[GitHub] spark issue #18935: [SPARK-9104][CORE] Expose Netty memory metrics in Spark

2017-09-05 Thread zsxwing
Github user zsxwing commented on the issue:

https://github.com/apache/spark/pull/18935
  
Merging to master.


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[GitHub] spark issue #18935: [SPARK-9104][CORE] Expose Netty memory metrics in Spark

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[GitHub] spark issue #18935: [SPARK-9104][CORE] Expose Netty memory metrics in Spark

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[GitHub] spark issue #18935: [SPARK-9104][CORE] Expose Netty memory metrics in Spark

2017-09-05 Thread SparkQA
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[GitHub] spark issue #18935: [SPARK-9104][CORE] Expose Netty memory metrics in Spark

2017-09-05 Thread SparkQA
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https://github.com/apache/spark/pull/18935
  
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[GitHub] spark issue #18935: [SPARK-9104][CORE] Expose Netty memory metrics in Spark

2017-09-05 Thread zsxwing
Github user zsxwing commented on the issue:

https://github.com/apache/spark/pull/18935
  
Just realized the last build is 18 days ago. Triggered a new now. Will 
merge after passing tests.


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[GitHub] spark issue #18935: [SPARK-9104][CORE] Expose Netty memory metrics in Spark

2017-09-05 Thread zsxwing
Github user zsxwing commented on the issue:

https://github.com/apache/spark/pull/18935
  
retest this please


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[GitHub] spark issue #18935: [SPARK-9104][CORE] Expose Netty memory metrics in Spark

2017-09-05 Thread zsxwing
Github user zsxwing commented on the issue:

https://github.com/apache/spark/pull/18935
  
LGTM since enableVerboseMetrics is off by default. Merging to master. 
Thanks!


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[GitHub] spark issue #18935: [SPARK-9104][CORE] Expose Netty memory metrics in Spark

2017-09-05 Thread jiangxb1987
Github user jiangxb1987 commented on the issue:

https://github.com/apache/spark/pull/18935
  
The change itself looks good, but I'm afraid it's a bit too verbose to add 
all of those metrics. cc @zsxwing .


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[GitHub] spark issue #18935: [SPARK-9104][CORE] Expose Netty memory metrics in Spark

2017-09-05 Thread squito
Github user squito commented on the issue:

https://github.com/apache/spark/pull/18935
  
lgtm

any more thoughts @jiangxb1987 @zsxwing  ?


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[GitHub] spark issue #18935: [SPARK-9104][CORE] Expose Netty memory metrics in Spark

2017-08-31 Thread jerryshao
Github user jerryshao commented on the issue:

https://github.com/apache/spark/pull/18935
  
@squito can you please review again? Thanks.


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[GitHub] spark issue #18935: [SPARK-9104][CORE] Expose Netty memory metrics in Spark

2017-08-22 Thread jerryshao
Github user jerryshao commented on the issue:

https://github.com/apache/spark/pull/18935
  
@squito , as the next following step, I would expose these metrics with 
MetricsSystem, I'm thinking of exposing shuffle related Netty memory usage. For 
RPC related memory usage, I'm not fully sure about the value of exposing them, 
though exposing them is a quite cheap call.

And furthermore, I think we can collect them in the driver side and display 
either through REST API or via web UI. But I think part of should be considered 
well on how to deliver to the end users.

As for the content of netty memory metrics, by default only two major 
memory usage will be exposed unless we enable verbose. I was thinking of 
picking some detailed metrics, but I found it is hard to decide which one is 
more important over others, so instead I chose to expose all of them and let 
user to decide which one is important. Also like you mentioned they're quite 
cheap and off by default, so I think it might be good to also optionally expose 
detailed infos.

> are you at all surprised that the direct & heap memory are exactly the 
same? Are things getting mixed up somewhere? Or maybe those are just the values 
from the initialization netty always does. 

I think it doesn't mix up anything. AFAIK it is what Netty 
`PooledByteBufAllocator` does at initialization, this 16MB is the default chunk 
size. I guess at initialization, Netty will create one chunk per arena.






