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Posted to users@kafka.apache.org by Jason Weiss <Ja...@rapid7.com> on 2013/05/20 17:11:57 UTC
Relationship between Zookeeper and Kafka
I'm trying to maximize my throughput and seem to have hit a ceiling. Everything described below is running in AWS.
I have configured a Kafka cluster with 5 machines, M1.Large, with 600 provisioned IOPS storage for each EC2 instance. I have a Zookeeper server (we aren't in production yet, so I didn't take the time to setup a ZK cluster). Publishing to a single topic from 7 different clients, I seem to max out at around 20,000 eps with a fixed 2K message size. Each broker defines 10 file segments, with a 25000 message / 5 second flush configuration in server.properties. I have stuck with 8 threads. My producers (Java) are configured with batch.num.messages at 50, and queue.buffering.max.messages at 100.
When I went from 4 servers in the cluster to 5 servers, I only saw an increase of about 500 events per second in throughput. In sharp contrast, when I run a complete environment on my MacBook Pro, tuned as described above but with a single ZK and a single Kafka broker, I am seeing 61,000 events per second. I don't think I'm network constrained in the AWS environment (producer side) because when I add one more client, my MacBook Pro, I see a proportionate decrease in EC2 client throughput, and the net result is an identical 20,000 eps. Stated differently, my EC2 instance give up throughput when my local MacBook Pro joins the array of producers such that the throughput is exactly the same.
Does anyone have any additional suggestions on what else I could tune to try and hit our goal, 50,000 eps with a 5 machine cluster? Based on the whitepapers published, LinkedIn describes a peak of 170,000 events per second across their cluster. My 20,000 seems so far away from their production figures.
What is the relationship, in terms of performance, between ZK and Kafka? Do I need to have a more performant ZK cluster, the same, or does it really not matter in terms of maximizing throughput.
Thanks for any suggestions – I've been pulling knobs and turning levers on this for several days now.
Jason
This electronic message contains information which may be confidential or privileged. The information is intended for the use of the individual or entity named above. If you are not the intended recipient, be aware that any disclosure, copying, distribution or use of the contents of this information is prohibited. If you have received this electronic transmission in error, please notify us by e-mail at (postmaster@rapid7.com) immediately.
Re: Relationship between Zookeeper and Kafka
Posted by Scott Clasen <sc...@heroku.com>.
Ahh, yeah, piops is definitely faster than standard EBS, but still much
slower than local disk.
you could try benchmarking local disk to see what the instances you are
using are capable of, then try tweaking iops etc to see where you get.
M1.Larges arent super fast so your macbook beating them isnt suprising to
me.
On Mon, May 20, 2013 at 10:01 AM, Jason Weiss <Ja...@rapid7.com>wrote:
> Hi Scott.
>
> I'm using Kafka 0.7.2. I am using the default replication factor, since I
> don't recall changing that configuration at all.
>
> I'm using provisioned IOPS, which from attending the AWS event in NYC a
> few weeks ago was presented as the "fastest storage option" for EC2. A
> number of partners presented success stories in terms of throughput with
> provisioned IOPS. I've tried to follow that model.
>
>
> Jason
>
> On 5/20/13 12:56 PM, "Scott Clasen" <sc...@heroku.com> wrote:
>
> >My guess, EBS is likely your bottleneck. Try running on instance local
> >disks, and compare your results. Is this 0.8? What replication factor are
> >you using?
> >
> >
> >On Mon, May 20, 2013 at 8:11 AM, Jason Weiss <Ja...@rapid7.com>
> >wrote:
> >
> >> I'm trying to maximize my throughput and seem to have hit a ceiling.
> >> Everything described below is running in AWS.
> >>
> >> I have configured a Kafka cluster with 5 machines, M1.Large, with 600
> >> provisioned IOPS storage for each EC2 instance. I have a Zookeeper
> >>server
> >> (we aren't in production yet, so I didn't take the time to setup a ZK
> >> cluster). Publishing to a single topic from 7 different clients, I seem
> >>to
> >> max out at around 20,000 eps with a fixed 2K message size. Each broker
> >> defines 10 file segments, with a 25000 message / 5 second flush
> >> configuration in server.properties. I have stuck with 8 threads. My
> >> producers (Java) are configured with batch.num.messages at 50, and
> >> queue.buffering.max.messages at 100.
