null| +| null| +| null| ++-----+ +``` + +Note: + +* For the two rows of 30 and 40 in `table1s1`, since the non-`null` result set (30, 40) of `table3 s1` makes 30 > 40 / 40 > 40 evaluate to `False`, that is, short-circuit evaluation occurs, and the result is `false`. +* For the three values of 50, 60, and 70, since ALL requires all comparison results to be `True` for the final result to be `True`, the comparisons of 50, 60, and 70 with `null` are all `null`, and the result is `null`. + +Example 2: ANY/SOME + +```SQL +IoTDB> SELECT s1 <= + any(SELECT (s1) from table3), s1 <= any(SELECT (s1) from table3 where s1 is not NULL) + from table1 where device_id = 'd01' ++-----+-----+ +|_col0|_col1| ++-----+-----+ +| true| true| +| true| true| +| null|false| +| null|false| +| null|false| ++-----+-----+ +``` + +Note: + +* For 30 and 40 in `table1`, because of the non-null result set (30, 40) of `table3 s1`, the comparison results are `true` (valid). +* For 50, 60, and 70, since `ANY` requires at least one comparison result to be `true` for the overall result to be `true`, and the comparison results with `null` are `null`, these results are `null`. +* In the second query, because we have excluded null values, for 50, 60, and 70, there are no larger non-null values in `table3`, so the comparison results are `false`. + diff --git a/src/zh/UserGuide/Master/Table/SQL-Manual/Nested-Queries.md b/src/zh/UserGuide/Master/Table/SQL-Manual/Nested-Queries.md new file mode 100644 index 000000000..c855fbfb3 --- /dev/null +++ b/src/zh/UserGuide/Master/Table/SQL-Manual/Nested-Queries.md @@ -0,0 +1,875 @@ + + +# 嵌套查询 + +## 1. 概述 + +嵌套查询又被称为子查询，是指一个查询语句内部包含另一个或多个查询语句。嵌套查询由内层查询和外层查询组成。 + +## 2. 嵌套查询分类 + +嵌套查询可以按照以下两种依据进行分类：按是否引用外层查询分类、按结果集行列数分类。 + +* **按是否引用外层查询分类：** + + + + + + + + + + + + + + + + + + + + +
分类依据嵌套查询类型描述IoTDB 支持情况
是否引用外层查询非关联子查询内层查询的执行和外层查询的执行是独立的，内层查询仅执行一次，执行完毕后将结果作为外层查询的条件使用。支持
关联子查询内层查询中使用到了外层查询的表中某些列，需要先执行外层查询，然后执行内层查询。不支持
+ +* **按照结果集行列数分类：** + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
分类依据子查询类型描述使用位置IoTDB 支持情况
结果集行列数标量子查询（Scalar Subquery）返回的结果集结构为一行一列。select、where、from、having支持
列子查询（Column Subquery）返回的结果集结构为 N 行一列。select、where、from、having支持
行子查询（Row Subquery）返回的结果集结构为一行 N 列。 - 不支持
表子查询（Table Subquery）返回的结果集结构为 N 行 M 列。from 支持
+ +## 3. 功能定义 + +1. 所有内层查询都需要用圆括号（）隔离，即以形如 （subquery） 的形式使用。 + +2. 非关联子查询在内层查询中不支持引用外层查询中的列，若引用则会报错： + + `Msg: org.apache.iotdb.jdbc.IoTDBSQLException： 701: Given correlated subquery is not supported` + +### 3.1 非关联标量子查询 + +标量子查询返回的结果是一个标量值，可以用于替换表达式 expression 中的操作数。 + +**语法** + +```SQL +primaryExpression + : literalExpression #Literal + | dateExpression #dateTimeExpression #dateTimeExpression + | '(' expression (',' expression)+ ')' #rowConstructor + | ROW '(' expression (',' expression)* ')' #rowConstructor + | qualifiedName '(' (label=identifier '.')? ASTERISK ')' #functionCall + | qualifiedName '(' (setQuantifier? expression (',' expression)*)?')' #functionCall +​ ​|​ ​'('​ query ​')'​ #subqueryExpression +``` + +**说明** + +标量子查询可以作为任意表达式（expression）的操作数，前提是这些输入参数在定义中未被强制规定为常量。 + +以下是一些不能使用标量子查询作为参数的例子： + +* `date_bin(interval,source,origin)` 的第一、三个参数。 +* `date_bin_gapfill(interval,source,origin)` 的第一、三个参数。 + * `interval` ：时间间隔 + * `origin`：起始时间戳 +* `Fill` 参数 + * `fill previous` + * `fill linear` + * `fill constant` + +### 3.2 非关联列子查询 + +#### 3.2.1 非关联 InPredicate + +InPredicate 是一个 predicate，其返回值是一列 boolean 值。 + +**语法** + +```SQL +predicate[ParserRuleContext value] + : comparisonOperator right=valueExpression #comparison + | comparisonOperator comparisonQuantifier '(' query ')' #quantifiedComparison + | NOT? BETWEEN lower=valueExpression AND upper=valueExpression #between + | NOT? IN '(' expression (',' expression)* ')' #inList + |​ ​NOT? ​IN​ ​'('​ query ​')'​ #inSubquery + | NOT? LIKE pattern=valueExpression (ESCAPE escape=valueExpression)? #like + | IS NOT? NULL #nullPredicate + | IS NOT? DISTINCT FROM right=valueExpression #distinctFrom + ; +``` + +**说明** + +使用形式：`X [NOT] IN (subquery)` + +* `X` 是一个表达式（expression）。 +* `NOT` 为可选，表示取反。 +* `subquery` 返回一个一列多行的结果集 `Result`。 +* 对于 `WHERE X IN (subquery)`，对于每一行 `X` 的结果，如果 `X` 在 `Result` 中，则 `SELECT` 中选取的当前行保留。 + +#### 3.2.2 非关联 Quantified Comparison + +Quantified Comparison 允许将一个值与一组值进行比较，通常由以下部分组成： + +1. 比较运算符：`<`， `>`， `=`， `<=`， `>=`， `!=` +2. 比较量词： + 1. `ALL`：所有元素 + 2. `ANY` 或 `SOME`：任意一个元素（ANY 和 SOME 是等价的） +3. 子查询：返回一个值的集合，用于与主查询中的值进行比较 + +**语法** + +```SQL +predicate[ParserRuleContext value] + : comparisonOperator right=valueExpression #comparison + |​ comparisonOperator comparisonQuantifier ​'('​ query ​')'​ #quantifiedComparison + | NOT? BETWEEN lower=valueExpression AND upper=valueExpression #between + | NOT? IN '(' expression (',' expression)* ')' #inList + | NOT? IN '(' query ')' #inSubquery + | NOT? LIKE pattern=valueExpression (ESCAPE escape=valueExpression)? #like + | IS NOT? NULL #nullPredicate + | IS NOT? DISTINCT FROM right=valueExpression #distinctFrom + ; +comparisonQuantifier + : ALL | SOME | ANY + ; +``` + +**说明** + +使用形式：`expression operator ALL/ANY/SOME (subquery)` + +* ALL：主查询中的 `expression` 与子查询返回的每一个值进行比较，所有比较都必须为 `True`，结果才为 `True`。 +* ANY/SOME：主查询中的 `expression` 与子查询返回的每一个值进行比较，任意一个比较为 `True`，结果就是 `True`。 + +## 4. 使用示例 +### 4.1 示例数据 + +s1， s2， s3， s4 分别为 INT， LONG， FLOAT， DOUBLE 类型 + +* Table1: + +```SQL +// table1 全部数据 +IoTDB> select * from table1; ++-----------------------------+--------+--------+--------+---------+------+----------------+----+-----+----+----+-----+--------------------------------+--------------------------------+------------+-----------------------------+----------+ +| time|province| city| region|device_id| color| type| s1| s2| s3| s4| s5| s6| s7| s8| s9| s10| ++-----------------------------+--------+--------+--------+---------+------+----------------+----+-----+----+----+-----+--------------------------------+--------------------------------+------------+-----------------------------+----------+ +|2024-09-24T14:15:30.000+08:00|shanghai|shanghai| pudong| d05| red| A| 30| null|30.0|null| null| shanghai_pudong_red_A_d05_30| null|0xcafebabe30|2024-09-24T14:15:30.000+08:00| null| +|2024-09-24T14:15:35.000+08:00|shanghai|shanghai| pudong| d05| red| A|null|35000|35.0|35.0| null| shanghai_pudong_red_A_d05_35| shanghai_pudong_red_A_d05_35| null|2024-09-24T14:15:35.000+08:00|2024-09-24| +|2024-09-24T14:15:40.000+08:00|shanghai|shanghai| pudong| d05| red| A| 40| null|40.0|null| true| null| shanghai_pudong_red_A_d05_40| null|2024-09-24T14:15:40.000+08:00| null| +|2024-09-24T14:15:50.000+08:00|shanghai|shanghai| pudong| d05| red| A|null|50000|null|null|false| null| null| null|2024-09-24T14:15:50.000+08:00|2024-09-24| +|2024-09-24T14:15:55.000+08:00|shanghai|shanghai| pudong| d05| red| A| 55| null|null|55.0| null| null| null|0xcafebabe55|2024-09-24T14:15:55.000+08:00| null| +|2024-09-24T14:15:31.000+08:00|shanghai|shanghai| pudong| d07|yellow| A|null|31000|null|null| null| null| null|0xcafebabe31|2024-09-24T14:15:31.000+08:00| null| +|2024-09-24T14:15:36.000+08:00|shanghai|shanghai| pudong| d07|yellow| A| 