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[GitHub] spark issue #18935: [SPARK-9104][CORE] Expose Netty memory metrics in Spark

2017-08-22 Thread squito
Github user squito commented on the issue:

https://github.com/apache/spark/pull/18935
  
thanks for the added info @jerryshao.

(a) ok makes sense now about the use of this -- it is not exposed now, you 
plan to expose it in future changes.  That is fine, however I would like to at 
least see a *plan* for how you want to expose this before we merge this.  I 
think past efforts have gotten tripped on how we'd expose it in the driver; 
perhaps the simplest thing to do is expose it to the metric system?  There just 
isn't any point in this unless we're going to do something with it.

(b) thanks for including the example of the metrics.  But one minor thing I 
noticed -- are you at all surprised that the direct & heap memory are exactly 
the same?  Are things getting mixed up somewhere?  Or maybe those are just the 
values from the initialization netty always does.  I definitely think that is 
more metrics than most users care about, and would want verbose off by default. 
 I am wondering if those metrics are useful at all ... but I guess they are 
pretty cheap, and maybe there is some scenario where a user would care about 
some of them, eg. `numHugeAllocations`.


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[GitHub] spark issue #18935: [SPARK-9104][CORE] Expose Netty memory metrics in Spark

2017-08-22 Thread jerryshao
Github user jerryshao commented on the issue:

https://github.com/apache/spark/pull/18935
  
@squito , here is the list of full metrics I dumped from running 
application. By default, if we don't enable verbose metric, only 2 metrics 
("usedHeapMemory" and "usedDirectMemory") will be tracked. If we enable verbose 
metrics, then the details of each arena will be tracked, the number of detailed 
metrics is 16, so the total verbose metric number will be "16 * arena number * 
2", here arena number is based on the number of cores, and "2" represents 
"direct arena" and "heap arena". 

