cloud-fan commented on a change in pull request #23259: [SPARK-26215][SQL]
Define reserved/non-reserved keywords based on the ANSI SQL standard
URL: https://github.com/apache/spark/pull/23259#discussion_r259228427
##########
File path:
sql/catalyst/src/main/antlr4/org/apache/spark/sql/catalyst/parser/SqlBase.g4
##########
@@ -744,40 +750,69 @@ number
| MINUS? BIGDECIMAL_LITERAL #bigDecimalLiteral
;
+// NOTE: You must follow a rule below when you add a new ANTLR taken in this
file:
+// - All the ANTLR tokens = UNION(`ansiReserved`, `ansiNonReserved`) =
UNION(`reserved`, `nonReserved`)
+//
+// Let's say you add a new token `NEWTOKEN` and this is not reserved
regardless of a `spark.sql.parser.ansi.enabled`
+// value. In this case, you must add a token `NEWTOKEN` in both
`ansiNonReserved` and `nonReserved`.
+
+// A list of the reserved keywords below in Spark SQL. These keywords cannot
be used for identifiers
+// when `spark.sql.parser.ansi.enabled` = true. Currently, we only reserve the
ANSI keywords
+// that almost all the ANSI SQL standards (SQL-92, SQL-99, SQL-2003, SQL-2008,
SQL-2011, and SQL-2016)
+// and PostgreSQL reserve.
+ansiReserved
+ : ALL | AND | ANTI | ANY | AS | AUTHORIZATION | BOTH | CASE | CAST | CHECK
| COLLATE | COLUMN | CONSTRAINT | CREATE
+ | CROSS | CURRENT_DATE | CURRENT_TIME | CURRENT_TIMESTAMP | CURRENT_USER |
DISTINCT | ELSE | END | EXCEPT | FALSE
+ | FETCH | FOR | FOREIGN | FROM | FULL | GRANT | GROUP | HAVING | IN |
INNER | INTERSECT | INTO | JOIN | IS
+ | LEADING | LEFT | NATURAL | NOT | NULL | ON | ONLY | OR | ORDER | OUTER |
OVERLAPS | PRIMARY | REFERENCES | RIGHT
+ | SELECT | SEMI | SESSION_USER | SETMINUS | SOME | TABLE | THEN | TO |
TRAILING | UNION | UNIQUE | USER | USING
+ | WHEN | WHERE | WITH
+ ;
+
+// When `spark.sql.parser.ansi.enabled` = true, the `ansiNonReserved` keywords
can be used for identifiers.
+// Otherwise (`spark.sql.parser.ansi.enabled` = false), we follow the existing
Spark SQL behaviour until v3.0:
Review comment:
```
The list of the non-reserved keywords when `spark.sql.parser.ansi.enabled`
is true.
```
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