> >>
> >> When I went from 4 servers in the cluster to 5 servers, I only saw an
> >> increase of about 500 events per second in throughput. In sharp
> >>contrast,
> >> when I run a complete environment on my MacBook Pro, tuned as described
> >> above but with a single ZK and a single Kafka broker, I am seeing 61,000
> >> events per second. I don't think I'm network constrained in the AWS
> >> environment (producer side) because when I add one more client, my
> >>MacBook
> >> Pro, I see a proportionate decrease in EC2 client throughput, and the
> >>net
> >> result is an identical 20,000 eps. Stated differently, my EC2 instance
> >>give
> >> up throughput when my local MacBook Pro joins the array of producers
> >>such
> >> that the throughput is exactly the same.
> >>
> >> Does anyone have any additional suggestions on what else I could tune to
> >> try and hit our goal, 50,000 eps with a 5 machine cluster? Based on the
> >> whitepapers published, LinkedIn describes a peak of 170,000 events per
> >> second across their cluster. My 20,000 seems so far away from their
> >> production figures.
> >>
> >> What is the relationship, in terms of performance, between ZK and Kafka?
> >> Do I need to have a more performant ZK cluster, the same, or does it
> >>really
> >> not matter in terms of maximizing throughput.
> >>
> >> Thanks for any suggestions I've been pulling knobs and turning levers
> >>on
> >> this for several days now.
> >>
> >>
> >> Jason
> >>
> >> This electronic message contains information which may be confidential
> >>or
> >> privileged. The information is intended for the use of the individual or
> >> entity named above. If you are not the intended recipient, be aware that
> >> any disclosure, copying, distribution or use of the contents of this
> >> information is prohibited. If you have received this electronic
> >> transmission in error, please notify us by e-mail at (
> >> postmaster@rapid7.com) immediately.
> >>
>
> This electronic message contains information which may be confidential or
> privileged. The information is intended for the use of the individual or
> entity named above. If you are not the intended recipient, be aware that
> any disclosure, copying, distribution or use of the contents of this
> information is prohibited. If you have received this electronic
> transmission in error, please notify us by e-mail at (
> postmaster@rapid7.com) immediately.
>
>
Re: Relationship between Zookeeper and Kafka
Posted by Philip O'Toole <ph...@loggly.com>.
Cool.
By the way, I do mean you should use 'atop'. That was not a typo on my part.
http://www.atoptool.nl/downloadatop.php
apt-get install atop
on Ubuntu systems.
Philip
On May 21, 2013, at 4:51 PM, Jason Weiss <Ja...@rapid7.com> wrote:
> Philip,
>
> Thanks for the response. I used top yesterday and determined that part of
> my problem was that the kafaka shell script is pre-configured to only use
> 512M of RAM, and thus it wasn't using memory efficiently. That has helped
> out tremendously. Adding an echo at the start of the script that it was
> defaulting to such a low value probably would have saved me some time. In
> the same vein, I should have inspected the launch command more closely.
>
> The virtualization of AWS makes it difficult to truly know what your
> performance is, IMHO. There are lots of people arguing on the web about
> the value of bare metal versus virtualization. I am still baffled how
> companies like Urban Airship are purportedly seeing bursts of 750,000
> messages per second on a 3-cluster machine, but by playing with the knobs
> in a controlled manner, I'm starting to better understand the relationship
> and effect on the overall system.
>
> Jason
>
>
> On 5/21/13 11:44 AM, "Philip O'Toole" <ph...@loggly.com> wrote:
>
>> As a test, why not just use a disk with provisioned IOPs of 4000? Just as
>> a test - see if it improves.
>>
>> Also, you have not supplied any metrics regarding the VM's performance.
>> Is the CPU busy? Is IO maxed out? Network? Disk? Use a tool like atop,
>> and tell us what you find.
>>
>> Philip
>>
>> On May 20, 2013, at 6:43 PM, Ken Krugler <kk...@transpac.com>
>> wrote:
>>
>>> Hi Jason,
>>>
>>> On May 20, 2013, at 10:01am, Jason Weiss wrote:
>>>
>>>> Hi Scott.
