It's fixable. Since we plan to rewrite the consumer client code in the near future, it could be considered at that point.
If you issue a metadata request with an empty topic list, you will get back the metadata of all topics. Thanks, Jun On Wed, Oct 2, 2013 at 1:28 PM, Jason Rosenberg <[email protected]> wrote: > How hard would it be to fix this issue, where we have a topic filter that > matches multiple topics, for the load to be distributed over multiple > threads, and over multiple consumers? For some reason, I had thought this > issue was fixed in 0.8, but I guess not? > > I am currently using a single partition, for multiple topics. I worry that > it won't scale ultimately to only ever have one thread on one consumer > doing all the work......We could move to multiple partitions, but for > ordering reasons in some use cases, this is not always ideal. > > Perhaps I can come up with some sort of dynamic topic sniffer, and have it > evenly divide the available topics between the available consumers (and > threads per consumer)! Is there a simple api within the kafka client code, > for getting the list of topics? > > Jason > > > On Fri, Aug 30, 2013 at 11:41 PM, Jun Rao <[email protected]> wrote: > > > It seems to me option 1) is easer. Option 2) has the same issue as option > > 1) since you have to manage different while lists. > > > > A more general solution is probably to change the consumer distribution > > model to divide partitions across topics. That way, one can create as > many > > streams as total # partitions for all topics. We can look into that in > the > > future. > > > > Thanks, > > > > Jun > > > > > > On Fri, Aug 30, 2013 at 8:24 AM, Rajasekar Elango < > [email protected] > > >wrote: > > > > > Yeah. The actual bottleneck is actually number of topics that match the > > > topic filter. Num of streams is going be shared between all topics it's > > > consuming from. I thought about following ideas to work around this. (I > > am > > > basically referring to mirrormaker consumer in examples). > > > > > > Option 1). Instead of running one mirrormaker process with topic filter > > > ".+", We can start multiple mirrormaker process with topic filter > > matching > > > each topic (Eg: mirrormaker1 => whitelist topic1.* , mirrormaker2 > > > => whitelist topic2.* etc) > > > > > > But this adds some operations overhead to start and manage multiple > > > processes on the host. > > > > > > Option 2) Modify mirrormaker code to support list of whitelist filters > > and > > > it should create message streams for each filter > > > (call createMessageStreamsByFilter for each filter). > > > > > > What would be your recommendation..? If adding feature to mirrormaker > is > > > worth kafka, we can do option 2. > > > > > > Thanks, > > > Raja. > > > > > > > > > > > > > > > On Fri, Aug 30, 2013 at 10:34 AM, Jun Rao <[email protected]> wrote: > > > > > > > Right, but if you set #partitions in each topic to 16, you can use a > > > total > > > > of 16 streams. > > > > > > > > Thanks, > > > > > > > > Jun > > > > > > > > > > > > On Thu, Aug 29, 2013 at 9:08 PM, Rajasekar Elango < > > > [email protected] > > > > >wrote: > > > > > > > > > With option 1) I can't really use 8 streams in each consumer, If I > do > > > > only > > > > > one consumer seem to be doing all work. So I had to actually use > > total > > > 8 > > > > > streams with 4 for each consumer. > > > > > > > > > > > > > > > > > > > > On Fri, Aug 30, 2013 at 12:01 AM, Jun Rao <[email protected]> > wrote: > > > > > > > > > > > The drawback of 2), as you said is no auto failover. I was > > suggesting > > > > > that > > > > > > you use 16 partitions. Then you can use option 1) with 8 streams > in > > > > each > > > > > > consumer. > > > > > > > > > > > > Thanks, > > > > > > > > > > > > Jun > > > > > > > > > > > > > > > > > > On Thu, Aug 29, 2013 at 8:51 PM, Rajasekar Elango < > > > > > [email protected] > > > > > > >wrote: > > > > > > > > > > > > > Hi Jun, > > > > > > > > > > > > > > If you read my previous posts, based on current re balancing > > logic, > > > > if > > > > > we > > > > > > > consumer from topic filter, consumer actively use all streams. > > Can > > > > you > > > > > > > provide your recommendation of option 1 vs option 2 in my > > previous > > > > > post? > > > > > > > > > > > > > > Thanks, > > > > > > > Raja. > > > > > > > > > > > > > > > > > > > > > On Thu, Aug 29, 2013 at 11:42 PM, Jun Rao <[email protected]> > > > wrote: > > > > > > > > > > > > > > > You can always use more partitions to get more parallelism in > > the > > > > > > > > consumers. > > > > > > > > > > > > > > > > Thanks, > > > > > > > > > > > > > > > > Jun > > > > > > > > > > > > > > > > > > > > > > > > On Thu, Aug 29, 2013 at 12:44 PM, Rajasekar Elango > > > > > > > > <[email protected]>wrote: > > > > > > > > > > > > > > > > > So what is best way to load balance multiple consumers > > > consuming > > > > > from > > > > > > > > topic > > > > > > > > > filter. > > > > > > > > > > > > > > > > > > Let's say we have 4 topics with 8 partitions and 2 > consumers. > > > > > > > > > > > > > > > > > > Option 1) To load balance consumers, we can set > num.streams=4 > > > so > > > > > that > > > > > > > > both > > > > > > > > > consumers