36| null|null|36.0| null| null| shanghai_pudong_yellow_A_d07_36| null|2024-09-24T14:15:36.000+08:00|2024-09-24| +|2024-09-24T14:15:41.000+08:00|shanghai|shanghai| pudong| d07|yellow| A| 41| null|41.0|null|false| shanghai_pudong_yellow_A_d07_41| null|0xcafebabe41|2024-09-24T14:15:41.000+08:00| null| +|2024-09-24T14:15:46.000+08:00|shanghai|shanghai| pudong| d07|yellow| A|null|46000|null|46.0| null| null| shanghai_pudong_yellow_A_d07_46| null|2024-09-24T14:15:46.000+08:00| null| +|2024-09-24T14:15:51.000+08:00|shanghai|shanghai| pudong| d07|yellow| A|null| null|51.0|null| null| shanghai_pudong_yellow_A_d07_51| null| null|2024-09-24T14:15:51.000+08:00| null| +|2024-09-24T14:13:30.000+08:00|shanghai|shanghai| huangpu| d01| red| A| 30| 30|30.0|30.0| true| shanghai_huangpu_red_A_d01_30| shanghai_huangpu_red_A_d01_30|0xcafebabe30|2024-09-24T14:13:00.000+08:00|2024-09-23| +|2024-09-24T14:14:30.000+08:00|shanghai|shanghai| huangpu| d01| red| A| 40| 40|40.0|40.0|false| shanghai_huangpu_red_A_d01_40| shanghai_huangpu_red_A_d01_40|0xcafebabe40|2024-09-24T14:14:00.000+08:00|2024-09-24| +|2024-09-24T14:15:30.000+08:00|shanghai|shanghai| huangpu| d01| red| A| 50| 50|50.0|50.0| true| shanghai_huangpu_red_A_d01_50| shanghai_huangpu_red_A_d01_50|0xcafebabe50|2024-09-24T14:15:00.000+08:00|2024-09-25| +|2024-09-24T14:16:30.000+08:00|shanghai|shanghai| huangpu| d01| red| A| 60| 60|60.0|60.0|false| shanghai_huangpu_red_A_d01_60| shanghai_huangpu_red_A_d01_60|0xcafebabe60|2024-09-24T14:16:00.000+08:00|2024-09-26| +|2024-09-24T14:17:30.000+08:00|shanghai|shanghai| huangpu| d01| red| A| 70| 70|70.0|70.0| true| shanghai_huangpu_red_A_d01_70| shanghai_huangpu_red_A_d01_70|0xcafebabe70|2024-09-24T14:17:00.000+08:00|2024-09-27| +|2024-09-24T14:15:31.000+08:00|shanghai|shanghai| huangpu| d03|yellow| A|null|31000|null|null| null| null| null|0xcafebabe31|2024-09-24T14:15:31.000+08:00| null| +|2024-09-24T14:15:36.000+08:00|shanghai|shanghai| huangpu| d03|yellow| A| 36| null|null|36.0| null| null|shanghai_huangpu_yellow_A_d03_36| null|2024-09-24T14:15:36.000+08:00|2024-09-24| +|2024-09-24T14:15:41.000+08:00|shanghai|shanghai| huangpu| d03|yellow| A| 41| null|41.0|null|false|shanghai_huangpu_yellow_A_d03_41| null|0xcafebabe41|2024-09-24T14:15:41.000+08:00| null| +|2024-09-24T14:15:46.000+08:00|shanghai|shanghai| huangpu| d03|yellow| A|null|46000|null|46.0| null| null|shanghai_huangpu_yellow_A_d03_46| null|2024-09-24T14:15:46.000+08:00| null| +|2024-09-24T14:15:51.000+08:00|shanghai|shanghai| huangpu| d03|yellow| A|null| null|51.0|null| null|shanghai_huangpu_yellow_A_d03_51| null| null|2024-09-24T14:15:51.000+08:00| null| +|2024-09-24T14:15:31.000+08:00| beijing| beijing|chaoyang| d11|yellow| A|null|31000|null|null| null| null| null|0xcafebabe31|2024-09-24T14:15:31.000+08:00| null| +|2024-09-24T14:15:36.000+08:00| beijing| beijing|chaoyang| d11|yellow| A| 36| null|null|36.0| null| null|beijing_chaoyang_yellow_A_d11_36| null|2024-09-24T14:15:36.000+08:00|2024-09-24| +|2024-09-24T14:15:41.000+08:00| beijing| beijing|chaoyang| d11|yellow| A| 41| null|41.0|null|false|beijing_chaoyang_yellow_A_d11_41| null|0xcafebabe41|2024-09-24T14:15:41.000+08:00| null| +|2024-09-24T14:15:46.000+08:00| beijing| beijing|chaoyang| d11|yellow| A|null|46000|null|46.0| null| null|beijing_chaoyang_yellow_A_d11_46| null|2024-09-24T14:15:46.000+08:00| null| +|2024-09-24T14:15:51.000+08:00| beijing| beijing|chaoyang| d11|yellow| A|null| null|51.0|null| null|beijing_chaoyang_yellow_A_d11_51| null| null|2024-09-24T14:15:51.000+08:00| null| +|2024-09-24T14:15:30.000+08:00| beijing| beijing|chaoyang| d09| red| A| 30| null|30.0|null| null| beijing_chaoyang_red_A_d09_30| null|0xcafebabe30|2024-09-24T14:15:30.000+08:00| null| +|2024-09-24T14:15:35.000+08:00| beijing| beijing|chaoyang| d09| red| A|null|35000|35.0|35.0| null| beijing_chaoyang_red_A_d09_35| beijing_chaoyang_red_A_d09_35| null|2024-09-24T14:15:35.000+08:00|2024-09-24| +|2024-09-24T14:15:40.000+08:00| beijing| beijing|chaoyang| d09| red| A| 40| null|40.0|null| true| null| beijing_chaoyang_red_A_d09_40| null|2024-09-24T14:15:40.000+08:00| null| +|2024-09-24T14:15:50.000+08:00| beijing| beijing|chaoyang| d09| red| A|null|50000|null|null|false| null| null| null|2024-09-24T14:15:50.000+08:00|2024-09-24| +|2024-09-24T14:15:55.000+08:00| beijing| beijing|chaoyang| d09| red| A| 55| null|null|55.0| null| null| null|0xcafebabe55|2024-09-24T14:15:55.000+08:00| null| +|2024-09-24T14:15:30.000+08:00| beijing| beijing| haidian| d13| red| A| 30| null|30.0|null| null| beijing_haidian_red_A_d13_30| null|0xcafebabe30|2024-09-24T14:15:30.000+08:00| null| +|2024-09-24T14:15:35.000+08:00| beijing| beijing| haidian| d13| red| A|null|35000|35.0|35.0| null| beijing_haidian_red_A_d13_35| beijing_haidian_red_A_d13_35| null|2024-09-24T14:15:35.000+08:00|2024-09-24| +|2024-09-24T14:15:40.000+08:00| beijing| beijing| haidian| d13| red| A| 40| null|40.0|null| true| null| beijing_haidian_red_A_d13_40| null|2024-09-24T14:15:40.000+08:00| null| +|2024-09-24T14:15:50.000+08:00| beijing| beijing| haidian| d13| red| A|null|50000|null|null|false| null| null| null|2024-09-24T14:15:50.000+08:00|2024-09-24| +|2024-09-24T14:15:55.000+08:00| beijing| beijing| haidian| d13| red| A| 55| null|null|55.0| null| null| null|0xcafebabe55|2024-09-24T14:15:55.000+08:00| null| +|2024-09-24T14:15:31.000+08:00| beijing| beijing| haidian| d15|yellow| A|null|31000|null|null| null| null| null|0xcafebabe31|2024-09-24T14:15:31.000+08:00| null| +|2024-09-24T14:15:36.000+08:00| beijing| beijing| haidian| d15|yellow| A| 36| null|null|36.0| null| null| beijing_haidian_yellow_A_d15_36| null|2024-09-24T14:15:36.000+08:00|2024-09-24| +|2024-09-24T14:15:41.000+08:00| beijing| beijing| haidian| d15|yellow| A| 41| null|41.0|null|false| beijing_haidian_yellow_A_d15_41| null|0xcafebabe41|2024-09-24T14:15:41.000+08:00| null| +|2024-09-24T14:15:46.000+08:00| beijing| beijing| haidian| d15|yellow| A|null|46000|null|46.0| null| null| beijing_haidian_yellow_A_d15_46| null|2024-09-24T14:15:46.000+08:00| null| +|2024-09-24T14:15:51.000+08:00| beijing| beijing| haidian| d15|yellow| A|null| null|51.0|null| null| beijing_haidian_yellow_A_d15_51| null| null|2024-09-24T14:15:51.000+08:00| null| +|2024-09-24T14:15:36.000+08:00|shanghai|shanghai| pudong| d06| red|BBBBBBBBBBBBBBBB| 36| null|null|null| true| shanghai_pudong_red_B_d06_36| shanghai_pudong_red_B_d06_36| null|2024-09-24T14:15:36.000+08:00| null| +|2024-09-24T14:15:40.000+08:00|shanghai|shanghai| pudong| d06| red|BBBBBBBBBBBBBBBB| 