We have been facing an issue where message rate of a xmitq is very slow comparing with what should be a normal performance.
We have many other Qmgrs with bigger MQ flows that don't have the same issue.
Our HUB qmgr connects to business line in the same company HUB qmgr, and even the destination queues on their side being empty the flow is really slow.
At OS and Network level they say nothing can be done. At MQ we have changed the Buffersizes so it matches the OS level and uses the system tcp windows.
Now at MQ level we have the channel SDR setup with BATCHSZ to 100, but seems the receiver is configured with 30.
We noticed that because we see messages flow in batches fof 30 messages. Also not sure if that is related but we see the XMITQ havs always 30 uncommited messages.
Our questiong for advice.
Would increase the BATCHSZ parameter on SDR/RCVR help the perfomance?
Is there any other parameter at MQ level that could help it?
DIS CHS(NAME) ALL
AMQ8417: Display Channel Status details.
CHANNEL(QMGRA.QMGRB.T7) CHLTYPE(SDR)
BATCHES(234) BATCHSZ(30)
BUFSRCVD(235) BUFSSENT(6391)
BYTSRCVD(6996) BYTSSENT(14396692)
CHSTADA(2020-04-16) CHSTATI(14.38.17)
COMPHDR(NONE,NONE) COMPMSG(NONE,NONE)
COMPRATE(0,0) COMPTIME(0,0)
CONNAME(159.50.69.38(48702)) CURLUWID(398F3E5EEA43381C)
CURMSGS(30) CURRENT
CURSEQNO(43488865) EXITTIME(0,0)
HBINT(300) INDOUBT(YES)
JOBNAME(000051FC00000001) LOCLADDR(10.185.8.122(54908))
LONGRTS(999999999) LSTLUWID(398F3E5EE943381C)
LSTMSGDA(2020-04-16) LSTMSGTI(14.49.46)
LSTSEQNO(43488835) MCASTAT(RUNNING)
MONCHL(HIGH) MSGS(6386)
NETTIME(2789746,3087573) NPMSPEED(NORMAL)
RQMNAME(QMGRB) SHORTRTS(10)
SSLCERTI(*******************)
SSLKEYDA( ) SSLKEYTI( )
SSLPEER(*******************)
SSLRKEYS(0) STATUS(RUNNING)
STOPREQ(NO) SUBSTATE(RECEIVE)
XBATCHSZ(23,7) XMITQ(QMGRB.X7)
XQTIME(215757414,214033427) RVERSION(08000008)
RPRODUCT(MQMM)
qm.ini:
Log:
LogPrimaryFiles=10
LogSecondaryFiles=10
LogFilePages=16384
LogType=LINEAR
LogBufferPages=4096
LogPath=/apps/wmq/QMGR/log/QMGR/
LogWriteIntegrity=SingleWrite
Service:
Name=AuthorizationService
EntryPoints=13
TCP:
SvrSndBuffSize=0
SvrRcvBuffSize=0
ServiceComponent:
Service=AuthorizationService
Name=MQSeries.UNIX.auth.service
Module=/opt/mqm75/lib64/amqzfu
ComponentDataSize=0
Channels:
MaxChannels=500
UPDATED: 15:41 GMT
Just to update the information, both sides are now with BATCHSZ 100 and seems slightly.
AMQ8417: Display Channel Status details.
CHANNEL(QMGRA.QMGRB.T7) CHLTYPE(SDR)
BATCHES(403) BATCHSZ(100)
BUFSRCVD(405) BUFSSENT(23525)
BYTSRCVD(11756) BYTSSENT(53751066)
CHSTADA(2020-04-17) CHSTATI(15.13.51)
COMPHDR(NONE,NONE) COMPMSG(NONE,NONE)
COMPRATE(0,0) COMPTIME(0,0)
CONNAME(159.50.69.38(48702)) CURLUWID(6D66985E94343410)
CURMSGS(0) CURRENT
CURSEQNO(44115897) EXITTIME(0,0)
HBINT(300) INDOUBT(NO)
JOBNAME(0000172A00000001) LOCLADDR(10.185.8.122(2223))
LONGRTS(999999999) LSTLUWID(6D66985E93343410)
LSTMSGDA(2020-04-17) LSTMSGTI(15.30.06)
LSTSEQNO(44115897) MCASTAT(RUNNING)
MONCHL(HIGH) MSGS(23505)
NETTIME(101563,480206) NPMSPEED(NORMAL)
RQMNAME(QMGRB) SHORTRTS(10)
SSLCERTI(*************************************)
SSLKEYDA( ) SSLKEYTI( )
SSLPEER(****************************)
SSLRKEYS(0) STATUS(RUNNING)
STOPREQ(NO) SUBSTATE(MQGET)
XBATCHSZ(1,1) XMITQ(QMGRB.X7)
XQTIME(191225,794134) RVERSION(08000008)
RPRODUCT(MQMM)
AMQ8450: Display queue status details.