>>>>
>>>> I'm using Kafka 0.7.2. I am using the default replication factor,
>>>> since I
>>>> don't recall changing that configuration at all.
>>>>
>>>> I'm using provisioned IOPS, which from attending the AWS event in NYC a
>>>> few weeks ago was presented as the "fastest storage option" for EC2. A
>>>> number of partners presented success stories in terms of throughput
>>>> with
>>>> provisioned IOPS. I've tried to follow that model.
>>>
>>> In my experience directly hitting an ephemeral drive on m1.large is
>>> faster than using EBS.
>>>
>>> I've seen some articles where RAIDing multiple EBS volumes can exceed
>>> the performance of ephemeral drives, but with high variability.
>>>
>>> If you want to maximize performance, set up up a (smaller) cluster of
>>> SSD-backed instances with 10Gb Ethernet in the same cluster group.
>>>
>>> E.g. test with three cr1.8xlarge instances.
>>>
>>> -- Ken
>>>
>>>
>>>> On 5/20/13 12:56 PM, "Scott Clasen" <sc...@heroku.com> wrote:
>>>>
>>>>> My guess, EBS is likely your bottleneck. Try running on instance
>>>>> local
>>>>> disks, and compare your results. Is this 0.8? What replication
>>>>> factor are
>>>>> you using?
>>>>>
>>>>>
>>>>> On Mon, May 20, 2013 at 8:11 AM, Jason Weiss <Ja...@rapid7.com>
>>>>> wrote:
>>>>>
>>>>>> I'm trying to maximize my throughput and seem to have hit a ceiling.
>>>>>> Everything described below is running in AWS.
>>>>>>
>>>>>> I have configured a Kafka cluster with 5 machines, M1.Large, with 600
>>>>>> provisioned IOPS storage for each EC2 instance. I have a Zookeeper
>>>>>> server
>>>>>> (we aren't in production yet, so I didn't take the time to setup a ZK
>>>>>> cluster). Publishing to a single topic from 7 different clients, I
>>>>>> seem
>>>>>> to
>>>>>> max out at around 20,000 eps with a fixed 2K message size. Each
>>>>>> brokers
>>>>>> defines 10 file segments, with a 25000 message / 5 second flush
>>>>>> configuration in server.properties. I have stuck with 8 threads. My
>>>>>> producers (Java) are configured with batch.num.messages at 50, and
>>>>>> queue.buffering.max.messages at 100.
>>>>>>
>>>>>> When I went from 4 servers in the cluster to 5 servers, I only saw an
>>>>>> increase of about 500 events per second in throughput. In sharp
>>>>>> contrast,
>>>>>> when I run a complete environment on my MacBook Pro, tuned as
>>>>>> described
>>>>>> above but with a single ZK and a single Kafka broker, I am seeing
>>>>>> 61,000
>>>>>> events per second. I don't think I'm network constrained in the AWS
>>>>>> environment (producer side) because when I add one more client, my
>>>>>> MacBook
>>>>>> Pro, I see a proportionate decrease in EC2 client throughput, and the
>>>>>> net
>>>>>> result is an identical 20,000 eps. Stated differently, my EC2
>>>>>> instance
>>>>>> give
>>>>>> up throughput when my local MacBook Pro joins the array of producers
>>>>>> such
>>>>>> that the throughput is exactly the same.
>>>>>>
>>>>>> Does anyone have any additional suggestions on what else I could
>>>>>> tune to
>>>>>> try and hit our goal, 50,000 eps with a 5 machine cluster? Based on
>>>>>> the
>>>>>> whitepapers published, LinkedIn describes a peak of 170,000 events
>>>>>> per
>>>>>> second across their cluster. My 20,000 seems so far away from their
>>>>>> production figures.
>>>>>>
>>>>>> What is the relationship, in terms of performance, between ZK and
>>>>>> Kafka?
>>>>>> Do I need to have a more performant ZK cluster, the same, or does it
>>>>>> really
>>>>>> not matter in terms of maximizing throughput.
>>>>>>
>>>>>> Thanks for any suggestions I've been pulling knobs and turning
>>>>>> levers
>>>>>> on
>>>>>> this for several days now.
