Hi, All. Currently, Spark shows different behavior when we uses CHAR types.
spark-sql> CREATE TABLE t1(a CHAR(3)); spark-sql> CREATE TABLE t2(a CHAR(3)) STORED AS ORC; spark-sql> CREATE TABLE t3(a CHAR(3)) STORED AS PARQUET; spark-sql> INSERT INTO TABLE t1 SELECT 'a '; spark-sql> INSERT INTO TABLE t2 SELECT 'a '; spark-sql> INSERT INTO TABLE t3 SELECT 'a '; spark-sql> SELECT a, length(a) FROM t1; a 3 spark-sql> SELECT a, length(a) FROM t2; a 3 spark-sql> SELECT a, length(a) FROM t3; a 2 The reason I'm asking here is that it's a little bit old default behavior of Spark `STORED AS PARQUET` in Spark. (Spark 1.6.3, too.) For me, `CREATE TABLE t1(a CHAR(3))` shows the correct one in Spark, but Parquet has been de-factor standard in Spark also. (I'm not comparing this with the other DBMS.) I'm wondering which way we need to go or want to go in Spark? Bests, Dongjoon.
