Zoo-keeper

ZK Motto

the motto “ZooKeeper: Because Coordinating Distributed Systems is a Zoo.”

Features of Zookeeper

  • Synchronization − Mutual exclusion and co-operation between server processes.
  • Ordered Messages - The strict ordering means that sophisticated synchronization primitives can be implemented at the client.
  • Reliability - The reliability aspects keep it from being a single point of failure.
  • Atomicity − Data transfer either succeeds or fails completely, but no transaction is partial.
  • High performant - The performance aspects of Zookeeper means it can be used in large, distributed systems.
  • Distributed.
  • High avaliablity.
  • Fault-tolerant.
  • Loose coupling.
  • Partial failure.
  • High throughput and low latency - data is stored data in memory and on disk as well.
  • Replicated.
  • Automatic failover: When a Zookeeper dies, the session is automatically migrated over to another Zookeeper.

Different type of data

When designing an application with ZooKeeper, one ideally separates application data from control or coordination data. For example, the users of a web-mail service are interested in their mailbox content, but not on which server is handling the requests of a particular mailbox. The mailbox content is application data, whereas the mapping of the mailbox to a specific mail server is part of the coordination data (or metadata). A ZooKeeper ensemble manages the latter.

The multiple processes consequently need to implement mutual exclusion. We can actually think of the task of acquiring mastership as the one of acquiring a lock: the process that acquires the mastership lock exercises the role of master.

Coordination does not always take the form of synchronization primitives like leader election or locks. Configuration metadata is often used as a way for a process to convey what others should be doing. For example, in a master-worker system, workers need to know the tasks that have been assigned to them, and this information must be available even if the master crashes.

How world work without ZooKeeper

It is certainly possible to build distributed systems without using ZooKeeper. ZooKeep‐ er, however, offers developers the possibility of focusing more on application logic rather than on arcane distributed systems concepts. Programming distributed systems without ZooKeeper is possible, but more difficult.

What does ZooKeeper does not do

The ensemble of ZooKeeper servers manages critical application data related to coor‐ dination. ZooKeeper is not for bulk storage. For bulk storage of application data, there are a number of options available, such as databases and distributed file systems. When designing an application with ZooKeeper, one ideally separates application data from control or coordination data.

ZooKeeper, however, does not implement the tasks for you. It does not elect a master or track live processes for the application out of the box. Instead, it provides the tools for implementing such tasks. The developer decides what coordination tasks to implement.

Processes in a distributed system have two broad options for communication: they can exchange messages directly through a network, or read and write to some shared storage. ZooKeeper uses the shared storage model to let applications implement coordination and synchronization primitives. But shared storage itself requires network communi‐ cation between the processes and the storage. It is important to stress the role of network communication because it is an important source of complications in the design of a distributed system.

This scenario leads to a problem commonly called split-brain: two or more parts of the system make progress independ‐ ently, leading to inconsistent behavior. As part of coming up with a way to cope with master failures, it is critical that we avoid split-brain scenarios.

Tasks

The following requirements for our master-worker architecture: Master election It is critical for progress to have a master available to assign tasks to workers. Crash detection The master must be able to detect when workers crash or disconnect. Group membership management The master must be able to figure out which workers are available to execute tasks. Metadata management The master and the workers must be able to store assignments and execution sta‐ tuses in a reliable manner.

CAP

known as CAP, which stands for Consistency, Availability, and Partition-tolerance, says that when designing a distributed system we may want all three of those properties, but that no system can handle all three.2 Zoo‐ Keeper has been designed with mostly consistency and availability in mind, although it also provides read-only capability in the presence of network partitions.

