[ 
https://issues.apache.org/jira/browse/CASSANDRA-20250?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17926966#comment-17926966
 ] 

Dmitry Konstantinov edited comment on CASSANDRA-20250 at 2/13/25 9:47 PM:
--------------------------------------------------------------------------

Updates:
 * adjust Timer instances to use new Meter implementation - DONE
 * move the ticks out of mark logic to a background thread - DONE
 * try to move average to another non-thread local array to improve 
fetching/caching during the bulk update - in progress
 * add metrics id release logic when metrics are unregistered from the registry 
- partially done, need to think about safety in some concurrency scenarios
 * code cleanup: remove LazySetArrayThreadLocalMetrics, rename 
PiggybackArrayThreadLocalMetrics to ThreadLocalMetrics - DONE
 * run a e2e stress test for the current logic in the branch - DONE

Additionally I have transferred codahale Histogram to the thread local metrics 
usage too - it had AtomicLong for count as well.
!Histogram_AtomicLong.png|width=500!

Write stress test results:
{code:java}
Results:
Op rate                   :  163,892 op/s  [WRITE: 163,892 op/s]
Partition rate            :  163,892 pk/s  [WRITE: 163,892 pk/s]
Row rate                  :  163,892 row/s [WRITE: 163,892 row/s]
Latency mean              :    0.6 ms [WRITE: 0.6 ms]
Latency median            :    0.5 ms [WRITE: 0.5 ms]
Latency 95th percentile   :    0.9 ms [WRITE: 0.9 ms]
Latency 99th percentile   :    1.3 ms [WRITE: 1.3 ms]
Latency 99.9th percentile :    7.7 ms [WRITE: 7.7 ms]
Latency max               :  111.1 ms [WRITE: 111.1 ms]
Total partitions          : 10,000,000 [WRITE: 10,000,000]
Total errors              :          0 [WRITE: 0]
Total GC count            : 0
Total GC memory           : 0 B
Total GC time             :    0.0 seconds
Avg GC time               :    NaN ms
StdDev GC time            :    0.0 ms
Total operation time      : 00:01:01
{code}
The current flamegraph: [^5.1_tl4_profile_cpu.html]

"metrics" weight is 4.69% now (it was 8.65%)
where "ThreadLocalMetrics" weight: 0.74%, "Reservoir": 2.87%

Regarding e2e throughput I feel that partially CASSANDRA-20226 and 
CASSANDRA-20310 bottlenecks are starting to play a major role..


was (Author: dnk):
Updates:
 * adjust Timer instances to use new Meter implementation - DONE
 * move the ticks out of mark logic to a background thread - DONE
 * try to move average to another non-thread local array to improve 
fetching/caching during the bulk update - in progress
 * add metrics id release logic when metrics are unregistered from the registry 
- partially done, need to think about safety in some concurrency scenarios
 * code cleanup: remove LazySetArrayThreadLocalMetrics, rename 
PiggybackArrayThreadLocalMetrics to ThreadLocalMetrics - DONE
 * run a e2e stress test for the current logic in the branch - DONE

Additionally I have transferred codahale Histogram to the thread local metrics 
usage too - it had AtomicLong for count as well.
!Histogram_AtomicLong.png|width=500!

Write stress test results:
{code:java}
Results:
Op rate                   :  163,892 op/s  [WRITE: 163,892 op/s]
Partition rate            :  163,892 pk/s  [WRITE: 163,892 pk/s]
Row rate                  :  163,892 row/s [WRITE: 163,892 row/s]
Latency mean              :    0.6 ms [WRITE: 0.6 ms]
Latency median            :    0.5 ms [WRITE: 0.5 ms]
Latency 95th percentile   :    0.9 ms [WRITE: 0.9 ms]
Latency 99th percentile   :    1.3 ms [WRITE: 1.3 ms]
Latency 99.9th percentile :    7.7 ms [WRITE: 7.7 ms]
Latency max               :  111.1 ms [WRITE: 111.1 ms]
Total partitions          : 10,000,000 [WRITE: 10,000,000]
Total errors              :          0 [WRITE: 0]
Total GC count            : 0
Total GC memory           : 0 B
Total GC time             :    0.0 seconds
Avg GC time               :    NaN ms
StdDev GC time            :    0.0 ms
Total operation time      : 00:01:01
{code}
The current flamegraph: [^5.1_tl4_profile_cpu.html]

"metrics" weight is 4.69% now (it was 8.65%)
where "ThreadLocalMetrics" weight: 0.74%, "Reservoir": 2.87%

> Provide the ability to disable specific metrics collection
> ----------------------------------------------------------
>
>                 Key: CASSANDRA-20250
>                 URL: https://issues.apache.org/jira/browse/CASSANDRA-20250
>             Project: Apache Cassandra
>          Issue Type: New Feature
>          Components: Observability/Metrics
>            Reporter: Dmitry Konstantinov
>            Assignee: Dmitry Konstantinov
>            Priority: Normal
>         Attachments: 5.1_profile_cpu.html, 
> 5.1_profile_cpu_without_metrics.html, 5.1_tl4_profile_cpu.html, 
> Histogram_AtomicLong.png, async_profiler_cpu_profiles.zip, 
> cpu_profile_insert.html, jmh-result.json, vmstat.log, 
> vmstat_without_metrics.log
>
>
> Cassandra has a lot of metrics collected, many of them are collected per 
> table, so their instance number is multiplied by number of tables. From one 
> side it gives a better observability, from another side metrics are not for 
> free, there is an overhead associated with them:
> 1) CPU overhead: in case of simple CPU bound load: I already see like 5.5% of 
> total CPU spent for metrics in cpu framegraphs for read load and 11% for 
> write load. 
> Example: [^cpu_profile_insert.html] (search by "codahale" pattern). The 
> framegraph is captured using Async profiler build: 
> async-profiler-3.0-29ee888-linux-x64
> 2) memory overhead: we spend memory for entities used to aggregate metrics 
> such as LongAdders and reservoirs + for MBeans (String concatenation within 
> object names is a major cause of it, for each table+metric name combination a 
> new String is created)
>  
> The idea of this ticket is to allow an operator to configure a list of 
> disabled metrics in cassandra.yaml, like:
> {code:java}
> disabled_metrics:
>     - metric_a
>     - metric_b
> {code}
> From implementation point of view I see two possible approaches (which can be 
> combined):
>  # Generic: when a metric is registering if it is listed in disabled_metrics 
> we do not publish it via JMX and provide a noop implementation of metric 
> object (such as histogram) for it.
> Logging analogy: log level check within log method
>  # Specialized: for some metrics the process of value calculation is not for 
> free and introduces an overhead as well, in such cases it would be useful to 
> check within specific logic using an API (like: isMetricEnabled) do we need 
> to do it. Example of such metric: 
> ClientRequestSizeMetrics.recordRowAndColumnCountMetrics
> Logging analogy: an explicit 'if (isDebugEnabled())' condition used when a 
> message parameter is expensive.



--
This message was sent by Atlassian Jira
(v8.20.10#820010)

---------------------------------------------------------------------
To unsubscribe, e-mail: [email protected]
For additional commands, e-mail: [email protected]

Reply via email to