40| null|null|40.0| null| null| shanghai_pudong_red_B_d06_40| null|2024-09-24T14:15:40.000+08:00|2024-09-24| +|2024-09-24T14:15:50.000+08:00|shanghai|shanghai| pudong| d06| red|BBBBBBBBBBBBBBBB|null|50000|null|null| null| null| shanghai_pudong_red_B_d06_50|0xcafebabe50|2024-09-24T14:15:50.000+08:00| null| +|2024-09-24T14:15:30.000+08:00|shanghai|shanghai| pudong| d08|yellow|BBBBBBBBBBBBBBBB|null| null|30.0|null| true| null| shanghai_pudong_yellow_B_d08_30| null|2024-09-24T14:15:30.000+08:00|2024-09-24| +|2024-09-24T14:15:40.000+08:00|shanghai|shanghai| pudong| d08|yellow|BBBBBBBBBBBBBBBB|null|40000|null|null| null| null| null| null|2024-09-24T14:15:40.000+08:00| null| +|2024-09-24T14:15:55.000+08:00|shanghai|shanghai| pudong| d08|yellow|BBBBBBBBBBBBBBBB| 55| null|null|55.0| null| shanghai_pudong_yellow_B_d08_55| null|0xcafebabe55|2024-09-24T14:15:55.000+08:00| null| +|2024-09-24T14:15:36.000+08:00|shanghai|shanghai| huangpu| d02| red|BBBBBBBBBBBBBBBB| 36| null|null|null| true| shanghai_huangpu_red_B_d02_36| shanghai_huangpu_red_B_d02_36| null|2024-09-24T14:15:36.000+08:00| null| +|2024-09-24T14:15:40.000+08:00|shanghai|shanghai| huangpu| d02| red|BBBBBBBBBBBBBBBB| 40| null|null|40.0| null| null| shanghai_huangpu_red_B_d02_40| null|2024-09-24T14:15:40.000+08:00|2024-09-24| +|2024-09-24T14:15:50.000+08:00|shanghai|shanghai| huangpu| d02| red|BBBBBBBBBBBBBBBB|null|50000|null|null| null| null| shanghai_huangpu_red_B_d02_50|0xcafebabe50|2024-09-24T14:15:50.000+08:00| null| +|2024-09-24T14:15:30.000+08:00|shanghai|shanghai| huangpu| d04|yellow|BBBBBBBBBBBBBBBB|null| null|30.0|null| true| null|shanghai_huangpu_yellow_B_d04_30| null|2024-09-24T14:15:30.000+08:00|2024-09-24| +|2024-09-24T14:15:40.000+08:00|shanghai|shanghai| huangpu| d04|yellow|BBBBBBBBBBBBBBBB|null|40000|null|null| null| null| null| null|2024-09-24T14:15:40.000+08:00| null| +|2024-09-24T14:15:55.000+08:00|shanghai|shanghai| huangpu| d04|yellow|BBBBBBBBBBBBBBBB| 55| null|null|55.0| null|shanghai_huangpu_yellow_B_d04_55| null|0xcafebabe55|2024-09-24T14:15:55.000+08:00| null| +|2024-09-24T14:15:36.000+08:00| beijing| beijing|chaoyang| d10| red|BBBBBBBBBBBBBBBB| 36| null|null|null| true| beijing_chaoyang_red_B_d10_36| beijing_chaoyang_red_B_d10_36| null|2024-09-24T14:15:36.000+08:00| null| +|2024-09-24T14:15:40.000+08:00| beijing| beijing|chaoyang| d10| red|BBBBBBBBBBBBBBBB| 40| null|null|40.0| null| null| beijing_chaoyang_red_B_d10_40| null|2024-09-24T14:15:40.000+08:00|2024-09-24| +|2024-09-24T14:15:50.000+08:00| beijing| beijing|chaoyang| d10| red|BBBBBBBBBBBBBBBB|null|50000|null|null| null| null| beijing_chaoyang_red_B_d10_50|0xcafebabe50|2024-09-24T14:15:50.000+08:00| null| +|2024-09-24T14:15:30.000+08:00| beijing| beijing|chaoyang| d12|yellow|BBBBBBBBBBBBBBBB|null| null|30.0|null| true| null|beijing_chaoyang_yellow_B_d12_30| null|2024-09-24T14:15:30.000+08:00|2024-09-24| +|2024-09-24T14:15:40.000+08:00| beijing| beijing|chaoyang| d12|yellow|BBBBBBBBBBBBBBBB|null|40000|null|null| null| null| null| null|2024-09-24T14:15:40.000+08:00| null| +|2024-09-24T14:15:55.000+08:00| beijing| beijing|chaoyang| d12|yellow|BBBBBBBBBBBBBBBB| 55| null|null|55.0| null|beijing_chaoyang_yellow_B_d12_55| null|0xcafebabe55|2024-09-24T14:15:55.000+08:00| null| +|2024-09-24T14:15:36.000+08:00| beijing| beijing| haidian| d14| red|BBBBBBBBBBBBBBBB| 36| null|null|null| true| beijing_haidian_red_B_d14_36| beijing_haidian_red_B_d14_36| null|2024-09-24T14:15:36.000+08:00| null| +|2024-09-24T14:15:40.000+08:00| beijing| beijing| haidian| d14| red|BBBBBBBBBBBBBBBB| 40| null|null|40.0| null| null| beijing_haidian_red_B_d14_40| null|2024-09-24T14:15:40.000+08:00|2024-09-24| +|2024-09-24T14:15:50.000+08:00| beijing| beijing| haidian| d14| red|BBBBBBBBBBBBBBBB|null|50000|null|null| null| null| beijing_haidian_red_B_d14_50|0xcafebabe50|2024-09-24T14:15:50.000+08:00| null| +|2024-09-24T14:15:30.000+08:00| beijing| beijing| haidian| d16|yellow|BBBBBBBBBBBBBBBB|null| null|30.0|null| true| null| beijing_haidian_yellow_B_d16_30| null|2024-09-24T14:15:30.000+08:00|2024-09-24| +|2024-09-24T14:15:40.000+08:00| beijing| beijing| haidian| d16|yellow|BBBBBBBBBBBBBBBB|null|40000|null|null| null| null| null| null|2024-09-24T14:15:40.000+08:00| null| +|2024-09-24T14:15:55.000+08:00| beijing| beijing| haidian| d16|yellow|BBBBBBBBBBBBBBBB| 55| null|null|55.0| null| beijing_haidian_yellow_B_d16_55| null|0xcafebabe55|2024-09-24T14:15:55.000+08:00| null| ++-----------------------------+--------+--------+--------+---------+------+----------------+----+-----+----+----+-----+--------------------------------+--------------------------------+------------+-----------------------------+----------+ +Total line number = 64 +``` + +* Table2: + +```SQL +IoTDB> select * from table2 ++-----------------------------+---------+----+----+----+----+-----+-----+-------+------------+-----------------------------+----------+ +| time|device_id| s1| s2| s3| s4| s5| s6| s7| s8| s9| s10| ++-----------------------------+---------+----+----+----+----+-----+-----+-------+------------+-----------------------------+----------+ +|1970-01-01T08:00:00.001+08:00| d1| 1| 11| 1.1|11.1| true|text1|string1|0xcafebabe01|1970-01-01T08:00:00.001+08:00|2024-10-01| +|1970-01-01T08:00:00.002+08:00| d1| 2| 22| 2.2|22.2|false| null| null| null| null| null| +|1970-01-01T08:00:00.003+08:00| d1|null|null|null|null| null|text3|string3|0xcafebabe03|1970-01-01T08:00:00.003+08:00|2024-10-03| +|1970-01-01T08:00:00.004+08:00| d1|null|null|null|null| null|text4|string4|0xcafebabe04|1970-01-01T08:00:00.004+08:00|2024-10-04| +|1970-01-01T08:00:00.005+08:00| d1| 5| 55| 5.5|55.5|false| null| null| null| null| null| ++-----------------------------+---------+----+----+----+----+-----+-----+-------+------------+-----------------------------+----------+ +Total line number = 5 +``` + +* Table3: 包含 null 值 + +```SQL +IoTDB> select device_id, s1 from table3; ++---------+----+ +|device_id| s1| ++---------+----+ +| d_null| 30| +| d_null|null| +| d01| 30| +| d01| 40| ++---------+----+ +Total line number = 4 +``` + +> From 子句中子查询使用示例可参考[FROM & JOIN 子句](../SQL-Manual/From-Join-Clause.md)，下文中主要介绍 Where、Having、Select 子句中的使用示例。 + +### 4.2 非关联标量子查询 + +**Where 子句** + +从 table1 中找出设备编号为`d01`的所有记录中，数值 s1 大于或等于该设备 s1 数值平均值的记录。 + +SQL: + +```SQL +IoTDB> SELECT s1 FROM table1 + WHERE device_id = 'd01' + and s1 >= (SELECT avg(s1) from table1 WHERE device_id = 'd01'); +``` + +结果： + +```SQL ++--+ +|s1| ++--+ +|50| +|60| +|70| ++--+ +Total line number = 3 +``` + +**Having 子句** + +统计 table1 中按设备编号（device\_id）分组，每个设备编号的记录数，找出记录数不少于 table2 中设备`d1`记录数的所有设备及其记录数。 + +SQL: + +```SQL +IoTDB> SELECT device_id, count(*) + from table1 group by device_id + having count(*) >= (SELECT count(*) from table2 where device_id = 'd1'); +``` + +结果： + +```SQL ++---------+-----+ +|device_id|_col1| ++---------+-----+ +| d01| 5| +| d03| 5| +| d05| 5| +| d07| 5| +| d09| 5| +| d11| 5| +| d13| 5| +| d15| 5| ++---------+-----+ +Total line number = 8 +``` + +**Select 子句** + +从 table1 中选择设备编号为`d01`的所有记录，把每个记录的 s1 字段值与子查询得到的结果（即同一设备编号下 s2 字段的最大值）相加，返回计算后的新字段值。 + +SQL: + +```SQL +IoTDB> SELECT s1 + + (SELECT max(s2) from table1 where device_id = 'd01') + from table1 where device_id = 'd01'; +``` + +结果： + +```SQL ++-----+ +|_col0| ++-----+ +| 100| +| 110| +| 120| +| 130| +| 140| ++-----+ +Total line number = 5 +``` + +**特殊情况** + +* 如果非聚合子查询返回的结果集刚好只有一行，也可以认为是标量子查询： + +```SQL +// 子查询返回的值为 1，结果集为空集 +IoTDB> SELECT s1 FROM table1 + WHERE device_id = 'd01' and + s1 = (SELECT s1 FROM table2 limit 1); +``` + +> 如果返回的值不止一行，则会报错 + +* 在 SELECT 子句中作为单独的一列时，可以认为和 select 一个常量列等价，结果集形式为标量子查询结果重复 X 次，X 等于外层查询的结果集行数。 + +SQL: + +```SQL +// 外层查询为 SELECT xx from table1 where device_id = 'd01'， +// 而 SELECT count(*) from table1 where device_id = 'd01' 的结果是5，即结果集有五行 + +IoTDB> SELECT + (SELECT max(s1) from table1 where device_id = 'd01') + from table1 where device_id = 'd01'; +``` + +结果： + +```SQL ++-----+ +|_col0| ++-----+ +| 70| +| 70| +| 70| +| 70| +| 70| ++-----+ +Total line number = 5 +``` + +### 4.3 非关联列子查询 + +#### 4.3.1 非关联 InPredicate + +**Where 子句** + +从`table1`中找出设备编号为`d01`，并且其`s1`值也出现在`table3`中相同设备编号`d01`的记录里的所有`s1`值。 + +SQL: + +```SQL +IoTDB> SELECT s1 FROM table1 + WHERE device_id = 'd01' and + s1 in (SELECT s1 from table3 WHERE device_id = 'd01'); +``` + +结果： + +```SQL ++--+ +|s1| ++--+ +|30| +|40| ++--+ +Total line number = 2 +``` + +**Having 子句** + +从`table1`表中按`device_id`（设备编号）分组，计算每个设备编号的记录数，找出分组记录数加上 25 后，其结果值出现在`table3`表中设备编号为'd01'的`s1`字段值中的所有设备编号及其对应的记录数。 + +SQL: + +```SQL +IoTDB> SELECT device_id, count(*) from table1 + group by device_id + having count(*) + 25 + in (SELECT cast(s1 as INT64) from table3 where device_id = 'd01'); +``` + +结果： + +```SQL ++---------+-----+ +|device_id|_col1| ++---------+-----+ +| d01| 5| +| d03| 5| +| d05| 5| +| d07| 5| +| d09| 5| +| d11| 5| +| d13| 5| +| d15| 5| ++---------+-----+ +Total line number = 8 +``` + +**Select 子句** + +从`table1`中选择设备编号为`d01`的记录，检查这些记录的`s1`字段值是否存在于`table3`中相同设备编号`d01`的`s1`字段值中。 + +SQL: + +```SQL +IoTDB> SELECT + s1 in (SELECT s1 from table3 WHERE device_id = 'd01') + from table1 where device_id = 'd01'; +``` + +结果： + +```SQL ++-----+ +|_col0| ++-----+ +| true| +| true| +|false| +|false| +|false| ++-----+ +Total line number = 5 +``` + +**特殊情况** + +在 select 子句中使用 InPredicate 时（select x [not] in （subquery） from table），结果规则总结为： + +* 当前行 x 为 null，结果行为 null +* 当前行 x 不为 null + * 无 NOT + * x 在 subquery 结果集中则当前行结果为 True + * x 不在 subquery 结果集中 + * 如果 subquery 结果集包含 null，则当前行结果为 null，否则为 False + * 有 NOT + * x 在 subquery 结果集中则当前行结果为 False + * x 不在 subquery 结果集中 + * 如果 subquery 结果集包含 null，则当前行结果为 null，否则为 True + +示例 1：X 结果集包含 null + +```SQL +IoTDB> select s1 from table3; ++----+ +| s1| ++----+ +| 30| +|null| +| 30| +| 40| ++----+ +Total line number = 4 + +IoTDB> select s1 from table3 where s1 in (select s1 from table3); ++--+ +|s1| ++--+ +|30| +|30| +|40| ++--+ +Total line number = 3 +``` + +示例 2：在 select 子句里面使用，对应的行的结果是 null + +```SQL +IoTDB> select device_id, s1 in (select s1 from table1 where device_id = 'd01'), s1 from table3 ; ++---------+-----+----+ +|device_id|_col1| s1| ++---------+-----+----+ +| d_null| true| 30| +| d01| true| 30| +| d01| true| 40| +| d_null| null|null| ++---------+-----+----+ +``` + +示例 3：子查询结果集包含 null + +```SQL +IoTDB> select s1 from table1 where device_id = 'd02' ++----+ +| s1| ++----+ +| 36| +| 40| +|null| ++----+ +Total line number = 3 + +IoTDB> select s1 from table3; ++----+ +| s1| ++----+ +| 30| +|null| +| 30| +| 40| ++----+ +Total line number = 4 +``` + +示例 4：在 where 子句中使用，即 where s1 in （subquery），结果集只包含 40 一行 + +```SQL +IoTDB> select s1 from table1 where device_id = 'd02' and s1 in (select s1 from table3); ++--+ +|s1| ++--+ +|40| ++--+ +Total line number = 1 +``` + +示例 5：在 select 子句中使用，s1 的结果集为 （36， 40， null），subquery 的结果集为（30， 40， null），由于 36 与非 null 的两个结果 30 和 40 不相等，且 subquery 的结果集包含 null，所以对应的结果是 null + +```SQL +IoTDB> SELECT +> s1 in (SELECT s1 from table3) from table1 +> where device_id = 'd02' ++-----+ +|_col0| ++-----+ +| null| +| true| +| null| ++-----+ +Total line number = 3 +``` + +#### 4.3.2 非关联 QuantifiedComparison + +**Where 子句** + +* ALL + +从`table1`表中找出设备编号为`d01`的记录，并且`s1`字段值要大于`table3`表中同样设备编号的所有`s1`字段值。 + +SQL: + +```SQL +IoTDB> SELECT s1 FROM table1 + WHERE device_id = 'd01' and + s1 > all (SELECT s1 FROM table3 WHERE device_id = 'd01'); +``` + +结果： + +```SQL ++--+ +|s1| ++--+ +|50| +|60| +|70| ++--+ +Total line number = 3 +``` + +* ANY/SOME + +从`table1`表中找出设备编号为`d01`的记录，并且`s1`字段值要大于`table3`表中同样设备编号的任意一条记录的`s1`字段值。 + +SQL: + +```SQL +IoTDB> SELECT s1 FROM table1 + WHERE device_id = 'd01' and + s1 > any (SELECT s1 FROM table1 WHERE device_id = 'd01'); +``` + +结果： + +```SQL ++--+ +|s1| ++--+ +|40| +|50| +|60| +|70| ++--+ +Total line number = 4 +``` + +**Having 子句** + +* ALL + +从`table1`中按`device_id`（设备编号）分组，计算每个设备编号的记录数量，找出分组记录数加上 35 后，大于或等于`table3`中设备编号为`d01`的所有`s1`字段值（转换为整数类型）的设备编号及其对应的记录数。 + +SQL: + +```SQL +IoTDB> SELECT device_id, count(*) from table1 + group by device_id + having count(*) + 35 >= + all(SELECT cast(s1 as INT64) from table3 where device_id = 'd01'); +``` + +结果： + +```SQL ++---------+-----+ +|device_id|_col1| ++---------+-----+ +| d01| 5| +| d03| 5| +| d05| 5| +| d07| 5| +| d09| 5| +| d11| 5| +| d13| 5| +| d15| 5| ++---------+-----+ +Total line number = 8 +``` + +* ANY/SOME + +从`table1`中按`device_id`（设备编号）分组，计算每个设备编号的记录数量，找出分组记录数加上 35 后，大于或等于`table3`中设备编号为`d01`的任意一条记录`s1`字段值（转换为整数类型）的设备编号及其对应的记录数。 + +SQL: + +```SQL +IoTDB> SELECT device_id, count(*) + from table1 group by device_id + having count(*) + 25 >= + any(SELECT cast(s1 as INT64) from table3 where device_id = 'd01'); +``` + +结果： + +```SQL ++---------+-----+ +|device_id|_col1| ++---------+-----+ +| d01| 5| +| d03| 5| +| d05| 5| +| d07| 5| +| d09| 5| +| d11| 5| +| d13| 5| +| d15| 5| ++---------+-----+ +Total line number = 8 +``` + +**Select 子句** + +* ALL + +从`table1`中选择设备编号为`d01`的记录，并且`s1`字段值要大于`table3`表中设备编号为`d01`的所有`s1`字段值。 + +SQL: + +```SQL +IoTDB> SELECT s1 > + all(SELECT (s1) from table3 WHERE device_id = 'd01') + from table1 where device_id = 'd01'; +``` + +结果： + +```SQL ++-----+ +|_col0| ++-----+ +|false| +|false| +| true| +| true| +| true| ++-----+ +Total line number = 5 +``` + +* ANY/SOME + +从`table1`中选择设备编号为`d01`的记录，并且`s1`字段值要大于`table3`表中设备编号为`d01`的任意一条记`s1`字段值。 + +SQL: + +```SQL +IoTDB> SELECT s1 > + any(SELECT (s1) from table3 WHERE device_id = 'd01') + from table1 where device_id = 'd01'; +``` + +结果： + +```SQL ++-----+ +|_col0| ++-----+ +|false| +| true| +| true| +| true| +| true| ++-----+ +Total line number = 5 +``` + +**特殊情况** + +ALL 要求所有比较都为 True 结果才为 True + +ANY/SOME 要求任意比较为 True 结果就为 True + +示例 1：ALL + +```SQL +IoTDB> select s1 from table1 where device_id = 'd01' ++--+ +|s1| ++--+ +|30| +|40| +|50| +|60| +|70| ++--+ +Total line number = 5 + +IoTDB> select s1 from table3; ++----+ +| s1| ++----+ +| 30| +|null| +| 30| +| 40| ++----+ + +IoTDB> select (s1 > all(select s1 from table3)) from table1 where device_id = 'd01'; ++-----+ +|_col0| ++-----+ +|false| +|false| +| null| +| null| +| null| ++-----+ +``` + +说明： + +* `table1s1` 的 30，40 两行，由于 `table3 s1` 的非 `null` 结果集 （30， 40） 让 30 > 40/ 40 > 40 为 `False` ，即短路求值，结果是 `false`。 +* 对于 50，60，70 三个值，由于 ALL 要求的是所有比较结果都是 `True` 结果才是 `True`， 50，60，70 与 `null` 的比较都是 `null`，结果是 `null`。 + +示例 2：ANY/SOME + +```SQL +IoTDB> SELECT s1 <= + any(SELECT (s1) from table3), s1 <= any(SELECT (s1) from table3 where s1 is not NULL) + from table1 where device_id = 'd01' ++-----+-----+ +|_col0|_col1| ++-----+-----+ +| true| true| +| true| true| +| null|false| +| null|false| +| null|false| ++-----+-----+ +``` + +说明： + +* 对于`table1`中的 30 和 40，由于 `table3 s1` 的非 null 结果集 （30， 40），使得比较结果为`true`（成立）。 +* 对于 50、60、70，由于`ANY`要求的是至少一个比较结果为`true`结果就是`true`，而与`null`的比较结果为`null`，所以这些结果为`null`。 +* 在第二个查询中，由于我们排除了空值，所以对于 50、60、70，由于`table3`中没有更大的非空值，比较结果为`false`。 + diff --git a/src/zh/UserGuide/latest-Table/SQL-Manual/Nested-Queries.md b/src/zh/UserGuide/latest-Table/SQL-Manual/Nested-Queries.md new file mode 100644 index 000000000..c855fbfb3 --- /dev/null +++ b/src/zh/UserGuide/latest-Table/SQL-Manual/Nested-Queries.md @@ -0,0 +1,875 @@ + + +# 嵌套查询 + +## 1. 概述 + +嵌套查询又被称为子查询，是指一个查询语句内部包含另一个或多个查询语句。嵌套查询由内层查询和外层查询组成。 + +## 2. 嵌套查询分类 + +嵌套查询可以按照以下两种依据进行分类：按是否引用外层查询分类、按结果集行列数分类。 + +* **按是否引用外层查询分类：** + + + + + + + + + + + + + + + + + + + + +
分类依据嵌套查询类型描述IoTDB 支持情况
是否引用外层查询非关联子查询内层查询的执行和外层查询的执行是独立的，内层查询仅执行一次，执行完毕后将结果作为外层查询的条件使用。支持
关联子查询内层查询中使用到了外层查询的表中某些列，需要先执行外层查询，然后执行内层查询。不支持
+ +* **按照结果集行列数分类：** + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
分类依据子查询类型描述使用位置IoTDB 支持情况
结果集行列数标量子查询（Scalar Subquery）返回的结果集结构为一行一列。select、where、from、having支持
列子查询（Column Subquery）返回的结果集结构为 N 行一列。select、where、from、having支持
行子查询（Row Subquery）返回的结果集结构为一行 N 列。 - 不支持
表子查询（Table Subquery）返回的结果集结构为 N 行 M 列。from 支持
+ +## 3. 功能定义 + +1. 所有内层查询都需要用圆括号（）隔离，即以形如 （subquery） 的形式使用。 + +2. 非关联子查询在内层查询中不支持引用外层查询中的列，若引用则会报错： + + `Msg: org.apache.iotdb.jdbc.IoTDBSQLException： 701: Given correlated subquery is not supported` + +### 3.1 非关联标量子查询 + +标量子查询返回的结果是一个标量值，可以用于替换表达式 expression 中的操作数。 + +**语法** + +```SQL +primaryExpression + : literalExpression #Literal + | dateExpression #dateTimeExpression #dateTimeExpression + | '(' expression (',' expression)+ ')' #rowConstructor + | ROW '(' expression (',' expression)* ')' #rowConstructor + | qualifiedName '(' (label=identifier '.')? ASTERISK ')' #functionCall + | qualifiedName '(' (setQuantifier? expression (',' expression)*)?')' #functionCall +​ ​|​ ​'('​ query ​')'​ #subqueryExpression +``` + +**说明** + +标量子查询可以作为任意表达式（expression）的操作数，前提是这些输入参数在定义中未被强制规定为常量。 + +以下是一些不能使用标量子查询作为参数的例子： + +* `date_bin(interval,source,origin)` 的第一、三个参数。 +* `date_bin_gapfill(interval,source,origin)` 的第一、三个参数。 + * `interval` ：时间间隔 + * `origin`：起始时间戳 +* `Fill` 参数 + * `fill previous` + * `fill linear` + * `fill constant` + +### 3.2 非关联列子查询 + +#### 3.2.1 非关联 InPredicate + +InPredicate 是一个 predicate，其返回值是一列 boolean 值。 + +**语法** + +```SQL +predicate[ParserRuleContext value] + : comparisonOperator right=valueExpression #comparison + | comparisonOperator comparisonQuantifier '(' query ')' #quantifiedComparison + | NOT? BETWEEN lower=valueExpression AND upper=valueExpression #between + | NOT? IN '(' expression (',' expression)* ')' #inList + |​ ​NOT? ​IN​ ​'('​ query ​')'​ #inSubquery + | NOT? LIKE pattern=valueExpression (ESCAPE escape=valueExpression)? #like + | IS NOT? NULL #nullPredicate + | IS NOT? DISTINCT FROM right=valueExpression #distinctFrom + ; +``` + +**说明** + +使用形式：`X [NOT] IN (subquery)` + +* `X` 是一个表达式（expression）。 +* `NOT` 为可选，表示取反。 +* `subquery` 返回一个一列多行的结果集 `Result`。 +* 对于 `WHERE X IN (subquery)`，对于每一行 `X` 的结果，如果 `X` 在 `Result` 中，则 `SELECT` 中选取的当前行保留。 + +#### 3.2.2 非关联 Quantified Comparison + +Quantified Comparison 允许将一个值与一组值进行比较，通常由以下部分组成： + +1. 比较运算符：`<`， `>`， `=`， `<=`， `>=`， `!=` +2. 比较量词： + 1. `ALL`：所有元素 + 2. `ANY` 或 `SOME`：任意一个元素（ANY 和 SOME 是等价的） +3. 子查询：返回一个值的集合，用于与主查询中的值进行比较 + +**语法** + +```SQL +predicate[ParserRuleContext value] + : comparisonOperator right=valueExpression #comparison + |​ comparisonOperator comparisonQuantifier ​'('​ query ​')'​ #quantifiedComparison + | NOT? BETWEEN lower=valueExpression AND upper=valueExpression #between + | NOT? IN '(' expression (',' expression)* ')' #inList + | NOT? IN '(' query ')' #inSubquery + | NOT? LIKE pattern=valueExpression (ESCAPE escape=valueExpression)? #like + | IS NOT? NULL #nullPredicate + | IS NOT? DISTINCT FROM right=valueExpression #distinctFrom + ; +comparisonQuantifier + : ALL | SOME | ANY + ; +``` + +**说明** + +使用形式：`expression operator ALL/ANY/SOME (subquery)` + +* ALL：主查询中的 `expression` 与子查询返回的每一个值进行比较，所有比较都必须为 `True`，结果才为 `True`。 +* ANY/SOME：主查询中的 `expression` 与子查询返回的每一个值进行比较，任意一个比较为 `True`，结果就是 `True`。 + +## 4. 使用示例 +### 4.1 示例数据 + +s1， s2， s3， s4 分别为 INT， LONG， FLOAT， DOUBLE 类型 + +* Table1: + +```SQL +// table1 全部数据 +IoTDB> select * from table1; ++-----------------------------+--------+--------+--------+---------+------+----------------+----+-----+----+----+-----+--------------------------------+--------------------------------+------------+-----------------------------+----------+ +| time|province| city| region|device_id| color| type| s1| s2| s3| s4| s5| s6| s7| s8| s9| s10| ++-----------------------------+--------+--------+--------+---------+------+----------------+----+-----+----+----+-----+--------------------------------+--------------------------------+------------+-----------------------------+----------+ +|2024-09-24T14:15:30.000+08:00|shanghai|shanghai| pudong| d05| red| A| 30| null|30.0|null| null| shanghai_pudong_red_A_d05_30| null|0xcafebabe30|2024-09-24T14:15:30.000+08:00| null| +|2024-09-24T14:15:35.000+08:00|shanghai|shanghai| pudong| d05| red| A|null|35000|35.0|35.0| null| shanghai_pudong_red_A_d05_35| shanghai_pudong_red_A_d05_35| null|2024-09-24T14:15:35.000+08:00|2024-09-24| +|2024-09-24T14:15:40.000+08:00|shanghai|shanghai| pudong| d05| red| A| 40| null|40.0|null| true| null| shanghai_pudong_red_A_d05_40| null|2024-09-24T14:15:40.000+08:00| null| +|2024-09-24T14:15:50.000+08:00|shanghai|shanghai| pudong| d05| red| A|null|50000|null|null|false| null| null| null|2024-09-24T14:15:50.000+08:00|2024-09-24| +|2024-09-24T14:15:55.000+08:00|shanghai|shanghai| pudong| d05| red| A| 55| null|null|55.0| null| null| null|0xcafebabe55|2024-09-24T14:15:55.000+08:00| null| +|2024-09-24T14:15:31.000+08:00|shanghai|shanghai| pudong| d07|yellow| A|null|31000|null|null| null| null| null|0xcafebabe31|2024-09-24T14:15:31.000+08:00| null| +|2024-09-24T14:15:36.000+08:00|shanghai|shanghai| pudong| d07|yellow| A| 36| null|null|36.0| null| null| shanghai_pudong_yellow_A_d07_36| null|2024-09-24T14:15:36.000+08:00|2024-09-24| +|2024-09-24T14:15:41.000+08:00|shanghai|shanghai| pudong| d07|yellow| A| 41| null|41.0|null|false| shanghai_pudong_yellow_A_d07_41| null|0xcafebabe41|2024-09-24T14:15:41.000+08:00| null| +|2024-09-24T14:15:46.000+08:00|shanghai|shanghai| pudong| d07|yellow| A|null|46000|null|46.0| null| null| shanghai_pudong_yellow_A_d07_46| null|2024-09-24T14:15:46.000+08:00| null| +|2024-09-24T14:15:51.000+08:00|shanghai|shanghai| pudong| d07|yellow| A|null| null|51.0|null| null| shanghai_pudong_yellow_A_d07_51| null| null|2024-09-24T14:15:51.000+08:00| null| +|2024-09-24T14:13:30.000+08:00|shanghai|shanghai| huangpu| d01| red| A| 