ZooKeeper Basics

Several primitives used for coordination are commonly shared across many applica‐ tions. Consequently, one way of designing a service used for coordination is to come up with a list of primitives, expose calls to create instances of each primitive, and ma‐ nipulate these instances directly. For example, we could say that distributed locks con‐ stitute an important primitive and expose calls to create, acquire, and release locks. Such a design, however, suffers from a couple of important shortcomings. First, we need to either come up with an exhaustive list of primitives used beforehand, or keep ex‐ tending the API to introduce new primitives. Second, it does not give flexibility to the application using the service to implement primitives in the way that is most suitable for it. We consequently have taken a different path with ZooKeeper. ZooKeeper does not ex‐ pose primitives directly. Instead, it exposes a file system-like API comprised of a small set of calls that enables applications to implement their own primitives. We typically use recipes to denote these implementations of primitives. Recipes include ZooKeeper operations that manipulate small data nodes, called znodes, that are organized hier‐ archically as a tree, just like in a file system.

znodes

a few other znodes that could be useful in a master- worker configuration:

  • The /workers znode is the parent znode to all znodes representing a worker avail‐ able in the system. Figure 2-1 shows that one worker (foo.com:2181) is available. If a worker becomes unavailable, its znode should be removed from /workers.
  • The /tasks znode is the parent of all tasks created and waiting for workers to execute them. Clients of the master-worker application add new znodes as children of /tasks to represent new tasks and wait for znodes representing the status of the task.
  • The /assign znode is the parent of all znodes representing an assignment of a task to a worker. When a master assigns a task to a worker, it adds a child znode to /assign.

    API

    API Overview Znodes may or may not contain data. If a znode contains any data, the data is stored as a byte array. The exact format of the byte array is specific to each application, and ZooKeeper does not directly provide support to parse it. Serialization packages such as Protocol Buffers, Thrift, Avro, and MessagePack may be handy for dealing with the format of the data stored in znodes, but sometimes string encodings such as UTF-8 or ASCII suffice.

The ZooKeeper API exposes the following operations:

create /path data
Creates a znode named with /path and containing data
delete /path
Deletes the znode /path
exists /path
Checks whether /path exists
setData /path data
Sets the data of znode /path to data
getData /path
Returns the data in /path
getChildren /path
Returns the list of children under /path
One important note is that ZooKeeper does not allow partial writes or reads of the znode data. When setting the data of a znode or reading it, the content of the znode is replaced or read entirely.

ZooKeeper clients connect to a ZooKeeper service and establish a session through which they make API calls.

If a worker becomes unavailable, its session expires and its znode in /workers disappears automatically.

An ephemeral znode can be deleted in two situations:

  1. When the session of the client creator ends, either by expiration or because it ex‐ plicitly closed.
  2. When a client, not necessarily the creator, deletes it.

Sequential znodes

A znode can also be set to be sequential. A sequential znode is assigned a unique, mo‐ notonically increasing integer. This sequence number is appended to the path used to create the znode. For example, if a client creates a sequential znode with the path /tasks/ task-, ZooKeeper assigns a sequence number, say 1, and appends it to the path. The path of the znode becomes /tasks/task-1. Sequential znodes provide an easy way to create znodes with unique names. They also provide a way to easily see the creation order of znodes.

watch

This is a common problem with polling. To replace the client polling, we have opted for a mechanism based on notifications: clients register with ZooKeeper to receive notifi‐ cations of changes to znodes. Registering to receive a notification for a given znode consists of setting a watch. A watch is a one-shot operation, which means that it triggers one notification. To receive multiple notifications over time, the client must set a new watch upon receiving each notification.

Versions

Each znode has a version number associated with it that is incremented every time its data changes. A couple of operations in the API can be executed conditionally: setDa ta and delete. Both calls take a version as an input parameter, and the operation suc‐ ceeds only if the version passed by the client matches the current version on the server. The use of versions is important when multiple ZooKeeper clients might be trying to perform operations over the same znode. For example, suppose that a client c1 writes a znode /config containing some configuration. If another client c2 concurrently updates the znode, the version c1 has is stale and the setData of c1 must not succeed. Using versions avoids such situations. In this case, the version that c1 uses when writing back doesn’t match and the operation fails.

ZooKeeper Architecture

Now that we have discussed at a high level the operations that ZooKeeper exposes to applications, we need to understand more of how the service actually works. Applica‐ tions make calls to ZooKeeper through a client library. The client library is responsible for the interaction with ZooKeeper servers.

ZooKeeper servers run in two modes: standalone and quorum. Standalone mode is pretty much what the term says: there is a single server, and ZooKeeper state is not replicated. In quorum mode, a group of ZooKeeper servers, which we call a ZooKeeper ensemble, replicates the state, and together they serve client requests. From this point on, we use the term “ZooKeeper ensemble” to denote an installation of servers. This installation could contain a single server and operate in standalone mode or contain a group of servers and operate in quorum mode.