I agree this might be too verbose for a user to track netty memory usage, 
so by default I will not enable verbose metric. Unless if developers wants to 
know the detailed behaviors of network memory usage, then they could enable 
this configuration, this might be useful for tuning and performance analysis. 
What do you think?

```

application_1503394031686_0002.1.NettyBlockTransfer.shuffle-client.directArena0.numActiveAllocations
 value = 0

application_1503394031686_0002.1.NettyBlockTransfer.shuffle-client.directArena0.numActiveBytes
 value = 16777216

application_1503394031686_0002.1.NettyBlockTransfer.shuffle-client.directArena0.numActiveHugeAllocations
 value = 0

application_1503394031686_0002.1.NettyBlockTransfer.shuffle-client.directArena0.numActiveNormalAllocations
 value = 0

application_1503394031686_0002.1.NettyBlockTransfer.shuffle-client.directArena0.numActiveSmallAllocations
 value = 0

application_1503394031686_0002.1.NettyBlockTransfer.shuffle-client.directArena0.numActiveTinyAllocations
 value = 0

application_1503394031686_0002.1.NettyBlockTransfer.shuffle-client.directArena0.numAllocations
 value = 7

application_1503394031686_0002.1.NettyBlockTransfer.shuffle-client.directArena0.numDeallocations
 value = 7

application_1503394031686_0002.1.NettyBlockTransfer.shuffle-client.directArena0.numHugeAllocations
 value = 0

application_1503394031686_0002.1.NettyBlockTransfer.shuffle-client.directArena0.numHugeDeallocations
 value = 0

application_1503394031686_0002.1.NettyBlockTransfer.shuffle-client.directArena0.numNormalAllocations
 value = 2

application_1503394031686_0002.1.NettyBlockTransfer.shuffle-client.directArena0.numNormalDeallocations
 value = 2

application_1503394031686_0002.1.NettyBlockTransfer.shuffle-client.directArena0.numSmallAllocations
 value = 3

application_1503394031686_0002.1.NettyBlockTransfer.shuffle-client.directArena0.numSmallDeallocations
 value = 3

application_1503394031686_0002.1.NettyBlockTransfer.shuffle-client.directArena0.numTinyAllocations
 value = 2

application_1503394031686_0002.1.NettyBlockTransfer.shuffle-client.directArena0.numTinyDeallocations
 value = 2

application_1503394031686_0002.1.NettyBlockTransfer.shuffle-client.heapArena0.numActiveAllocations
 value = 0

application_1503394031686_0002.1.NettyBlockTransfer.shuffle-client.heapArena0.numActiveBytes
 value = 16777216

application_1503394031686_0002.1.NettyBlockTransfer.shuffle-client.heapArena0.numActiveHugeAllocations
 value = 0

application_1503394031686_0002.1.NettyBlockTransfer.shuffle-client.heapArena0.numActiveNormalAllocations
 value = 0

application_1503394031686_0002.1.NettyBlockTransfer.shuffle-client.heapArena0.numActiveSmallAllocations
 value = 0

application_1503394031686_0002.1.NettyBlockTransfer.shuffle-client.heapArena0.numActiveTinyAllocations
 value = 0

application_1503394031686_0002.1.NettyBlockTransfer.shuffle-client.heapArena0.numAllocations
 value = 4

application_1503394031686_0002.1.NettyBlockTransfer.shuffle-client.heapArena0.numDeallocations
 value = 4

application_1503394031686_0002.1.NettyBlockTransfer.shuffle-client.heapArena0.numHugeAllocations
 value = 0

application_1503394031686_0002.1.NettyBlockTransfer.shuffle-client.heapArena0.numHugeDeallocations
 value = 0

application_1503394031686_0002.1.NettyBlockTransfer.shuffle-client.heapArena0.numNormalAllocations
 value = 0

application_1503394031686_0002.1.NettyBlockTransfer.shuffle-client.heapArena0.numNormalDeallocations
 value = 0

application_1503394031686_0002.1.NettyBlockTransfer.shuffle-client.heapArena0.numSmallAllocations
 value = 0

application_1503394031686_0002.1.NettyBlockTransfer.shuffle-client.heapArena0.numSmallDeallocations
 value = 0

application_1503394031686_0002.1.NettyBlockTransfer.shuffle-client.he

[GitHub] spark issue #18935: [SPARK-9104][CORE] Expose Netty memory metrics in Spark

2017-08-22 Thread jerryshao
Github user jerryshao commented on the issue:

https://github.com/apache/spark/pull/18935
  
Hi @squito , thanks a lot for your review. This PR doesn't expose Netty 
metrics to MetricsSystem or collect to driver side (what did before), it just 
provides a way for `TransportClientFactory` and `TransportServer` to expose 
metrics to other components. So we can either pull this into MetricsSystem, or 
report to driver in the following PRs. That's why you don't find any way for 
user to query in this PR. This will be done it following ones.


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[GitHub] spark issue #18935: [SPARK-9104][CORE] Expose Netty memory metrics in Spark

2017-08-18 Thread AmplabJenkins
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https://github.com/apache/spark/pull/18935
  
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[GitHub] spark issue #18935: [SPARK-9104][CORE] Expose Netty memory metrics in Spark

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[GitHub] spark issue #18935: [SPARK-9104][CORE] Expose Netty memory metrics in Spark

2017-08-18 Thread SparkQA
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https://github.com/apache/spark/pull/18935
  
