Hi,

I've tried using the patched `storm-kafka-client` and my throughput was up
from 48K TPS to 585K TPS using my 6 supervisor node setup.
Thank you Stig and Roshan.

-Bernard

On Mon, Jan 7, 2019 at 5:47 PM Bernard Quizon <
[email protected]> wrote:

> Wow, thanks Stig! That's very helpful.
>
> On Mon, Jan 7, 2019 at 4:50 PM Stig Rohde Døssing <[email protected]>
> wrote:
>
>> I'm not sure if it's the only issue, but you might be affected by
>> https://issues.apache.org/jira/browse/STORM-3102.
>>
>> Den man. 7. jan. 2019 kl. 09.37 skrev Bernard Quizon <
>> [email protected]>:
>>
>>> Hi Roshan,
>>>
>>> Just to narrow it down .. can u get rid of the bolt  and see what
>>> numbers you get ?
>>> > Thanks, I will try that.
>>>
>>> Which Kafka spout are you using (new/old) ?
>>> > The new one, from kafka-clients.
>>>
>>> I assume you mean msgs when you say ‘transactions’.
>>> > Yes that would be messages
>>>
>>> Did you mean you are getting 48k aggregate Msgs/sec or is that 48k per
>>> worker ?
>>> > That would be the throughput of the whole topology, not per worker.
>>>
>>> Thanks,
>>> Bernard
>>>
>>> On Mon, Jan 7, 2019 at 4:24 PM Roshan Naik <[email protected]>
>>> wrote:
>>>
>>>> Just to narrow it down .. can u get rid of the bolt  and see what
>>>> numbers you get ?
>>>>
>>>> Which Kafka spout are you using (new/old) ?
>>>>
>>>> I assume you mean msgs when you say ‘transactions’.
>>>> Did you mean you are getting 48k aggregate Msgs/sec or is that 48k per
>>>> worker ?
>>>>
>>>>
>>>>
>>>> Sent from Yahoo Mail for iPhone
>>>> <https://overview.mail.yahoo.com/?.src=iOS>
>>>>
>>>> On Sunday, January 6, 2019, 11:29 PM, Bernard Quizon <
>>>> [email protected]> wrote:
>>>>
>>>> Hi,
>>>>
>>>> Before anything else, I'm using Apache Storm 1.2.1 and Apache Kafka
>>>> 1.1.1.
>>>> On my initial tests, I have:
>>>>
>>>>    - *6 supervisor nodes *
>>>>    - 1 worker per node
>>>>    - 7 KafkaSpout executors per worker
>>>>    - 1 bolt (that does nothing) per worker
>>>>    - 0 Ackers
>>>>    - 2 Kafka brokers with *42 partitions *on the topic
>>>>
>>>> With that configuration, no matter how I change some other configs
>>>> (Please see list below), my topology is capping out at around 48k TPS.
>>>> Please note that CPU usage, for the Supervisor nodes, is only around
>>>> 20% and Network usage is only around 20Mbps for both the Kafka Brokers and
>>>> Supervisor nodes, well below the network capacities.
>>>>
>>>> Now, I have increased the supervisor nodes from 6 to 12 and used a new
>>>> topic with 82 partitions, thinking that scaling out could help the
>>>> performance.
>>>> So is this the new configuration:
>>>>
>>>>    - *12 supervisor nodes *
>>>>    - 1 worker per node
>>>>    - 7 KafkaSpout executors per worker
>>>>    - 1 bolt (that does nothing) per worker
>>>>    - 0 Ackers
>>>>    - 2 Kafka brokers with *84 partitions* on the topic
>>>>
>>>> And I'm still getting around 48k TPS.
>>>>
>>>> Some other configs I played around with:
>>>>
>>>>    - max.poll.records
>>>>    - max.spout.pending
>>>>    - processing.guarantee
>>>>    - offset.commit.period.ms
>>>>    - max.uncommitted.offsets
>>>>    - poll.timeout.ms
>>>>    - fetch.min.bytes
>>>>    - fetch.max.bytes
>>>>    - max.partition.fetch.bytes
>>>>    - receive.buffer.bytes
>>>>    - fetch.max.wait.ms
>>>>    - topology.executor.receive.buffer.size
>>>>    - topology.executor.send.buffer.size
>>>>    - topology.receiver.buffer.size
>>>>    - topology.transfer.buffer.size
>>>>
>>>>
>>>> Am I missing something here? Why is the throughput not improving?
>>>>
>>>> Just to add, I have also done some performance isolation tests on both
>>>> Kafka and Storm.
>>>> On a distributed consumer using Spark and Kafka, I was able to get
>>>> around 700K TPS (So we know that Kafka isn't the issue here).
>>>> And also I could get around 400k TPS on a custom Storm topology with 1
>>>> spout that generates random transactions and 1 bolt that does nothing.
>>>> I feel like the numbers don't add up and the topology shouldn't be
>>>> capping out at around 48K TPS.
>>>> Your suggestions would be very much appreciated.
>>>>
>>>>
>>>> Thanks,
>>>> Bernard
>>>>
>>>>

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