>>>>>>
>>>>>>
>>>>>> Jason
>>>
>>> --------------------------
>>> Ken Krugler
>>> +1 530-210-6378
>>> http://www.scaleunlimited.com
>>> custom big data solutions & training
>>> Hadoop, Cascading, Cassandra & Solr
>
> This electronic message contains information which may be confidential or privileged. The information is intended for the use of the individual or entity named above. If you are not the intended recipient, be aware that any disclosure, copying, distribution or use of the contents of this information is prohibited. If you have received this electronic transmission in error, please notify us by e-mail at (postmaster@rapid7.com) immediately.
Re: Relationship between Zookeeper and Kafka
Posted by Jason Weiss <Ja...@rapid7.com>.
Philip,
Thanks for the response. I used top yesterday and determined that part of
my problem was that the kafaka shell script is pre-configured to only use
512M of RAM, and thus it wasn't using memory efficiently. That has helped
out tremendously. Adding an echo at the start of the script that it was
defaulting to such a low value probably would have saved me some time. In
the same vein, I should have inspected the launch command more closely.
The virtualization of AWS makes it difficult to truly know what your
performance is, IMHO. There are lots of people arguing on the web about
the value of bare metal versus virtualization. I am still baffled how
companies like Urban Airship are purportedly seeing bursts of 750,000
messages per second on a 3-cluster machine, but by playing with the knobs
in a controlled manner, I'm starting to better understand the relationship
and effect on the overall system.
Jason
On 5/21/13 11:44 AM, "Philip O'Toole" <ph...@loggly.com> wrote:
>As a test, why not just use a disk with provisioned IOPs of 4000? Just as
>a test - see if it improves.
>
>Also, you have not supplied any metrics regarding the VM's performance.
>Is the CPU busy? Is IO maxed out? Network? Disk? Use a tool like atop,
>and tell us what you find.
>
>Philip
>
>On May 20, 2013, at 6:43 PM, Ken Krugler <kk...@transpac.com>
>wrote:
>
>> Hi Jason,
>>
>> On May 20, 2013, at 10:01am, Jason Weiss wrote:
>>
>>> Hi Scott.
>>>
>>> I'm using Kafka 0.7.2. I am using the default replication factor,
>>>since I
>>> don't recall changing that configuration at all.
>>>
>>> I'm using provisioned IOPS, which from attending the AWS event in NYC a
>>> few weeks ago was presented as the "fastest storage option" for EC2. A
>>> number of partners presented success stories in terms of throughput
>>>with
>>> provisioned IOPS. I've tried to follow that model.
>>
>> In my experience directly hitting an ephemeral drive on m1.large is
>>faster than using EBS.
>>
>> I've seen some articles where RAIDing multiple EBS volumes can exceed
>>the performance of ephemeral drives, but with high variability.
>>
>> If you want to maximize performance, set up up a (smaller) cluster of
>>SSD-backed instances with 10Gb Ethernet in the same cluster group.
>>
>> E.g. test with three cr1.8xlarge instances.
>>
>> -- Ken
>>
>>
>>> On 5/20/13 12:56 PM, "Scott Clasen" <sc...@heroku.com> wrote:
>>>
>>>> My guess, EBS is likely your bottleneck. Try running on instance
>>>>local
>>>> disks, and compare your results. Is this 0.8? What replication
>>>>factor are
>>>> you using?
>>>>
>>>>
>>>> On Mon, May 20, 2013 at 8:11 AM, Jason Weiss <Ja...@rapid7.com>
>>>> wrote:
>>>>
>>>>> I'm trying to maximize my throughput and seem to have hit a ceiling.
>>>>> Everything described below is running in AWS.
>>>>>
>>>>> I have configured a Kafka cluster with 5 machines, M1.Large, with 600
>>>>> provisioned IOPS storage for each EC2 instance. I have a Zookeeper
>>>>> server
>>>>> (we aren't in production yet, so I didn't take the time to setup a ZK
>>>>> cluster). Publishing to a single topic from 7 different clients, I
>>>>>seem
>>>>> to
>>>>> max out at around 20,000 eps with a fixed 2K message size. Each
>>>>>brokers
>>>>> defines 10 file segments, with a 25000 message / 5 second flush
>>>>> configuration in server.properties. I have stuck with 8 threads. My
>>>>> producers (Java) are configured with batch.num.messages at 50, and
>>>>> queue.buffering.max.messages at 100.