30| 30|30.0|30.0| true| shanghai_huangpu_red_A_d01_30| shanghai_huangpu_red_A_d01_30|0xcafebabe30|2024-09-24T14:13:00.000+08:00|2024-09-23| +|2024-09-24T14:14:30.000+08:00|shanghai|shanghai| huangpu| d01| red| A| 40| 40|40.0|40.0|false| shanghai_huangpu_red_A_d01_40| shanghai_huangpu_red_A_d01_40|0xcafebabe40|2024-09-24T14:14:00.000+08:00|2024-09-24| +|2024-09-24T14:15:30.000+08:00|shanghai|shanghai| huangpu| d01| red| A| 50| 50|50.0|50.0| true| shanghai_huangpu_red_A_d01_50| shanghai_huangpu_red_A_d01_50|0xcafebabe50|2024-09-24T14:15:00.000+08:00|2024-09-25| +|2024-09-24T14:16:30.000+08:00|shanghai|shanghai| huangpu| d01| red| A| 60| 60|60.0|60.0|false| shanghai_huangpu_red_A_d01_60| shanghai_huangpu_red_A_d01_60|0xcafebabe60|2024-09-24T14:16:00.000+08:00|2024-09-26| +|2024-09-24T14:17:30.000+08:00|shanghai|shanghai| huangpu| d01| red| A| 70| 70|70.0|70.0| true| shanghai_huangpu_red_A_d01_70| shanghai_huangpu_red_A_d01_70|0xcafebabe70|2024-09-24T14:17:00.000+08:00|2024-09-27| +|2024-09-24T14:15:31.000+08:00|shanghai|shanghai| huangpu| d03|yellow| A|null|31000|null|null| null| null| null|0xcafebabe31|2024-09-24T14:15:31.000+08:00| null| +|2024-09-24T14:15:36.000+08:00|shanghai|shanghai| huangpu| d03|yellow| A| 36| null|null|36.0| null| null|shanghai_huangpu_yellow_A_d03_36| null|2024-09-24T14:15:36.000+08:00|2024-09-24| +|2024-09-24T14:15:41.000+08:00|shanghai|shanghai| huangpu| d03|yellow| A| 41| null|41.0|null|false|shanghai_huangpu_yellow_A_d03_41| null|0xcafebabe41|2024-09-24T14:15:41.000+08:00| null| +|2024-09-24T14:15:46.000+08:00|shanghai|shanghai| huangpu| d03|yellow| A|null|46000|null|46.0| null| null|shanghai_huangpu_yellow_A_d03_46| null|2024-09-24T14:15:46.000+08:00| null| +|2024-09-24T14:15:51.000+08:00|shanghai|shanghai| huangpu| d03|yellow| A|null| null|51.0|null| null|shanghai_huangpu_yellow_A_d03_51| null| null|2024-09-24T14:15:51.000+08:00| null| +|2024-09-24T14:15:31.000+08:00| beijing| beijing|chaoyang| d11|yellow| A|null|31000|null|null| null| null| null|0xcafebabe31|2024-09-24T14:15:31.000+08:00| null| +|2024-09-24T14:15:36.000+08:00| beijing| beijing|chaoyang| d11|yellow| A| 36| null|null|36.0| null| null|beijing_chaoyang_yellow_A_d11_36| null|2024-09-24T14:15:36.000+08:00|2024-09-24| +|2024-09-24T14:15:41.000+08:00| beijing| beijing|chaoyang| d11|yellow| A| 41| null|41.0|null|false|beijing_chaoyang_yellow_A_d11_41| null|0xcafebabe41|2024-09-24T14:15:41.000+08:00| null| +|2024-09-24T14:15:46.000+08:00| beijing| beijing|chaoyang| d11|yellow| A|null|46000|null|46.0| null| null|beijing_chaoyang_yellow_A_d11_46| null|2024-09-24T14:15:46.000+08:00| null| +|2024-09-24T14:15:51.000+08:00| beijing| beijing|chaoyang| d11|yellow| A|null| null|51.0|null| null|beijing_chaoyang_yellow_A_d11_51| null| null|2024-09-24T14:15:51.000+08:00| null| +|2024-09-24T14:15:30.000+08:00| beijing| beijing|chaoyang| d09| red| A| 30| null|30.0|null| null| beijing_chaoyang_red_A_d09_30| null|0xcafebabe30|2024-09-24T14:15:30.000+08:00| null| +|2024-09-24T14:15:35.000+08:00| beijing| beijing|chaoyang| d09| red| A|null|35000|35.0|35.0| null| beijing_chaoyang_red_A_d09_35| beijing_chaoyang_red_A_d09_35| null|2024-09-24T14:15:35.000+08:00|2024-09-24| +|2024-09-24T14:15:40.000+08:00| beijing| beijing|chaoyang| d09| red| A| 40| null|40.0|null| true| null| beijing_chaoyang_red_A_d09_40| null|2024-09-24T14:15:40.000+08:00| null| +|2024-09-24T14:15:50.000+08:00| beijing| beijing|chaoyang| d09| red| A|null|50000|null|null|false| null| null| null|2024-09-24T14:15:50.000+08:00|2024-09-24| +|2024-09-24T14:15:55.000+08:00| beijing| beijing|chaoyang| d09| red| A| 55| null|null|55.0| null| null| null|0xcafebabe55|2024-09-24T14:15:55.000+08:00| null| +|2024-09-24T14:15:30.000+08:00| beijing| beijing| haidian| d13| red| A| 30| null|30.0|null| null| beijing_haidian_red_A_d13_30| null|0xcafebabe30|2024-09-24T14:15:30.000+08:00| null| +|2024-09-24T14:15:35.000+08:00| beijing| beijing| haidian| d13| red| A|null|35000|35.0|35.0| null| beijing_haidian_red_A_d13_35| beijing_haidian_red_A_d13_35| null|2024-09-24T14:15:35.000+08:00|2024-09-24| +|2024-09-24T14:15:40.000+08:00| beijing| beijing| haidian| d13| red| A| 40| null|40.0|null| true| null| beijing_haidian_red_A_d13_40| null|2024-09-24T14:15:40.000+08:00| null| +|2024-09-24T14:15:50.000+08:00| beijing| beijing| haidian| d13| red| A|null|50000|null|null|false| null| null| null|2024-09-24T14:15:50.000+08:00|2024-09-24| +|2024-09-24T14:15:55.000+08:00| beijing| beijing| haidian| d13| red| A| 55| null|null|55.0| null| null| null|0xcafebabe55|2024-09-24T14:15:55.000+08:00| null| +|2024-09-24T14:15:31.000+08:00| beijing| beijing| haidian| d15|yellow| A|null|31000|null|null| null| null| null|0xcafebabe31|2024-09-24T14:15:31.000+08:00| null| +|2024-09-24T14:15:36.000+08:00| beijing| beijing| haidian| d15|yellow| A| 36| null|null|36.0| null| null| beijing_haidian_yellow_A_d15_36| null|2024-09-24T14:15:36.000+08:00|2024-09-24| +|2024-09-24T14:15:41.000+08:00| beijing| beijing| haidian| d15|yellow| A| 41| null|41.0|null|false| beijing_haidian_yellow_A_d15_41| null|0xcafebabe41|2024-09-24T14:15:41.000+08:00| null| +|2024-09-24T14:15:46.000+08:00| beijing| beijing| haidian| d15|yellow| A|null|46000|null|46.0| null| null| beijing_haidian_yellow_A_d15_46| null|2024-09-24T14:15:46.000+08:00| null| +|2024-09-24T14:15:51.000+08:00| beijing| beijing| haidian| d15|yellow| A|null| null|51.0|null| null| beijing_haidian_yellow_A_d15_51| null| null|2024-09-24T14:15:51.000+08:00| null| +|2024-09-24T14:15:36.000+08:00|shanghai|shanghai| pudong| d06| red|BBBBBBBBBBBBBBBB| 36| null|null|null| true| shanghai_pudong_red_B_d06_36| shanghai_pudong_red_B_d06_36| null|2024-09-24T14:15:36.000+08:00| null| +|2024-09-24T14:15:40.000+08:00|shanghai|shanghai| pudong| d06| red|BBBBBBBBBBBBBBBB| 40| null|null|40.0| null| null| shanghai_pudong_red_B_d06_40| null|2024-09-24T14:15:40.000+08:00|2024-09-24| +|2024-09-24T14:15:50.000+08:00|shanghai|shanghai| pudong| d06| red|BBBBBBBBBBBBBBBB|null|50000|null|null| null| null| shanghai_pudong_red_B_d06_50|0xcafebabe50|2024-09-24T14:15:50.000+08:00| null| +|2024-09-24T14:15:30.000+08:00|shanghai|shanghai| pudong| d08|yellow|BBBBBBBBBBBBBBBB|null| null|30.0|null| true| null| shanghai_pudong_yellow_B_d08_30| null|2024-09-24T14:15:30.000+08:00|2024-09-24| +|2024-09-24T14:15:40.000+08:00|shanghai|shanghai| pudong| d08|yellow|BBBBBBBBBBBBBBBB|null|40000|null|null| null| null| null| null|2024-09-24T14:15:40.000+08:00| null| +|2024-09-24T14:15:55.000+08:00|shanghai|shanghai| pudong| d08|yellow|BBBBBBBBBBBBBBBB| 55| null|null|55.0| null| shanghai_pudong_yellow_B_d08_55| null|0xcafebabe55|2024-09-24T14:15:55.000+08:00| null| +|2024-09-24T14:15:36.000+08:00|shanghai|shanghai| huangpu| d02| red|BBBBBBBBBBBBBBBB| 