Efficiently Storing the data in Hive

Question

How can I efficiently store data in Hive and also store and retrieve compressed data in hive? Currently I am storing it as a TextFile. I was going through Bejoy article and I found that LZO compression will be good for storing the files and also it is splittable.

I have one HiveQL Select query that is generating some output and I am storing that output somewhere so that one of my Hive table (quality) can use that data so that I can query that quality table.

Below is the quality table in which I am loading the data from the below SELECT query by making the partition I am using to overwrite table quality.

create table quality
(id bigint,
  total bigint,
  error bigint
 )
partitioned by (ds string)
row format delimited fields terminated by '\t'
stored as textfile
location '/user/uname/quality'
;

insert overwrite table quality partition (ds='20120709')
SELECT id  , count2 , coalesce(error, cast(0 AS BIGINT)) AS count1  FROM Table1;

So here currently I am storing it as a TextFile, should I make this as a Sequence file and start storing the data in LZO compression format? Or text file will be fine here also? As from the select query I will be getting some GB of data, that need to be uploaded on table quality on a daily basis.

So which way is best? Should I store the output as a TextFile or SequenceFile format (LZO compression) so that when I am querying the Hive quality table, I am getting result fasters. Means querying is faster.

Update:-

What If I am storing as a SequenceFile with Block Compression? Like below-

set mapred.output.compress=true;
set mapred.output.compression.type=BLOCK;
set mapred.output.compression.codec=org.apache.hadoop.io.compress.LzoCodec;

I need to set some other things to enable BLOCK Compression apart from above? And also I am creating Table as a SequenceFile format

Update Again

I should create the table like this below? Or some other changes need to be made to enable BLOCK compression with Sequence File?

create table lipy
( buyer_id bigint,
  total_chkout bigint,
  total_errpds bigint
 )
 partitioned by (dt string)
row format delimited fields terminated by '\t'
stored as sequencefile
location '/apps/hdmi-technology/lipy'
;

Answer 1

I have not used Hive much, but from experience with Hadoop and structured data, I was getting the best performance from SequenceFiles with BLOCK compression. The default is row compression, but it is not as efficient as BLOCK compression when you store structured data and rows are not particularly big. To switch it on I used mapred.output.compression.type=BLOCK