ZooKeeper Quorums

In quorum mode, ZooKeeper replicates its data tree across all servers in the ensemble. But if a client had to wait for every server to store its data before continuing, the delays might be unacceptable. In public administration, a quorum is the minimum number of legislators required to be present for a vote. In ZooKeeper, it is the minimum number of servers that have to be running and available in order for ZooKeeper to work. This number is also the minimum number of servers that have to store a client’s data before telling the client it is safely stored. For instance, we might have five ZooKeeper servers in total, but a quorum of three. So long as any three servers have stored the data, the client can continue, and the other two servers will eventually catch up and store the data.

It is important to choose an adequate size for the quorum. Quorums must guarantee that, regardless of delays and crashes in the system, any update request the service pos‐ itively acknowledges will persist until another request supersedes it.

The bottom line is that we should always shoot for an odd number of servers.

sessions

All operations a client submits to ZooKeeper are associated to a session. When a session ends for any reason, the ephemeral nodes created during that session disappear.

the session may be moved to a different server if the client has not heard from its current server for some time. Moving a session to a different server is handled transparently by the ZooKeeper client library.

Sessions offer order guarantees, which means that requests in a session are executed in FIFO (first in, first out) order. Typically, a client has only a single session open, so its requests are all executed in FIFO order. If a client has multiple concurrent sessions, FIFO ordering is not necessarily preserved across the sessions.

Commands

[zk: 127.0.0.1:2181,127.0.0.1:2182(CONNECTED) 5] stat /master
cZxid = 0x4
ctime = Mon Aug 20 21:10:23 AEST 2018
mZxid = 0x4
mtime = Mon Aug 20 21:10:23 AEST 2018
pZxid = 0x4
cversion = 0
dataVersion = 0
aclVersion = 0
ephemeralOwner = 0x10003c70e250001
dataLength = 11
numChildren = 0


[zk: 127.0.0.1:2181,127.0.0.1:2182(CONNECTED) 8] create /workers ""
Created /workers
[zk: 127.0.0.1:2181,127.0.0.1:2182(CONNECTED) 9] create /tasks ""
Created /tasks
[zk: 127.0.0.1:2181,127.0.0.1:2182(CONNECTED) 10] create /assign ""
Created /assign
[zk: 127.0.0.1:2181,127.0.0.1:2182(CONNECTED) 11] ls /
[assign, master, tasks, workers, zookeeper]

In a real application, these znodes need to be created either by a primary process before it starts assigning tasks or by some bootstrap procedure. Regardless of how they are created, once they exist, the master needs to watch for changes in the children of /workers and /tasks: [zk: localhost:2181(CONNECTED) 4] ls /workers true [] [zk: localhost:2181(CONNECTED) 5] ls /tasks true [] [zk: localhost:2181(CONNECTED) 6] Note that we have used the optional true parameter with ls, as we did before with stat on the master. The true parameter, in this case, creates a watch for changes to the set of children of the corresponding znode.

[zk: 127.0.0.1:2181,127.0.0.1:2182(CONNECTED) 14] create -e /workers/todd-worker1 ""
Created /workers/todd-worker1

WATCHER::

WatchedEvent state:SyncConnected type:NodeChildrenChanged path:/workers
[zk: 127.0.0.1:2181,127.0.0.1:2182(CONNECTED) 15]

Recall that the master has set a watch for changes to the children of /workers. Once the worker creates a znode under /workers, the master observes the following notification: WATCHER:: WatchedEvent state:SyncConnected type:NodeChildrenChanged path:/workers

