Help Center/ GaussDB/ Distributed_3.x/ SQL Reference/ SQL Syntax/ SELECT

Updated on 2024-05-07 GMT+08:00

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SELECT

Description

SELECT retrieves data from tables or views.

Serving as an overlaid filter on database tables, the SELECT statement uses SQL keywords to filter data tables and extract the required data.

Precautions

The owner of a table, users granted with the SELECT permission on the table, or users granted with the SELECT ANY TABLE permission can read data in the table or view. The system administrator has the permission to read data in the table or view by default.
SELECT can join ordinary tables, but cannot join ordinary and GDS foreign tables. That is, the SELECT statement cannot contain both an ordinary table and a GDS foreign table.
You must have the SELECT permission on each field used in the SELECT statement.

UPDATE permission is required when FOR UPDATE or FOR SHARE is used.

Syntax

Query data.

    
         [ WITH [ RECURSIVE ] with_query [, ...] ]
SELECT [/*+ plan_hint */] [ ALL | DISTINCT [ ON ( expression [, ...] ) ] ]
    { * | {expression [ [ AS ] output_name ]} [, ...] }
    [ FROM from_item [, ...] ]
    [ WHERE condition ]
    [ GROUP BY grouping_element [, ...] ]
    [ HAVING condition [, ...] ]
    [ WINDOW {window_name AS ( window_definition )} [, ...] ]
    [ { UNION | INTERSECT | EXCEPT | MINUS } [ ALL | DISTINCT ] select ]
    [ ORDER BY {expression [ [ ASC | DESC | USING operator ] | nlssort_expression_clause ] [ NULLS { FIRST | LAST } ]} [, ...] ]
    [ LIMIT { [offset,] count | ALL } ]
    [ OFFSET start [ ROW | ROWS ] ]
    [ FETCH { FIRST | NEXT } [ count ] { ROW | ROWS } ONLY ]
    [ {FOR { UPDATE | SHARE } [ OF table_name [, ...] ] [ NOWAIT | WAIT N]} [...] ]
TABLE { ONLY { (table_name) | table_name } | table_name [ * ]};

In condition and expression, you can use the aliases of expressions in targetlist in compliance with the following rules:

Reference only within the same level.
Reference only the aliases in the target list.
Reference a prior expression in a subsequent expression.
Volatile functions cannot be used.
Window functions cannot be used.
Aliases cannot be referenced in the condition of JOIN ON.
An error is reported if the target list contains multiple aliases to be referenced.

In the scenario where the SELECT statement plan is cached, the WHERE IN candidate subset cannot be too large. It is recommended that the number of conditions be less than or equal to 100 to prevent high dynamic memory.

If the WHERE IN candidate subset is too large, the memory usage of the generated plan increases.
If the WHERE IN subsets constructed by concatenated SQL statements are different, the SQL template of the cache plan cannot be reused. A large number of different plans are generated, and the plans cannot be shared. As a result, a large amount of memory is occupied.

The subquery with_query is as follows:

      
           with_query_name [ ( column_name [, ...] ) ]
    AS [ [ NOT ] MATERIALIZED ] ( {select | values | insert | update | delete} )

The specified query source from_item is as follows:

      
           {[ ONLY ] table_name [ * ] [ partition_clause ] [ [ AS ] alias [ ( column_alias [, ...] ) ] ]
[ TABLESAMPLE sampling_method ( argument [, ...] ) [ REPEATABLE ( seed ) ] ]
|( select ) [ AS ] alias [ ( column_alias [, ...] ) ]
|with_query_name [ [ AS ] alias [ ( column_alias [, ...] ) ] ]
|function_name ( [ argument [, ...] ] ) [ AS ] alias [ ( column_alias [, ...] | column_definition [, ...] ) ]
|function_name ( [ argument [, ...] ] ) AS ( column_definition [, ...] )
|from_item unpivot_clause
|from_item pivot_clause
|from_item [ NATURAL ] join_type from_item [ ON join_condition | USING ( join_column [, ...] ) ]}

The GROUP clause is as follows:

      
           ( )
| expression
| ( expression [, ...] )
| ROLLUP ( { expression | ( expression [, ...] ) } [, ...] )
| CUBE ( { expression | ( expression [, ...] ) } [, ...] )
| GROUPING SETS ( grouping_element [, ...] )

The specified partition partition_clause is as follows:

      
           PARTITION { ( partition_name ) | 
        FOR (  partition_value [, ...] ) }

The specified partition applies only to ordinary tables.

The sorting order nlssort_expression_clause is as follows:

      
           NLSSORT ( column_name, ' NLS_SORT = { SCHINESE_PINYIN_M | generic_m_ci } ' )
The second parameter can be generic_m_ci, which supports only the case-insensitive order for English characters.

Simplified query syntax, equivalent to select * from table_name.

      
           TABLE { ONLY {(table_name)| table_name} | table_name [ * ]};

Parameters

WITH [ RECURSIVE ] with_query [, ...]
Specifies one or more subqueries that can be referenced by name in the main query, which is equivalent to a temporary table. This subquery statement structure is called the common table expression (CTE) structure. When this structure is used, the execution plan contains the CTE SCAN content.

If RECURSIVE is specified, it allows a SELECT subquery to reference itself by name.

