ZooKeeper 秘诀 与解决方案

• A Guide to Creating Higher-level Constructs with ZooKeeper
  • Out of the Box Applications: Name Service, Configuration, Group Membership
  • Barriers
    • Double Barriers
  • Queues
    • Priority Queues
  • Locks
    • Shared Locks
    • Recoverable Shared Locks
  • Two-phased Commit
  • Leader Election

A Guide to Creating Higher-level Constructs with ZooKeeper

In this article, you‘ll find guidelines for using ZooKeeper to implement higher order functions. All of them are conventions

implemented at the client and do not require special support from ZooKeeper. Hopfully the community will capture these

conventions in client-side libraries to ease their use and to encourage standardization.

在这里你可以找到使用Zookeeper实现高级功能指南。所以这些功能都在客户端实现。希望社区开发人员能在客户端库中遵循这些约定，以

提高易用性和标准化。

One of the most interesting things about ZooKeeper is that even though ZooKeeper uses asynchronous notifications, you

can use it to build synchronous consistency primitives, such as queues and locks. As you will see, this is possible because

ZooKeeper imposes an overall order on updates, and has mechanisms to expose this ordering.

最令人关注的事之一是：即使Zookeeper 使用异步通知，但你也可以使用它构建同步一致性原语，比如队列和锁。你将看到，这是可能的。

因为Zookeeper 强制update整体有序，有机制来保证这个顺序

Note that the recipes below attempt to employ best practices. In particular, they avoid polling, timers or anything else

that would result in a "herd effect", causing bursts of traffic and limiting scalability.

注意：下面的指南使用最佳实践。特别地，避免使用投票、定时器或其他会型成“羊群效应”，造成网络阻塞，限制扩展性的机制。

There are many useful functions that can be imagined that aren‘t included here - revocable read-write priority locks, as

just one example. And some of the constructs mentioned here - locks, in particular - illustrate certain points, even

though you may find other constructs, such as event handles or queues, a more practical means of performing the

same function. In general, the examples in this section are designed to stimulate thought.

Out of the Box Applications: Name Service, Configuration, Group Membership

Name service and configuration are two of the primary applications of ZooKeeper. These two functions are provided

directly by the ZooKeeper API. Another function directly provided by ZooKeeper is group membership. The group is

represented by a node. Members of the group create ephemeral nodes under the group node. Nodes of the members

that fail abnormally will be removed automatically when ZooKeeper detects the failure.

Name service 和 configuration 是Zookeeper的两个主要应用。这两个功能直接由Zookeeper API提供。 另一个功能是 group

membership。一个节点代表一个组。 组成员创建在组节点上临时节点。Zookeeper检测到失败时会移除异常节点 。

Barriers

Distributed systems use barriers to block processing of a set of nodes until a condition is met at which time all the

nodes are allowed to proceed. Barriers are implemented in ZooKeeper by designating a barrier node. The barrier is

in place if the barrier node exists. Here‘s the pseudo code:

1. Client calls the ZooKeeper API‘s exists() function on the barrier node, with watch set to true.
2. If exists() returns false, the barrier is gone and the client proceeds
3. Else, if exists() returns true, the clients wait for a watch event from ZooKeeper for the barrier node.
4. When the watch event is triggered, the client reissues the exists( ) call, again waiting until the barrier node is removed.

Double Barriers

Double barriers enable clients to synchronize the beginning and the end of a computation. When enough processes have

joined the barrier, processes start their computation and leave the barrier once they have finished. This recipe shows how

to use a ZooKeeper node as a barrier.

The pseudo code in this recipe represents the barrier node as b. Every client process p registers with the barrier node on

entry and unregisters when it is ready to leave. A node registers with the barrier node via the Enter procedure below, it

waits until x client process register before proceeding with the computation. (The x here is up to you to determine for your

system.)

On entering, all processes watch on a ready node and create an ephemeral node as a child of the barrier node. Each process but the last enters the barrier and waits for the ready node to appear at line 5. The process that creates the xth node, the last process, will see x nodes in the list of children and create the ready node, waking up the other processes. Note that waiting processes wake up only when it is time to exit, so waiting is efficient.

On exit, you can‘t use a flag such as ready because you are watching for process nodes to go away. By using ephemeral nodes, processes that fail after the barrier has been entered do not prevent correct processes from finishing. When processes are ready to leave, they need to delete their process nodes and wait for all other processes to do the same.