>>>>>
>>>>> When I went from 4 servers in the cluster to 5 servers, I only saw an
>>>>> increase of about 500 events per second in throughput. In sharp
>>>>> contrast,
>>>>> when I run a complete environment on my MacBook Pro, tuned as
>>>>>described
>>>>> above but with a single ZK and a single Kafka broker, I am seeing
>>>>>61,000
>>>>> events per second. I don't think I'm network constrained in the AWS
>>>>> environment (producer side) because when I add one more client, my
>>>>> MacBook
>>>>> Pro, I see a proportionate decrease in EC2 client throughput, and the
>>>>> net
>>>>> result is an identical 20,000 eps. Stated differently, my EC2
>>>>>instance
>>>>> give
>>>>> up throughput when my local MacBook Pro joins the array of producers
>>>>> such
>>>>> that the throughput is exactly the same.
>>>>>
>>>>> Does anyone have any additional suggestions on what else I could
>>>>>tune to
>>>>> try and hit our goal, 50,000 eps with a 5 machine cluster? Based on
>>>>>the
>>>>> whitepapers published, LinkedIn describes a peak of 170,000 events
>>>>>per
>>>>> second across their cluster. My 20,000 seems so far away from their
>>>>> production figures.
>>>>>
>>>>> What is the relationship, in terms of performance, between ZK and
>>>>>Kafka?
>>>>> Do I need to have a more performant ZK cluster, the same, or does it
>>>>> really
>>>>> not matter in terms of maximizing throughput.
>>>>>
>>>>> Thanks for any suggestions I've been pulling knobs and turning
>>>>>levers
>>>>> on
>>>>> this for several days now.
>>>>>
>>>>>
>>>>> Jason
>>
>> --------------------------
>> Ken Krugler
>> +1 530-210-6378
>> http://www.scaleunlimited.com
>> custom big data solutions & training
>> Hadoop, Cascading, Cassandra & Solr
>>
>>
>>
>>
>>
This electronic message contains information which may be confidential or privileged. The information is intended for the use of the individual or entity named above. If you are not the intended recipient, be aware that any disclosure, copying, distribution or use of the contents of this information is prohibited. If you have received this electronic transmission in error, please notify us by e-mail at (postmaster@rapid7.com) immediately.
Re: Relationship between Zookeeper and Kafka
Posted by Philip O'Toole <ph...@loggly.com>.
As a test, why not just use a disk with provisioned IOPs of 4000? Just as a test - see if it improves.
Also, you have not supplied any metrics regarding the VM's performance. Is the CPU busy? Is IO maxed out? Network? Disk? Use a tool like atop, and tell us what you find.
Philip
On May 20, 2013, at 6:43 PM, Ken Krugler <kk...@transpac.com> wrote:
> Hi Jason,
>
> On May 20, 2013, at 10:01am, Jason Weiss wrote:
>
>> Hi Scott.
>>
>> I'm using Kafka 0.7.2. I am using the default replication factor, since I
>> don't recall changing that configuration at all.
>>
>> I'm using provisioned IOPS, which from attending the AWS event in NYC a
>> few weeks ago was presented as the "fastest storage option" for EC2. A
>> number of partners presented success stories in terms of throughput with
>> provisioned IOPS. I've tried to follow that model.
>
> In my experience directly hitting an ephemeral drive on m1.large is faster than using EBS.
>
> I've seen some articles where RAIDing multiple EBS volumes can exceed the performance of ephemeral drives, but with high variability.
>
> If you want to maximize performance, set up up a (smaller) cluster of SSD-backed instances with 10Gb Ethernet in the same cluster group.
>
> E.g. test with three cr1.8xlarge instances.
>
> -- Ken
>
>
>> On 5/20/13 12:56 PM, "Scott Clasen" <sc...@heroku.com> wrote:
>>
>>> My guess, EBS is likely your bottleneck. Try running on instance local
>>> disks, and compare your results. Is this 0.8? What replication factor are
>>> you using?
