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Premium eBook free for Geeks. Contribute to arpitjindal97/technology_books development by creating an account on GitHub. Short Desciption: This books is Free to download. "Apache ZooKeeper Essentials book" is available in PDF Formate. Learn from this free book and enhance. Apache ZooKeeper provides a simple interface to a centralized coordinating service for distributed Apache ZooKeeper Essentials PDF下载地址( MB).

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ZooKeeper: A Distributed Coordination Service for Distributed. Applications. ZooKeeper is a distributed, open-source coordination service for distributed. Apache ZooKeeper Essentials 电子书PDF下载. Apache ZooKeeper Essentials于 年01月出版,全书共页。本书是使用Apache. ZooKeeper 的快速入门指南. How the World Survived without ZooKeeper. 6. What ZooKeeper Doesn't Do. 6. The Apache Project. 7. Building Distributed Systems with.

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Distributed system designers have to design the system keeping in mind all the preceding points. Beyond this, the next tricky problem to solve is to make the participating computing entities, or independent programs, coordinate their actions. Often, developers and designers get bogged down while implementing this coordination logic; this results in incorrect and inefficient system design. It is with this motive in mind that Apache ZooKeeper is designed and developed; this enables a highly reliable distributed coordination.

Apache ZooKeeper is an effort to develop a highly scalable, reliable, and robust centralized service to implement coordination in distributed systems that developers can straightaway use in their applications through a very simple interface to a centralized coordination service. It enables application developers to concentrate on the core business logic of their applications and rely entirely on the ZooKeeper service to get the coordination part correct and help them get going with their applications.

It simplifies the development process, thus making it more nimble. Zookeeper mitigates the need to implement coordination and synchronization services in distributed applications from scratch by providing simple and elegant primitives through a rich set of APIs.

Why coordination in a distributed system is so challenging After getting introduced to Apache ZooKeeper and its role in the design and development of a distributed application, let's drill down deeper into why coordination in a distributed system is a hard problem. Let's take the example of doing configuration management for a distributed application that comprises multiple software components running independently and concurrently, spanning across multiple physical servers.

Now, having a master node where the cluster configuration is stored and other worker nodes that download it from this master node and auto configure themselves seems to be a simple and elegant solution. However, this solution suffers from a potential problem of the master node being a single point of failure. Even if we assume that the master node is designed to be fault-tolerant, designing a system where change in the configuration is propagated to all worker nodes dynamically is not straightforward.

Another coordination problem in a distributed system is service discovery. Often, to sustain the load and increase the availability of the application, we add more physical servers to the system. However, we can get the client or worker nodes to know about this change in the cluster memberships and availability of newer machines that host different services in the cluster is something.

This needs careful design and implementation of logic in the client application itself. A horizontally scalable distributed system that spans over hundreds and thousands of physical machines is often prone to failures such as hardware faults, system crashes, communication link failures, and so on.

These types of failures don't really follow any pattern, and hence, to handle such failures in the application logic and design the system to be fault-tolerant is truly a difficult problem.

Chapter 1 Thus, from what has been noted so far, it's apparent that architecting a distributed system is not so simple. Making correct, fast, and scalable cluster coordination is hard and often prone to errors, thus leading to an overall inconsistency in the cluster. This is where Apache ZooKeeper comes to the rescue as a robust coordination service in the design and development of distributed systems.

Introducing Apache ZooKeeper Apache ZooKeeper is a software project of the Apache Software Foundation; it provides an open source solution to the various coordination problems in large distributed systems. ZooKeeper was originally developed at Yahoo! A paper on ZooKeeper, ZooKeeper: Grid and Flavio P. Junqueira and Benjamin Reed from Yahoo! Distributed consensus, group management, presence protocols, and leader election are implemented by the service so that the applications do not need to reinvent the wheel by implementing them on their own.

On top of these, the primitives exposed by ZooKeeper can be used by applications to build much more powerful abstractions to solve a wide variety of problems. Apache ZooKeeper is implemented in Java. It ships with C, Java, Perl, and Python client bindings. Community-contributed client libraries are available for a plethora of languages such as Go, Scala, Erlang, and so on.

Getting hands-on with Apache ZooKeeper In this section, we will show you how to download and install Apache ZooKeeper so that we can start using ZooKeeper straightaway. This section is aimed at developers wanting to get their hands dirty using ZooKeeper for their distributed applications' needs by giving detailed installation and usage instructions.

