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https://issues.apache.org/jira/browse/STORM-2153?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15587039#comment-15587039
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Jungtaek Lim edited comment on STORM-2153 at 10/18/16 11:40 PM:
----------------------------------------------------------------

If worker reports metrics directly there is going to be no room for 
aggregation. That is fine for external time-series DB (since they are able to 
aggregate before showing), but sometimes they're still too many metrics points 
which slow down aggregation.

Btw, I don't intend to put more pressures to anyone, but only addressing 
reporter doesn't resolve the issues behind current metrics.
I really would like to emphasize that there're design issues on metrics, not 
just API itself. I just waited JStorm merger phase 2 to address this, but this 
will not be going to happen even this year, so would just shout out again.

Please refer below links: 

* 
https://cwiki.apache.org/confluence/display/STORM/Limitations+of+current+metrics+feature
* 
https://cwiki.apache.org/confluence/display/STORM/Wishlist+for+new+metrics+feature

While I don't think we should address whole kinds of wishlist, I strongly think 
we should get rid of current limitations of metrics if we really want to touch 
the thing.
And JStorm approach seems to be able to address all kinds of current 
limitations. Centralize (to Nimbus) + internal fast storage (RocksDB) is the 
key, and TopologyMaster sends workers metrics to Nimbus efficiently. (TM seems 
not aggregate the value of metric itself, but maximize the throughput between 
TM and Nimbus) 

I haven't look at metrics system on Kafka Streams and Flink (they seemed to 
renew the metrics) but having a look should help to set direction right.


was (Author: kabhwan):
If worker reports metrics directly there is going to be no room for 
aggregation. That is fine for external time-series DB (since they are able to 
aggregate before showing), but sometimes they're still too many metrics points 
which slows down aggregation.

Btw, I don't intend to put more pressures to anyone, but only addressing 
reporter doesn't resolve the issues behind current metrics.
I really would like to emphasize that there're design issues on metrics, not 
just API itself. I just waited JStorm merger phase 2 to address this, but this 
will not be going to happen even this year, so would just shout out again.

Please refer below links: 

* 
https://cwiki.apache.org/confluence/display/STORM/Limitations+of+current+metrics+feature
* 
https://cwiki.apache.org/confluence/display/STORM/Wishlist+for+new+metrics+feature

While I don't think we should address whole kinds of wishlist, I strongly think 
we should get rid of current limitations of metrics if we really want to touch 
the thing.
And JStorm approach seems to be able to address all kinds of current 
limitations. Centralize (to Nimbus) + internal fast storage (RocksDB) is the 
key, and TopologyMaster sends workers metrics to Nimbus efficiently. (TM seems 
not aggregate the value of metric itself, but maximize the throughput between 
TM and Nimbus) 

I haven't look at metrics system on Kafka Streams and Flink (they seemed to 
renew the metrics) but having a look should help to set direction right.

> New Metrics Reporting API
> -------------------------
>
>                 Key: STORM-2153
>                 URL: https://issues.apache.org/jira/browse/STORM-2153
>             Project: Apache Storm
>          Issue Type: Improvement
>            Reporter: P. Taylor Goetz
>
> This is a proposal to provide a new metrics reporting API based on [Coda 
> Hale's metrics library | http://metrics.dropwizard.io/3.1.0/] (AKA 
> Dropwizard/Yammer metrics).
> h2. Background
> In a [discussion on the dev@ mailing list | 
> http://mail-archives.apache.org/mod_mbox/storm-dev/201610.mbox/%3ccagx0urh85nfh0pbph11pmc1oof6htycjcxsxgwp2nnofukq...@mail.gmail.com%3e]
>   a number of community and PMC members recommended replacing Storm’s metrics 
> system with a new API as opposed to enhancing the existing metrics system. 
> Some of the objections to the existing metrics API include:
> # Metrics are reported as an untyped Java object, making it very difficult to 
> reason about how to report it (e.g. is it a gauge, a counter, etc.?)
> # It is difficult to determine if metrics coming into the consumer are 
> pre-aggregated or not.
> # Storm’s metrics collection occurs through a specialized bolt, which in 
> addition to potentially affecting system performance, complicates certain 
> types of aggregation when the parallelism of that bolt is greater than one.
> In the discussion on the developer mailing list, there is growing consensus 
> for replacing Storm’s metrics API with a new API based on Coda Hale’s metrics 
> library. This approach has the following benefits:
> # Coda Hale’s metrics library is very stable, performant, well thought out, 
> and widely adopted among open source projects (e.g. Kafka).
> # The metrics library provides many existing metric types: Meters, Gauges, 
> Counters, Histograms, and more.
> # The library has a pluggable “reporter” API for publishing metrics to 
> various systems, with existing implementations for: JMX, console, CSV, SLF4J, 
> Graphite, Ganglia.
> # Reporters are straightforward to implement, and can be reused by any 
> project that uses the metrics library (i.e. would have broader application 
> outside of Storm)
> As noted earlier, the metrics library supports pluggable reporters for 
> sending metrics data to other systems, and implementing a reporter is fairly 
> straightforward (an example reporter implementation can be found here). For 
> example if someone develops a reporter based on Coda Hale’s metrics, it could 
> not only be used for pushing Storm metrics, but also for any system that used 
> the metrics library, such as Kafka.
> h2. Scope of Effort
> The effort to implement a new metrics API for Storm can be broken down into 
> the following development areas:
> # Implement API for Storms internal worker metrics: latencies, queue sizes, 
> capacity, etc.
> # Implement API for user defined, topology-specific metrics (exposed via the 
> {{org.apache.storm.task.TopologyContext}} class)
> # Implement API for storm daemons: nimbus, supervisor, etc.
> h2. Relationship to Existing Metrics
> This would be a new API that would not affect the existing metrics API. Upon 
> completion, the old metrics API would presumably be deprecated, but kept in 
> place for backward compatibility.
> Internally the current metrics API uses Storm bolts for the reporting 
> mechanism. The proposed metrics API would depend on any of Storm's messaging 
> capabilities and instead use the [metrics library's built-in reporter 
> mechanism | 
> http://metrics.dropwizard.io/3.1.0/manual/core/#man-core-reporters]. This 
> would allow users to use existing {{Reporter}} implementations which are not 
> Storm-specific, and would simplify the process of collecting metrics. 
> Compared to Storm's {{IMetricCollector}} interface, implementing a reporter 
> for the metrics library is much more straightforward (an example can be found 
> [here | 
> https://github.com/dropwizard/metrics/blob/3.2-development/metrics-core/src/main/java/com/codahale/metrics/ConsoleReporter.java].
> The new metrics capability would not use or affect the ZooKeeper-based 
> metrics used by Storm UI.
> h2. Relationship to JStorm Metrics
> [TBD]
> h2. Target Branches
> [TBD]
> h2. Performance Implications
> [TBD]
> h2. Metrics Namespaces
> [TBD]
> h2. Metrics Collected
> *Worker*
> || Namespace || Metric Type || Description ||
> *Nimbus*
> || Namespace || Metric Type || Description ||
> *Supervisor*
> || Namespace || Metric Type || Description ||
> h2. User-Defined Metrics
> [TBD]



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