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Hive >> mail # user >> Merging different HDFS file for HIVE


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Re: Merging different HDFS file for HIVE
Hi

I am using Oozie Coordinators to schedule and run daily Oozie Workflows that contain 35-40 actions each (I use shell, java , hive and map reduce oozie actions)

So if anyone needs help and has questions please fire away…

sanjay
From: Sanjay Subramanian <[EMAIL PROTECTED]<mailto:[EMAIL PROTECTED]>>
Reply-To: "[EMAIL PROTECTED]<mailto:[EMAIL PROTECTED]>" <[EMAIL PROTECTED]<mailto:[EMAIL PROTECTED]>>
Date: Friday, July 26, 2013 6:23 PM
To: "[EMAIL PROTECTED]<mailto:[EMAIL PROTECTED]>" <[EMAIL PROTECTED]<mailto:[EMAIL PROTECTED]>>
Subject: Re: Merging different HDFS file for HIVE

We have a similar situation like this in production…for your case case I would propose the following steps

1. Design a map reduce job (Job Output format - Text, Lzo, Snappy, your choice)
     Inputs to Mapper
     -- records from these three feeds
    Outputs from Mapper
     -- Key = <EMP1>   Value = <feed1~field1  field2  field6  field9>
     -- Key = <EMP1>   Value = <feed2~field5  field7  field10>
     -- Key = <EMP1>   Value = <feed3~field3  field4  field8>

   Reducer Output
     -- Key = <EMP1>   Value = <field1  field2  field3  field4  field5  field6  field7  field8  field9  field10>

2. (Optional) If u use LZO then u will need to run LzoIndexer

3. CREATE TABLE IF NOT EXISTS YOUR_HIVE_TABLE

4. ALTER TABLE ADD PARTITION (foo1 = , foo2 = ) LOCATION 'path/to/files'
From: Stephen Sprague <[EMAIL PROTECTED]<mailto:[EMAIL PROTECTED]>>
Reply-To: "[EMAIL PROTECTED]<mailto:[EMAIL PROTECTED]>" <[EMAIL PROTECTED]<mailto:[EMAIL PROTECTED]>>
Date: Friday, July 26, 2013 4:37 PM
To: "[EMAIL PROTECTED]<mailto:[EMAIL PROTECTED]>" <[EMAIL PROTECTED]<mailto:[EMAIL PROTECTED]>>
Subject: Re: Merging different HDFS file for HIVE

i like #2.

so you have three, say, external tables representing your three feed files. After the third and final file is loaded then join 'em all together - maybe make the table partitioned for one per day.

for example:

alter table final add partition (datekey=YYYYMMDD);
insert overwrite table final partition (datekey=YYYYMMDD)  select EMP_ID,f1,...,f10 from FF1 a join FF2 b on (a.EMP_ID=b.EMP_ID join FF3 c on (b.EMP_ID=c.EMP_ID)
Or a variation on #3.   make a view on the three tables which would look just like the select statement above.
What do you want to optimize for?
On Fri, Jul 26, 2013 at 5:30 AM, Nitin Pawar <[EMAIL PROTECTED]<mailto:[EMAIL PROTECTED]>> wrote:
Option 1 ) Use pig or oozie, write a workflow and join the files to a single file
Option 2 ) Create a temp table for each of the different file and then join them to a single table and delete temp table
Option 3 ) don't do anything, change your queries to look at three different files when they query  about different files

Wait for others to give better suggestions :)
On Fri, Jul 26, 2013 at 4:22 PM, Ramasubramanian Narayanan <[EMAIL PROTECTED]<mailto:[EMAIL PROTECTED]>> wrote:
Hi,

Please help in providing solution for the below problem... this scenario is applicable in Banking atleast...

I have a HIVE table with the below structure...

Hive Table:
Field1
...
Field 10
For the above table, I will get the values for each feed in different file. You can imagine that these files belongs to same branch and will get at any time interval. I have to load into table only if I get all 3 files for the same branch. (assume that we have a common field in all the files to join)

Feed file 1 :
EMP ID
Field 1
Field 2
Field 6
Field 9

Feed File2 :
EMP ID
Field 5
Field 7
Field 10

Feed File3 :
EMP ID
Field 3
Field 4
Field 8

Now the question is,
what is the best way to make all these files to make it as a single file so that it can be placed under the HIVE structure.

regards,
Rams

--
Nitin Pawar
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NEW: Monitor These Apps!
elasticsearch, apache solr, apache hbase, hadoop, redis, casssandra, amazon cloudwatch, mysql, memcached, apache kafka, apache zookeeper, apache storm, ubuntu, centOS, red hat, debian, puppet labs, java, senseiDB