Hive alter table column fails when it has struct column - hive

Question

I've created hive external table.
CREATE EXTERNAL TABLE test_db.test_table (
`testfield` string,
`teststruct` struct<teststructfield:string>
)
ROW FORMAT SERDE
'org.apache.hive.hcatalog.data.JsonSerDe'
STORED AS INPUTFORMAT
'org.apache.hadoop.mapred.TextInputFormat'
OUTPUTFORMAT
'org.apache.hadoop.hive.ql.io.HiveIgnoreKeyTextOutputFormat'
LOCATION
'hdfs://some/path';
hive> describe test_table;
+-------------+---------------------------------+--------------------+
| col_name | data_type | comment |
+-------------+---------------------------------+--------------------+
| testfield | string | from deserializer |
| teststruct | struct<teststructfield:string> | from deserializer |
+-------------+---------------------------------+--------------------+
and I want to alter table column. but when table has struct column (teststruct),
error occurs with < less than sign.
ALTER TABLE test_db.test_table CHANGE COLUMN testfield testfield2 string;
INFO : Semantic Analysis Completed (retrial = false)
INFO : Returning Hive schema: Schema(fieldSchemas:null, properties:null)
INFO : Concurrency mode is disabled, not creating a lock manager
INFO : Starting task [Stage-0:DDL] in serial mode
ERROR : FAILED: Execution Error, return code 1 from org.apache.hadoop.hive.ql.exec.DDLTask. Error: type expected at the position 7 of 'string:<derived from deserializer>' but '<' is found.
It succeed without struct column which has <. what should I do for this problem?

Answer 1

If nothing else helps, as a workaround you can drop/create table and recover partitions. The table is EXTERNAL and drop will not affect the data.
(1) Drop table
DROP TABLE test_db.test_table;
(2) Create table with required column name
CREATE EXTERNAL TABLE test_db.test_table (
testfield2 string,
teststruct struct<teststructfield:string>
)
PARTITIONED BY (....)
ROW FORMAT SERDE
'org.apache.hive.hcatalog.data.JsonSerDe'
LOCATION
'hdfs://some/path';
(3) Recover partitions
MSCK REPAIR TABLE test_db.test_table;
or if you are running Hive on EMR:
ALTER TABLE test_db.test_table RECOVER PARTITIONS;