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I have been inserted about 15 millions of rows and 32 columns in hbase table through Map-reduce program
key-valued data eg : company= ibm ! employee= sw 
... in hbase it's look like as
row =1 column = f1: company time stamp=1123344456 value =ibm 
And while i fired the query
scan 'sample_names', {COLUMNS=>"f1:company", FILTER=>'f1'), Bytes.toBytes('company'), CompareFilter::CompareOp.valueOf('EQUAL'),"ibm")) }

it took about 360.09 seconds to fetch the data ,

can u please any one tell me how to improve the hbase query performance ?
can we reduce this query time by secondary indexing if Yes ! please suggest me how to add indexing for particular column qualifier ?

Thanks in Advance Smile | :)

[Torsten]Structure! You needed some here![/Torsten]
Posted 9-Jan-13 4:15am
Edited 9-Jan-13 4:25am
TorstenH. 9-Jan-13 9:27am
Did I get that right - you have 15 million data sets in that table with each 32 columns???


Can't you structure the DB?
Madhusudhana_reddy 9-Jan-13 12:21pm
Yep ! have the 15 millions of data sets with each 32 columns , can u please tell me to structure the DB ? bye the way is that way of inserting data also matters or wat while we are fetching the data from tables ?... please suggest me ... Thanx for ur quick feed back :) :)
Madhusudhana_reddy 10-Jan-13 13:10pm
what would be best query time for the 5 million records in hbase , like when i ran the single columnvalue filter query for the evendate = 01/5/2010 , it gave about ** 36 records out of 5 million records, and taken 154.09 seconds **, so please suggest me to improve the query performance :) .....

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