36| null|null|null| true| shanghai_huangpu_red_B_d02_36| shanghai_huangpu_red_B_d02_36| null|2024-09-24T14:15:36.000+08:00| null| +|2024-09-24T14:15:40.000+08:00|shanghai|shanghai| huangpu| d02| red|BBBBBBBBBBBBBBBB| 40| null|null|40.0| null| null| shanghai_huangpu_red_B_d02_40| null|2024-09-24T14:15:40.000+08:00|2024-09-24| +|2024-09-24T14:15:50.000+08:00|shanghai|shanghai| huangpu| d02| red|BBBBBBBBBBBBBBBB|null|50000|null|null| null| null| shanghai_huangpu_red_B_d02_50|0xcafebabe50|2024-09-24T14:15:50.000+08:00| null| +|2024-09-24T14:15:30.000+08:00|shanghai|shanghai| huangpu| d04|yellow|BBBBBBBBBBBBBBBB|null| null|30.0|null| true| null|shanghai_huangpu_yellow_B_d04_30| null|2024-09-24T14:15:30.000+08:00|2024-09-24| +|2024-09-24T14:15:40.000+08:00|shanghai|shanghai| huangpu| d04|yellow|BBBBBBBBBBBBBBBB|null|40000|null|null| null| null| null| null|2024-09-24T14:15:40.000+08:00| null| +|2024-09-24T14:15:55.000+08:00|shanghai|shanghai| huangpu| d04|yellow|BBBBBBBBBBBBBBBB| 55| null|null|55.0| null|shanghai_huangpu_yellow_B_d04_55| null|0xcafebabe55|2024-09-24T14:15:55.000+08:00| null| +|2024-09-24T14:15:36.000+08:00| beijing| beijing|chaoyang| d10| red|BBBBBBBBBBBBBBBB| 36| null|null|null| true| beijing_chaoyang_red_B_d10_36| beijing_chaoyang_red_B_d10_36| null|2024-09-24T14:15:36.000+08:00| null| +|2024-09-24T14:15:40.000+08:00| beijing| beijing|chaoyang| d10| red|BBBBBBBBBBBBBBBB| 40| null|null|40.0| null| null| beijing_chaoyang_red_B_d10_40| null|2024-09-24T14:15:40.000+08:00|2024-09-24| +|2024-09-24T14:15:50.000+08:00| beijing| beijing|chaoyang| d10| red|BBBBBBBBBBBBBBBB|null|50000|null|null| null| null| beijing_chaoyang_red_B_d10_50|0xcafebabe50|2024-09-24T14:15:50.000+08:00| null| +|2024-09-24T14:15:30.000+08:00| beijing| beijing|chaoyang| d12|yellow|BBBBBBBBBBBBBBBB|null| null|30.0|null| true| null|beijing_chaoyang_yellow_B_d12_30| null|2024-09-24T14:15:30.000+08:00|2024-09-24| +|2024-09-24T14:15:40.000+08:00| beijing| beijing|chaoyang| d12|yellow|BBBBBBBBBBBBBBBB|null|40000|null|null| null| null| null| null|2024-09-24T14:15:40.000+08:00| null| +|2024-09-24T14:15:55.000+08:00| beijing| beijing|chaoyang| d12|yellow|BBBBBBBBBBBBBBBB| 55| null|null|55.0| null|beijing_chaoyang_yellow_B_d12_55| null|0xcafebabe55|2024-09-24T14:15:55.000+08:00| null| +|2024-09-24T14:15:36.000+08:00| beijing| beijing| haidian| d14| red|BBBBBBBBBBBBBBBB| 36| null|null|null| true| beijing_haidian_red_B_d14_36| beijing_haidian_red_B_d14_36| null|2024-09-24T14:15:36.000+08:00| null| +|2024-09-24T14:15:40.000+08:00| beijing| beijing| haidian| d14| red|BBBBBBBBBBBBBBBB| 40| null|null|40.0| null| null| beijing_haidian_red_B_d14_40| null|2024-09-24T14:15:40.000+08:00|2024-09-24| +|2024-09-24T14:15:50.000+08:00| beijing| beijing| haidian| d14| red|BBBBBBBBBBBBBBBB|null|50000|null|null| null| null| beijing_haidian_red_B_d14_50|0xcafebabe50|2024-09-24T14:15:50.000+08:00| null| +|2024-09-24T14:15:30.000+08:00| beijing| beijing| haidian| d16|yellow|BBBBBBBBBBBBBBBB|null| null|30.0|null| true| null| beijing_haidian_yellow_B_d16_30| null|2024-09-24T14:15:30.000+08:00|2024-09-24| +|2024-09-24T14:15:40.000+08:00| beijing| beijing| haidian| d16|yellow|BBBBBBBBBBBBBBBB|null|40000|null|null| null| null| null| null|2024-09-24T14:15:40.000+08:00| null| +|2024-09-24T14:15:55.000+08:00| beijing| beijing| haidian| d16|yellow|BBBBBBBBBBBBBBBB| 55| null|null|55.0| null| beijing_haidian_yellow_B_d16_55| null|0xcafebabe55|2024-09-24T14:15:55.000+08:00| null| ++-----------------------------+--------+--------+--------+---------+------+----------------+----+-----+----+----+-----+--------------------------------+--------------------------------+------------+-----------------------------+----------+ +Total line number = 64 +``` + +* Table2: + +```SQL +IoTDB> select * from table2 ++-----------------------------+---------+----+----+----+----+-----+-----+-------+------------+-----------------------------+----------+ +| time|device_id| s1| s2| s3| s4| s5| s6| s7| s8| s9| s10| ++-----------------------------+---------+----+----+----+----+-----+-----+-------+------------+-----------------------------+----------+ +|1970-01-01T08:00:00.001+08:00| d1| 1| 11| 1.1|11.1| true|text1|string1|0xcafebabe01|1970-01-01T08:00:00.001+08:00|2024-10-01| +|1970-01-01T08:00:00.002+08:00| d1| 2| 22| 2.2|22.2|false| null| null| null| null| null| +|1970-01-01T08:00:00.003+08:00| d1|null|null|null|null| null|text3|string3|0xcafebabe03|1970-01-01T08:00:00.003+08:00|2024-10-03| +|1970-01-01T08:00:00.004+08:00| d1|null|null|null|null| null|text4|string4|0xcafebabe04|1970-01-01T08:00:00.004+08:00|2024-10-04| +|1970-01-01T08:00:00.005+08:00| d1| 5| 55| 5.5|55.5|false| null| null| null| null| null| ++-----------------------------+---------+----+----+----+----+-----+-----+-------+------------+-----------------------------+----------+ +Total line number = 5 +``` + +* Table3: 包含 null 值 + +```SQL +IoTDB> select device_id, s1 from table3; ++---------+----+ +|device_id| s1| ++---------+----+ +| d_null| 30| +| d_null|null| +| d01| 30| +| d01| 40| ++---------+----+ +Total line number = 4 +``` + +> From 子句中子查询使用示例可参考[FROM & JOIN 子句](../SQL-Manual/From-Join-Clause.md)，下文中主要介绍 Where、Having、Select 子句中的使用示例。 + +### 4.2 非关联标量子查询 + +**Where 子句** + +从 table1 中找出设备编号为`d01`的所有记录中，数值 s1 大于或等于该设备 s1 数值平均值的记录。 + +SQL: + +```SQL +IoTDB> SELECT s1 FROM table1 + WHERE device_id = 'd01' + and s1 >= (SELECT avg(s1) from table1 WHERE device_id = 'd01'); +``` + +结果： + +```SQL ++--+ +|s1| ++--+ +|50| +|60| +|70| ++--+ +Total line number = 3 +``` + +**Having 子句** + +统计 table1 中按设备编号（device\_id）分组，每个设备编号的记录数，找出记录数不少于 table2 中设备`d1`记录数的所有设备及其记录数。 + +SQL: + +```SQL +IoTDB> SELECT device_id, count(*) + from table1 group by device_id + having count(*) >= (SELECT count(*) from table2 where device_id = 'd1'); +``` + +结果： + +```SQL ++---------+-----+ +|device_id|_col1| ++---------+-----+ +| d01| 5| +| d03| 5| +| d05| 5| +| d07| 5| +| d09| 5| +| d11| 5| +| d13| 5| +| d15| 5| ++---------+-----+ +Total line number = 8 +``` + +**Select 子句** + +从 table1 中选择设备编号为`d01`的所有记录，把每个记录的 s1 字段值与子查询得到的结果（即同一设备编号下 s2 字段的最大值）相加，返回计算后的新字段值。 + +SQL: + +```SQL +IoTDB> SELECT s1 + + (SELECT max(s2) from table1 where device_id = 'd01') + from table1 where device_id = 'd01'; +``` + +结果： + +```SQL ++-----+ +|_col0| ++-----+ +| 100| +| 110| +| 120| +| 130| +| 140| ++-----+ +Total line number = 5 +``` + +**特殊情况** + +* 如果非聚合子查询返回的结果集刚好只有一行，也可以认为是标量子查询： + +```SQL +// 子查询返回的值为 1，结果集为空集 +IoTDB> SELECT s1 FROM table1 + WHERE device_id = 'd01' and + s1 = (SELECT s1 FROM table2 limit 1); +``` + +> 如果返回的值不止一行，则会报错 + +* 在 SELECT 子句中作为单独的一列时，可以认为和 select 一个常量列等价，结果集形式为标量子查询结果重复 X 次，X 等于外层查询的结果集行数。 + +SQL: + +```SQL +// 外层查询为 SELECT xx from table1 where device_id = 'd01'， +// 而 SELECT count(*) from table1 where device_id = 'd01' 的结果是5，即结果集有五行 + +IoTDB> SELECT + (SELECT max(s1) from table1 where device_id = 'd01') + from table1 where device_id = 'd01'; +``` + +结果： + +```SQL ++-----+ +|_col0| ++-----+ +| 70| +| 70| +| 70| +| 70| +| 70| ++-----+ +Total line number = 5 +``` + +### 4.3 非关联列子查询 + +#### 4.3.1 非关联 InPredicate + +**Where 子句** + +从`table1`中找出设备编号为`d01`，并且其`s1`值也出现在`table3`中相同设备编号`d01`的记录里的所有`s1`值。 + +SQL: + +```SQL +IoTDB> SELECT s1 FROM table1 + WHERE device_id = 'd01' and + s1 in (SELECT s1 from table3 WHERE device_id = 'd01'); +``` + +结果： + +```SQL ++--+ +|s1| ++--+ +|30| +|40| ++--+ +Total line number = 2 +``` + +**Having 子句** + +从`table1`表中按`device_id`（设备编号）分组，计算每个设备编号的记录数，找出分组记录数加上 25 后，其结果值出现在`table3`表中设备编号为'd01'的`s1`字段值中的所有设备编号及其对应的记录数。 + +SQL: + +```SQL +IoTDB> SELECT device_id, count(*) from table1 + group by device_id + having count(*) + 25 + in (SELECT cast(s1 as INT64) from table3 where device_id = 'd01'); +``` + +结果： + +```SQL ++---------+-----+ +|device_id|_col1| ++---------+-----+ +| d01| 5| +| d03| 5| +| d05| 5| +| d07| 5| +| d09| 5| +| d11| 5| +| d13| 5| +| d15| 5| ++---------+-----+ +Total line number = 8 +``` + +**Select 子句** + +从`table1`中选择设备编号为`d01`的记录，检查这些记录的`s1`字段值是否存在于`table3`中相同设备编号`d01`的`s1`字段值中。 + +SQL: + +```SQL +IoTDB> SELECT + s1 in (SELECT s1 from table3 WHERE device_id = 'd01') + from table1 where device_id = 'd01'; +``` + +结果： + +```SQL ++-----+ +|_col0| ++-----+ +| true| +| true| +|false| +|false| +|false| ++-----+ +Total line number = 5 +``` + +**特殊情况** + +在 select 子句中使用 InPredicate 时（select x [not] in （subquery） from table），结果规则总结为： + +* 当前行 x 为 null，结果行为 null +* 当前行 x 不为 null + * 无 NOT + * x 在 subquery 结果集中则当前行结果为 True + * x 不在 subquery 结果集中 + * 如果 subquery 结果集包含 null，则当前行结果为 null，否则为 False + * 有 NOT + * x 在 subquery 结果集中则当前行结果为 False + * x 不在 subquery 结果集中 + * 如果 subquery 结果集包含 null，则当前行结果为 null，否则为 True + +示例 1：X 结果集包含 null + +```SQL +IoTDB> select s1 from table3; ++----+ +| s1| ++----+ +| 30| +|null| +| 30| +| 40| ++----+ +Total line number = 4 + +IoTDB> select s1 from table3 where s1 in (select s1 from table3); ++--+ +|s1| ++--+ +|30| +|30| +|40| ++--+ +Total line number = 3 +``` + +示例 2：在 select 子句里面使用，对应的行的结果是 null + +```SQL +IoTDB> select device_id, s1 in (select s1 from table1 where device_id = 'd01'), s1 from table3 ; ++---------+-----+----+ +|device_id|_col1| s1| ++---------+-----+----+ +| d_null| true| 30| +| d01| true| 30| +| d01| true| 40| +| d_null| null|null| ++---------+-----+----+ +``` + +示例 3：子查询结果集包含 null + +```SQL +IoTDB> select s1 from table1 where device_id = 'd02' ++----+ +| s1| ++----+ +| 36| +| 40| +|null| ++----+ +Total line number = 3 + +IoTDB> select s1 from table3; ++----+ +| s1| ++----+ +| 30| +|null| +| 30| +| 40| ++----+ +Total line number = 4 +``` + +示例 4：在 where 子句中使用，即 where s1 in （subquery），结果集只包含 40 一行 + +```SQL +IoTDB> select s1 from table1 where device_id = 'd02' and s1 in (select s1 from table3); ++--+ +|s1| ++--+ +|40| ++--+ +Total line number = 1 +``` + +示例 5：在 select 子句中使用，s1 的结果集为 （36， 40， null），subquery 的结果集为（30， 40， null），由于 36 与非 null 的两个结果 30 和 40 不相等，且 subquery 的结果集包含 null，所以对应的结果是 null + +```SQL +IoTDB> SELECT +> s1 in (SELECT s1 from table3) from table1 +> where device_id = 'd02' ++-----+ +|_col0| ++-----+ +| null| +| true| +| null| ++-----+ +Total line number = 3 +``` + +#### 4.3.2 非关联 QuantifiedComparison + +**Where 子句** + +* ALL + +从`table1`表中找出设备编号为`d01`的记录，并且`s1`字段值要大于`table3`表中同样设备编号的所有`s1`字段值。 + +SQL: + +```SQL +IoTDB> SELECT s1 FROM table1 + WHERE device_id = 'd01' and + s1 > all (SELECT s1 FROM table3 WHERE device_id = 'd01'); +``` + +结果： + +```SQL ++--+ +|s1| ++--+ +|50| +|60| +|70| ++--+ +Total line number = 3 +``` + +* ANY/SOME + +从`table1`表中找出设备编号为`d01`的记录，并且`s1`字段值要大于`table3`表中同样设备编号的任意一条记录的`s1`字段值。 + +SQL: + +```SQL +IoTDB> SELECT s1 FROM table1 + WHERE device_id = 'd01' and + s1 > any (SELECT s1 FROM table1 WHERE device_id = 'd01'); +``` + +结果： + +```SQL ++--+ +|s1| ++--+ +|40| +|50| +|60| +|70| ++--+ +Total line number = 4 +``` + +**Having 子句** + +* ALL + +从`table1`中按`device_id`（设备编号）分组，计算每个设备编号的记录数量，找出分组记录数加上 35 后，大于或等于`table3`中设备编号为`d01`的所有`s1`字段值（转换为整数类型）的设备编号及其对应的记录数。 + +SQL: + +```SQL +IoTDB> SELECT device_id, count(*) from table1 + group by device_id + having count(*) + 35 >= + all(SELECT cast(s1 as INT64) from table3 where device_id = 'd01'); +``` + +结果： + +```SQL ++---------+-----+ +|device_id|_col1| ++---------+-----+ +| d01| 5| +| d03| 5| +| d05| 5| +| d07| 5| +| d09| 5| +| d11| 5| +| d13| 5| +| d15| 5| ++---------+-----+ +Total line number = 8 +``` + +* ANY/SOME + +从`table1`中按`device_id`（设备编号）分组，计算每个设备编号的记录数量，找出分组记录数加上 35 后，大于或等于`table3`中设备编号为`d01`的任意一条记录`s1`字段值（转换为整数类型）的设备编号及其对应的记录数。 + +SQL: + +```SQL +IoTDB> SELECT device_id, count(*) + from table1 group by device_id + having count(*) + 25 >= + any(SELECT cast(s1 as INT64) from table3 where device_id = 'd01'); +``` + +结果： + +```SQL ++---------+-----+ +|device_id|_col1| ++---------+-----+ +| d01| 5| +| d03| 5| +| d05| 5| +| d07| 5| +| d09| 5| +| d11| 5| +| d13| 5| +| d15| 5| ++---------+-----+ +Total line number = 8 +``` + +**Select 子句** + +* ALL + +从`table1`中选择设备编号为`d01`的记录，并且`s1`字段值要大于`table3`表中设备编号为`d01`的所有`s1`字段值。 + +SQL: + +```SQL +IoTDB> SELECT s1 > + all(SELECT (s1) from table3 WHERE device_id = 'd01') + from table1 where device_id = 'd01'; +``` + +结果： + +```SQL ++-----+ +|_col0| ++-----+ +|false| +|false| +| true| +| true| +| true| ++-----+ +Total line number = 5 +``` + +* ANY/SOME + +从`table1`中选择设备编号为`d01`的记录，并且`s1`字段值要大于`table3`表中设备编号为`d01`的任意一条记`s1`字段值。 + +SQL: + +```SQL +IoTDB> SELECT s1 > + any(SELECT (s1) from table3 WHERE device_id = 'd01') + from table1 where device_id = 'd01'; +``` + +结果： + +```SQL ++-----+ +|_col0| ++-----+ +|false| +| true| +| true| +| true| +| true| ++-----+ +Total line number = 5 +``` + +**特殊情况** + +ALL 要求所有比较都为 True 结果才为 True + +ANY/SOME 要求任意比较为 True 结果就为 True + +示例 1：ALL + +```SQL +IoTDB> select s1 from table1 where device_id = 'd01' ++--+ +|s1| ++--+ +|30| +|40| +|50| +|60| +|70| ++--+ +Total line number = 5 + +IoTDB> select s1 from table3; ++----+ +| s1| ++----+ +| 30| +|null| +| 30| +| 40| ++----+ + +IoTDB> select (s1 > all(select s1 from table3)) from table1 where device_id = 'd01'; ++-----+ +|_col0| ++-----+ +|false| +|false| +| null| +| null| +| null| ++-----+ +``` + +说明： + +* `table1s1` 的 30，40 两行，由于 `table3 s1` 的非 `null` 结果集 （30， 40） 让 30 > 40/ 40 > 40 为 `False` ，即短路求值，结果是 `false`。 +* 对于 50，60，70 三个值，由于 ALL 要求的是所有比较结果都是 `True` 结果才是 `True`， 50，60，70 与 `null` 的比较都是 `null`，结果是 `null`。 + +示例 2：ANY/SOME + +```SQL +IoTDB> SELECT s1 <= + any(SELECT (s1) from table3), s1 <= any(SELECT (s1) from table3 where s1 is not NULL) + from table1 where device_id = 'd01' ++-----+-----+ +|_col0|_col1| ++-----+-----+ +| true| true| +| true| true| +| null|false| +| null|false| +| null|false| ++-----+-----+ +``` + +说明： + +* 对于`table1`中的 30 和 40，由于 `table3 s1` 的非 null 结果集 （30， 40），使得比较结果为`true`（成立）。 +* 对于 50、60、70，由于`ANY`要求的是至少一个比较结果为`true`结果就是`true`，而与`null`的比较结果为`null`，所以这些结果为`null`。 +* 在第二个查询中，由于我们排除了空值，所以对于 50、60、70，由于`table3`中没有更大的非空值，比较结果为`false`。 +