There is a key piece of information that should be critical to guess where the
problem is:
When I change from ack = all to ack = 1, instead of increasing message/s, it
actually devises it by half!
As if the problem is about how fast I produce data (given when I use ack 1 I
assume I block less time in the synchronous send, and therefore my producing
pump increases.
I wonder if some sort of contention happen when producer populate the 200
partition queues when the rate of production is high in the user thread?
Eric
-----Original Message-----
From: Eric Owhadi <eric.owh...@esgyn.com>
Sent: Thursday, October 3, 2019 1:33 PM
To: users@kafka.apache.org
Subject: RE: poor producing performance with very low CPU utilization?
External
Hi Eric,
Thanks a lot for your answer. Please find inline responses:
>>You've given hardware information about your brokers, but I don't think
>>you've provided information about the machine your producer is running on.
>>Have you verified that you're not reaching any caps on your producer's
>>machine?
The producer is on the same machine that the broker. Running very quiet, 3% CPU
when I run my test. So no there is no stress on the producing side
>>I also think you might be hitting the limit of what a single producer is
>>capable of pushing through with your current setup. With record size of ~12k
>>and the >>default batch size configuration of 64k, you'll only be able to
>>send 5 records per batch. The default number of in flight batches is 5.
I have 200 partition on my topic, and the load is well balanced across all
partition. So the math you are doing should be X200 right? In addition, I found
that batch size had no effect, and the linger.ms was the triggering factor to
cause a buffer send. I played with batch size and in flight number of request
upward, and that had no effect.
>>This means at any given time, you'll only have 25 records in flight per
>>connection. I'm assuming your partitions are configured with at least 2
>>replicas. Acks=all >>means your producer is going to wait for the records to
>>be fully replicated before considering it complete.
>>Doing the math, you have ~200 records per second, but this is split
>>between
>>2 brokers. This means you're producing 100 records per second per broker.
>>Simplifying a bit to 25 records in flight per broker, that's a latency
>>of
>>~250 ms to move around 300kb. At minimum, this includes the time to,
>>[compress the batch], [send the batch over the network to the leader], [write
>>the batch >>to the leader's log], [fetch the batch over the network to the
>>replica], [write the batch to the replica's log], and all of the assorted
>>responses to those calls.
given all is local (producer running on same node as broker), and the size of
my node (80 vcore), I hope I don t need 250ms to do that...
The equivalent workload on hbase2.0 is 10 to 20X faster (and that include same
replica config etc).
On Wed, Oct 2, 2019 at 8:38 PM Eric Owhadi <eric.owh...@esgyn.com> wrote:
-----Original Message-----
From: Eric Azama <eazama...@gmail.com>
Sent: Thursday, October 3, 2019 1:07 PM
To: users@kafka.apache.org
Subject: Re: poor producing performance with very low CPU utilization?
External
Hi Eric,
You've given hardware information about your brokers, but I don't think you've
provided information about the machine your producer is running on.
Have you verified that you're not reaching any caps on your producer's machine?
I also think you might be hitting the limit of what a single producer is
capable of pushing through with your current setup. With record size of ~12k
and the default batch size configuration of 64k, you'll only be able to send 5
records per batch. The default number of in flight batches is 5.
This means at any given time, you'll only have 25 records in flight per
connection. I'm assuming your partitions are configured with at least 2
replicas. Acks=all means your producer is going to wait for the records to be
fully replicated before considering it complete.
Doing the math, you have ~200 records per second, but this is split between
2 brokers. This means you're producing 100 records per second per broker.
Simplifying a bit to 25 records in flight per broker, that's a latency of
~250 ms to move around 300kb. At minimum, this includes the time to, [compress
the batch], [send the batch over the network to the leader], [write the batch
to the leader's log], [fetch the batch over the network to the replica], [write
the batch to the replica's log], and all of the assorted responses to those
calls.
On Wed, Oct 2, 2019 at 8:38 PM Eric Owhadi <eric.owh...@esgyn.com> wrote:
> Hi Jamie,
> Thanks for the hint. I played with these parameters, and found only
> linger.ms is playing a significant role for my test case.
> It is very sensitive and highly non linear.
> I get these results:
> Linger.ms message per second
> 80 100
> 84 205
> 85 215 -> top
> 86 213
> 90 205
> 95 195
> 100 187
> 200 100
>
> So as you can see, this is very sensitive and one can miss the peek easily.
> However, 200 messages per second for 2 powerful nodes and relatively
> small message (12016bytes) is still at least 10X bellow what I would have
> hoped.
