Znodes can either be persistent or ephemeral. This znodes have some very interesting properties, which are presented in the following list: ZooKeeper holds a hierarchical tree of nodes called znodes. The data model of ZooKeeper helps us with that too. Once a lock is obtained it should be released, if a client crashes before being able to finish. Because of the Timeliness not all client might immediately see the lock, but the sequential ordering of the updates ensures that no two request can obtain the same lock for the same element. The Sequential Consistency and the Single System Image ensure that a client can obtain a lock for an element. Up on this constraints we can build a persistent queue that stores it’s element in a sequential order by the time they were send. This also implies that a client never reads an older state of ZooKeeper than the one it has read before.Ī client always sees the same state of ZooKeeper regardless of what server it connects to.Ī client’s view can be outdated but not more than some of tens of seconds. Updates are applied in the order they are send. Once a update succeeds it’s persisted surviving server failures. A failed update will never be seen by any client. Updates to ZooKeeper either fail or succeed. ZooKeeper makes the following guarantees for data consistency: Let’s find out how ZooKeeper can help us meet this requirements. But a queue also follows the FIFO principle, so that we would expect a sequential ordering of the elements added to the queue. Surely we would want our queue to be persistent and atomic, so we wont loose any information. ConsistencyĪ distributed queue has to meet at least some guarantees to be useful. All this can easily be done with ZooKeeper. On the other hand if the instance dies unexpectedly during the fetch the lock needs to be released, so another instance can pick from there. We don’t just remove it from the queue, because the fetch could fail. In this scenario we wouldn’t want multiple instances crawling the same link, therefor we lock the link prior to performing the fetch. Imagine a web crawler who stores it’s links in a queue, so that other instances can grab link by link from the queue and crawl the web pages. I decided to implement a distributed queue with locking, which I found as an example on the Solutions and Recipes page. You’ll find here a brief overview of the consistency guarantees ZooKeeper makes, and a sample application. And it’s sure worth looking at the ZooKeeper Recipes and Solutions page.Īs I just recently had the opportunity to take a closer look at ZooKeeper for the first time, this article does little more than provide the ‘Notes of a Beginner’. To get an better understanding of what Zookeeper can do for you it’s a good idea to gain a solid understand of it’s implementation details and the consistency guarantees it makes. It promises to be simple, expressive, highly available, and highly reliable. ZooKeeper is in use at many different distributed systems and could probably also be of great help to your application, when it comes to distributed synchronization, and maintaining configuration.
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