Good to hear that you got to the root cause, Viktor!
Do you have any suggestions for extra performance/troubleshooting
tips/tricks that you had to learn hard way as long as the information was
not documented?
-
Denis
On Fri, Dec 6, 2019 at 4:11 AM Victor wrote:
> Update,
>
> 1. So there were
Update,
1. So there were 2 issues, there was old batch processing app that
periodically ran, that loaded lot of data in memory. Which i think was
causing some memory contention. So i shut that down for me tests.
2. Thread dumps showed some odd wait times between 2 get calls. I had
overtly
As you have 4 nodes on the same machine now, you have a lot of context
switching, probably all the nodes just competing for CPU resources with each
other.
Evgenii
--
Sent from: http://apache-ignite-users.70518.x6.nabble.com/
Hello!
Not if there's enough parallelism, since nodes are not busy while requests
do round trips.
I recommend gathering jstack stack traces from all nodes, seeing what
threads are up to.
Regards,
--
Ilya Kasnacheev
чт, 28 нояб. 2019 г. в 21:58, Victor :
> Not sure i follow. The data is on
Not sure i follow. The data is on server node/s. Even for a single/multiple
requests, 'get' from a client will need to make a n/w round trip if server
and client are on different boxes vs both being on the same box. So n/w
latency becomes quite relevant.
--
Sent from:
Hello!
I don't understand why the network hop is relevant here, if you are
(supposedly) running those gets in parallel.
Regards,
--
Ilya Kasnacheev
чт, 28 нояб. 2019 г. в 04:09, Victor :
> Performed one more test. Moved the client on the same box, and changed the
> off & on heap values.
>
>
Performed one more test. Moved the client on the same box, and changed the
off & on heap values.
The Employee record is barely about 75-100bytes. So 500k records would just
range between 40-50mb + 1 backup, so another 40-50mb, so about 100mb worth
of data.
I set the off-heap to 1GB and -Xmx to
Victor,
Then, I would recommend to check if you have a swapping enabled in OS. If
you have only 75gb on the machine and you started 3 nodes with 14 gb off
heap and something like a 16gb heap each, probably OS started a swapping
process, which will affect a performance.
Additionally, there is no
Yes, ran Cassandra on the same box. Similar config, 3 nodes on one box and
client on another. Have about 75G on both boxes.
However for now, i am keeping Cassandra aside, since my primary goal around
evaluating Ignite is to see similar performance numbers for "get" as seen in
the benchmark.
--
Thanks Denis for confirming the benchmarks are real.
I am using the latest ignite version i.e. 2.6.7.
I tried with Atomic as well, don't see much variation. Marginal changes. So
currently, in my test,
I am using
/examples/config/persistentstore/example-persistent-store.xml, with
persistence
Hi Viktor,
It looks like you're running 3 server nodes on the same physical machine,
right? How do you run Cassandra benchmarks? Do you use the same 2 machines?
How many Cassandra instances do you have?
Also, how much memory do you have on this machine?
Best Regards,
Evgenii
ср, 27 нояб. 2019
Hello Viktor,
The benchmarks you're referring to are real and list all the configuration
parameters as well as the source code. No cheating.
The first catchy difference between your and those benchmarks is that
you're using TRANSACTIONAL mode for Ignite. This involves a 2-phase-commit
protocol
It's 500k unique gets, spread across multiple threads. Max i tried with 30
threads.
I cant use getAll for this usecase, since it is user driven and the user
will load one record at a time. In any case i expected event the single gets
to be pretty fast as well. Given the benchmark reference -
Hi!
The numbers sound very low, I run on hardware close to yours (3 nodes
(X5660*5) and 1 client), and I get way more than 1500/sec, not sure how
much, I will have to check, but as long as you do single get's there is
not so much you can do, each get will be one roundtrip over the network,
I am running some comparison tests (ignite vs cassandra) to check how to
improve the performance of 'get' operation. The data is fairly
straightforward. A simple Employee Object(10 odd fields), being stored as
BinaryObject in the cache as
IgniteCache empCache;
The cache is configured with, Write
15 matches
Mail list logo
