更新时间:2022-05-12 GMT+08:00
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DML语法定义

DML语句

语法定义

INSERT INTO table_name [PARTITION part_spec] query

part_spec:  (part_col_name1=val1 [, part_col_name2=val2, ...])

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

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' )。两个单引号表示转移(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 '#'
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