On 11/18/2014 05:53 PM, Yanrui Hu wrote:
Adrian,
I saw that in two case, one is 54502 transactions and the other is 13966
but that is caused by capacity decrease.
And fps is transaction per second, so it's not the transactions but
transaction per second, so I don't think the total transactions
different has any problem.
Please point if my understanding is not correct.
Alright
If:
kph = kilometer per hour = kilometer/hour
100 km/1 hr = 100 km/hr
200 km/1 hr = 200 km/hr
If you cover 100 km in 1 hour you have an average rate of speed of 100
km/hr if you cover 200 km in 1 hour your average rate of speed is 200 km/hr
then
tps = transactions per second = transactions/sec
54502 transactions/600 sec = 90.84 transactions/sec
13966 transactions/600 sec = 23.28 transactions/sec
The numbers are not exactly the same as the below, but that is probably
down to rounding error. They pass the close enough rule though:) Any way
you look at it, if run a two tests over the same time period and one
does less transactions then the other you will have different
transactions rates(tps) You where asking about the why behind the
different tps rates, the answer is above. In other words you cannot
ignore the raw numbers for the transactions.
My initial plan is to know the impact if I move that db client (also a
server runs web server with restful api) out side to internet.
On Tue, Nov 18, 2014 at 10:35 PM, Adrian Klaver
<adrian.klaver@xxxxxxxxxxx <mailto:adrian.klaver@xxxxxxxxxxx>> wrote:
On 11/18/2014 12:33 AM, Yanrui Hu wrote:
I am working on a evaluation to put db client outside the
datacenter and
to know how the network impact on the business.
After several round of testing, I have a question regarding to
the two
tps result in stress output.
Test A:
Client and DB server exist in same AWS datacenter.
transaction type: Custom query
scaling factor: 500
query mode: simple
number of clients: 25
number of threads: 25
duration: 600 s
number of transactions actually processed: 54502
tps = 90.814930 (including connections establishing)
tps = 204.574432 (excluding connections establishing)
Test B:
Client and DB server exist in different AWS datacenter (west and
east).
transaction type: Custom query
scaling factor: 500
query mode: simple
number of clients: 25
number of threads: 25
duration: 600 s
number of transactions actually processed: 13966
tps = 23.235705 (including connections establishing)
tps = 42.915990 (excluding connections establishing)
Its obviously that both tps become lower if client and server do not
exist in same datacetner since the network connection have more
latency.
But I can not explain why the tps that excluding connections
establishing is changed so much.
For my understanding, tps excluding connections establishing get
rid of
the time that create socket cost. That means in above two test
cases(only network different), the tps excluding connections
establishing should be very close, right?
Not that I can see from the numbers. In the non-network case you
processed 54,502 transactions over 600s and in the network case
13,966 transactions over 600s. Even if you factor out the connection
establishment you have fewer transactions over the same time period
for the network case. So there is no way the tps can be equivalent.
As others have pointed out this due to the effect of network latency
on the processing of the queries.
You might want to take a look at the Notes section of here:
http://www.postgresql.org/__docs/9.3/static/pgbench.html
<http://www.postgresql.org/docs/9.3/static/pgbench.html>
In particular the different logging options that are available. They
may make it easier to see what is going on.
Because the database is same
and capability is same only network latency is different.
--
Best Regards,
Yanrui Hu (Ray)
--
Adrian Klaver
adrian.klaver@xxxxxxxxxxx <mailto:adrian.klaver@xxxxxxxxxxx>
--
Best Regards,
Yanrui Hu (Ray)
--
Adrian Klaver
adrian.klaver@xxxxxxxxxxx
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