Tasks workflows

  • Clients add tasks to the system. Here we assume that the client asks the master-worker system to run a command cmd. To add a task to the system, a client executes the following: [zk: localhost:2181(CONNECTED) 0] create -s /tasks/task- “cmd” Created /tasks/task-0000000000
  • The client now has to wait until the task is executed.
  • The worker that executes the task creates a status znode for the task once the task completes.
  • The client determines that the task has been executed when it sees that a status znode for the task has been created;
  • the client consequently must watch for the creation of the status znode:
[zk: 127.0.0.1:2181,127.0.0.1:2182(CONNECTED) 18] create -s /tasks/task- "cmd"
Created /tasks/task-0000000000
[zk: 127.0.0.1:2181,127.0.0.1:2182(CONNECTED) 19] ls /tasks
[task-0000000000]
[zk: 127.0.0.1:2181,127.0.0.1:2182(CONNECTED) 20] ls -w /tasks/task-0000000000 
[]
[zk: 127.0.0.1:2181,127.0.0.1:2182(CONNECTED) 21] ls -w /workers
[todd-worker1]
[zk: 127.0.0.1:2181,127.0.0.1:2182(CONNECTED) 22] create /assign/todd-worker1/task-0000000000 ""
Ephemerals cannot have children: /assign/todd-worker1/task-0000000000
[zk: 127.0.0.1:2181,127.0.0.1:2182(CONNECTED) 23] delete /assign/todd-worker1
[zk: 127.0.0.1:2181,127.0.0.1:2182(CONNECTED) 24] create /assign/todd-worker1
Created /assign/todd-worker1
[zk: 127.0.0.1:2181,127.0.0.1:2182(CONNECTED) 25] create /assign/todd-worker1/task-0000000000 ""
Created /assign/todd-worker1/task-0000000000
[zk: 127.0.0.1:2181,127.0.0.1:2182(CONNECTED) 26] ls /assign/todd-worker1
[task-0000000000]



# Once the worker finishes executing the task, it adds a status znode to /tasks:
    [zk: localhost:2181(CONNECTED) 4] create /tasks/task-0000000000/status "done"
    Created /tasks/task-0000000000/status
    [zk: localhost:2181(CONNECTED) 5]
# and the client receives a notification and checks the result:
WATCHER::
    WatchedEvent state:SyncConnected type:NodeChildrenChanged
    path:/tasks/task-0000000000
    [zk: localhost:2181(CONNECTED) 2] get /tasks/task-0000000000
    "cmd"

ZooKeeper API

Setting the ZooKeeper CLASSPATH

ZOOBINDIR=”/bin" . "$ZOOBINDIR"/zkEnv.sh

handle

The ZooKeeper API is built around a ZooKeeper handle that is passed to every API call. This handle represents a session with ZooKeeper. A session that is established with one ZooKeeper server will migrate to another ZooKeeper server if its connection is broken. As long as the session is alive, the handle will remain valid, and the ZooKeeper client library will continually try to keep an active connection to a ZooKeeper server to keep the session alive. If the handle is closed, the ZooKeeper client library will tell the ZooKeeper servers to kill the session. If ZooKeeper decides that a client has died, it will invalidate the session. If a client later tries to reconnect to a Zoo‐ Keeper server using the handle that corresponds to the invalidated session, the Zoo‐ Keeper server informs the client library that the session is no longer valid and the handle returns errors for all operations.

The constructor that creates a ZooKeeper handle usually looks like: ZooKeeper( String connectString, int sessionTimeout, Watcher watcher)

Implementing a Watcher

To receive notifications from ZooKeeper, we need to implement watchers. Let’s look a bit more closely at the Watcher interface. It has the following declaration: public interface Watcher { void process(WatchedEvent event); }

Sample ZooKeeper handle

import org.apache.zookeeper.ZooKeeper; 
import org.apache.zookeeper.Watcher;

public class Master implements Watcher { 
  ZooKeeper zk;
        String hostPort;

Master(String hostPort) 
{ this.hostPort = hostPort;
}
void startZK() {
zk = new ZooKeeper(hostPort, 15000, this);
}
public void process(WatchedEvent e) { System.out.println(e);
}
public static void main(String args[]) throws Exception {
Master m = new Master(args[0]);
            m.startZK();
            // wait for a bit
            Thread.sleep(60000);
        }
}

nce we have connected to ZooKeeper, there will be a background thread that will maintain the ZooKeeper session. This thread is a daemon thread, which means that the program may exit even if the thread is still active. Here we sleep for a bit so that we can see some events come in before the program exits. We can compile this simple example using the following: $ javac -cp $CLASSPATH Master.java Once we have compiled Master.java, we run it and see the following: $ java -cp $CLASSPATH Master 127.0.0.1:2181

disconnect

When developers see the Disconnected event, some think they need to create a new ZooKeeper handle to reconnect to the service. Do not do that! See what happens when you start the server, start the Master, and then stop and start the server while the Master is still running. You should see the SyncConnected event followed by the Disconnec ted event and then another SyncConnected event. The ZooKeeper client library takes care of reconnecting to the service for you. Unfortunately, network outages and server failures happen. Usually, ZooKeeper can deal with these failures.