The detailed format of with_query is as follows: with_query_name [ ( column_name [, ...] ) ] AS [ [ NOT ] MATERIALIZED ] ( {select | values | insert | update | delete} )
- with_query_name specifies the name of the result set generated by a subquery. Such names can be used to access the result sets of subqueries in a query.
- column_name specifies the column name displayed in the subquery result set.
- Each subquery can be a SELECT, VALUES, INSERT, UPDATE or DELETE statement.
- RECURSIVE can appear only after WITH. In the case of multiple CTEs, you only need to declare RECURSIVE at the first CTE.
- You can use MATERIALIZED or NOT MATERIALIZED to modify the CTE. Currently, only inline execution is supported for stream plans. In this case, this syntax does not take effect.
  - If MATERIALIZED is specified, the WITH query will be materialized, and a copy of the subquery result set is generated. The copy is directly queried at the reference point. Therefore, the WITH subquery cannot be jointly optimized with the SELECT statement trunk (for example, predicate pushdown and equivalence class transfer). In this scenario, you can use NOT MATERIALIZED for modification. If the WITH query can be executed as a subquery inline, the preceding optimization can be performed.
  - If the user does not explicitly declare the materialized attribute, comply with the following rules: If the CTE is referenced only once in the SELECT statement trunk to which it belongs and semantically supports inline execution, it will be rewritten as subquery inline execution. Otherwise, the materialized execution will be performed in CTE Scan mode.
plan_hint clause
Follows the SELECT keyword in the /*+<Plan hint> */ format. It is used to optimize the plan of a SELECT statement block. For details, see Hint-based Tuning. In each statement, only the first /*+ plan_hint */ comment block takes effect as a hint. Multiple hints can be written.
ALL
Specifies that all rows that meet the conditions are returned. This is the default behavior and can be omitted.
DISTINCT [ ON ( expression [, ...] ) ]
Removes all duplicate rows from the SELECT result set so one row is kept from each group of duplicates.

Retains only the first row in the set of rows that have the same result calculated on the given expression.

DISTINCT ON expression is explained with the same rule of ORDER BY. Unless you use ORDER BY to ensure that the required row appears first, you cannot know what the first row is.
SELECT list
Specifies the name of a column in the table to be queried. The value can be a part of the column name or all of the column names. The wildcard (*) is used to represent the column name.

You may use the AS output_name clause to give an alias for an output column. The alias is used for the displaying of the output column. The name, value, and type keywords can be used as column aliases.

Column names can be expressed in the following formats:
- Manually input column names which are spaced using commas (,).
- Columns computed in the FROM clause.
FROM clause
Specifies one or more source tables for SELECT.

The FROM clause can contain the following elements:
- table_name
  Specifies the name of a table or view. The schema name can be added before the table name or view name, for example, schema_name.table_name.
  
  You can use database link to perform operations on remote tables and synonyms. For details, see DATABASE LINK.
- alias
  Gives a temporary alias to a table to facilitate the quotation by other queries.
  
  An alias is used for brevity or to eliminate ambiguity for self-joins. If an alias is provided, it completely replaces the actual name of the table.
  
  If an alias is specified for the joined_table table created by JOIN and joined_table is wrapped with "()", that is, (joined_table), non-reserved keywords UNPIVOT and PIVOT cannot be used as aliases.
- TABLESAMPLE sampling_method ( argument [, ...] ) [ REPEATABLE ( seed ) ]
  The TABLESAMPLE clause following table_name specifies that the specified sampling_method should be used to retrieve the subset of rows in the table.
  
  The optional REPEATABLE clause specifies the number of seeds used to generate random numbers in the sampling method. The seed value can be any non-null constant value. If the table was not changed during the query, the two queries having the same seed and argument values will select the same sampling in this table. However, different seed values usually generate different samples. If REPEATABLE is not specified, a new random sample will be selected for each query based on the seed generated by the system.
- TIMECAPSULE { TIMESTAMP | CSN } expression
  Queries the table data of a specified CSN or at a specified time point.
  
  Currently, the following tables do not support flashback query: system catalogs, DFS tables, global temporary tables, local temporary tables, unlogged tables, views, sequence tables, hash bucket tables, shared tables, and inherited tables.
  - TIMECAPSULE TIMESTAMP
    Searches for the result set of a specified time point based on the date as the flashback query flag. date must be a valid past timestamp
  - TIMECAPSULE CSN
    Searches for the result set of a specified CSN point based on the CSN flashback of the table as the flashback query flag. The CSN can be obtained from snpcsn recorded in gs_txn_snapshot.
    A flashback query cannot span statements that affect the table structure or physical storage. Otherwise, an error is reported. Between the flashback point and the current point, if a statement (TRUNCATE, DDL, DCL, or VACUUM FULL) has been executed to modify the table structure or affect physical storage, the flashback fails.
    
    Flashback query does not support index query. Flashback query supports only seqScan for full table scanning.
    
    When the flashback point is too old, the old version cannot be obtained because the flashback version is recycled. As a result, the flashback fails and the error message "Restore point too old" is displayed.
    
    The flashback point is specified by time. The maximum difference between the flashback point and the actual time is 3 seconds.
    
    After truncating a table, perform a flashback query or flashback on the table. The error message "Snapshot too old" is displayed when a flashback is performed at a specified time point. Data cannot be found or the error message "Snapshot too old" is reported during the CSN-based flashback.
    