> When I see system resources still being barely moving, with cpu at 3%,
> I am sure something is not right.
> Regards,
> Eric
>
> -----Original Message-----
> From: Jamie <jamied...@aol.co.uk.INVALID>
> Sent: Wednesday, October 2, 2019 4:27 PM
> To: users@kafka.apache.org
> Subject: Re: poor producing performance with very low CPU utilization?
>
> External
>
> Hi Eric,
> I found increasing the linger.ms to between 50-100 ms significantly
> increases performance (fewer larger requests instead of many small
> ones), I'd also increase the batch size and the buffer.memory.
> Thanks,
> Jamie
>
>
> -----Original Message-----
> From: Eric Owhadi <eric.owh...@esgyn.com>
> To: users@kafka.apache.org <users@kafka.apache.org>
> Sent: Wed, 2 Oct 2019 16:42
> Subject: poor producing performance with very low CPU utilization?
>
> Hi Kafka users,
> I am new to Kafka and am struggling with getting acceptable producing rate.
> I am using a cluster of 2 nodes, 40 CPU cores/ 80 if counting
> hyperthreading. 256GB memory on a 10Gbit network Kafka is installed as
> part of cloudera parcel, with 5GB java heap.
> Producer version: Kafka client 2.2.1
>
> Wed Oct 2 07:56:59 PDT 2019
> JAVA_HOME=/usr/lib/jvm/java-1.8.0-openjdk-1.8.0.131-0.b11.el6_9.x86_64
> Using -XX:+HeapDumpOnOutOfMemoryError
> -XX:HeapDumpPath=/tmp/kafka_kafka-KAFKA_BROKER-c1871edf37153578a6fc7f4
> 1462d01d2_pid6908.hprof
> -XX:OnOutOfMemoryError=/usr/lib64/cmf/service/common/killparent.sh as
> CSD_JAVA_OPTS Using
> /var/run/cloudera-scm-agent/process/33853-kafka-KAFKA_BROKER as conf
> dir Using scripts/control.sh as process script
> CONF_DIR=/var/run/cloudera-scm-agent/process/33853-kafka-KAFKA_BROKER
> CMF_CONF_DIR=/etc/cloudera-scm-agent
>
> Date: Wed Oct 2 07:56:59 PDT 2019
> Host: xxxxx.esgyn.local
> Pwd: /var/run/cloudera-scm-agent/process/33853-kafka-KAFKA_BROKER
> CONF_DIR: /var/run/cloudera-scm-agent/process/33853-kafka-KAFKA_BROKER
> KAFKA_HOME: /opt/cloudera/parcels/KAFKA-4.1.0-1.4.1.0.p0.4/lib/kafka
> Zookeeper Quorum:
> xxx.esgyn.local:2181,xxx.esgyn.local:2181,xxx.esgyn.local:2181
> Zookeeper Chroot:
> PORT: 9092
> JMX_PORT: 9393
> SSL_PORT: 9093
> ENABLE_MONITORING: true
> METRIC_REPORTERS: nl.techop.kafka.KafkaHttpMetricsReporter
> BROKER_HEAP_SIZE: 5120
> BROKER_JAVA_OPTS: -server -XX:+UseG1GC -XX:MaxGCPauseMillis=20
> -XX:InitiatingHeapOccupancyPercent=35 -XX:+DisableExplicitGC
> -Djava.awt.headless=true
> BROKER_SSL_ENABLED: false
> KERBEROS_AUTH_ENABLED: false
> KAFKA_PRINCIPAL:
> SECURITY_INTER_BROKER_PROTOCOL: INFERRED
> AUTHENTICATE_ZOOKEEPER_CONNECTION: true
> SUPER_USERS: kafka
> Kafka version found: 2.2.1-kafka4.1.0
> Sentry version found: 1.5.1-cdh5.15.0
> ZK_PRINCIPAL_NAME: zookeeper
> Final Zookeeper Quorum is
> xxx.esgyn.local:2181,xx.esgyn.local:2181,x.esgyn.local:2181
> security.inter.broker.protocol inferred as PLAINTEXT
> LISTENERS=listeners=PLAINTEXT://xxxxx.esgyn.local:9092,
>
> I am producing messages of 12016 bytes uncompressed, then snappy
> compressed by kafka.
> I am using a topic with 200 partitions, and a custom partitioner that
> I verified is doing good job at spreading the load on the 2 brokers.