Processes exit when there are no process nodes left as children of b. However, as an efficiency, you can use the lowest process node as the ready flag. All other processes that are ready to exit watch for the lowest existing process node to go away, and the owner of the lowest process watches for any other process node (picking the highest for simplicity) to go away. This means that only a single process wakes up on each node deletion except for the last node, which wakes up everyone when it is removed.

Queues

Distributed queues are a common data structure. To implement a distributed queue in ZooKeeper, first designate a znode to hold the queue, the queue node. The distributed clients put something into the queue by calling create() with a pathname ending in "queue-", with the sequence and ephemeral flags in the create() call set to true. Because the sequence flag is set, the new pathnames will have the form _path-to-queue-node_/queue-X, where X is a monotonic increasing number. A client that wants to be removed from the queue calls ZooKeeper‘s getChildren( ) function, with watch set to true on the queue node, and begins processing nodes with the lowest number. The client does not need to issue another getChildren( ) until it exhausts the list obtained from the first getChildren( ) call. If there are are no children in the queue node, the reader waits for a watch notification to check the queue again.

Note

There now exists a Queue implementation in ZooKeeper recipes directory. This is distributed with the release -- src/recipes/queue directory of the release artifact.

Priority Queues

To implement a priority queue, you need only make two simple changes to the generic queue recipe . First, to add to a queue, the pathname ends with "queue-YY" where YY is the priority of the element with lower numbers representing higher priority (just like UNIX). Second, when removing from the queue, a client uses an up-to-date children list meaning that the client will invalidate previously obtained children lists if a watch notification triggers for the queue node.

Locks

Fully distributed locks that are globally synchronous, meaning at any snapshot in time no two clients think they hold the same lock. These can be implemented using ZooKeeeper. As with priority queues, first define a lock node.

Note

There now exists a Lock implementation in ZooKeeper recipes directory. This is distributed with the release -- src/recipes/lock directory of the release artifact.

Clients wishing to obtain a lock do the following:

1. Call create( ) with a pathname of "_locknode_/lock-" and the sequence and ephemeral flags set.
2. Call getChildren( ) on the lock node without setting the watch flag (this is important to avoid the herd effect).
3. If the pathname created in step 1 has the lowest sequence number suffix, the client has the lock and the client exits the protocol.
4. The client calls exists( ) with the watch flag set on the path in the lock directory with the next lowest sequence number.
5. if exists( ) returns false, go to step 2. Otherwise, wait for a notification for the pathname from the previous step before going to step 2.

The unlock protocol is very simple: clients wishing to release a lock simply delete the node they created in step 1.

Here are a few things to notice:

• The removal of a node will only cause one client to wake up since each node is watched by exactly one client. In this way, you avoid the herd effect.

• There is no polling or timeouts.

• Because of the way you implement locking, it is easy to see the amount of lock contention, break locks, debug locking problems, etc.

Shared Locks

You can implement shared locks by with a few changes to the lock protocol:

Note

It might appear that this recipe creates a herd effect: when there is a large group of clients waiting for a read lock, and all getting notified more or less simultaneously when the "write-" node with the lowest sequence number is deleted. In fact. that‘s valid behavior: as all those waiting reader clients should be released since they have the lock. The herd effect refers to releasing a "herd" when in fact only a single or a small number of machines can proceed.

Recoverable Shared Locks

With minor modifications to the Shared Lock protocol, you make shared locks revocable by modifying the shared lock protocol:

In step 1, of both obtain reader and writer lock protocols, call getData( ) with watch set, immediately after the call to create( ).

If the client subsequently receives notification for the node it created in step 1, it does another getData( ) on that node,

with watch set and looks for the string "unlock", which signals to the client that it must release the lock. This is because,

according to this shared lock protocol, you can request the client with the lock give up the lock by calling setData() on the

lock node, writing "unlock" to that node.

Note that this protocol requires the lock holder to consent to releasing the lock. Such consent is important, especially if the

lock holder needs to do some processing before releasing the lock. Of course you can always implement Revocable Shared

Locks with Freaking Laser Beams by stipulating in your protocol that the revoker is allowed to delete the lock node if after

some length of time the lock isn‘t deleted by the lock holder.

请注意，这个协议要求锁定持有人同意释放锁。这种同意是很重要的，尤其是当锁持有者需要释放锁之前做一些处理。

Two-phased Commit

A two-phase commit protocol is an algorithm that lets all clients in a distributed system agree either to commit a transaction or abort.