    In the GTM-Free scenario, each node uses the local CSN and does not have a globally unified CSN. Therefore, flashback in CSN mode is not supported.
- column_alias
  Specifies the column alias.
- PARTITION
  Queries data in the specified partition in a partitioned table.
- partition_name
  Specifies the name of a partition.
- partition_value
  Specifies the value of the specified partition key. If there are many partition keys, use the PARTITION FOR clause to specify the value of the only partition key you want to use.
- subquery
  Performs a subquery in the FROM clause. A temporary table is created to save subquery results.
- with_query_name
  Specifies that the WITH clause can also be used as the source of the FROM clause and can be referenced by the name of the WITH query.
- function_name
  Function name. Function calls can appear in the FROM clause.
- join_type
  The options are as follows:
  - [ INNER ] JOIN
    A JOIN clause combines two FROM items. You can use parentheses to determine the order of nesting. In the absence of parentheses, JOIN nests left-to-right.
    
    In any case, JOIN binds more tightly than the commas separating FROM items.
  - LEFT [ OUTER ] JOIN
    Returns all rows that meet join conditions in the Cartesian product, plus those rows that do not match the right table rows in the left table by join conditions. This left-hand row is extended to the full width of the joined table by inserting NULL values for the right-hand columns. Note that only the JOIN clause's own condition is considered while the system decides which rows have matches. Outer conditions are applied afterward.
  - RIGHT [ OUTER ] JOIN
    Returns all the joined rows, plus one row for each unmatched right-hand row (extended with NULL on the left).
    
    This is just a notational convenience, since you could convert it to a LEFT OUTER JOIN by switching the left and right inputs.
  - FULL [ OUTER ] JOIN
    Returns all the joined rows, pluses one row for each unmatched left-hand row (extended with NULL on the right), and pluses one row for each unmatched right-hand row (extended with NULL on the left).
  - CROSS JOIN
    Is equivalent to INNER JOIN ON (TRUE), which means no rows are removed by qualification. These join types are just a notational convenience, since they do nothing you could not do with plain FROM and WHERE.
    
    For the INNER and OUTER join types, a join condition must be specified, namely exactly one of NATURAL ON, join_condition, or USING (join_column [, ...]). For CROSS JOIN, none of these clauses can appear.
  CROSS JOIN and INNER JOIN produce a simple Cartesian product, the same result as you get from listing the two items at the top level of FROM.
- ON join_condition
  Defines which rows have matches in joins. Example: ON left_table.a = right_table.a You are advised not to use numeric types such as int for join_condition, because such types can be implicitly converted to bool values (non-zero values are implicitly converted to true and 0 is implicitly converted to false), which may cause unexpected results.
- USING(join_column[, ...])
  ON left_table.a = right_table.a AND left_table.b = right_table.b ... abbreviation. Corresponding columns must have the same name.
- NATURAL
  Is a shorthand for a USING list that mentions all columns in the two tables that have the same names.
- from item
  Specifies the name of the query source object connected.
- unpivot_clause
  Converts a column to a row. The syntax format is as follows:
```
 UNPIVOT [ {INCLUDE | EXCLUDE} NULLS ]
    (   
        unpiovt_col_clause
        unpivot_for_clause
        unpivot_in_clause
    )
```
  - {INCLUDE | EXCLUDE} NULLS
    Controls whether the converted result contains NULL rows. INCLUDE NULLS indicates that the converted results contain NULL rows. EXCLUDE NULLS indicates that the converted results do not contain NULL rows. If this clause is ignored, the unpivot operation removes NULL rows from the converted results by default.
  - unpiovt_col_clause
```
unpivot_col_element 
```
    unpivot_col_element specifies the output column names. These columns store the values to be converted.
  - unpivot_col_element
```
{ column | ( column [, column]... ) }
```
    unpivot_col_element has two forms: column and ( column [, column]... ).
  - unpivot_for_clause
```
FOR { unpivot_col_element }
```
    unpivot_col_element contained in the unpivot_for_clause is used to specify the output column names. These columns store the alias and names of the column to be converted.
  - unpivot_in_clause
```
IN ( unpivot_in_element [,unpivot_in_element...] )
```
    unpivot_in_clause specifies the columns to be converted. The column names and column values are saved in the previously specified output columns.
    unpivot_in_element
```
{ unpivot_col_element }[  AS { unpivot_alias_element } ]
```
    unpivot_col_element specifies the column to be converted. If ( column [, column]...) is used to specify the column to be converted, the column names are connected by underscores (_) and saved in the output columns. For example, IN ((col1, col2)) generates the column name col1_col2 and saves it in the output column specified by unpivot_for_clause. In addition, the AS keyword can be used to specify an alias for the column to be converted. Once an alias is specified, the alias is saved in the output column instead of the name of column to be converted.
  - unpivot_alias_element
```
{ alias | ( alias [, alias]... )}
```
    Similar to unpivot_col_element, unpivot_alias_element has two forms. alias indicates the specified alias.
  Currently, unpivot_clause has the following restrictions:
  - This parameter can be used only in ORA compatibility mode.
  - The unpivot_clause clause cannot be used with hints.
  - For unpiovt_col_clause, the number of output columns specified by unpivot_col_element must be the same as that of unpivot_col_element contained in unpivot_in_clause.
  - For unpivot_for_clause, the number of output columns specified by unpivot_col_element must be the same as the number of aliases specified by unpivot_alias_element contained in unpivot_in_clause.
  - For unpivot_in_clause, the alias must be a constant or an expression that can be converted to a constant.
  - For unpivot_in_clause, constant expressions support only IMMUTABLE functions.
  - For all unpivot_col_element parameters contained in unpivot_in_clause, if the column types in the same position of these unpivot_col_element parameters are different, UNPIVOT attempts to convert the column types in order to convert the values of columns to be converted to a public type. Similarly, for all unpivot_alias_element parameters, if the alias types of these unpivot_alias_element parameters in the same position are different, UNPIVOT attempts to do the similar type conversion.
    For example, assume that there is an unpivot_in_clause in the form of IN (col1, col2), where col1 is of the int type and col2 is of the float type, UNPIVOT attempts to convert the column value of col1 to the public type float during the calculation.
- pivot_clause
  Converts a row into column. The syntax format is as follows:
```
PIVOT [ XML ]
( aggregate_function ( expr ) [[AS] alias ]
    [, aggregate_function ( expr ) [[AS] alias ] ]...
    pivot_for_clause
    pivot_in_clause
)
```
  - aggregate_function ( expr ) [[AS] alias ]
    Aggregates calculation on a given expression. The calculation result is saved in the output column specified by pivot_in_clause. [AS] alias (The AS keyword can be omitted.) can be used to specify an alias for aggregate_function. The alias is appended to the output column name specified by pivot_in_clause in the format of "_alias".
  - pivot_for_clause
```
FOR { column
    | ( column [, column]... )
    }
```
    Specifies the row to be converted. The column indicates a column of the row to be converted.
  - pivot_in_clause
```
IN ( { { { expr
         | ( expr [, expr]... )
         } [ [AS] alias]
       }...
     }
  )
```
    Specifies the name of the output column. The column name can consist of one or more expressions, for example, (expr1, expr2). When a column name consists of multiple expressions, these expressions are connected by underscores (_) in sequence. That is, the output column name corresponding to (expr1, expr2) is "expr1_expr2". These expressions not only generate output column names, but also determine the time when the aggregation function is triggered. If the values of row to be converted is the same as the value of these expressions, the results calculated by aggregate_function are saved in the output column names that consist of these expressions. Assume that expr1 is "1" and expr2 is "2". For row "1 2", aggregate_function is used for calculation. For row "1 1", the calculation is not triggered.
  Currently, pivot_clause has the following restrictions:
  - This parameter can be used only in ORA compatibility mode.
  - The pivot_clause clause cannot be used with hints.
  - If more than one aggregate_function is specified, at most one aggregate_function is allowed to have no alias, the rest of the aggregate_function functions are required to specify an alias.
  - XML supports only syntax but does not support functions.
  - The expression in pivot_in_clause can be a constant or an expression that can be converted to a constant. If the expression is not a unary expression, specify an alias for the expression.
  - For pivot_in_clause, constant expressions support only IMMUTABLE functions.
  - For the expression in pivot_in_clause, when the keyword AS is used to specify an alias for the expression, only the non-reserved keywords can be used as aliases.
  - If the length of an output column name exceeds 63 characters, subsequent characters will not be printed.
WHERE clause
Forms an expression for row selection to narrow down the query range of SELECT. condition indicates any expression that returns a value of Boolean type. Rows that do not meet this condition will not be retrieved. You are advised not to use numeric types such as int for condition, because such types can be implicitly converted to bool values (non-zero values are implicitly converted to true and 0 is implicitly converted to false), which may cause unexpected results.