>>>
>>>
>>> On Mon, May 20, 2013 at 8:11 AM, Jason Weiss <Ja...@rapid7.com>
>>> wrote:
>>>
>>>> I'm trying to maximize my throughput and seem to have hit a ceiling.
>>>> Everything described below is running in AWS.
>>>>
>>>> I have configured a Kafka cluster with 5 machines, M1.Large, with 600
>>>> provisioned IOPS storage for each EC2 instance. I have a Zookeeper
>>>> server
>>>> (we aren't in production yet, so I didn't take the time to setup a ZK
>>>> cluster). Publishing to a single topic from 7 different clients, I seem
>>>> to
>>>> max out at around 20,000 eps with a fixed 2K message size. Each brokers
>>>> defines 10 file segments, with a 25000 message / 5 second flush
>>>> configuration in server.properties. I have stuck with 8 threads. My
>>>> producers (Java) are configured with batch.num.messages at 50, and
>>>> queue.buffering.max.messages at 100.
>>>>
>>>> When I went from 4 servers in the cluster to 5 servers, I only saw an
>>>> increase of about 500 events per second in throughput. In sharp
>>>> contrast,
>>>> when I run a complete environment on my MacBook Pro, tuned as described
>>>> above but with a single ZK and a single Kafka broker, I am seeing 61,000
>>>> events per second. I don't think I'm network constrained in the AWS
>>>> environment (producer side) because when I add one more client, my
>>>> MacBook
>>>> Pro, I see a proportionate decrease in EC2 client throughput, and the
>>>> net
>>>> result is an identical 20,000 eps. Stated differently, my EC2 instance
>>>> give
>>>> up throughput when my local MacBook Pro joins the array of producers
>>>> such
>>>> that the throughput is exactly the same.
>>>>
>>>> Does anyone have any additional suggestions on what else I could tune to
>>>> try and hit our goal, 50,000 eps with a 5 machine cluster? Based on the
>>>> whitepapers published, LinkedIn describes a peak of 170,000 events per
>>>> second across their cluster. My 20,000 seems so far away from their
>>>> production figures.
>>>>
>>>> What is the relationship, in terms of performance, between ZK and Kafka?
>>>> Do I need to have a more performant ZK cluster, the same, or does it
>>>> really
>>>> not matter in terms of maximizing throughput.
>>>>
>>>> Thanks for any suggestions I've been pulling knobs and turning levers
>>>> on
>>>> this for several days now.
>>>>
>>>>
>>>> Jason
>
> --------------------------
> Ken Krugler
> +1 530-210-6378
> http://www.scaleunlimited.com
> custom big data solutions & training
> Hadoop, Cascading, Cassandra & Solr
>
>
>
>
>
Re: Relationship between Zookeeper and Kafka
Posted by Ken Krugler <kk...@transpac.com>.
Hi Jason,
On May 20, 2013, at 10:01am, Jason Weiss wrote:
> Hi Scott.
>
> I'm using Kafka 0.7.2. I am using the default replication factor, since I
> don't recall changing that configuration at all.
>
> I'm using provisioned IOPS, which from attending the AWS event in NYC a
> few weeks ago was presented as the "fastest storage option" for EC2. A
> number of partners presented success stories in terms of throughput with
> provisioned IOPS. I've tried to follow that model.
In my experience directly hitting an ephemeral drive on m1.large is faster than using EBS.
I've seen some articles where RAIDing multiple EBS volumes can exceed the performance of ephemeral drives, but with high variability.
If you want to maximize performance, set up up a (smaller) cluster of SSD-backed instances with 10Gb Ethernet in the same cluster group.
E.g. test with three cr1.8xlarge instances.
-- Ken
> On 5/20/13 12:56 PM, "Scott Clasen" <sc...@heroku.com> wrote:
>
>> My guess, EBS is likely your bottleneck. Try running on instance local
>> disks, and compare your results. Is this 0.8? What replication factor are
>> you using?
>>
>>
>> On Mon, May 20, 2013 at 8:11 AM, Jason Weiss <Ja...@rapid7.com>
>> wrote:
>>
>>> I'm trying to maximize my throughput and seem to have hit a ceiling.
>>> Everything described below is running in AWS.