In ZooKeeper, you can implement a two-phased commit by having a coordinator create a transaction node, say "/app/Tx", and one

child node per participating site, say "/app/Tx/s_i". When coordinator creates the child node, it leaves the content undefined. Once

each site involved in the transaction receives the transaction from the coordinator, the site reads each child node and sets a watch.

Each site then processes the query and votes "commit" or "abort" by writing to its respective node. Once the write completes, the

other sites are notified, and as soon as all sites have all votes, they can decide either "abort" or "commit". Note that a node can

decide "abort" earlier if some site votes for "abort".

在 Zookeeper 中，你可以让一个协调者创建一个事务节点/app/Tx，每个参与方一个子节点/app/Tx/s_i，从而实现一个两阶段提交协议。

当协调者创建了子节点时，子节点内容是未定义的，由于每个事务参与方都会从协调者接收事务，参与方读取每个子节点并设置监视。

然后每个参与方通过向与自身相关的节点写入数据来投票提交或中止事务。一旦写入完成，其他的参与方会被通知到，当所有的参与方都投完票后，

协调者就可以决定究竟是提交或中止事务。注意，如果某些参与方投票中止，节点是可以决定提前中止事务的。

An interesting aspect of this implementation is that the only role of the coordinator is to decide upon the group of sites, to create

the ZooKeeper nodes, and to propagate the transaction to the corresponding sites. In fact, even propagating the transaction can

be done through ZooKeeper by writing it in the transaction node.

There are two important drawbacks of the approach described above. One is the message complexity, which is O(n²). The second

is the impossibility of detecting failures of sites through ephemeral nodes. To detect the failure of a site using ephemeral nodes,

it is necessary that the site create the node.

To solve the first problem, you can have only the coordinator notified of changes to the transaction nodes, and then notify the

sites once coordinator reaches a decision. Note that this approach is scalable, but it‘s is slower too, as it requires all

communication to go through the coordinator.

To address the second problem, you can have the coordinator propagate the transaction to the sites, and have each site creating

its own ephemeral node.

Leader Election

A simple way of doing leader election with ZooKeeper is to use the SEQUENCE|EPHEMERAL flags when creating znodes

that represent "proposals" of clients. The idea is to have a znode, say "/election", such that each znode creates a child znode

"/election/n_" with both flags SEQUENCE|EPHEMERAL. With the sequence flag, ZooKeeper automatically appends a sequence

number that is greater that any one previously appended to a child of "/election". The process that created the znode with

the smallest appended sequence number is the leader.

序列号最小的节点是leader

竞争创建子节点，节点序列号最小的获取锁，其他节点等待，但是等待在什么条件上是有讲究的，如果所有节点都等待最小节点的删除事件，

那么当最小节点释放锁的时候，就需要广播消息给所有其他等待的节点；换一个思路，如果每个等待节点只是等待比它序列号小的节点上，那么

就可以避免这种广播风暴，变成一个顺序唤醒的过程。

That‘s not all, though. It is important to watch for failures of the leader, so that a new client arises as the new leader in the

case the current leader fails. A trivial solution is to have all application processes watching upon the current smallest znode,

and checking if they are the new leader when the smallest znode goes away (note that the smallest znode will go away if

the leader fails because the node is ephemeral). But this causes a herd effect: upon of failure of the current leader, all other

processes receive a notification, and execute getChildren on "/election" to obtain the current list of children of "/election". If

the number of clients is large, it causes a spike on the number of operations that ZooKeeper servers have to process. To avoid

the herd effect, it is sufficient to watch for the next znode down on the sequence of znodes. If a client receives a notification that

the znode it is watching is gone, then it becomes the new leader in the case that there is no smaller znode. Note that this avoids

the herd effect by not having all clients watching the same znode.

Here‘s the pseudo code:

Let ELECTION be a path of choice of the application. To volunteer to be a leader:

1. Create znode z with path "ELECTION/n_" with both SEQUENCE and EPHEMERAL flags;
2. Let C be the children of "ELECTION", and i be the sequence number of z;
3. Watch for changes on "ELECTION/n_j", where j is the smallest sequence number such that j < i and n_j is a znode in C;

Upon receiving a notification of znode deletion:

1. Let C be the new set of children of ELECTION;
2. If z is the smallest node in C, then execute leader procedure;
3. Otherwise, watch for changes on "ELECTION/n_j", where j is the smallest sequence number such that j < i and n_j is a znode in C;

Note that the znode having no preceding znode on the list of children does not imply that the creator of this znode

is aware that it is the current leader. Applications may consider creating a separate to znode to acknowledge that

the leader has executed the leader procedure.