QUEUE(QMGRB.X7) TYPE(QUEUE)
CURDEPTH(0) IPPROCS(1)
LGETDATE(2020-04-17) LGETTIME(15.30.06)
LPUTDATE(2020-04-17) LPUTTIME(15.30.06)
MEDIALOG(S2488154.LOG) MONQ(LOW)
MSGAGE(0) OPPROCS(9)
QTIME(794134, 191225) UNCOM(NO)
I'll put a few observations in this answer, but based on any further feedback I may add more.
You are running a very old version of the software on the sender side, MQ 7.5 went out of support almost two years ago (April 30 2018). IBM for a cost will provide extended support for an additional three years, so maybe you fall in that group. The 7.5.0.2 maintenance release itself came out in July 11th 2013, so it is almost seven years old at this point. I would strongly suggest you move to a newer version.
Note that MQ v8.0 goes out of support April 30 2020, and IBM just announced a few days ago that MQ v9.0 goes out of support September 30 2021. When you do migrate you should go with either 9.1 which has no announced end of support (they give five years minimum so it could be 2023) or go with the next version of MQ that should be out some time this year.
You mention setting the following:
TCP:
SvrSndBuffSize=0
SvrRcvBuffSize=0
The above setting apply to the SVRCONN end of a client connection. You can see this in the MQ v7.5 Knowledge Center page WebSphere MQ>Configuring>Changing configuration information>Changing queue manager configuration information>TCP, LU62, NETBIOS, and SPX:
SvrSndBuffSize=32768|number
The size in bytes of the TCP/IP send buffer used by the server end of a client-connection
server-connection channel.
SvrRcvBuffSize=32768|number
The size in bytes of the TCP/IP receive buffer used by the server end of a client-connection
server-connection channel.
At IBM MQ v7.5.0.2 APAR IV58073 introduced the concept of setting various buffer settings to a value to 0 which means that it will allow the operating system defaults to be used. Unfortunately like many things in the Knowledge Center it does not look like IBM documented this correctly for 7.5.
You can however review the IBM MQ v8.0 Knowledge Center to get the full picture regarding these settings at the page Configuring>Changing configuration information>Changing queue manager configuration information>TCP, LU62, and NETBIOS, specifically you would want to set these two settings to have any impact on your Sender Channel:
SndBuffSize=number| 0
The size in bytes of the TCP/IP send buffer used by the sending end of
channels. This stanza value can be overridden by a stanza more
specific to the channel type, for example RcvSndBuffSize. If the
value is set as zero, the operating system defaults are used. If no
value is set, then the IBM MQ default, 32768, is used.
RcvSndBuffSize=number| 0
The size in bytes of the TCP/IP send buffer used by the sender end of
a receiver channel. If the value is set as zero, the operating system
defaults are used. If no value is set, then the IBM MQ default, 32768,
is used.
Starting at IBM MQ v8.0 any newly created queue manager will have all of the following in the qm.ini:
TCP:
SndBuffSize=0
RcvBuffSize=0
RcvSndBuffSize=0
RcvRcvBuffSize=0
ClntSndBuffSize=0
ClntRcvBuffSize=0
SvrSndBuffSize=0
SvrRcvBuffSize=0
However, any queue manager that is upgraded will not by default get those settings, meaning if those are not present they will not be added, if they are present they will remain the same. If the setting is not present then as it says above "the IBM MQ default, 32768, is used."
I had extensive discussions with IBM support on this topic and came to the conclusion that they did not see any reason to not set it to 0, they only saw benefit in doing so, but with an abundance of caution they do not change it to 0 for you.
I would recommend you add all of those to your qm.ini, but at minimum add the two I highlighted above.
These are good setting to implement but may not solve your problem if nothing changed recently on either end. If however something did change, for example a network difference, or MQ was upgraded to 8.0.0.8 on the remote side, then this setting just might solve your problem.
