They are multiple ways of doing this without relying any vendors release.
1) Using hive EXPORT/IMPORT utility
EXPORT TABLE table_or_partition TO hdfs_path;
IMPORT [[EXTERNAL] TABLE table_or_partition] FROM hdfs_path [LOCATION
[table_location]];
2) This works for individual tables but you can easily write a generic
script to pick up name of tables for a given database from Hive metadata.
example
SELECT
t.owner AS Owner
, d.NAME AS DBName
, t.TBL_NAME AS Tablename
, TBL_TYPE
FROM tbls t, dbs d
WHERE
t.DB_ID = d.DB_ID
AND
TBL_TYPE IN ('MANAGED_TABLE','EXTERNAL_TABLE')
ORDER BY 1,2
Then a Linux shell script will table 5 min max to create and you have full
control of the code. You can even do multiple EXPORT/IMPORT at the same
time.
3) Easier to create a shared NFS mount between PROD and UAT so you can put
the tables data and metadata on this NFS
2) Use Spark shell script to get data via JDBC from the source database and
push schema and data into the new env. Again this is no different from
getting the underlying data from Oracle or Sybase database and putting in
Hive
3) Using vendor's product to do the same. I am not sure vendors do
parallelise this sort of things.
HTH
Dr Mich Talebzadeh
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On 25 May 2016 at 14:50, Suresh Kumar Sethuramaswamy <rock...@gmail.com>
wrote:
> Hi
>
> If you are using CDH, via CM , Backup->replications you could do inter
> cluster hive data transfer including metadata
>
> Regards
> Suresh
>
>
> On Wednesday, May 25, 2016, mahender bigdata <mahender.bigd...@outlook.com>
> wrote:
>
>> Any Document on it.
>>
>> On 4/8/2016 6:28 PM, Will Du wrote:
>>
>> did you try export and import statement in HQL?
>>
>> On Apr 8, 2016, at 6:24 PM, Ashok Kumar <ashok34...@yahoo.com> wrote:
>>
>> Hi,
>>
>> Anyone has suggestions how to create and copy Hive and Spark tables from
>> Production to UAT.
>>
>> One way would be to copy table data to external files and then move the
>> external files to a local target directory and populate the tables in
>> target Hive with data.
>>
>> Is there an easier way of doing so?
>>
>> thanks
>>
>>
>>
>>
>>