split 8 partitions. but can only use half of > > consumer > > > > > > > streams. > > > > > > > > > > > > > > > > > > Option 2) Configure mutually exclusive topic filter regex > > such > > > > > that 2 > > > > > > > > > topics will match consumer1 and 2 topics will match > > consumer2. > > > > Now > > > > > we > > > > > > > can > > > > > > > > > set num.streams=8 and fully utilize consumer streams. I > > believe > > > > > this > > > > > > > will > > > > > > > > > improve performance, but if consumer dies, we will not get > > any > > > > data > > > > > > > from > > > > > > > > > the topic used by that consumer. > > > > > > > > > > > > > > > > > > What would be your recommendation? > > > > > > > > > > > > > > > > > > Thanks, > > > > > > > > > Raja. > > > > > > > > > > > > > > > > > > > > > > > > > > > On Thu, Aug 29, 2013 at 12:42 PM, Neha Narkhede < > > > > > > > [email protected] > > > > > > > > > >wrote: > > > > > > > > > > > > > > > > > > > >> 2) When I started mirrormaker with num.streams=16, > looks > > > > like > > > > > 16 > > > > > > > > > > consumer > > > > > > > > > > threads were created, but only 8 are showing up as active > > as > > > > > owner > > > > > > in > > > > > > > > > > consumer offset tracker and all topics/partitions are > > > > distributed > > > > > > > > > between 8 > > > > > > > > > > consumer threads. > > > > > > > > > > > > > > > > > > > > This is because currently the consumer rebalancing > process > > of > > > > > > > assigning > > > > > > > > > > partitions to consumer streams is at a per topic level. > > > Unless > > > > > you > > > > > > > have > > > > > > > > > at > > > > > > > > > > least one topic with 16 partitions, the remaining 8 > threads > > > > will > > > > > > not > > > > > > > do > > > > > > > > > any > > > > > > > > > > work. This is not ideal and we want to look into a better > > > > > > rebalancing > > > > > > > > > > algorithm. Though it is a big change and we prefer doing > it > > > as > > > > > part > > > > > > > of > > > > > > > > > the > > > > > > > > > > consumer client rewrite. > > > > > > > > > > > > > > > > > > > > Thanks, > > > > > > > > > > Neha > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > On Thu, Aug 29, 2013 at 8:03 AM, Rajasekar Elango < > > > > > > > > > [email protected] > > > > > > > > > > >wrote: > > > > > > > > > > > > > > > > > > > > > So my understanding is num of active streams that a > > > consumer > > > > > can > > > > > > > > > utilize > > > > > > > > > > is > > > > > > > > > > > number of partitions in topic. This is fine if we > > consumer > > > > from > > > > > > > > > specific > > > > > > > > > > > topic. But if we consumer from TopicFilter, I thought > > > > consumer > > > > > > > should > > > > > > > > > > able > > > > > > > > > > > to utilize (number of topics that match filter * number > > of > > > > > > > partitions > > > > > > > > > in > > > > > > > > > > > topic) . But looks like number of streams that consumer > > can > > > > use > > > > > > is > > > > > > > > > > limited > > > > > > > > > > > by just number if partitions in topic although it's > > > consuming > > > > > > from > > > > > > > > > > multiple > > > > > > > > > > > topic. > > > > > > > > > > > > > > > > > > > > > > Here what I observed with 1 mirrormaker consuming from > > > > > whitelist > > > > > > > > '.+'. > > > > > > > > > > > > > > > > > > > > > > The white list matches 5 topics and each topic has 8 > > > > > partitions. > > > > > > I > > > > > > > > used > > > > > > > > > > > consumer offset checker to look at owner of each/topic > > > > > partition. > > > > > > > > > > > > > > > > > > > > > > 1) When I started mirrormaker with num.streams=8, all > > > > > > > > topics/partitions > > > > > > > > > > are > > > > > > > > > > > distributed between 8 consumer threads. > > > > > > > > > > > > > > > > > > > > > > 2) When I started mirrormaker with num.streams=16, > looks > > > like > > > > > 16 > > > > > > > > > consumer > > > > > > > > > > > threads were created, but only 8 are showing up as > active > > > as > > > > > > owner > > > > > > > in > > > > > > > > > > > consumer offset tracker and all topics/partitions are > > > > > distributed > > > > > > > > > > between 8 > > > > > > > > > > > consumer threads. > > > > > > > > > > > > > > > > > > > > > > So this could be bottleneck for consumers as although > we > > > > > > > partitioned > > > > > > > > > > topic, > > > > > > > > > > > if we are consuming from topic filter it can't utilize > > much > > > > of > > > > > > > > > > parallelism > > > > > > > > > > > with num of streams. Am i missing something, is there a > > way > > > > to > > > > > > make > > > > > > > > > > > cosumers/mirrormakers to utilize more number of active > > > > streams? > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > -- > > > > > > > > > > > Thanks, > > > > > > > > > > > Raja. > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > -- > > > > > > > > > Thanks, > > > > > > > > > Raja. > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > -- > > > > > > > Thanks, > > > > > > > Raja. > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > -- > > > > > Thanks, > > > > > Raja. > > > > > > > > > > > > > > > > > > > > > -- > > > Thanks, > > > Raja. > > > > > >