In the channel status output two values are interesting:
NETTIME(2789746,3087573)
XQTIME(215757414,214033427)
NETTIME means that based on recent activity it took 2.7 seconds to receive a response from the RCVR channel, over a longer period of time it took 3.1 seconds to receive a response from the RCVR channel. Can you compare this to a TCP ping from the sender channel server to the receive channel server, 2.7 seconds for a response over the network seems excessive. In the presentation Keeping MQ Channels Up and Running given at Capitalware's MQ Technical Conference v2.0.1.4, Paul Clarke who used to work for IBM states "NETTIME only measures network time, and does not include
the MQCMIT for example".
XQTIME means that based on recent activity and over a longer period of time it took ~215 seconds for a message on the XMITQ to be picked up by the SDR channel to be sent.
See below for how IBM documents these:
NETTIME
Amount of time, displayed in microseconds, to send a request to the remote end of the channel and receive a response. This time only measures the network time for such an operation. Two values are displayed:
A value based on recent activity over a short period.
A value based on activity over a longer period.
XQTIME
The time, in microseconds, that messages remained on the transmission queue before being retrieved. The time is measured from when the message is put onto the transmission queue until it is retrieved to be sent on the channel and, therefore, includes any interval caused by a delay in the putting application.
Two values are displayed:
A value based on recent activity over a short period.
A value based on activity over a longer period.
Information on the BATCHSZ channel parameter can be found in the IBM MQ v8.0 Knowledge Center page Reference>Configuration reference>Channel attributes>Channel attributes in alphabetical order>Batch size (BATCHSZ). I have quoted it and highlighted a few areas in bold.
This attribute is the maximum number of messages to be sent before a sync point is taken.
The batch size does not affect the way the channel transfers messages; messages are always transferred individually, but are committed or backed out as a batch.
To improve performance, you can set a batch size to define the maximum number of messages to be transferred between two sync points. The batch size to be used is negotiated when a channel starts, and the lower of the two channel definitions is taken. On some implementations, the batch size is calculated from the lowest of the two channel definitions and the two queue manager MAXUMSGS values. The actual size of a batch can be less; for example, a batch completes when there are no messages left on the transmission queue or the batch interval expires.
A large value for the batch size increases throughput, but recovery times are increased because there are more messages to back out and send again. The default BATCHSZ is 50, and you are advised to try that value first. You might choose a lower value for BATCHSZ if your communications are unreliable, making the need to recover more likely.
This attribute is valid for channel types of:
Sender
Server
Receiver
Requester
Cluster sender
Cluster receiver
Follow up questions:
Are the messages that are PUT to this XMITQ persistent?
Answer: Yes, in our PROD env all messages are pesistent.
Have you had a recent increase in volume going to this XMITQ?
Answer: No, we use a monitoring tools, we extracted a report that show very similar message rate during the period. The same rate over the last 2 weeks.
Do the putting applications set MQPMO_SYNCPOINT and then commit after 1 or more messages are PUT to the queue?
Answer: I will check with the application team.
A couple of things..
You have XBATCHSZ(1,1) so your recent batch size is 1 message per batch.
Total messages 23505 batches 403, so an average of 58 messages per batch. If your recent batch size is 1, then you must have had some larger (100?) batch sizes
XQTIME 191225 is number of microseconds messages were on the xmit queue before being sent. This is 0.1 second!
Nettime 101563 microseconds. This is a long time ( 0.1 seconds) 10,000 would be a good value. Compare this with a "TCP PING"
BUFSSENT 23525 is similar to number of messages - so message size is typically under 32K. Bytessent. messages gives 2286 so small messages.
Things to check
The queue at the remote end. Has it filled up? This would cause the sender queue to get more messages
The nettime seems very long. Compare this with TCP Ping. Nettime can include slow IO at the remote end - or a queue full at the remote end
XQTIME is high. This could be caused by sending applications not committing, or slow disk IO
I wrote "Why is my xmit queue filling up" in this blog
*Search for the title
have a read.
Capture these metrics over a day and see if they are typical
regards
Colin Paice
We are testing the capacity of a Mail relay based on RHEL 7.6.
We are observing issues when sending an important number of msgs (e.g.: ~1000 msgs in 60 seconds).
While we have sent all the msgs and the recipient has received all the msgs, logs are missing in the /var/log/maillog_rfc5424.