We will start with a single node ZooKeeper installation by getting acquainted with the basic configuration, followed by learning the ZooKeeper shell. Finally, you will be taught how to to set up a multinode ZooKeeper cluster. Download and installation ZooKeeper is supported by a wide variety of platforms. Windows and Mac OS X are recommended only as development platforms for both server and client. ZooKeeper is implemented in Java and requires Java 6 or later versions to run. While Oracle's version of Java is recommended, OpenJDK should also work fine for the correct functioning of ZooKeeper and many of the code samples in this book.

In a production cluster, three ZooKeeper servers is the minimum recommended size for an ensemble, and it is recommended that you run them on separate machines.

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However, you can learn and evaluate ZooKeeper by installing it on a single machine in standalone mode. A recent stable ZooKeeper distribution can be downloaded from one of the Apache Download Mirrors At the time of writing this book, release was the latest stable version available.

Downloading Let's download the stable version from one of the mirrors, say Georgia Tech's Apache download mirror in the following example: The conf folder holds the configuration files for ZooKeeper. ZooKeeper needs a configuration file called zoo. There is a sample configuration file that contains some of the configuration parameters for reference.

Let's create our configuration file with the following minimal parameters and save it in the conf directory: This is measured in milliseconds; it is used for session registration and to do regular heartbeats by clients with the ZooKeeper service.

The minimum session timeout will be twice the ticktime parameter. This is the location to store the in-memory state of ZooKeeper; it includes database snapshots and the transaction log of updates to the database. Extracting the ZooKeeper archive won't create this directory, so if this directory doesn't exist in the system, you will need to create it and set writable permission to it. This is the port that listens for client connections, so it is where the ZooKeeper clients will initiate a connection.

The client port can be set to any number, and different servers can be configured to listen on different ports. The default is We will learn about the various storage, network, and cluster configuration parameters of ZooKeeper in more detail in Chapter 5, Administering Apache ZooKeeper. It is assumed that readers already have a working version of Java running in their system where ZooKeeper is being installed and configured.

For example, in my system, I have Java installed. So, using the preceding command, this will return the following output in my system: To see if this is set in your system, run the following command: This script gives options to start, stop, restart, and see the status of the ZooKeeper server: A successful start of the server will show the following output: In this case, as reported by jps, the ZooKeeper server is running with the process ID that matches the one reported by the ps command.

It is probably not running. Once our ZooKeeper instance is running, the next thing to do is to connect to it.

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ZooKeeper ships with a default Java-based command-line shell to connect to a ZooKeeper instance. There is a C client as well, which we will discuss in a later section. Connecting to localhost: Welcome to ZooKeeper! JLine support is enabled WatchedEvent state: Let's start by running the ls command, which, as in Unix, is used for listing: We can create a znode through the ZooKeeper shell as follows: To begin with, let's create a HelloWorld znode with empty data: We will look at setting up the C language-based command-line shell of the ZooKeeper distribution.

To build them, just run the following three commands in the preceding directory: The C client libraries are built for both single-threaded as well as multithreaded libraries. These two binaries are the single-threaded and multithreaded command-line shells, respectively. ZooKeeper cli c client version To connect to our ZooKeeper server instance with this C-based shell, execute the following command in your terminal: Let's see the available commands under this shell by executing the help command: A return code equal to zero denotes successful execution of the command.

The Perl and Python client bindings shipped with the ZooKeeper distribution are also based on this C-based interface. A standalone instance is a potential single point of failure. If the ZooKeeper server fails, the whole application that was using the instance for its distributed coordination will fail and stop functioning. Hence, running ZooKeeper in standalone mode is not recommended for production, although for development and evaluation purposes, it serves the need.

In a production environment, ZooKeeper should be run on multiple servers in a replicated mode, also called a ZooKeeper ensemble. The minimum recommended number of servers is three, and five is the most common in a production environment. The replicated group of servers in the same application domain is called a quorum. In this mode, the ZooKeeper server instance runs on multiple different machines, and all servers in the quorum have copies of the same configuration file.

One of the instances is elected the leader, and others become followers. If the leader fails, a new leader election happens, and another running instance is made the leader.

