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Takeshi Yamamuro edited comment on SPARK-26905 at 6/11/20, 12:15 PM: --------------------------------------------------------------------- Ah, I got noticed that they are already reserved in the ANSI mode (the document says so, too: [https://github.com/apache/spark/blob/master/docs/sql-ref-ansi-compliance.md]); {code:java} scala> sql("SET spark.sql.ansi.enabled=false") scala> sql("create table t1 (anti int)") res10: org.apache.spark.sql.DataFrame = [] scala> sql("create table t2 (semi int)") res11: org.apache.spark.sql.DataFrame = [] scala> sql("create table t3 (minus int)") res12: org.apache.spark.sql.DataFrame = [] scala> sql("SET spark.sql.ansi.enabled=true") scala> sql("create table t4 (anti int)") org.apache.spark.sql.catalyst.parser.ParseException: no viable alternative at input 'anti'(line 1, pos 17) == SQL == create table t4 (anti int) -----------------^^^ scala> sql("create table t5 (semi int)") org.apache.spark.sql.catalyst.parser.ParseException: no viable alternative at input 'semi'(line 1, pos 17) == SQL == create table t5 (semi int) -----------------^^^ scala> sql("create table t6 (minus int)") org.apache.spark.sql.catalyst.parser.ParseException: no viable alternative at input 'minus'(line 1, pos 17) == SQL == create table t6 (minus int) -----------------^^^ {code} Actually, the Spark reserved keywords in the ANSI mode are computed by `spark-keywords-list.txt – spark-ansiNonReserved.txt – "strict non-reserved keywords"`. Yay, I think we already follow the standard SQL2016, haha was (Author: maropu): Ah, I got noticed that they are already reserved in the ANSI mode (the document says so, too: [https://github.com/apache/spark/blob/master/docs/sql-ref-ansi-compliance.md]); {code:java} scala> sql("SET spark.sql.ansi.enabled=false") scala> sql("create table t1 (anti int)") res10: org.apache.spark.sql.DataFrame = [] scala> sql("create table t2 (semi int)") res11: org.apache.spark.sql.DataFrame = [] scala> sql("create table t3 (minus int)") res12: org.apache.spark.sql.DataFrame = [] scala> sql("SET spark.sql.ansi.enabled=true") scala> sql("create table t4 (anti int)") org.apache.spark.sql.catalyst.parser.ParseException: no viable alternative at input 'anti'(line 1, pos 17) == SQL == create table t4 (anti int) -----------------^^^ scala> sql("create table t5 (semi int)") org.apache.spark.sql.catalyst.parser.ParseException: no viable alternative at input 'semi'(line 1, pos 17) == SQL == create table t5 (semi int) -----------------^^^ scala> sql("create table t6 (minus int)") org.apache.spark.sql.catalyst.parser.ParseException: no viable alternative at input 'minus'(line 1, pos 17) == SQL == create table t6 (minus int) -----------------^^^ {code} Actually, the Spark reserved keywords in the ANSI mode are computed by `spark-keywords-list.txt – spark-ansiNonReserved.txt – "strict non-reserved keywords"`. Yay, I think we already follow the standard SQL2016, haha > Revisit reserved/non-reserved keywords based on the ANSI SQL standard > --------------------------------------------------------------------- > > Key: SPARK-26905 > URL: https://issues.apache.org/jira/browse/SPARK-26905 > Project: Spark > Issue Type: Sub-task > Components: SQL > Affects Versions: 3.0.0 > Reporter: Xiao Li > Priority: Major > Attachments: spark-ansiNonReserved.txt, spark-keywords-list.txt, > spark-nonReserved.txt, spark-strictNonReserved.txt, > sql2016-02-nonreserved.txt, sql2016-02-reserved.txt, > sql2016-09-nonreserved.txt, sql2016-09-reserved.txt, > sql2016-14-nonreserved.txt, sql2016-14-reserved.txt > > -- This message was sent by Atlassian Jira (v8.3.4#803005) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org