We have the following message in the /var/log/messages:
rsyslogd: imjournal: XYZ messages lost due to rate-limiting
We adapted the /etc/rsyslog.conf with the following settings but without effect:
$SystemLogRateLimitInterval 0 # turn off rate limit
$SystemLogRateLimitBurst 0 # turn rate limit off
Any ideas ?
The error is from imjournal, but your configuration settings are for imuxsock.
According to the rsyslog configuration page you need to set
$imjournalRatelimitInterval 0
$imjournalRatelimitBurst 0
Note that for very high message rates you might like to change to imuxsock, as it says:
this module may be notably slower than when using imuxsock. The journal provides imuxsock with a copy of all “classical” syslog messages, however, it does not provide structured data. Only if that structured data is needed, imjournal must be used. Otherwise, imjournal may simply be replaced by imuxsock, and we highly suggest doing so.
RocketMQ version: 3.2.6
Our cluster:
2 NameServer
6 Master Broker
6 Slave Broker
We have a lot of consumers(about 100) consume message from broker ,
We use command to monitor consume diff command:
/data/alibaba-rocketmq/bin/mqadmin consumerProgress -n XXX:XX The
diff is negative (eg: -898232391123,-8323231872) in only one
broker,other brokers is healthy.
A lot of broker warn log below
a lot of errors : Consumer request offset is much bigger than max offset
a lot of errors : connection reset frequently
finally，I found the answer in github
https://github.com/alibaba/RocketMQ/releases
It's a bug and fixed in version 3.4.6. That's ok.
I have running ZooKeeper and single Kafka broker and I want to get metrics with MetricBeat, index it with ElasticSearch and display with Kibana.
However, MetricBeat can only get data from partition metricset and nothing comes from consumergroup metricset.
Since kafka module is defined as periodical in metricbeat.yml, it should send some data on it's own, not just waiting for users interaction (f.exam. - write to topic) ?
To ensure myself, I tried to create consumer group, write and consume from topic, but still no data was collected by consumergroup metricset.
consumergroup is defined in both metricbeat.template.json and metricbeat.template-es2x.json.
While metricbeat.full.yml is completely commented off, this is my metricbeat.yml kafka module definition :
- module: kafka
metricsets: ["partition", "consumergroup"]
enabled: true
period: 10s
hosts: ["localhost:9092"]
client_id: metricbeat1
retries: 3
backoff: 250ms
topics: []
In /logs directory of MetricBeat, lines like this show up :
INFO Non-zero metrics in the last 30s:
libbeat.es.published_and_acked_events=109
libbeat.es.publish.write_bytes=88050
libbeat.publisher.messages_in_worker_queues=109
libbeat.es.call_count.PublishEvents=5
fetches.kafka-partition.events=106
fetches.kafka-consumergroup.success=2
libbeat.publisher.published_events=109
libbeat.es.publish.read_bytes=2701
fetches.kafka-partition.success=2
fetches.zookeeper-mntr.events=3
fetches.zookeeper-mntr.success=3
With ZooKeeper's mntr and Kafka's partition, I can see events= and success= values, but for consumergroup there is only success. It looks like no events are fired.
partition and mntr data are properly visible in Kibana, while consumergroup is missing.
Data stored in ElasticSearch are not readable with human eye, there are some internal strings used for directory names and logs do not contain any useful information.
Can anybody help me to understand what is going on and fix it(probably MetricBeat) to send data to ElasticSearch ? Thanks :)
You need to have an active consumer consuming out of the topics, to be able to generate events for consumergroup metricset.
This is what my storm UI stat looks like.
The problem is that I have no idea where those numbers (of emitted tuples are coming from).
My topology is pretty simple: kafka spout -> bolt (persisting data into hbase)
topology works - when I put data into kafka topic, I get them processed by bolt and persisted in hbase, which I then verify with scan operator in hbase shell (so new records are being inserted)
however each time I submit new message into kafka and when it’s persisted by bolt - my topology doesn’t increase number of emitted by ‘1’.
periodically I get all numbers increased by 20 - without sending any new messages into kafka. I.e. my kafka topic gets no messages for hours, but the number of tuples emitted always get increased in chunks of 20 over time. I still get the same number of records in hbase.
I get no exceptions/errors anywhere in apache storm logs.
I’m not doing ack() or fail() any of my tuples in my bolt implementation (which is BasicBolt type doing ack automatically)
my capacity or latency in bolt metrics is always staying zero even when I load a lot of messages in Kafka
my kafka offset log ($KAFKA/kafka-run-class.sh kafka.tools.ConsumerOffsetChecker) shows all the messages are processed and Kafka Lag for given topic/group is 0.