In the WHERE clause, you can use the operator (+) to convert a table join to an outer join. However, this method is not recommended because it is not the standard SQL syntax and may raise syntax compatibility issues during platform migration. There are many restrictions on using the operator (+):
1. It can appear only in the WHERE clause.
2. If a table join has been specified in the FROM clause, the operator (+) cannot be used in the WHERE clause.
3. The operator (+) can work only on columns of tables or views, instead of on expressions.
4. If table A and table B have multiple join conditions, the operator (+) must be specified in all the conditions. Otherwise, the operator (+) will not take effect, and the table join will be converted into an inner join without any prompt information.
5. Tables specified in a join condition where the operator (+) works cannot cross queries or subqueries. If tables where the operator (+) works are not in the FROM clause of the current query or subquery, an error will be reported. If a peer table for the operator (+) does not exist, no error will be reported and the table join will be converted into an inner join.
6. Expressions where the operator (+) is used cannot be directly connected through OR.
7. If a column where the operator (+) works is compared with a constant, the expression becomes a part of the join condition.
8. A table cannot have multiple foreign tables.
9. The operator (+) can appear only in the following expressions: comparison, NOT, ANY, ALL, IN, NULLIF, IS DISTINCT FROM, and IS OF. It is not allowed in other types of expressions. In addition, these expressions cannot be connected through AND or OR.
10. The operator (+) can be used to convert a table join only to a left or right outer join, instead of a full join. That is, the operator (+) cannot be specified on both tables of an expression.
For the WHERE clause, if special character %, _, or \ is queried in LIKE, add the slash \ before each character.
GROUP BY clause
Condenses query results into a single row all selected rows that share the same values for the grouped expressions.
- CUBE ( { expression | ( expression [, ...] ) } [, ...] )
  A CUBE grouping is an extension to the GROUP BY clause that creates subtotals for all of the possible combinations of the given list of grouping columns (or expressions). In terms of multidimensional analysis, CUBE generates all the subtotals that could be calculated for a data cube with the specified dimensions. For example, given three expressions (n=3) in the CUBE clause, the operation results in 2ⁿ = 2³ = 8 groupings. Rows grouped on the values of n expressions are called regular rows, and the rest are called superaggregate rows.
- GROUPING SETS ( grouping_element [, ...] )
  Another extension to the GROUP BY clause. It allows users to specify multiple GROUP BY clauses. This improves efficiency by trimming away unnecessary data. After you specify the set of groups that you want to create using a GROUPING SETS expression within a GROUP BY clause, the database does not need to compute a whole ROLLUP or CUBE.
- If a SELECT list expression references ungrouped columns and no aggregate function is used, an error is reported. This is because multiple values may be returned for ungrouped columns.
- If a SELECT list expression references a constant, the GROUP BY clause does not need to group the constant. Otherwise, an error is reported.
HAVING clause
Selects special groups by working with the GROUP BY clause. The HAVING clause compares some attributes of groups with a constant. Only groups that matching the logical expression in the HAVING clause are extracted.
WINDOW clause
The general format is WINDOW window_name AS ( window_definition ) [, ...]. window_name is a name can be referenced by window_definition. window_definition can be expressed in the following forms:

[ existing_window_name ]

[ PARTITION BY expression [, ...] ]

[ ORDER BY expression [ ASC | DESC | USING operator ] [ NULLS { FIRST | LAST } ] [, ...] ]

[ frame_clause ]

frame_clause defines a window frame for the window function. The window function (not all window functions) depends on window frame and window frame is a set of relevant rows of the current query row. frame_clause can be expressed in the following forms:

[ RANGE | ROWS ] frame_start

[ RANGE | ROWS ] BETWEEN frame_start AND frame_end

frame_start and frame_end can be expressed in the following forms:

UNBOUNDED PRECEDING

value PRECEDING

CURRENT ROW

value FOLLOWING

UNBOUNDED FOLLOWING
UNION clause
Computes the set union of the rows returned by the involved SELECT statements.

The UNION clause has the following constraints:
- By default, the result of UNION does not contain any duplicate rows unless the ALL clause is declared.
- Multiple UNION operators in the same SELECT statement are evaluated left to right, unless otherwise specified by parentheses.
- FOR UPDATE cannot be specified either for a UNION result or for any input of a UNION.
General expression:

select_statement UNION [ALL] select_statement
- select_statement can be any SELECT statement without an ORDER BY, LIMIT, or FOR UPDATE statement.
- ORDER BY and LIMIT can be attached to the subexpression if it is enclosed in parentheses.
INTERSECT clause
Computes the set intersection of rows returned by the involved SELECT statements. The result of INTERSECT does not contain any duplicate rows.

The INTERSECT clause has the following constraints:
- Multiple INTERSECT operators in the same SELECT statement are evaluated left to right, unless otherwise specified by parentheses.
- Processing INTERSECT preferentially when UNION and INTERSECT operations are executed for results of multiple SELECT statements.
General format:

select_statement INTERSECT select_statement

select_statement can be any SELECT statement without a FOR UPDATE clause.
EXCEPT clause
Has the following common form:

select_statement EXCEPT [ ALL ] select_statement

select_statement can be any SELECT statement without a FOR UPDATE clause.

The EXCEPT operator computes the set of rows that are in the result of the left SELECT statement but not in the result of the right one.

The result of EXCEPT does not contain any duplicate rows unless the ALL clause is declared. To execute ALL, a row that has m duplicates in the left table and n duplicates in the right table will appear MAX(m–n, 0) times in the result set.

Multiple EXCEPT operators in the same SELECT statement are evaluated left to right, unless parentheses dictate otherwise. EXCEPT binds at the same level as UNION.

Currently, FOR UPDATE cannot be specified either for an EXCEPT result or for any input of an EXCEPT.
MINUS clause
Has the same function and syntax as EXCEPT clause.
ORDER BY clause
Sorts data retrieved by SELECT in descending or ascending order. If the ORDER BY expression contains multiple columns:
- If two columns are equal according to the leftmost expression, they are compared according to the next expression and so on.
- If they are equal according to all specified expressions, they are returned in an implementation-dependent order.
- When used with the DISTINCT keyword, the columns to be sorted in ORDER BY must be included in the columns of the result set retrieved by the SELECT statement.
- When used with the GROUP BY clause, the columns to be sorted in ORDER BY must be included in the columns of the result set retrieved by the SELECT statement.
To support Chinese pinyin order, set the encoding format to UTF-8, GB18030, GB18030_2022, or GBK when initializing the database. The statements are as follows:

initdb –E UTF8 –D ../data –locale=zh_CN.UTF-8, initdb -E GB18030 -D ../data -locale=zh_CN.GB18030, initdb -E GB18030_2022 -D ../data -locale=zh_CN.GB18030, or initdb –E GBK –D ../data –locale=zh_CN.GBK.
LIMIT clause
Consists of two independent sub-clauses:

LIMIT { count | ALL }

OFFSET start count specifies the maximum number of rows to return, while start specifies the number of rows to skip before starting to return rows. When both are specified, start rows are skipped before starting to count the count rows to be returned.

ROWNUM cannot be used as count or offset in the LIMIT clause.
OFFSET clause
The SQL: 2008 standard has introduced a different clause:

OFFSET start { ROW | ROWS }

start specifies the number of rows to skip before starting to return rows.
FETCH { FIRST | NEXT } [ count ] { ROW | ROWS } ONLY
If count is omitted in a FETCH clause, it defaults to 1.
FOR UPDATE clause
The FOR UPDATE clause locks the rows retrieved by SELECT. This ensures that the rows cannot be modified or deleted by other transactions until the current transaction ends. That is, other transactions that attempt UPDATE, DELETE, or SELECT FOR UPDATE of these rows will be blocked until the current transaction ends.

To prevent the operation from waiting for the commit of other transactions, you can use NOWAIT. If the selected row cannot be locked immediately, an error is reported immediately when you execute SELECT FOR UPDATE NOWAIT. If you use WAIT N and the selected row cannot be locked immediately, the operation needs to wait for N seconds (the value of N is of the int type with a range of 0 ≤ N ≤ 2147483). If the lock is obtained within N seconds, the operation is performed normally. Otherwise, an error is reported.