However, these intricacies are fully hidden from applications using ZooKeeper and from developers. The ZooKeeper configuration file for a multinode mode is similar to the one we used for a single instance mode, except for a few entries. An example configuration file is shown here: This parameter is the timeout, specified in number of ticks, for a follower to initially connect to a leader synclimit: This is the timeout, specified in number of ticks, for a follower to sync with a leader [ 22 ].

Thus, in our example, the timeout for initlimit is 5 ticks at milliseconds a tick, or 10 seconds. In our example configuration, the zoo1 quorum member host is assigned an identifier 1.

The identifier is needed to be specified in a file called myid in the data directory of that server. The id must be unique within the ensemble and should have a value between 1 and Again, we have the two port numbers after each server hostname: The first port, , is mostly used for peer-to-peer communication in the quorum, such as to connect followers to leaders.

A follower opens a TCP connection to the leader using this port. The second port, , is used for leader election, in case a new leader arises in the quorum.

As all communication happens over TCP, a second port is required to respond to leader election inside the quorum.

Starting the server instances After setting up the configuration file for each of the servers in the quorum, we need to start the ZooKeeper server instances. The procedure is the same as for standalone mode. We have to connect to each of the machines and execute the following command: Connecting to the ZooKeeper quorum through the command-line shell is also the same as in standalone mode, except that we should now specify a connection string in the host1: Running multiple node modes for ZooKeeper It is also possible to run ZooKeeper in multiple node modes on a single machine.

This is useful for testing purposes. To run multinode modes on the same machine, we need to tweak the configuration a bit; for example, we can set the server name as localhost and specify the unique quorum and leader election ports. Let's use the following configuration file to set up a multinode ZooKeeper cluster using a single machine: The first field is the hostname or IP address of server X.

The second and third fields are the TCP port numbers used for quorum communication and leader election, respectively. As we are starting three ZooKeeper server instances on the same machine, we need to use different port numbers for each of the server entries.

Second, as we are running more than one ZooKeeper server process on the same machine, we need to have different client ports for each of the instances. Last but not least, we have to customize the datadir parameter as well for each of the instances we are running. Putting all these together, for a three-instance ZooKeeper cluster, we will create three different configuration files.

We will call these zoo1.

Thus, the three configuration files are shown next. Here, you will see the configuration file for the first instance: This can be done using the following three commands: Let's start the instances as follows: We have a three-node ZooKeeper cluster running on the same machine!

You learned how Apache ZooKeeper is a great tool for distributed system designer and developers to solve coordination problems.

This chapter provided details on installing and configuring a ZooKeeper in various modes, such as standalone, clustered, and also talked about how to connect to a ZooKeeper service from the command line with the ZooKeeper shell.

In the next chapter, you will learn about the internals and architecture of Apache ZooKeeper. The concepts introduced in the next chapter will help you master the design semantics of ZooKeeper and equip readers with confidence in using ZooKeeper in their distributed applications. We learned how Apache ZooKeeper solves this problem, followed by how to install and configure it. In this chapter, we will read more about the internals and architecture of ZooKeeper.

As such, we will cover the following topics here in this second chapter: It aims to solve the tough problems associated with the coordination of components in a distributed application. It does this by exposing a simple yet powerful interface of primitives. Applications can be designed on these primitives implemented through ZooKeeper APIs to solve the problems of distributed synchronization, cluster configuration management, group membership, and so on.

A view of the ZooKeeper service is shown in the following diagram: A ZooKeeper service and how clients connect to the service From the preceding diagram the image is referenced from apache.

This is called an ensemble. Clients can connect to a ZooKeeper service by connecting to any member of the ensemble.

You can send and receive requests and responses as well as event notifications between clients and the service, which are all done by maintaining a TCP connection and by periodically sending heartbeats. The members of the ensemble are aware of each other's state. By this, I mean that the current in-memory state, transaction logs, and the point-in-time copies of the state of the service are stored in a durable manner in the local data store by the individual hosts that form the ensemble.

It is important to remember that ZooKeeper is a highly available service, so as long as a majority of the servers are available, the service will always be available. With this, ZooKeeper maintains a strict ordering of its transactions, which enables the implementation of advanced distributed synchronization primitives that are simple and reliable.

