Do you mean I implement a new rowCount method in Aggregation Client Class.
I cannot understand, could u illustrate with a code sample Ram? Thanks, > Date: Tue, 25 Dec 2012 00:21:14 +0530 > Subject: Re: Hbase Count Aggregate Function > From: [email protected] > To: [email protected] > > Hi > You could have custom filter implemented which is similar to > FirstKeyOnlyfilter. > Implement the filterKeyValue method such that it should match your keyvalue > (the specific qualifier that you are looking for). > > Deploy it in your cluster. It should work. > > Regards > Ram > > On Mon, Dec 24, 2012 at 10:35 PM, Dalia Sobhy > <[email protected]>wrote: > > > > > So do you have a suggestion how to enable/work the filter? > > > > > Date: Mon, 24 Dec 2012 22:22:49 +0530 > > > Subject: Re: Hbase Count Aggregate Function > > > From: [email protected] > > > To: [email protected] > > > > > > Okie, seeing the shell script and the code I feel that while you use this > > > counter, the user's filter is not taken into account. > > > It adds a FirstKeyOnlyFilter and proceeds with the scan. :(. > > > > > > Regards > > > Ram > > > > > > On Mon, Dec 24, 2012 at 10:11 PM, Dalia Sobhy < > > [email protected]>wrote: > > > > > > > > > > > yeah scan gives the correct number of rows, while count returns the > > total > > > > number of rows. > > > > > > > > Both are using the same filter, I even tried it using Java API, using > > row > > > > count method. > > > > > > > > rowCount = aggregationClient.rowCount(TABLE_NAME, null, scan); > > > > > > > > I get the total number of rows not the number of rows filtered. > > > > > > > > So any idea ?? > > > > > > > > Thanks Ram :) > > > > > > > > > Date: Mon, 24 Dec 2012 21:57:54 +0530 > > > > > Subject: Re: Hbase Count Aggregate Function > > > > > From: [email protected] > > > > > To: [email protected] > > > > > > > > > > So you find that scan with a filter and count with the same filter is > > > > > giving you different results? > > > > > > > > > > Regards > > > > > Ram > > > > > > > > > > On Mon, Dec 24, 2012 at 8:33 PM, Dalia Sobhy < > > [email protected] > > > > >wrote: > > > > > > > > > > > > > > > > > Dear all, > > > > > > > > > > > > I have 50,000 row with diagnosis qualifier = "cardiac", and another > > > > 50,000 > > > > > > rows with "renal". > > > > > > > > > > > > When I type this in Hbase shell, > > > > > > > > > > > > import org.apache.hadoop.hbase.filter.CompareFilter > > > > > > import org.apache.hadoop.hbase.filter.SingleColumnValueFilter > > > > > > import org.apache.hadoop.hbase.filter.SubstringComparator > > > > > > import org.apache.hadoop.hbase.util.Bytes > > > > > > > > > > > > scan 'patient', { COLUMNS => "info:diagnosis", FILTER => > > > > > > SingleColumnValueFilter.new(Bytes.toBytes('info'), > > > > > > Bytes.toBytes('diagnosis'), > > > > > > CompareFilter::CompareOp.valueOf('EQUAL'), > > > > > > SubstringComparator.new('cardiac'))} > > > > > > > > > > > > Output = 50,000 row > > > > > > > > > > > > import org.apache.hadoop.hbase.filter.CompareFilter > > > > > > import org.apache.hadoop.hbase.filter.SingleColumnValueFilter > > > > > > import org.apache.hadoop.hbase.filter.SubstringComparator > > > > > > import org.apache.hadoop.hbase.util.Bytes > > > > > > > > > > > > count 'patient', { COLUMNS => "info:diagnosis", FILTER => > > > > > > SingleColumnValueFilter.new(Bytes.toBytes('info'), > > > > > > Bytes.toBytes('diagnosis'), > > > > > > CompareFilter::CompareOp.valueOf('EQUAL'), > > > > > > SubstringComparator.new('cardiac'))} > > > > > > Output = 100,000 row > > > > > > > > > > > > Even though I tried it using Hbase Java API, Aggregation Client > > > > Instance, > > > > > > and I enabled the Coprocessor aggregation for the table. > > > > > > rowCount = aggregationClient.rowCount(TABLE_NAME, null, scan) > > > > > > > > > > > > Also when measuring the improved performance on case of adding more > > > > nodes > > > > > > the operation takes the same time. > > > > > > > > > > > > So any advice please? > > > > > > > > > > > > I have been throughout all this mess from a couple of weeks > > > > > > > > > > > > Thanks, > > > > > > > > > > > >
