Roger, These are good questions.
1. The producer since 0.8 is actually zookeeper free, so this is not new to this client it is true for the current client as well. Our experience was that direct zookeeper connections from zillions of producers wasn't a good idea for a number of reasons. Our intention is to remove this dependency from the consumer as well. The configuration in the producer doesn't need the full set of brokers, though, just one or two machines to bootstrap the state of the cluster from--in other words it isn't like you need to reconfigure your clients every time you add some servers. This is exactly how zookeeper works too--if we used zookeeper you would need to give a list of zk urls in case a particular zk server was down. Basically either way you need a few statically configured nodes to go to discover the full state of the cluster. For people who don't like hard coding hosts you can use a VIP or dns or something instead. 2. Yes this is a good point and was a concern I had too--the current behavior is that with bad urls the client would start normally and then hang trying to fetch metadata when the first message is sent and finally give up and throw an exception. This is not ideal. The challenge is this: we use the bootstrap urls to fetch metadata for particular topics but we don't know which until we start getting messages for them. We have the option of fetching metadata for all topics but the problem is that for a cluster hosting tens of thousands of topics that is actually a ton of data. An alternative that this just made me think of is that we could proactively connect to bootstrap urls sequentially until one succeeds when the producer is first created and fail fast if we can't establish a connection. This would not be wasted work as we could use the connection for the metadata request when the first message is sent. I like this solution and will implement it. So thanks for asking! -Jay On Fri, Jan 24, 2014 at 2:46 PM, Roger Hoover <roger.hoo...@gmail.com>wrote: > A couple comments: > > 1) Why does the config use a broker list instead of discovering the brokers > in ZooKeeper? It doesn't match the HighLevelConsumer API. > > 2) It looks like broker connections are created on demand. I'm wondering > if sometimes you might want to flush out config or network connectivity > issues before pushing the first message through. > > Should there also be a KafkaProducer.connect() or .open() method or > connectAll()? I guess it would try to connect to all brokers in the > BROKER_LIST_CONFIG > > HTH, > > Roger > > > On Fri, Jan 24, 2014 at 11:54 AM, Jay Kreps <jay.kr...@gmail.com> wrote: > > > As mentioned in a previous email we are working on a re-implementation of > > the producer. I would like to use this email thread to discuss the > details > > of the public API and the configuration. I would love for us to be > > incredibly picky about this public api now so it is as good as possible > and > > we don't need to break it in the future. > > > > The best way to get a feel for the API is actually to take a look at the > > javadoc, my hope is to get the api docs good enough so that it is > > self-explanatory: > > > > > http://empathybox.com/kafka-javadoc/index.html?kafka/clients/producer/KafkaProducer.html > > > > Please take a look at this API and give me any thoughts you may have! > > > > It may also be reasonable to take a look at the configs: > > > > > http://empathybox.com/kafka-javadoc/kafka/clients/producer/ProducerConfig.html > > > > The actual code is posted here: > > https://issues.apache.org/jira/browse/KAFKA-1227 > > > > A few questions or comments to kick things off: > > 1. We need to make a decision on whether serialization of the user's key > > and value should be done by the user (with our api just taking byte[]) or > > if we should take an object and allow the user to configure a Serializer > > class which we instantiate via reflection. We take the later approach in > > the current producer, and I have carried this through to this prototype. > > The tradeoff I see is this: taking byte[] is actually simpler, the user > can > > directly do whatever serialization they like. The complication is > actually > > partitioning. Currently partitioning is done by a similar plug-in api > > (Partitioner) which the user can implement and configure to override how > > partitions are assigned. If we take byte[] as input then we have no > access > > to the original object and partitioning MUST be done on the byte[]. This > is > > fine for hash partitioning. However for various types of semantic > > partitioning (range partitioning, or whatever) you would want access to > the > > original object. In the current approach a producer who wishes to send > > byte[] they have serialized in their own code can configure the > > BytesSerialization we supply which is just a "no op" serialization. > > 2. We should obsess over naming and make sure each of the class names are > > good. > > 3. Jun has already pointed out that we need to include the topic and > > partition in the response, which is absolutely right. I haven't done that > > yet but that definitely needs to be there. > > 4. Currently RecordSend.await will throw an exception if the request > > failed. The intention here is that producer.send(message).await() exactly > > simulates a synchronous call. Guozhang has noted that this is a little > > annoying since the user must then catch exceptions. However if we remove > > this then if the user doesn't check for errors they won't know one has > > occurred, which I predict will be a common mistake. > > 5. Perhaps there is more we could do to make the async callbacks and > future > > we give back intuitive and easy to program against? > > > > Some background info on implementation: > > > > At a high level the primary difference in this producer is that it > removes > > the distinction between the "sync" and "async" producer. Effectively all > > requests are sent asynchronously but always return a future response > object > > that gives the offset as well as any error that may have occurred when > the > > request is complete. The batching that is done in the async producer only > > today is done whenever possible now. This means that the sync producer, > > under load, can get performance as good as the async producer > (preliminary > > results show the producer getting 1m messages/sec). This works similar to > > group commit in databases but with respect to the actual network > > transmission--any messages that arrive while a send is in progress are > > batched together. It is also possible to encourage batching even under > low > > load to save server resources by introducing a delay on the send to allow > > more messages to accumulate; this is done using the linger.ms config > (this > > is similar to Nagle's algorithm in TCP). > > > > This producer does all network communication asynchronously and in > parallel > > to all servers so the performance penalty for acks=-1 and waiting on > > replication should be much reduced. I haven't done much benchmarking on > > this yet, though. > > > > The high level design is described a little here, though this is now a > > little out of date: > > https://cwiki.apache.org/confluence/display/KAFKA/Client+Rewrite > > > > -Jay > > >