With its design to be robust, reliable, high performing, and fast, this coordination service makes it possible to be used in large and complex distributed applications. The namespace looks quite similar to a Unix filesystem.

The data registers are known as znodes in the ZooKeeper nomenclature. You can see examples of znodes in the following image: A ZooKeeper's hierarchical namespace Here, you can see that znodes are organized hierarchically, much like a tree, as a standard filesystem. Some important points to take note of are as follows: The znodes are called data registers because they can store data. Thus, a znode can have children as well as data associated with it.

It's analogous to having a filesystem that allows a file to also be a path. The data in a znode is typically stored in a byte format, with a maximum data size in each znode of no more than 1 MB. ZooKeeper is designed for coordination, and almost all forms of coordination data are relatively small in size; hence, this limit on the size of data is imposed. It is recommended that the actual data size be much less than this limit as well. Relative paths and references are not recognized by ZooKeeper.

It is useful to know that the znode names can be composed of Unicode characters and that the znodes can have any name. The exception to this is that the word ZooKeeper is reserved. On top of this, the use of ". Like files in a filesystem, znodes maintain a stat structure that includes version numbers for data changes and an access control list that changes along with timestamps associated with changes. The version number increases whenever the znode's data changes.

ZooKeeper uses the version numbers along with the associated timestamps to validate its in-core cache. The znode version number also enables the client to update or delete a particular znode through ZooKeeper APIs. If the version number specified doesn't match the current version of a znode, the operation fails.

However, this can be overridden by specifying 0 as the version number while performing a znode update or delete operation. Types of znodes ZooKeeper has two types of znodes: There is a third type that you might have heard of, called a sequential znode, which is a kind of a qualifier for the other two types.

Both persistent and ephemeral znodes can be sequential znodes as well. Note that a znode's type is set at its creation time. The persistent znode As the name suggests, persistent znodes have a lifetime in the ZooKeeper's namespace until they're explicitly deleted.

A znode can be deleted by calling the delete API call. It's not necessary that only the client that created a persistent znode has to delete it. Note that any authorized client of the ZooKeeper service can delete a znode. It's time to put this newly acquired knowledge into practice, so let's create a persistent znode using the ZooKeeper Java shell: For example, an application can store the configuration data in a persistent znode.

The data as well as the znode will exist even if the creator client dies. An end to a client's session can happen because of disconnection due to a client crash or explicit termination of the connection. Even though ephemeral nodes are tied to a client session, they are visible to all clients, depending on the configured Access Control List ACL policy. An ephemeral znode can also be explicitly deleted by the creator client or any other authorized client by using the delete API call.

An ephemeral znode ceases to exist once its creator client's session with the ZooKeeper service ends. Hence, in the current version of ZooKeeper, ephemeral znodes are not allowed to have children. To create an ephemeral znode using the ZooKeeper Java Shell, we have to specify the -e flag in the create command, which can be done using the following command: For example, a distributed group membership service can be implemented by using ephemeral znodes.

The property of ephemeral nodes getting deleted when the creator client's session ends can be used as an analogue of a node that is joining or leaving a distributed cluster. Using the membership service, any node is able discover the members of the group at any particular time.

The sequential znode A sequential znode is assigned a sequence number by ZooKeeper as a part of its name during its creation. The value of a monotonously increasing counter maintained by the parent znode is appended to the name of the znode.

The counter used to store the sequence number is a signed integer 4 bytes. It has a format of 10 digits with 0 zero padding. They may also be used to design a lock service for a distributed application. The recipes for a distributed queue and lock service will be discussed in Chapter 4, Performing Common Distributed System Tasks.

Since both persistent and ephemeral znodes can be sequential znodes, we have a total of four modes of znodes: A common design anti-pattern associated while accessing such services by clients is through polling or a pull kind of model.

A pull model often suffers from scalability problems when implemented in large and complex distributed systems. To solve this problem, ZooKeeper designers implemented a mechanism where clients can get notifications from the ZooKeeper service instead of polling for events. This resembles a push model, where notifications are pushed to the registered clients of the ZooKeeper service. Clients can register with the ZooKeeper service for any changes associated with a znode.

This registration is known as setting a watch on a znode in ZooKeeper terminology. Watches allow clients to get notifications when a znode changes in any way.