>
> My producer config look like:
>
> kafkaProps.put("bootstrap.servers","nap052.esgyn.local:9092,localhost:9092");
> kafkaProps.put("key.serializer",
> "org.apache.kafka.common.serialization.LongSerializer");
>
> kafkaProps.put("value.serializer","org.trafodion.sql.kafka.SmartpumpCo
> llectorVectorSerializer");
>
> kafkaProps.put("partitioner.class","org.trafodion.sql.kafka.TimeSeriesPartitioner");
> kafkaProps.put("compression.type","snappy");
> kafkaProps.put("batch.size","65536");
> kafkaProps.put("acks", "all");
> kafkaProps.put("linger.ms","1");
>
> I tried first doing fire and forget send, thinking I would get best
> performance.
> Then I tried synchronous send, and amazingly found that I would get
> better performance with sync send.
>
> However, after 1 or 2 minute of load test, I start getting error on
> the synchronous send like this:
> ava.util.concurrent.ExecutionException:
> org.apache.kafka.common.errors.TimeoutException: Expiring 1 record(s)
> for
> DEFAULT-.TIMESERIES.SmartpumpCollectorVector--112:120000 ms has passed
> since batch creation
> at
> org.apache.kafka.clients.producer.internals.FutureRecordMetadata.valueOrError(FutureRecordMetadata.java:98)
> at
> org.apache.kafka.clients.producer.internals.FutureRecordMetadata.get(FutureRecordMetadata.java:67)
> at
> org.apache.kafka.clients.producer.internals.FutureRecordMetadata.get(FutureRecordMetadata.java:30)
> at
> org.trafodion.sql.kafka.TimeseriesEndPoint$customHandler.handle(TimeseriesEndPoint.java:315)
> at
> org.eclipse.jetty.server.handler.HandlerWrapper.handle(HandlerWrapper.java:132)
> at org.eclipse.jetty.server.Server.handle(Server.java:505)
> at
> org.eclipse.jetty.server.HttpChannel.handle(HttpChannel.java:370)
> at
> org.eclipse.jetty.server.HttpConnection.onFillable(HttpConnection.java:267)
> at org.eclipse.jetty.io
> .AbstractConnection$ReadCallback.succeeded(AbstractConnection.java:305)
> at org.eclipse.jetty.io
> .FillInterest.fillable(FillInterest.java:103)
> at org.eclipse.jetty.io
> .ChannelEndPoint$2.run(ChannelEndPoint.java:117)
> at
> org.eclipse.jetty.util.thread.strategy.EatWhatYouKill.runTask(EatWhatYouKill.java:333)
> at
> org.eclipse.jetty.util.thread.strategy.EatWhatYouKill.doProduce(EatWhatYouKill.java:310)
> at
> org.eclipse.jetty.util.thread.strategy.EatWhatYouKill.tryProduce(EatWhatYouKill.java:168)
> at
> org.eclipse.jetty.util.thread.strategy.EatWhatYouKill.run(EatWhatYouKill.java:126)
> at
> org.eclipse.jetty.util.thread.ReservedThreadExecutor$ReservedThread.run(ReservedThreadExecutor.java:366)
> at
> org.eclipse.jetty.util.thread.QueuedThreadPool.runJob(QueuedThreadPool.java:781)
> at
> org.eclipse.jetty.util.thread.QueuedThreadPool$Runner.run(QueuedThreadPool.java:917)
> at java.lang.Thread.run(Thread.java:748)
> Caused by: org.apache.kafka.common.errors.TimeoutException: Expiring 1
> record(s) for DEFAULT-.TIMESERIES.SmartpumpCollectorVector--112:120000
> ms has passed since batch creation
>
> So I am suspecting that I am producing too fast, and brokers cannot
> catch up.
> I tried bumping up the io thread from default 8 to 40, that did not help.
>
> I am getting a producing rate of only about 100 message per seconds,
> and about 1 Megabyte per seconds according to kafka metrics.
> The CPU utilization is barely noticeable (3%), network is ridiculously
> unaffected, and having googled around, this is not the kind of perf I
> should expect out of my config. I was hoping for at least 10X more if
> not 100X better. Was my expectations too high, or am I missing
> something in config that is causing this performance numbers?
>
> Some details: I produce using a jetty custom handler that I verified
> to be super-fast when I am not producing (commenting out the send()),
> and I am using a single (I also tried with 2) producer reused on all jetty
> threads.
>
> Any help/clue would be much appreciated, Thanks in advance, Eric
> Owhadi Esgyn Corporation.
>
>
>
