Finally start the zookeeper Service on all the servers This ensures that metadata changes will always arrive in the same order. Increasing the size of test matrix in this fashion would really hurt the project.Additionally, if we supported multiple metadata storage options, we would have to use "least common denominator" APIs. Hence, in this role of ZooKeeper in Kafka tutorial, we have seen that Kafka really needs ZooKeeper to work efficiently in the Kafka cluster. {"serverDuration": 128, "requestCorrelationId": "4558f3bfb050964a"} We will create follow-on KIPs to hash out the concrete details of each change. If the configuration for the zookeeper server addresses is left in the configuration, it will be ignored.Once the last broker node has been rolled, there will be no more need for ZooKeeper. One example of this is that when the leader of a partition wants to modify the in-sync replica set, it currently modifies ZooKeeper directly In the post-ZK world, the leader will make an RPC to the active controller instead.Currently, some tools and scripts directly contact ZooKeeper.
When the controller pushes out state change notifications (such as LeaderAndIsrRequest) to other brokers in the cluster, it is possible for brokers to get some of the changes, but not all. Resolved comments As much as possible, we will perform all access to ZooKeeper in the controller, rather than in other brokers, clients, or tools.
Auto-suggest helps you quickly narrow down your search results by suggesting possible matches as you type.Alert: Welcome to the Unified Cloudera Community. People who can view The controller nodes elect a single leader for the metadata partition, shown in orange. Therefore, a three-node controller cluster can survive one failure. In order to preserve compatibility with old clients that sent these operations to a random broker, the brokers will forward these requests to the active controller.In some cases, we will need to create a new API to replace an operation that was formerly done via ZooKeeper. Rather than pushing out notifications to brokers, brokers should simply consume metadata events from the event log.
However, drawing that many lines would make the diagram difficult to read.
The active controller handles all RPCs made from the brokers. In the post-KIP-500 world, the Kafka controller will store its metadata in a Kafka partition rather than in ZooKeeper. Just like with a fetch request, the broker will track the offset of the last updates it fetched, and only request newer updates from the active controller.
Other brokers besides the controller can and do communicate with ZooKeeper.
We will discuss this further in follow-on KIPs.Currently, brokers register themselves with ZooKeeper right after they start up. View in Hierarchy Another issue which this diagram leaves out is that external command line tools and utilities can modify the state in ZooKeeper, without the involvement of the controller. Fortunately, "KIP-4: Command line and centralized administrative operations" began the task of removing direct ZooKeeper access several years ago, and it is nearly complete.We will preserve compatibility with the existing Kafka clients. This will enable us to manage metadata in a more scalable and robust way, enabling support for more partitions. When they start up, they will only need to read what has changed from the controller, not the full state. By the time the controller re-reads the znode and sets up a new watch, the state may have changed from what it was when the watch originally fired. Page History )Most of the time, the broker should only need to fetch the deltas, not the full state. Unifying the system would greatly improve the "day one" experience of running Kafka, and help broaden its adoption.Because the Kafka and ZooKeeper configurations are separate, it is easy to make mistakes. That is why the arrows point towards the controller rather than away.Note that although the controller processes are logically separate from the broker processes, they need not be physically separate. This request will double as a heartbeat, letting the controller know that the broker is alive.Note that while this KIP only discusses broker metadata management, client metadata management is important for scalability as well. We have pictured 4 broker nodes and 3 ZooKeeper nodes in this diagram. Currently, a Kafka cluster contains several broker nodes, and an external quorum of ZooKeeper nodes. The controller (depicted in orange) loads its state from the ZooKeeper quorum after it is elected. In order to present the big picture, I have mostly left out details like RPC formats, on-disk formats, and so on. This registration accomplishes two things: it lets the broker know whether it has been elected as the controller, and it lets other nodes know how to contact it.In the post-ZooKeeper world, brokers will register themselves with the controller quorum, rather than with ZooKeeper.Currently, if a broker loses its ZooKeeper session, the controller removes it from the cluster metadata. Export to Word The controller nodes and the broker nodes run in separate JVMs. This log contains information about each change to the cluster metadata.