Did you read the PDF Stu sent over, start to finish? There are several different approaches described there.
With Cassandra, what we found works best for pagination:
* Keep a separate 'total_records' count and increment/decrement it on every insert/delete
* When getting slices, pass 'last seen' as the 'from' and keep the 'to' empty. Pass the number of records you want to show per page in the 'count'.
* Avoid letting user skip to page X, using Next/Prev/First/Last only (same way GMail does it)
Michal Augustın wrote:I know that "Prev/Next" is good solution for web applications. But when I want to access data from another application or when I want to access pages randomly...
I don't know the internal structure of memtables etc., so I don't know if columns in row are indexable. If now, then I just want to transfer my workaround to server (to avoid huge network traffic)...
2010/9/5 Stu Hood <email@example.com>
Cassandra supports the recommended approach from: http://www.percona.com/ppc2009/PPC2009_mysql_pagination.pdf
For large numbers of items, skip + limit is extremely inefficent.
From: "Michal Augustın" <firstname.lastname@example.org>
Sent: Sunday, September 5, 2010 5:39am
Subject: skip + limit support in GetSlice
probably this is feature request. Simply, I would like to have support for
standard pagination (skip + limit) in GetSlice Thrift method. Is this
feature on the road map?
Now, I have to perform GetSlice call, that starts on "" and "limit" is set
to "skip" value. Then I read the last column name returned and subsequently
perform the final GetSlice call - I use the last column name as "start" and
set "limit" to "limit" value.
This workaround is not very efficient when I need to skip a lot of columns
(so "skip" is high) - then a lot of data must be transferred via network. So
I think that support for Skip in GetSlice would be very useful (to avoid
high network traffic).
The implementation could be very straightforward (same as the workaround) or
maybe it could be more efficient - I think that whole row (so all columns)
must fit into memory so if we have all columns in memory...