Column names when exporting ORC files from hive server 2 using beeline

Question

I am facing a problem where exporting results from hive server 2 to ORC files show some kind of default column names (e.g. _col0, _col1, _col2) instead of the original ones created in hive. We are using pretty much default components from HDP-2.6.3.0.

I am also wondering if the below issue is related:

https://issues.apache.org/jira/browse/HIVE-4243

Below are the steps we are taking:

Connecting:

export SPARK_HOME=/usr/hdp/current/spark2-client
beeline
!connect jdbc:hive2://HOST1:2181,HOST2:2181,HOST2:2181/;serviceDiscoveryMode=zooKeeper;zooKeeperNamespace=hiveserver2

Creating test table and inserting sample values:

create table test(str string);
insert into test values ('1');
insert into test values ('2');
insert into test values ('3');

Running test query:

select * from test;
+-----------+--+
| test.str  |
+-----------+--+
| 1         |
| 2         |
| 3         |
+-----------+--+

Exporting as ORC:

insert overwrite directory 'hdfs://HOST1:8020/tmp/test' stored as orc select * from test;

Getting the results:

hdfs dfs -get /tmp/test/000000_0 test.orc

Checking the results:

java -jar orc-tools-1.4.1-uber.jar data test.orc
Processing data file test.orc [length: 228]
{"_col0":"1"}
{"_col0":"2"}
{"_col0":"3"}

java -jar orc-tools-1.4.1-uber.jar meta test.orc
Processing data file test.orc [length: 228]
Structure for test.orc
File Version: 0.12 with HIVE_13083
Rows: 2
Compression: SNAPPY
Compression size: 262144
Type: struct<_col0:string>

Stripe Statistics:
  Stripe 1:
    Column 0: count: 2 hasNull: false
    Column 1: count: 2 hasNull: false min: 1 max: 3 sum: 2

File Statistics:
  Column 0: count: 2 hasNull: false
  Column 1: count: 2 hasNull: false min: 1 max: 3 sum: 2

Stripes:
  Stripe: offset: 3 data: 11 rows: 2 tail: 60 index: 39
    Stream: column 0 section ROW_INDEX start: 3 length 11
    Stream: column 1 section ROW_INDEX start: 14 length 28
    Stream: column 1 section DATA start: 42 length 5
    Stream: column 1 section LENGTH start: 47 length 6
    Encoding column 0: DIRECT
    Encoding column 1: DIRECT_V2

File length: 228 bytes
Padding length: 0 bytes
Padding ratio: 0%

Looking at the results I can see _col0 as the column name while expecting the original str.

Any ideas on what I am missing?

Update

I noticed that the connection from beeline was going to hive 1.x, and not 2.x as wanted. I changed the connection to the Hive Server 2 Interactive URL:

Connected to: Apache Hive (version 2.1.0.2.6.3.0-235)
Driver: Hive JDBC (version 1.21.2.2.6.3.0-235)
Transaction isolation: TRANSACTION_REPEATABLE_READ

And tried again with the same sample. It even prints out the schema correctly:

INFO  : Returning Hive schema: Schema(fieldSchemas:[FieldSchema(name:test.str, type:string, comment:null)], properties:null)

But still no luck in getting it to the ORC file.

Answer 1

Solution

You need to enable Hive LLAP (Interactive SQL) in Ambari, then change the connection string you are using. For example, my connection became jdbc:hive2://.../;serviceDiscoveryMode=zooKeeper;zooKeeperNamespace=hiveserver2-hive2

Note the additional "-hive2" at the end of the URL. Here is a tutorial vid from hortonworks.

"Proof"

After connecting to the updated Hive endpoint, I ran

create table t_orc(customer string, age int) stored as orc;
insert into t_orc values('bob', 12),('kate', 15);

Then

~$ hdfs dfs -copyToLocal /apps/hive/warehouse/t_orc/000000_0 ~/tmp/orc/hive2.orc 
~$ orc-metadata tmp/orc/hive2.orc 
{ "name": "tmp/orc/hive2.orc",
  "type": "struct<customer:string,age:int>",
  "rows": 2,
  "stripe count": 1,
  "format": "0.12", "writer version": "HIVE-13083",
  "compression": "zlib", "compression block": 262144,
  "file length": 305,
  "content": 139, "stripe stats": 46, "footer": 96, "postscript": 23,
  "row index stride": 10000,
  "user metadata": {
  },
  "stripes": [
    { "stripe": 0, "rows": 2,
      "offset": 3, "length": 136,
      "index": 67, "data": 23, "footer": 46
    }
  ]
}

Where orc-metadata is a tool distributed by the ORC repo on github.