>>>
>>> I have configured a Kafka cluster with 5 machines, M1.Large, with 600
>>> provisioned IOPS storage for each EC2 instance. I have a Zookeeper
>>> server
>>> (we aren't in production yet, so I didn't take the time to setup a ZK
>>> cluster). Publishing to a single topic from 7 different clients, I seem
>>> to
>>> max out at around 20,000 eps with a fixed 2K message size. Each broker
>>> defines 10 file segments, with a 25000 message / 5 second flush
>>> configuration in server.properties. I have stuck with 8 threads. My
>>> producers (Java) are configured with batch.num.messages at 50, and
>>> queue.buffering.max.messages at 100.
>>>
>>> When I went from 4 servers in the cluster to 5 servers, I only saw an
>>> increase of about 500 events per second in throughput. In sharp
>>> contrast,
>>> when I run a complete environment on my MacBook Pro, tuned as described
>>> above but with a single ZK and a single Kafka broker, I am seeing 61,000
>>> events per second. I don't think I'm network constrained in the AWS
>>> environment (producer side) because when I add one more client, my
>>> MacBook
>>> Pro, I see a proportionate decrease in EC2 client throughput, and the
>>> net
>>> result is an identical 20,000 eps. Stated differently, my EC2 instance
>>> give
>>> up throughput when my local MacBook Pro joins the array of producers
>>> such
>>> that the throughput is exactly the same.
>>>
>>> Does anyone have any additional suggestions on what else I could tune to
>>> try and hit our goal, 50,000 eps with a 5 machine cluster? Based on the
>>> whitepapers published, LinkedIn describes a peak of 170,000 events per
>>> second across their cluster. My 20,000 seems so far away from their
>>> production figures.
>>>
>>> What is the relationship, in terms of performance, between ZK and Kafka?
>>> Do I need to have a more performant ZK cluster, the same, or does it
>>> really
>>> not matter in terms of maximizing throughput.
>>>
>>> Thanks for any suggestions I've been pulling knobs and turning levers
>>> on
>>> this for several days now.
>>>
>>>
>>> Jason
>>>
--------------------------
Ken Krugler
+1 530-210-6378
http://www.scaleunlimited.com
custom big data solutions & training
Hadoop, Cascading, Cassandra & Solr
Re: Relationship between Zookeeper and Kafka
Posted by Jason Weiss <Ja...@rapid7.com>.
Hi Scott.
I'm using Kafka 0.7.2. I am using the default replication factor, since I
don't recall changing that configuration at all.
I'm using provisioned IOPS, which from attending the AWS event in NYC a
few weeks ago was presented as the "fastest storage option" for EC2. A
number of partners presented success stories in terms of throughput with
provisioned IOPS. I've tried to follow that model.
Jason
On 5/20/13 12:56 PM, "Scott Clasen" <sc...@heroku.com> wrote:
>My guess, EBS is likely your bottleneck. Try running on instance local
>disks, and compare your results. Is this 0.8? What replication factor are
>you using?
>
>
>On Mon, May 20, 2013 at 8:11 AM, Jason Weiss <Ja...@rapid7.com>
>wrote:
>
>> I'm trying to maximize my throughput and seem to have hit a ceiling.
>> Everything described below is running in AWS.
>>
>> I have configured a Kafka cluster with 5 machines, M1.Large, with 600
>> provisioned IOPS storage for each EC2 instance. I have a Zookeeper
>>server
>> (we aren't in production yet, so I didn't take the time to setup a ZK
>> cluster). Publishing to a single topic from 7 different clients, I seem
>>to
>> max out at around 20,000 eps with a fixed 2K message size. Each broker
>> defines 10 file segments, with a 25000 message / 5 second flush
>> configuration in server.properties. I have stuck with 8 threads. My
>> producers (Java) are configured with batch.num.messages at 50, and
>> queue.buffering.max.messages at 100.
>>
>> When I went from 4 servers in the cluster to 5 servers, I only saw an
>> increase of about 500 events per second in throughput. In sharp
>>contrast,
>> when I run a complete environment on my MacBook Pro, tuned as described
>> above but with a single ZK and a single Kafka broker, I am seeing 61,000
>> events per second. I don't think I'm network constrained in the AWS
>> environment (producer side) because when I add one more client, my
>>MacBook
>> Pro, I see a proportionate decrease in EC2 client throughput, and the
>>net
>> result is an identical 20,000 eps. Stated differently, my EC2 instance
>>give
>> up throughput when my local MacBook Pro joins the array of producers
>>such
>> that the throughput is exactly the same.