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JDK Versions JDK 1.5 in 2005 JDK 1.6 in 2006 JDK 1.7 in 2011 JDK 1.8 in 2014 Sun之前风光无限,但是在2010年1月27号被Oracle收购。 在被Oracle收购后对外承诺要回到每2年一个realse的节奏。但是20...

Simpler chronicle of CI(Continuous Integration) “乱弹系列”之持续集成工具

引言 有句话说有人的地方就有江湖,同样,有江湖的地方就有恩怨。在软件行业历史长河(虽然相对于其他行业来说,软件行业的历史实在太短了,但是确是充满了智慧的碰撞也是十分的精彩)中有一些恩怨情愁,分分合合的小故事,比如类似的有,从一套代码发展出来后面由于合同到期就分道扬镳,然后各自发展成独门产品的Sybase DB和微...

浅谈软件单元测试中的“断言” (assert),从石器时代进步到黄金时代。

大家都知道,在软件测试特别是在单元测试时,必用的一个功能就是“断言”(Assert),可能有些人觉得不就一个Assert语句,没啥花头,也有很多人用起来也是懵懵懂懂,认为只要是Assert开头的方法,拿过来就用。一个偶然的机会跟人聊到此功能,觉得还是有必要在此整理一下如何使用以及对“断言”的理解。希望可以帮助大家...

Kubernetes 与 Docker Swarm的对比

Kubernetes 和Docker Swarm 可能是使用最广泛的工具,用于在集群环境中部署容器。但是这两个工具还是有很大的差别。

http methods

RFC origion http://www.w3.org/Protocols/rfc2616/rfc2616-sec9.html#sec9.1.2)

Spark-vs-Storm

The stark difference among Spark and Storm. Although both are claimed to process the streaming data in real time. But Spark processes it as micro-batches; wh...

微服务

可以想像一下,之前的传统应用系统,像是一个大办公室里面,有各个部门,销售部,采购部,财务部。办一件事情效率比较高。但是也有一些弊端,首先,各部门都在一个房间里。

kibana, view layer of elasticsearch

What’s Kibana kibana is an open source data visualization plugin for Elasticsearch. It provides visualization capabilities on top of the content indexed on...

kibana, view layer of elasticsearch

What’s Kibana kibana is an open source data visualization plugin for Elasticsearch. It provides visualization capabilities on top of the content indexed on...

iConnect

UI HTML5, AngularJS, BootStrap, REST API, JSON Backend Hadoop core (HDFS), Hive, HBase, MapReduce, Oozie, Pig, Solr

Data Structure

Binary Tree A binary tree is a tree in which no node can have more than two children. A property of a binary tree that is sometimes important is that th...

Something about authentication

It’s annoying to keep on repeating typing same login and password when you access multiple systems within office or for systems in external Internet. There a...

SQL

Differences between not in, not exists , and left join with null

Github page commands notes

404 error for customized domain (such as godday) 404 There is not a GitHub Pages site here. Go to github master branch for gitpages site, manually add CN...

RenMinBi International

RQFII RQFII stands for Renminbi Qualified Foreign Institutional Investor. RQFII was introduced in 2011 to allow qualified foreign institutional investors to ...

Load Balancing

Concepts LVS means Linux Virtual Server, which is one Linux built-in component.

Python

(‘—–Unexpected error:’, <type ‘exceptions.TypeError’>) datetime.datetime.now()

Microservices vs. SOA

Microservice Services are organized around capabilities, e.g., user interface front-end, recommendation, logistics, billing, etc. Services are small in ...

Java Class Loader

Codecache The maximum size of the code cache is set via the -XX:ReservedCodeCacheSize=N flag (where N is the default just mentioned for the particular com...

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