FOR SHARE behaves similarly, except that it acquires a shared rather than exclusive lock on each retrieved row. A share lock blocks other transaction from performing UPDATE, DELETE, or SELECT FOR UPDATE on these rows, but it does not prevent them from performing SELECT FOR SHARE.

If specified tables are named in FOR UPDATE or FOR SHARE, then only rows coming from those tables are locked. Any other tables used in SELECT are simply read as usual. Otherwise, locking all tables in the statement.

If FOR UPDATE or FOR SHARE is applied to a view or sub-query, it affects all tables used in the view or sub-query.

Multiple FOR UPDATE and FOR SHARE clauses can be written if it is necessary to specify different locking behaviors for different tables.

If the same table is mentioned (or implicitly affected) by both FOR UPDATE and FOR SHARE clauses, it is processed as FOR UPDATE. Similarly, a table is processed as NOWAIT if that is specified in any of the clauses affecting it.
- For SQL statements containing FOR UPDATE or FOR SHARE, their execution plans will be pushed down to DNs. If the pushdown fails, an error will be reported.
- The query of row number contained in the projection column or WHERE conditions does not support for update/share.
- For the FOR UPDATE/SHARE statements whose subquery is a stream plan, the same locked row cannot be concurrently updated.
- For the ORDER BY FOR UPDATE/SHARE statement, the execution sequence of the SORT and LOCKROW operators in the stream plan is different from that in other plans. In the stream plan, LOCK is executed before SORT. In other plans, SORT is executed before LOCK. The reason is that if the data in the stream plan is not on the current DN, the data needs to be redistributed and locked on the original DN. After redistribution, data becomes disordered. Therefore, the SORT operator needs to be added. If SORT is performed before LOCK, the original ordered data becomes disordered again. In this case, the SORT operator is meaningless and can be eliminated. The final plan execution sequence is changed from sort > lock > sort to lock > sort.
- In scenarios where FOR UPDATE/SHARE statements are concurrently executed, ORDER BY is used to sort data to avoid deadlocks. This method is not feasible for distributed systems because the DN lock sequence cannot be ensured by ORDER BY. In addition, adding ORDER BY causes performance overhead. Therefore, you are advised not to add ORDER BY to solve the deadlock problem.
NLS_SORT
Specifies that a field is sorted in a special order. Currently, only Chinese Pinyin and case-insensitive sorting are supported. To support this sorting mode, you need to set the encoding format to UTF8, GB18030, GB18030_2022, or GBK when creating a database. If you set the encoding format to another format, for example, SQL_ASCII, an error may be reported or the sorting mode may be invalid.

Value range:
- SCHINESE_PINYIN_M, sorted by Pinyin order.
- generic_m_ci: sorted in case-insensitive order (optional; only English characters are supported in the case-insensitive order.)
PARTITION clause
Queries data in the specified partition in a partitioned table.

Examples

    
     
       
       
         -- Create a schema.
gaussdb=# CREATE SCHEMA tpcds;

-- Create the tpcds.reason table.
gaussdb=# CREATE TABLE tpcds.reason(
  r_reason_sk      integer,
  r_reason_id      character(16),
  r_reason_desc    character(100)
);

-- Insert multiple records into the table.
gaussdb=# INSERT INTO tpcds.reason values(3,'AAAAAAAABAAAAAAA','reason 1'),(10,'AAAAAAAABAAAAAAA','reason 2'),(4,'AAAAAAAABAAAAAAA','reason 3'),(10,'AAAAAAAABAAAAAAA','reason 4'),(10,'AAAAAAAABAAAAAAA','reason 5'),(20,'AAAAAAAACAAAAAAA','N%reason 6'),(30,'AAAAAAAACAAAAAAA','W%reason 7');

-- Obtain the temp_t temporary table by a subquery and query all records in this table.
gaussdb=# WITH temp_t(name,isdba) AS (SELECT usename,usesuper FROM pg_user) SELECT * FROM temp_t;

-- Query all r_reason_sk records in the tpcds.reason table and delete duplicate records:
gaussdb=# SELECT DISTINCT(r_reason_sk) FROM tpcds.reason;

-- Example of a LIMIT clause: Obtain a record from the table.
gaussdb=# SELECT * FROM tpcds.reason LIMIT 1;

-- Query all records and sort them in alphabetic order.
gaussdb=# SELECT r_reason_desc FROM tpcds.reason ORDER BY r_reason_desc;

-- Use table aliases to obtain data from the pg_user and pg_user_status tables:
gaussdb=# SELECT a.usename,b.locktime FROM pg_user a,pg_user_status b WHERE a.usesysid=b.roloid;

-- Example of the FULL JOIN clause: Join data in the pg_user and pg_user_status tables.
gaussdb=# SELECT a.usename,b.locktime,a.usesuper FROM pg_user a FULL JOIN pg_user_status b on a.usesysid=b.roloid;

-- Example of the GROUP BY clause: Filter data based on query conditions, and group the results.
gaussdb=# SELECT r_reason_id, AVG(r_reason_sk) FROM tpcds.reason GROUP BY r_reason_id HAVING AVG(r_reason_sk) > 25;

-- Example of the GROUP BY CUBE clause: Filter data based on query conditions, and group the results.
gaussdb=# SELECT r_reason_id,AVG(r_reason_sk) FROM tpcds.reason GROUP BY CUBE(r_reason_id,r_reason_sk);

