[GitHub] [spark] gengliangwang edited a comment on pull request #35690: [SPARK-38335][SQL] Implement parser support for DEFAULT column values

[GitBox <gi...@apache.org>]

gengliangwang edited a comment on pull request #35690:
URL: https://github.com/apache/spark/pull/35690#issuecomment-1057620996


   Supporting default column values is very common among DBMS. However, this will be a breaking change for Spark SQL
   Currently Spark SQL
   ```
   > create table t(i int, j int);
   > insert into t values(1);
   Error in query: `default`.`t` requires that the data to be inserted have the same number of columns as the target table: target table has 2 column(s) but the inserted data has 1 column(s), including 0 partition column(s) having constant value(s).
   ```
   
   After supporting default column value:
   ```
   > create table t(i int, j int);
   > insert into t values(1);
   > select * from t;
   1	NULL
   
   > create table t2(i int, j int default 0);
   > insert into t2 values(1);
   > select * from t2;
   1	0
   ```
   
   I am +1 with the change.
   Before merging this PR, I would like to collect the opinions of more committers. We can send SPIP for voting if necessary.
   cc @cloud-fan  @dongjoon-hyun @viirya @dbtsai @huaxingao @maropu @zsxwing @wangyum @yaooqinn WDYT? 


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