Hi Quizhuang, Right now, char is not supported in DDL. Can you try varchar or string?
Thanks, Yin On Mon, Feb 16, 2015 at 10:39 PM, Qiuzhuang Lian <qiuzhuang.l...@gmail.com> wrote: > Hi, > > I am not sure this has been reported already or not, I run into this error > under spark-sql shell as build from newest of spark git trunk, > > spark-sql> describe qiuzhuang_hcatlog_import; > 15/02/17 14:38:36 ERROR SparkSQLDriver: Failed in [describe > qiuzhuang_hcatlog_import] > org.apache.spark.sql.sources.DDLException: Unsupported dataType: [1.1] > failure: ``varchar'' expected but identifier char found > > char(32) > ^ > at org.apache.spark.sql.sources.DDLParser.parseType(ddl.scala:52) > at > > org.apache.spark.sql.hive.MetastoreRelation$SchemaAttribute.toAttribute(HiveMetastoreCatalog.scala:664) > at > > org.apache.spark.sql.hive.MetastoreRelation$$anonfun$23.apply(HiveMetastoreCatalog.scala:674) > at > > org.apache.spark.sql.hive.MetastoreRelation$$anonfun$23.apply(HiveMetastoreCatalog.scala:674) > at > > scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244) > at > > scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244) > at scala.collection.Iterator$class.foreach(Iterator.scala:727) > at scala.collection.AbstractIterator.foreach(Iterator.scala:1157) > at scala.collection.IterableLike$class.foreach(IterableLike.scala:72) > at scala.collection.AbstractIterable.foreach(Iterable.scala:54) > at scala.collection.TraversableLike$class.map(TraversableLike.scala:244) > at scala.collection.AbstractTraversable.map(Traversable.scala:105) > at > > org.apache.spark.sql.hive.MetastoreRelation.<init>(HiveMetastoreCatalog.scala:674) > at > > org.apache.spark.sql.hive.HiveMetastoreCatalog.lookupRelation(HiveMetastoreCatalog.scala:185) > at org.apache.spark.sql.hive.HiveContext$$anon$2.org > > $apache$spark$sql$catalyst$analysis$OverrideCatalog$$super$lookupRelation(HiveContext.scala:234) > > As in hive 0.131, console, this commands works, > > hive> describe qiuzhuang_hcatlog_import; > OK > id char(32) > assistant_no varchar(20) > assistant_name varchar(32) > assistant_type int > grade int > shop_no varchar(20) > shop_name varchar(64) > organ_no varchar(20) > organ_name varchar(20) > entry_date string > education int > commission decimal(8,2) > tel varchar(20) > address varchar(100) > identity_card varchar(25) > sex int > birthday string > employee_type int > status int > remark varchar(255) > create_user_no varchar(20) > create_user varchar(32) > create_time string > update_user_no varchar(20) > update_user varchar(32) > update_time string > Time taken: 0.49 seconds, Fetched: 26 row(s) > hive> > > > Regards, > Qiuzhuang >