phoenix-dev mailing list archives

Site index · List index
Message view « Date » · « Thread »
Top « Date » · « Thread »
From Enis Söztutar <>
Subject Re: Coprocessor metrics
Date Mon, 14 Nov 2016 20:22:18 GMT
Thanks everyone, this is really helpful. If we can leverage the work
already Josh/Nick did in Avatica in HBase that will be really good.

Seems that the consensus is to follow #2 approach, and pay the price at
replicating the API layer in HBase for the convenience of coprocessors and
not to tie ourselves with a third party API + implementation.

However, even if we do an avatica release, HBase depending on metrics API
in Avatica is the same thing as HBase depending on dropwizard directly
since HBase does not "control" the Avatica API either. At this point
blindly forking the code inside HBase seems like the way to go (possibly in
it's own module).

Let me poke around, and fork the code if possible inside HBase. I'll send
reviews your way.


On Mon, Nov 14, 2016 at 7:58 AM, Josh Elser <> wrote:

> Yep -- see avatica-metrics[1], avatica-dropwizard-metrics3[2], and my
> dropwizard-hadoop-metrics2[3] project for what Nick is referring to.
> What I ended up doing in Calcite/Avatica was a step beyond your #3, Enis.
> Instead of choosing a subset of some standard metrics library to expose, I
> "re-built" the actual API that I wanted to expose. At the end of the day,
> the API I "built" was nearly 100% what dropwizard metrics' API was. I like
> the dropwizard-metrics API; however, we wanted to avoid the strong coupling
> to a single metrics implementation.
> My current feeling is that external API should never include
> classes/interfaces which you don't "own". Re-building the API that already
> exists is pedantic, but I think it's a really good way to pay down the
> maintenance debt (whenever the next metrics library "hotness" takes off).
> If it's amenable to you, Enis, I'm happy to work with you to do whatever
> decoupling of this metrics abstraction away from the "core" of Avatica
> (e.g. presently, a new update of the library would also require a full
> release of Avatica which is no-good for HBase). I think a lot of the
> lifting I've done already would be reusable by you and help make a better
> product at the end of the day.
> - Josh
> [1]
> [2]
> s-dropwizardmetrics3
> [3]
> Nick Dimiduk wrote:
>> IIRC, the plan is to get off of Hadoop Metrics2, so I am in favor of
>> either
>> (2) or (3). Specifically for (3), I believe there is an implementation for
>> translating Dropwizard Metrics to Hadoop Metrics2, in or around Avatica
>> and/or Phoenix Query Server.
>> On Fri, Nov 11, 2016 at 3:15 PM, Enis Söztutar<>  wrote:
>> HBase / Phoenix devs,
>>> I would like to solicit early feedback on the design approach that we
>>> would
>>> pursue for exposing coprocessor metrics. It has implications for our
>>> compatibility, so lets try to have some consensus. Added Phoenix devs as
>>> well since this will affect how coprocessors can emit metrics via region
>>> server metrics bus.
>>> The issue is HBASE-9774 [1].
>>> We have a couple of options:
>>> (1) Expose Hadoop Metrics2 + HBase internal classes (like BaseSourceImpl,
>>> MutableFastCounter, FastLongHistogram, etc). This option is the least
>>> amount of work in terms of defining the API. We would mark the important
>>> classes with LimitedPrivate(Coprocessor) and have the coprocessors each
>>> write their metrics source classes separately. The disadvantage would be
>>> that some of the internal APIs are now public and has to be evolved with
>>> regards to coprocessor API compatibility. Also it will make it so that
>>> breaking coprocessors are now easier across minor releases.
>>> (2) Build a Metrics subset API in HBase to abstract away HBase metrics
>>> classes and Hadoop2 metrics classes and expose this API only. The API
>>> will
>>> probably be limited and will be a small subset. HBase internals do not
>>> need
>>> to be changed that much, but the API has to be kept
>>> LimitedPrivate(Coprocessor) with the compatibility implications.
>>> (3) Expose (a limited subset of) third-party API to the coprocessors
>>> (like
>>> Yammer metrics) and never expose internal HBase / Hadoop implementation.
>>> Build a translation layer between the yammer metrics and our Hadoop
>>> metrics
>>> 2 implementation so that things will still work. If we end up changing
>>> the
>>> implementation, existing coprocessors will not be affected. The downside
>>> is
>>> that whatever API that we agree to expose becomes our compatibility
>>> point.
>>> We cannot change that dependency version unless it is acceptable via our
>>> compatibility guidelines.
>>> Personally, I would like to pursue option (3) especially with Yammer
>>> metrics since we do not have to build yet another API endpoint. Hadoop's
>>> metrics API is not the best and we do not know whether we will end up
>>> changing that dependency. What do you guys think?
>>> [1]

  • Unnamed multipart/alternative (inline, None, 0 bytes)
View raw message