-- Example of the GROUP BY GROUPING SETS clause: Filter data based on query conditions, and group the results.
gaussdb=# SELECT r_reason_id,AVG(r_reason_sk) FROM tpcds.reason GROUP BY GROUPING SETS((r_reason_id,r_reason_sk),r_reason_sk);

-- Example of the UNION clause: Merge the names started with W and N in the r_reason_desc column in the tpcds.reason table.
gaussdb=# SELECT r_reason_sk, tpcds.reason.r_reason_desc
    FROM tpcds.reason
    WHERE tpcds.reason.r_reason_desc LIKE 'W%'
UNION
SELECT r_reason_sk, tpcds.reason.r_reason_desc
    FROM tpcds.reason
    WHERE tpcds.reason.r_reason_desc LIKE 'N%';

-- Example of the NLS_SORT clause: Sort by Chinese Pinyin.
gaussdb=# SELECT * FROM tpcds.reason ORDER BY NLSSORT( r_reason_desc, 'NLS_SORT = SCHINESE_PINYIN_M');


-- sorting by case-insensitive order (optional; only English characters are supported in the case-insensitive order.)
gaussdb=# SELECT * FROM tpcds.reason ORDER BY NLSSORT( r_reason_desc, 'NLS_SORT = generic_m_ci');

-- Create a partitioned table tpcds.reason_p:
gaussdb=# CREATE TABLE tpcds.reason_p
(
  r_reason_sk integer,
  r_reason_id character(16),
  r_reason_desc character(100)
)
PARTITION BY RANGE (r_reason_sk)
(
  partition P_05_BEFORE values less than (05),
  partition P_15 values less than (15),
  partition P_25 values less than (25),
  partition P_35 values less than (35),
  partition P_45_AFTER values less than (MAXVALUE)
)
;

-- Insert data.
gaussdb=# INSERT INTO tpcds.reason_p values(3,'AAAAAAAABAAAAAAA','reason 1'),(10,'AAAAAAAABAAAAAAA','reason 2'),(4,'AAAAAAAABAAAAAAA','reason 3'),(10,'AAAAAAAABAAAAAAA','reason 4'),(10,'AAAAAAAABAAAAAAA','reason 5'),(20,'AAAAAAAACAAAAAAA','reason 6'),(30,'AAAAAAAACAAAAAAA','reason 7');

-- Example of the PARTITION clause: Obtain data from the P_05_BEFORE partition in the tpcds.reason_p table.
gaussdb=# SELECT * FROM tpcds.reason_p PARTITION (P_05_BEFORE);
 r_reason_sk |   r_reason_id    |   r_reason_desc                   
-------------+------------------+------------------------------------
           3 | AAAAAAAABAAAAAAA | reason 1
           4 | AAAAAAAABAAAAAAA | reason 3                          
(2 rows)

-- Example of the GROUP BY clause: Group records in the tpcds.reason_p table by r_reason_id, and count the number of records in each group.
gaussdb=# SELECT COUNT(*),r_reason_id FROM tpcds.reason_p GROUP BY r_reason_id;
 count |   r_reason_id    
-------+------------------
     2 | AAAAAAAACAAAAAAA
     5 | AAAAAAAABAAAAAAA
(2 rows)

-- Example of the GROUP BY CUBE clause: Filter data based on query conditions, and group the results.
gaussdb=# SELECT * FROM tpcds.reason GROUP BY  CUBE (r_reason_id,r_reason_sk,r_reason_desc);

-- Example of the GROUP BY GROUPING SETS clause: Filter data based on query conditions, and group the results.
gaussdb=# SELECT * FROM tpcds.reason GROUP BY  GROUPING SETS ((r_reason_id,r_reason_sk),r_reason_desc);

-- Example of the HAVING clause: Group records in the tpcds.reason_p table by r_reason_id, count the number of records in each group, and display only values whose number of r_reason_id is greater than 2.
gaussdb=# SELECT COUNT(*) c,r_reason_id FROM tpcds.reason_p GROUP BY r_reason_id HAVING c>2;
 c |   r_reason_id    
---+------------------
 5 | AAAAAAAABAAAAAAA
(1 row)

-- Example of the IN clause: Group records in the tpcds.reason_p table by r_reason_id, count the number of records in each group, and display only the numbers of records whose r_reason_id is AAAAAAAABAAAAAAA or AAAAAAAADAAAAAAA.
gaussdb=# SELECT COUNT(*),r_reason_id FROM tpcds.reason_p GROUP BY r_reason_id HAVING r_reason_id IN('AAAAAAAABAAAAAAA','AAAAAAAADAAAAAAA'); 
count |   r_reason_id    
-------+------------------
     5 | AAAAAAAABAAAAAAA
(1 row)

-- Example of the INTERSECT clause: Query records whose r_reason_id is AAAAAAAABAAAAAAA and whose r_reason_sk is smaller than 5.
gaussdb=# SELECT * FROM tpcds.reason_p WHERE r_reason_id='AAAAAAAABAAAAAAA' INTERSECT SELECT * FROM tpcds.reason_p WHERE r_reason_sk<5;
 r_reason_sk |   r_reason_id    |     r_reason_desc                 
-------------+------------------+------------------------------------
           4 | AAAAAAAABAAAAAAA | reason 3                           
           3 | AAAAAAAABAAAAAAA | reason 1                           
(2 rows)

