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From <j.guilm...@accenture.com>
Subject RE: All channels in an agent get slower after a channel is full
Date Fri, 14 Nov 2014 00:21:45 GMT
Hi Hari,

I’m jumping in this discussion as I’m facing similar behavior on channel full impacts.

I was trying to optimize an HTTPSink that does not sustain the performance it should when
I faced same issue than described below, but with MemoryChannels:
1 source (let’s say Avro), with a Replicating Selector duplicating the events in 2 MemoryChannels.
When one MemoryChannel is full, the other one is getting down, and even worse, the Source
is getting down as well.

So I suspected initially my particular Sink to have effect on other threads or on the JVM.
So I removed it, and tried a very simple config:
a1.sources = r1
a1.channels = c1
a1.sinks = k1

a1.sources.r1.type = avro
a1.sources.r1.channels = c1
a1.sources.r1.bind =
a1.sources.r1.port = 1234

a1.channels.c1.type = memory
a1.channels.c1.capacity = 1000

a1.sinks.k1.type = avro
a1.sinks.k1.channel = c1
a1.sinks.k1.hostname =
a1.sinks.k1.port = 3456

I put another agent listening on the AVRO events on 3456, and I inject load into the main
one, then I stop the listener agent.

ð  The channel c1 is off course filling up… but the source is impacted as well, by the

The threaddump is explicit:
"New I/O  worker #15" prio=6 tid=0x000000000d252000 nid=0x2990 waiting on condition [0x0000000010cee000]
   java.lang.Thread.State: TIMED_WAITING (parking)
                at sun.misc.Unsafe.park(Native Method)
                - parking to wait for  <0x00000007818f9c00> (a java.util.concurrent.Semaphore$NonfairSync)
                at java.util.concurrent.locks.LockSupport.parkNanos(LockSupport.java:226)
                at java.util.concurrent.locks.AbstractQueuedSynchronizer.doAcquireSharedNanos(AbstractQueuedSynchronizer.java:1033)
                at java.util.concurrent.locks.AbstractQueuedSynchronizer.tryAcquireSharedNanos(AbstractQueuedSynchronizer.java:1326)
                at java.util.concurrent.Semaphore.tryAcquire(Semaphore.java:588)
                at org.apache.flume.channel.MemoryChannel$MemoryTransaction.doCommit(MemoryChannel.java:128)
                at org.apache.flume.channel.BasicTransactionSemantics.commit(BasicTransactionSemantics.java:151)
                at org.apache.flume.channel.ChannelProcessor.processEvent(ChannelProcessor.java:267)
                at org.apache.flume.source.AvroSource.append(AvroSource.java:348)
                at sun.reflect.GeneratedMethodAccessor40.invoke(Unknown Source)
                at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
                at java.lang.reflect.Method.invoke(Method.java:606)
                at org.apache.avro.ipc.specific.SpecificResponder.respond(SpecificResponder.java:88)
                at org.apache.avro.ipc.Responder.respond(Responder.java:149)
                at org.apache.avro.ipc.NettyServer$NettyServerAvroHandler.messageReceived(NettyServer.java:188)

The source gets stuck on these commits, until the “keep-alive” timeout expires. I cannot
lower a lot this keep-alive, as the lowest value seems to be 1 second. (Unit is seconds).

To put it in a nutshell, I don’t know if this behavior is expected, but if one Channel is
filling up (at least a MemoryChannel), as per my understand it will impact any other channel
linked to the same source, and will impact the Source itself.

Do you see any way to prevent a Source from being impacted by the channel filling up ? In
my specific scenario, I would prefer losing some events, or at least keep the other channels

PS: I’m using Flume 1.5 for these tests.


From: Hari Shreedharan [mailto:hshreedharan@cloudera.com]
Sent: jeudi 13 novembre 2014 22:04
To: user@flume.apache.org
Cc: user@flume.apache.org
Subject: Re: All channels in an agent get slower after a channel is full

Yeah, when you are sharing disks — that would cause one channel’s behavior affect others
since your disk is your bottleneck.


On Thu, Nov 13, 2014 at 1:02 PM, Vincentius Martin <vincentiusmartin@gmail.com<mailto:vincentiusmartin@gmail.com>>
Right now, I am using FileChannel.

Vincentius Martin

On Fri, Nov 14, 2014 at 4:00 AM, Hari Shreedharan <hshreedharan@cloudera.com<mailto:hshreedharan@cloudera.com>>
Are you using MemoryChannel or File Channel?


On Thu, Nov 13, 2014 at 12:59 PM, Vincentius Martin <vincentiusmartin@gmail.com<mailto:vincentiusmartin@gmail.com>>
Yes, they are sharing the same disk
I used to try it with memory channel, it also produced the same impact when a channel in an
agent with many channels reaches its channel capacity. It caused ChannelException and made
other channels slower.

Vincentius Martin

On Fri, Nov 14, 2014 at 3:47 AM, Hari Shreedharan <hshreedharan@cloudera.com<mailto:hshreedharan@cloudera.com>>
Are all the channels sharing the same disk(s)?


On Thu, Nov 13, 2014 at 12:44 PM, Vincentius Martin <vincentiusmartin@gmail.com<mailto:vincentiusmartin@gmail.com>>
it is between agents, I am using avro sinks and file channels while all of those channels
write the checkpoint to a disk.
For the rest, I am using default configuration.

Vincentius Martin

On Fri, Nov 14, 2014 at 1:39 AM, Hari Shreedharan <hshreedharan@cloudera.com<mailto:hshreedharan@cloudera.com>>
What does your configuration look like? What sink are you using?

On Thu, Nov 13, 2014 at 8:23 AM, Vincentius Martin <vincentiusmartin@gmail.com<mailto:vincentiusmartin@gmail.com>>
In my cluster, I have an agent with one source connected to multiple channels. Each channel
connected to different sink (1 channel paired with 1 sink) which send events to different
agents (like one to many relation). Just like the multiplexing flow example in Flume user
guide website.

However, when a channel reaches its capacity (already full)  I see that the agent performance
gets slower.

What I mean by getting slower is that, all other channel-sink pairs in that agent also get
slower when sending events to their destination. I can understand if the overfilled channel-sink
pair get slower, but why it affects another channel-sink pairs in that agent? From what I
see here, the other pairs should be independent with the overfilled channel except that they
use the same source, right?

Vincentius Martin


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