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From cem <cayiro...@gmail.com>
Subject data clean up problem
Date Tue, 28 May 2013 18:46:18 GMT
Hi Experts,

We have general problem about cleaning up data from the disk. I need to
free the disk space after retention period and the customer wants to
dimension the disk space base on that.

After running multiple performance tests with TTL of 1 day we saw that the
compaction couldn't keep up with the request rate. Disks were getting full
after 3 days. There were also a lot of sstables that are older than 1 day
after 3 days.

Things that we tried:

-Change the compaction strategy to leveled. (helped a bit but not much)

-Use big sstable size (10G) with leveled compaction to have more aggressive
compaction.(helped a bit but not much)

-Upgrade Cassandra from 1.0 to 1.2 to use TTL histograms (didn't help at
all since it has key overlapping estimation algorithm that generates %100
match. Although we don't have...)

Our column family structure is like this:

Event_data_cf: (we store event data. Event_id  is randomly generated and
each event has attributes like location=london)

row                  data

event id          data blob

timeseries_cf: (key is the attribute that we want to index. It can be
location=london, we didnt use secondary indexes because the indexes are
dynamic.)

row                  data

index key       time series of event id (event1_id, event2_id….)

timeseries_inv_cf: (this is used for removing event by event row key. )

row                  data

event id          set of index keys

Candidate Solution: Implementing time range partitions.

Each partition will have column family set and will be managed by client.

Suppose that you want to have 7 days retention period. Then you can
configure the partition size as 1 day and have 7 active partitions at any
time. Then you can drop inactive partitions (older that 7 days). Dropping
will immediate remove the data from the disk. (With proper Cassandra.yaml
configuration)

Storing an event:

Find the current partition p1

store to event_data to Event_data_cf_p1

store to indexes to timeseries_cff_p1

store to inverted indexes to timeseries_inv_cf_p1


A time range query with an index:

Find the all partitions belongs to that time range

Do read starting from the first partition until you reach to limit

.....

Could you please provide your comments and concerns ?

Is there any other option that we can try?

What do you think about the candidate solution?

Does anyone have the same issue? How would you solve it in another way?


Thanks in advance!

Cem

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