So my question:
what are those ‘stealth’ tuples that increase ‘emitted’ in both Spout and Bolt over time by 20s?
is it possible to enable ‘debugging’ in storm UI to see what those tuples are?
why capacity/latency in bolt metrics is always zero while bolt is confirmed to persist data?
Environment details
I’m using Java 8 + Apache Storm 1.0.3
[devops#storm-wk1-prod]~/storm/supervisor/stormdist% storm version
Running: /usr/lib/jvm/jre-1.8.0-openjdk/bin/java -client -Ddaemon.name= -Dstorm.options= -Dstorm.home=/opt/apache-storm-1.0.3 -Dstorm.log.dir=/opt/apache-storm-1.0.3/logs -Djava.library.path=/usr/local/lib:/opt/local/lib:/usr/lib -Dstorm.conf.file= -cp /opt/apache-storm-1.0.3/lib/storm-core-1.0.3.jar:/opt/apache-storm-1.0.3/lib/kryo-3.0.3.jar:/opt/apache-storm-1.0.3/lib/reflectasm-1.10.1.jar:/opt/apache-storm-1.0.3/lib/asm-5.0.3.jar:/opt/apache-storm-1.0.3/lib/minlog-1.3.0.jar:/opt/apache-storm-1.0.3/lib/objenesis-2.1.jar:/opt/apache-storm-1.0.3/lib/clojure-1.7.0.jar:/opt/apache-storm-1.0.3/lib/disruptor-3.3.2.jar:/opt/apache-storm-1.0.3/lib/log4j-api-2.1.jar:/opt/apache-storm-1.0.3/lib/log4j-core-2.1.jar:/opt/apache-storm-1.0.3/lib/log4j-slf4j-impl-2.1.jar:/opt/apache-storm-1.0.3/lib/slf4j-api-1.7.7.jar:/opt/apache-storm-1.0.3/lib/log4j-over-slf4j-1.6.6.jar:/opt/apache-storm-1.0.3/lib/servlet-api-2.5.jar:/opt/apache-storm-1.0.3/lib/storm-rename-hack-1.0.3.jar:/opt/storm/conf org.apache.storm.utils.VersionInfo
Storm 1.0.3
URL https://git-wip-us.apache.org/repos/asf/storm.git -r eac433b0beb3798c4723deb39b3c4fad446378f4
Branch (no branch)
Compiled by ptgoetz on 2017-02-07T20:22Z
From source with checksum c78e52de4b8a22d99551d45dfe9c1a4b
My storm.yaml:
I'm running 2 instances with storm supervisor, each having the following config:
storm.zookeeper.servers:
- "10.138.0.8"
- "10.138.0.9"
- "10.138.0.16"
storm.zookeeper.port: 2181
nimbus.seeds: ["10.138.0.10"]
storm.local.dir: "/var/log/storm"
supervisor.slots.ports:
- 6700
- 6701
- 6702
- 6703
worker.childopts: "-Xmx768m"
nimbus.childopts: "-Xmx512m"
supervisor.childopts: "-Xmx256m"
toplogy.yaml
nimbus.host: "10.138.0.10"
# In Storm 0.7.x, this is necessary in order to give workers time to
# initialize. In Storm 0.8.0 and later, it may not be necessary because Storm
# has added a separate, longer timeout for the initial launch of a worker.
supervisor.worker.timeout.secs: 60
topology.workers: 1
topology
import tbolts
import tspouts
def create(builder):
"""Create toplogy through Petrel library
"""
# spout getting data from kafka instance
# we run 2 tasks of kafka spout
builder.setSpout("kafka",
tspouts.KafkaSpout(), 2)
# persistence bolt
# we run 4 tasks of persistence bolt
builder.setBolt("persistence",
tbolts.PersistenceBolt(), 4).shuffleGrouping("kafka")
The reason your emit count jumps up by 20 is due to the fact that Storm only samples every 20th tuple buy default to update its metrics. This sampling rate is controlled by the topology.stats.sample.rate config variable and can be changed per topology. So you could set this to be 1.0 (it is 0.05 by default) and you would get an accurate emit count, however this would introduce a significant processing overhead and may cause your Acker and/or metrics consumer instances to become overloaded. Use with caution.