>>
>> Does anyone have any additional suggestions on what else I could tune to
>> try and hit our goal, 50,000 eps with a 5 machine cluster? Based on the
>> whitepapers published, LinkedIn describes a peak of 170,000 events per
>> second across their cluster. My 20,000 seems so far away from their
>> production figures.
>>
>> What is the relationship, in terms of performance, between ZK and Kafka?
>> Do I need to have a more performant ZK cluster, the same, or does it
>>really
>> not matter in terms of maximizing throughput.
>>
>> Thanks for any suggestions I've been pulling knobs and turning levers
>>on
>> this for several days now.
>>
>>
>> Jason
>>
>> This electronic message contains information which may be confidential
>>or
>> privileged. The information is intended for the use of the individual or
>> entity named above. If you are not the intended recipient, be aware that
>> any disclosure, copying, distribution or use of the contents of this
>> information is prohibited. If you have received this electronic
>> transmission in error, please notify us by e-mail at (
>> postmaster@rapid7.com) immediately.
>>
This electronic message contains information which may be confidential or privileged. The information is intended for the use of the individual or entity named above. If you are not the intended recipient, be aware that any disclosure, copying, distribution or use of the contents of this information is prohibited. If you have received this electronic transmission in error, please notify us by e-mail at (postmaster@rapid7.com) immediately.
Re: Relationship between Zookeeper and Kafka
Posted by Scott Clasen <sc...@heroku.com>.
My guess, EBS is likely your bottleneck. Try running on instance local
disks, and compare your results. Is this 0.8? What replication factor are
you using?
On Mon, May 20, 2013 at 8:11 AM, Jason Weiss <Ja...@rapid7.com> wrote:
> I'm trying to maximize my throughput and seem to have hit a ceiling.
> Everything described below is running in AWS.
>
> I have configured a Kafka cluster with 5 machines, M1.Large, with 600
> provisioned IOPS storage for each EC2 instance. I have a Zookeeper server
> (we aren't in production yet, so I didn't take the time to setup a ZK
> cluster). Publishing to a single topic from 7 different clients, I seem to
> max out at around 20,000 eps with a fixed 2K message size. Each broker
> defines 10 file segments, with a 25000 message / 5 second flush
> configuration in server.properties. I have stuck with 8 threads. My
> producers (Java) are configured with batch.num.messages at 50, and
> queue.buffering.max.messages at 100.
>
> When I went from 4 servers in the cluster to 5 servers, I only saw an
> increase of about 500 events per second in throughput. In sharp contrast,
> when I run a complete environment on my MacBook Pro, tuned as described
> above but with a single ZK and a single Kafka broker, I am seeing 61,000
> events per second. I don't think I'm network constrained in the AWS
> environment (producer side) because when I add one more client, my MacBook
> Pro, I see a proportionate decrease in EC2 client throughput, and the net
> result is an identical 20,000 eps. Stated differently, my EC2 instance give
> up throughput when my local MacBook Pro joins the array of producers such
> that the throughput is exactly the same.
>
> Does anyone have any additional suggestions on what else I could tune to
> try and hit our goal, 50,000 eps with a 5 machine cluster? Based on the
> whitepapers published, LinkedIn describes a peak of 170,000 events per
> second across their cluster. My 20,000 seems so far away from their
> production figures.
>
> What is the relationship, in terms of performance, between ZK and Kafka?
> Do I need to have a more performant ZK cluster, the same, or does it really
> not matter in terms of maximizing throughput.
>
> Thanks for any suggestions – I've been pulling knobs and turning levers on
> this for several days now.
>
>
> Jason
>
> This electronic message contains information which may be confidential or
> privileged. The information is intended for the use of the individual or
> entity named above. If you are not the intended recipient, be aware that
> any disclosure, copying, distribution or use of the contents of this
> information is prohibited. If you have received this electronic
> transmission in error, please notify us by e-mail at (
> postmaster@rapid7.com) immediately.
>