DQL语法定义
DQL语句
- 语法定义
query: values | { select | selectWithoutFrom | query UNION [ ALL ] query | query EXCEPT query | query INTERSECT query } [ ORDER BY orderItem [, orderItem ]* ] [ LIMIT { count | ALL } ] [ OFFSET start { ROW | ROWS } ] [ FETCH { FIRST | NEXT } [ count ] { ROW | ROWS } ONLY] orderItem: expression [ ASC | DESC ] select: SELECT [ ALL | DISTINCT ] { * | projectItem [, projectItem ]* } FROM tableExpression [ WHERE booleanExpression ] [ GROUP BY { groupItem [, groupItem ]* } ] [ HAVING booleanExpression ] [ WINDOW windowName AS windowSpec [, windowName AS windowSpec ]* ] selectWithoutFrom: SELECT [ ALL | DISTINCT ] { * | projectItem [, projectItem ]* } projectItem: expression [ [ AS ] columnAlias ] | tableAlias . * tableExpression: tableReference [, tableReference ]* | tableExpression [ NATURAL ] [ LEFT | RIGHT | FULL ] JOIN tableExpression [ joinCondition ] joinCondition: ON booleanExpression | USING '(' column [, column ]* ')' tableReference: tablePrimary [ matchRecognize ] [ [ AS ] alias [ '(' columnAlias [, columnAlias ]* ')' ] ] tablePrimary: [ TABLE ] [ [ catalogName . ] schemaName . ] tableName | LATERAL TABLE '(' functionName '(' expression [, expression ]* ')' ')' | UNNEST '(' expression ')' values: VALUES expression [, expression ]* groupItem: expression | '(' ')' | '(' expression [, expression ]* ')' | CUBE '(' expression [, expression ]* ')' | ROLLUP '(' expression [, expression ]* ')' | GROUPING SETS '(' groupItem [, groupItem ]* ')' windowRef: windowName | windowSpec windowSpec: [ windowName ] '(' [ ORDER BY orderItem [, orderItem ]* ] [ PARTITION BY expression [, expression ]* ] [ RANGE numericOrIntervalExpression {PRECEDING} | ROWS numericExpression {PRECEDING} ] ')' matchRecognize: MATCH_RECOGNIZE '(' [ PARTITION BY expression [, expression ]* ] [ ORDER BY orderItem [, orderItem ]* ] [ MEASURES measureColumn [, measureColumn ]* ] [ ONE ROW PER MATCH ] [ AFTER MATCH ( SKIP TO NEXT ROW | SKIP PAST LAST ROW | SKIP TO FIRST variable | SKIP TO LAST variable | SKIP TO variable ) ] PATTERN '(' pattern ')' [ WITHIN intervalLiteral ] DEFINE variable AS condition [, variable AS condition ]* ')' measureColumn: expression AS alias pattern: patternTerm [ '|' patternTerm ]* patternTerm: patternFactor [ patternFactor ]* patternFactor: variable [ patternQuantifier ] patternQuantifier: '*' | '*?' | '+' | '+?' | '?' | '??' | '{' { [ minRepeat ], [ maxRepeat ] } '}' ['?'] | '{' repeat '}'
- 注意事项
- SecMaster SQL兼容Flink 1.7.2 版本SQL语法。
- Flink SQL 对于标识符(表、属性、函数名)有类似于 Java 的词法约定:
- 不管是否引用标识符,都保留标识符的大小写。
- 且标识符需区分大小写。
- 与 Java 不一样的地方在于,通过反引号,可以允许标识符带有非字母的字符(如:"SELECT a AS `my field` FROM t")。
字符串文本常量需要被单引号包起来(如 SELECT 'Hello World' )。两个单引号表示转义(如 SELECT 'It''s me.')。字符串文本常量支持 Unicode 字符,如需明确使用 Unicode 编码,请使用以下语法:
- 使用反斜杠(\)作为转义字符(默认):SELECT U&'\263A'
- 使用自定义的转义字符: SELECT U&'#263A' UESCAPE '#'
- 慎用正则函数(REGEXP)
正则表达式是非常耗时的操作,对比加减乘除通常有百倍的性能开销,而且正则表达式在某些极端情况下可能会进入无限循环,导致作业阻塞,因此建议使用LIKE。正则函数包括:
REGEXP
REGEXP_REPLACE