Performance degradation of inserts when database size grows

Hi, guys.

I have following environment configuration

- Postgres 8.4.7 with following postresql.conf settings modified:

listen_addresses = '*'

max_connections = 100

shared_buffers = 2048MB

max_prepared_transactions = 100

wal_buffers = 1024kB

checkpoint_segments = 64

checkpoint_completion_target = 0.8

log_checkpoints = on

- Two databases. Let's call them db_1 and db_2

- J2EE application server that performs inserts into databases defined
above. (distribution transactions are used).

- All constraints and indexes are on.

- JMeter that acts as HTTP client and sends requests to server causing it to
insert rows. (case of new users registration)

After running scenario scenario described above (with 10 concurrent threads)
I have observed following behavior:

For the first time everything is fine and J2EE server handles about 700
requests/sec (about 2500 inserts into several tables per second). But after
some amount of time I observe performance degradation. In general it looks
like the following:

Total number of requests passed; Requests per second;

382000; 768;

546000; 765;

580000; 723;

650000; 700;

671000; 656;

700000; 628;

Checkpoint logging gives me the following:

2011-05-17 18:55:51 NOVST LOG: checkpoint starting: xlog

2011-05-17 18:57:20 NOVST LOG: checkpoint complete: wrote 62861 buffers
(24.0%); 0 transaction log file(s) added, 0 removed, 0 recycled;
write=89.196 s, sync=0.029 s, total=89.242 s

2011-05-17 18:57:47 NOVST LOG: checkpoint starting: xlog

2011-05-17 18:59:02 NOVST LOG: checkpoint complete: wrote 83747 buffers
(31.9%); 0 transaction log file(s) added, 0 removed, 64 recycled;
write=75.001 s, sync=0.043 s, total=75.061 s

2011-05-17 18:59:29 NOVST LOG: checkpoint starting: xlog

2011-05-17 19:00:30 NOVST LOG: checkpoint complete: wrote 97341 buffers
(37.1%); 0 transaction log file(s) added, 0 removed, 64 recycled;
write=60.413 s, sync=0.050 s, total=60.479 s

2011-05-17 19:00:55 NOVST LOG: checkpoint starting: xlog

2011-05-17 19:01:48 NOVST LOG: checkpoint complete: wrote 110149 buffers
(42.0%); 0 transaction log file(s) added, 0 removed, 64 recycled;
write=52.285 s, sync=0.072 s, total=52.379 s

2011-05-17 19:02:11 NOVST LOG: checkpoint starting: xlog

2011-05-17 19:02:58 NOVST LOG: checkpoint complete: wrote 120003 buffers
(45.8%); 0 transaction log file(s) added, 0 removed, 64 recycled;
write=46.766 s, sync=0.082 s, total=46.864 s

2011-05-17 19:03:20 NOVST LOG: checkpoint starting: xlog

2011-05-17 19:04:18 NOVST LOG: checkpoint complete: wrote 122296 buffers
(46.7%); 0 transaction log file(s) added, 0 removed, 64 recycled;
write=57.795 s, sync=0.054 s, total=57.867 s

2011-05-17 19:04:38 NOVST LOG: checkpoint starting: xlog

2011-05-17 19:05:34 NOVST LOG: checkpoint complete: wrote 128165 buffers
(48.9%); 0 transaction log file(s) added, 0 removed, 64 recycled;
write=55.061 s, sync=0.087 s, total=55.188 s

2011-05-17 19:05:53 NOVST LOG: checkpoint starting: xlog

2011-05-17 19:06:51 NOVST LOG: checkpoint complete: wrote 138508 buffers
(52.8%); 0 transaction log file(s) added, 0 removed, 64 recycled;
write=57.919 s, sync=0.106 s, total=58.068 s

2011-05-17 19:07:08 NOVST LOG: checkpoint starting: xlog

2011-05-17 19:08:21 NOVST LOG: checkpoint complete: wrote 132485 buffers
(50.5%); 0 transaction log file(s) added, 0 removed, 64 recycled;
write=72.949 s, sync=0.081 s, total=73.047 s

2011-05-17 19:08:40 NOVST LOG: checkpoint starting: xlog

2011-05-17 19:09:48 NOVST LOG: checkpoint complete: wrote 139542 buffers
(53.2%); 0 transaction log file(s) added, 0 removed, 64 recycled;
write=68.193 s, sync=0.107 s, total=68.319 s

2011-05-17 19:10:06 NOVST LOG: checkpoint starting: xlog

2011-05-17 19:11:31 NOVST LOG: checkpoint complete: wrote 137657 buffers
(52.5%); 0 transaction log file(s) added, 0 removed, 64 recycled;
write=84.575 s, sync=0.047 s, total=84.640 s

Also I observed more heavy IO from iostat utility.

So my questions are:

1. How does database size affect insert performance?

2. Why does number of written buffers increase when database size grows?

3. How can I further analyze this problem?

--
Best regards.