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[GitHub] spark issue #18935: [SPARK-9104][CORE] Expose Netty memory metrics in Spark

2017-08-18 Thread SparkQA
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https://github.com/apache/spark/pull/18935
  
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[GitHub] spark issue #18935: [SPARK-9104][CORE] Expose Netty memory metrics in Spark

2017-08-18 Thread jerryshao
Github user jerryshao commented on the issue:

https://github.com/apache/spark/pull/18935
  
Jenkins, retest this please.


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[GitHub] spark issue #18935: [SPARK-9104][CORE] Expose Netty memory metrics in Spark

2017-08-18 Thread AmplabJenkins
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[GitHub] spark issue #18935: [SPARK-9104][CORE] Expose Netty memory metrics in Spark

2017-08-18 Thread SparkQA
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[GitHub] spark issue #18935: [SPARK-9104][CORE] Expose Netty memory metrics in Spark

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[GitHub] spark issue #18935: [SPARK-9104][CORE] Expose Netty memory metrics in Spark

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[GitHub] spark issue #18935: [SPARK-9104][CORE] Expose Netty memory metrics in Spark

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[GitHub] spark issue #18935: [SPARK-9104][CORE] Expose Netty memory metrics in Spark

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[GitHub] spark issue #18935: [SPARK-9104][CORE] Expose Netty memory metrics in Spark

2017-08-17 Thread SparkQA
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[GitHub] spark issue #18935: [SPARK-9104][CORE] Expose Netty memory metrics in Spark

2017-08-17 Thread jerryshao
Github user jerryshao commented on the issue:

https://github.com/apache/spark/pull/18935
  
Jenkins, retest this please.


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[GitHub] spark issue #18935: [SPARK-9104][CORE] Expose Netty memory metrics in Spark

2017-08-17 Thread AmplabJenkins
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[GitHub] spark issue #18935: [SPARK-9104][CORE] Expose Netty memory metrics in Spark

2017-08-17 Thread AmplabJenkins
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https://github.com/apache/spark/pull/18935
  
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[GitHub] spark issue #18935: [SPARK-9104][CORE] Expose Netty memory metrics in Spark

2017-08-17 Thread SparkQA
Github user SparkQA commented on the issue:

https://github.com/apache/spark/pull/18935
  
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 * This patch **fails SparkR unit tests**.
 * This patch merges cleanly.
 * This patch adds no public classes.


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[GitHub] spark issue #18935: [SPARK-9104][CORE] Expose Netty memory metrics in Spark

2017-08-17 Thread SparkQA
Github user SparkQA commented on the issue:

https://github.com/apache/spark/pull/18935
  
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[GitHub] spark issue #18935: [SPARK-9104][CORE] Expose Netty memory metrics in Spark

2017-08-17 Thread SparkQA
Github user SparkQA commented on the issue:

https://github.com/apache/spark/pull/18935
  
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[GitHub] spark issue #18935: [SPARK-9104][CORE] Expose Netty memory metrics in Spark

2017-08-16 Thread jerryshao
Github user jerryshao commented on the issue:

https://github.com/apache/spark/pull/18935
  
Thanks @zsxwing . I was thinking to expose the details of memory allocation 
in Netty for user to monitor and tune, user could filter out unrelated metrics. 
Maybe you're right, it is too verbose and too detailed to expose each arena's 
detail, let me change the codes.


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[GitHub] spark issue #18935: [SPARK-9104][CORE] Expose Netty memory metrics in Spark

2017-08-16 Thread zsxwing
Github user zsxwing commented on the issue:

https://github.com/apache/spark/pull/18935
  
Could you bump the netty version to use its new APIs rather than reflection?


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[GitHub] spark issue #18935: [SPARK-9104][CORE] Expose Netty memory metrics in Spark

2017-08-16 Thread jiangxb1987
Github user jiangxb1987 commented on the issue:

https://github.com/apache/spark/pull/18935
  
I'll review this tomorrow.


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[GitHub] spark issue #18935: [SPARK-9104][CORE] Expose Netty memory metrics in Spark

2017-08-16 Thread jerryshao
Github user jerryshao commented on the issue:

https://github.com/apache/spark/pull/18935
  
@jiangxb1987 @zsxwing would you please help to review this PR, thanks!


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[GitHub] spark issue #18935: [SPARK-9104][CORE] Expose Netty memory metrics in Spark

2017-08-15 Thread AmplabJenkins
Github user AmplabJenkins commented on the issue:

https://github.com/apache/spark/pull/18935
  