-- Example of the EXCEPT clause: Query records whose r_reason_id is AAAAAAAABAAAAAAA and whose r_reason_sk is greater than or equal to 4.
gaussdb=# SELECT * FROM tpcds.reason_p WHERE r_reason_id='AAAAAAAABAAAAAAA' EXCEPT SELECT * FROM tpcds.reason_p WHERE r_reason_sk<4;
r_reason_sk |   r_reason_id    |      r_reason_desc                  
-------------+------------------+------------------------------------
          10 | AAAAAAAABAAAAAAA | reason 5                          
          10 | AAAAAAAABAAAAAAA | reason 4                          
           4 | AAAAAAAABAAAAAAA | reason 3                          
          10 | AAAAAAAABAAAAAAA | reason 2                          
(4 rows)

-- Specify the operator (+) in the WHERE clause to indicate a left join.
gaussdb=# select t1.sr_item_sk ,t2.c_customer_id from store_returns t1, customer t2 where t1.sr_customer_sk  = t2.c_customer_sk(+) 
order by 1 desc limit 1;
 sr_item_sk | c_customer_id
------------+---------------
      18000 |
(1 row)

-- Specify the operator (+) in the WHERE clause to indicate a right join.
gaussdb=# select t1.sr_item_sk ,t2.c_customer_id from store_returns t1, customer t2 where t1.sr_customer_sk(+)  = t2.c_customer_sk 
order by 1 desc limit 1;
 sr_item_sk |  c_customer_id
------------+------------------
            | AAAAAAAAJNGEBAAA
(1 row)

-- Specify the operator (+) in the WHERE clause to indicate a left join and add a join condition.
gaussdb=# select t1.sr_item_sk ,t2.c_customer_id from store_returns t1, customer t2 where t1.sr_customer_sk  = t2.c_customer_sk(+) and t2.c_customer_sk(+) < 1 order by 1  limit 1;
 sr_item_sk | c_customer_id
------------+---------------
          1 |
(1 row)

-- If the operator (+) is specified in the WHERE clause, do not use expressions connected through AND/OR.
gaussdb=# select t1.sr_item_sk ,t2.c_customer_id from store_returns t1, customer t2 where not(t1.sr_customer_sk  = t2.c_customer_sk(+) and t2.c_customer_sk(+) < 1);
ERROR:  Operator "(+)" can not be used in nesting expression.
LINE 1: ...tomer_id from store_returns t1, customer t2 where not(t1.sr_...
                                                             ^
-- If the operator (+) is specified in the WHERE clause which does not support expression macros, an error will be reported.
gaussdb=# select t1.sr_item_sk ,t2.c_customer_id from store_returns t1, customer t2 where (t1.sr_customer_sk  = t2.c_customer_sk(+))::bool;
ERROR:  Operator "(+)" can only be used in common expression.

-- If the operator (+) is specified on both sides of an expression in the WHERE clause, an error will be reported.
gaussdb=# select t1.sr_item_sk ,t2.c_customer_id from store_returns t1, customer t2 where t1.sr_customer_sk(+)  = t2.c_customer_sk(+);
ERROR:  Operator "(+)" can't be specified on more than one relation in one join condition
HINT:  "t1", "t2"...are specified Operator "(+)" in one condition.

-- Delete the table.
gaussdb=# DROP TABLE tpcds.reason_p;

-- Example of a WITH RECURSIVE query: Calculate the accumulated value from 1 to 100.
gaussdb=# WITH RECURSIVE t1(a) as (
 select 100
),
t(n) AS (
    VALUES (1)
  UNION ALL
    SELECT n+1 FROM t WHERE n < (select max(a) from t1)
)
SELECT sum(n) FROM t;
 sum
------
 5050
(1 row)

-- Example of the UNPIVOT clause: Convert the math and phy columns in the table p1 to the rows (class, score).
gaussdb=# CREATE TABLE p1(id int, math int, phy int);
gaussdb=# INSERT INTO p1 values(1,20,30);
gaussdb=# INSERT INTO p1 values(2,30,40);
gaussdb=# INSERT INTO p1 values(3,40,50);
gaussdb=# SELECT * FROM p1;
 id | math | phy
----+------+-----
  1 |   20 |  30
  2 |   30 |  40
  3 |   40 |  50
(3 rows)

gaussdb=# SELECT * FROM p1 UNPIVOT(score FOR class IN(math, phy));
 id | class | score
----+-------+-------
  1 | MATH  |    20
  1 | PHY   |    30
  2 | MATH  |    30
  2 | PHY   |    40
  3 | MATH  |    40
  3 | PHY   |    50
(6 rows)

-- Example of the PIVOT clause: Convert the rows (class, score) in the table p2 to the math and phy columns.
gaussdb=# CREATE TABLE p2(id int, class varchar(10), score int);
gaussdb=# INSERT INTO p2 SELECT * FROM p1 UNPIVOT(score FOR class IN(math, phy));
gaussdb=# SELECT * FROM p2;
 id | class | score
----+-------+-------
  1 | MATH  |    20
  1 | PHY   |    30
  2 | MATH  |    30
  2 | PHY   |    40
  3 | MATH  |    40
  3 | PHY   |    50
(6 rows)

gaussdb=# SELECT * FROM p2 PIVOT(max(score) FOR class IN ('MATH', 'PHY'));
 id | 'MATH' | 'PHY'
----+--------+-------
  1 |     20 |    30
  3 |     40 |    50
  2 |     30 |    40
(3 rows)

-- Delete the table.
gaussdb=# DROP TABLE p1, p2, tpcds.reason;

-- Delete a schema.
gaussdb=# DROP SCHEMA tpcds CASCADE;

        

      

    
   

Parent topic: SQL Syntax

Previous topic: SAVEPOINT

Next topic: SELECT INTO

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