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[GitHub] spark issue #18935: [SPARK-9104][CORE] Expose Netty memory metrics in Spark

2017-08-15 Thread AmplabJenkins
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[GitHub] spark issue #18935: [SPARK-9104][CORE] Expose Netty memory metrics in Spark

2017-08-15 Thread SparkQA
Github user SparkQA commented on the issue:

https://github.com/apache/spark/pull/18935
  
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 * This patch passes all tests.
 * This patch merges cleanly.
 * This patch adds the following public classes _(experimental)_:
  * `public class TransportClientFactory implements Closeable `


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[GitHub] spark issue #18935: [SPARK-9104][CORE] Expose Netty memory metrics in Spark

2017-08-15 Thread SparkQA
Github user SparkQA commented on the issue:

https://github.com/apache/spark/pull/18935
  
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[GitHub] spark issue #18935: [SPARK-9104][CORE] Expose Netty memory metrics in Spark

2017-08-15 Thread jerryshao
Github user jerryshao commented on the issue:

https://github.com/apache/spark/pull/18935
  
Thanks @dongjoon-hyun for your review, will change it soon.


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[GitHub] spark issue #18935: [SPARK-9104][CORE] Expose Netty memory metrics in Spark

2017-08-14 Thread AmplabJenkins
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https://github.com/apache/spark/pull/18935
  
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[GitHub] spark issue #18935: [SPARK-9104][CORE] Expose Netty memory metrics in Spark

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[GitHub] spark issue #18935: [SPARK-9104][CORE] Expose Netty memory metrics in Spark

2017-08-14 Thread SparkQA
Github user SparkQA commented on the issue:

https://github.com/apache/spark/pull/18935
  
**[Test build #80641 has 
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 for PR 18935 at commit 
[`05c1f4d`](https://github.com/apache/spark/commit/05c1f4de4f00639d5f1acf1b9c061e4894d8286d).
 * This patch passes all tests.
 * This patch merges cleanly.
 * This patch adds the following public classes _(experimental)_:
  * `  public class TransportClientFactory implements Closeable `
  * `public class NettyMemoryMetrics implements MetricSet `


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[GitHub] spark issue #18935: [SPARK-9104][CORE] Expose Netty memory metrics in Spark

2017-08-14 Thread SparkQA
Github user SparkQA commented on the issue:

https://github.com/apache/spark/pull/18935
  
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[GitHub] spark issue #18935: [SPARK-9104][CORE] Expose Netty memory metrics in Spark

2017-08-14 Thread dongjoon-hyun
Github user dongjoon-hyun commented on the issue:

https://github.com/apache/spark/pull/18935
  
Retest this please.


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[GitHub] spark issue #18935: [SPARK-9104][CORE] Expose Netty memory metrics in Spark

2017-08-14 Thread AmplabJenkins
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https://github.com/apache/spark/pull/18935
  
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[GitHub] spark issue #18935: [SPARK-9104][CORE] Expose Netty memory metrics in Spark

2017-08-14 Thread AmplabJenkins
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[GitHub] spark issue #18935: [SPARK-9104][CORE] Expose Netty memory metrics in Spark

2017-08-14 Thread SparkQA
Github user SparkQA commented on the issue:

https://github.com/apache/spark/pull/18935
  
**[Test build #80618 has 
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 for PR 18935 at commit 
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 * This patch **fails SparkR unit tests**.
 * This patch merges cleanly.
 * This patch adds the following public classes _(experimental)_:
  * `  public class TransportClientFactory implements Closeable `
  * `public class NettyMemoryMetrics implements MetricSet `


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[GitHub] spark issue #18935: [SPARK-9104][CORE] Expose Netty memory metrics in Spark

2017-08-14 Thread jerryshao
Github user jerryshao commented on the issue:

https://github.com/apache/spark/pull/18935
  
@jsoltren @squito I take the liberty to get another shot of exposing Netty 
memory metrics. This PR doesn't address any display related things, only expose 
memory usage from Netty client factory and server. The following PRs could 
leverage this to display shuffle, RPC as well as other component's memory usage 
for Netty. This can be connected to `MetricsSystem`, also can be collected back 
to driver as you did before.

Please help to review, your comments are greatly appreciated, thanks!



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[GitHub] spark issue #18935: [SPARK-9104][CORE] Expose Netty memory metrics in Spark

2017-08-14 Thread SparkQA
Github user SparkQA commented on the issue:

https://github.com/apache/spark/pull/18935
  
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