A watch is a one-time operation, which means that it triggers only one notification. To continue receiving notifications over time, the client must reregister the watch upon receiving each event notification. In the cluster, a node, say Client1, is interested in getting notified when another node joins the cluster.

This flow of the setting of watches, and notifications and subsequent resetting of the watches is shown in the following image: An image to representing how the relationship between two clients and ZooKeeper works through watches and notifications [ 35 ]. What this means is that if a client receives a watch event and wants to get notified of future changes, it must set another watch.

Whenever a watch is triggered, a notification is dispatched to the client that had set the watch. Watches are maintained in the ZooKeeper server to which a client is connected, and this makes it a fast and lean method of event notification. The watches are triggered for the following three changes to a znode: Any changes to the data of a znode, such as when new data is written to the znode's data field using the setdata operation.

Any changes to the children of a znode. For instance, children of a znode are deleted with the delete operation. A znode being created or deleted, which could happen in the event that a new znode is added to a path or an existing one is deleted. Again, ZooKeeper asserts the following guarantees with respect to watches and notifications: ZooKeeper ensures that watches are always ordered in the first in first out FIFO manner and that notifications are always dispatched in order Watch notifications are delivered to a client before any other change is made to the same znode The order of the watch events are ordered with respect to the updates seen by the ZooKeeper service Since ZooKeeper watches are one-time triggers and due to the latency involved between getting a watch event and resetting of the watch, it's possible that a client might lose changes done to a znode during this interval.

In a distributed application in which a znode changes multiple times between the dispatch of an event and resetting the watch for events, developers must be careful to handle such situations in the application logic. When a client gets disconnected from the ZooKeeper server, it doesn't receive any watches until the connection is re-established. If the client then reconnects, any previously registered watches will also be reregistered and triggered.

If the client connects to a new server, the watch will be triggered for any session events. This disconnection from a server and reconnection to a new server happens in a transparent way for the client applications.

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This specific scenario is when a client has set a watch for the existence of a znode that has not yet been created. In this case, a watch event will be missed if the znode is created, and deleted while the client is in the disconnected state. Get the content of the just created znode root: Create a child znode child-1 for root with ThisIsChild-1 as its data: Create a child znode child-2 for root with ThisIsChild-2 as its data: List the children of root: Get the access control listing for root: Deleting the root is not allowed as root has 2 child znodes: Delete child This batches together multiple primitive operations into a single unit.

A multi operation is also atomic in nature, which means that either all the updates succeed or the whole bunch of updates fails in its entirety. 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. Update operations in ZooKeeper, such as a delete or setdata operation, have to specify the version number of the znode that is being updated.

The version number can be obtained by using the exists call. The update operation will fail if the specified version number does not match the one in the znode. Also, another important thing to note is that updates in ZooKeeper are non-blocking operations.

The read and write operations in ZooKeeper are shown in the following image: An image that shows the read and write operations in ZooKeeper [ 39 ]. Read requests: These are processed locally in the ZooKeeper server to which the client is currently connected Write requests: These are forwarded to the leader and go through majority consensus before a response is generated The read and write processing by ZooKeeper is described in more detail in the ZooKeeper implementation section later in this chapter.

There is the guarantee of a successful write operation if it has been written to persistent storage on a majority of ZooKeeper's servers. However, the eventual consistency model of ZooKeeper permits reads to log the latest state of the ZooKeeper service, and the sync operation allows a client to be up-to-date with the most recent state of the ZooKeeper service.

The read operations in znodes, such as exists, getchildren, and getdata, allow watches to be set on them. On the other hand, the watches triggered by znode's write operations, such as create, delete, and setdata ACL operations do not participate in watches. The following are the types of watch events that might occur during a znode state change: A znode's child is created or deleted NodeCreated: The data associated with a znode is updated NodeDeleted: A znode is deleted in a ZooKeeper path [ 40 ].

Some crucial information about how the three main operations have event-generating actions is shown in this table: Operation exists getchildren getdata Event-generating Actions A znode is created or deleted, or its data is updated A child of a znode is created or deleted, or the znode itself is deleted A znode is deleted or its data is updated A watch event includes the path of the znode where the event was generated.

Thus, a client can find a znode creation and deletion for the NodeCreated and NodeDeleted events through the inspection of the path to the znode. To discover which children have changed after a NodeChildrenChanged event, the operation getchildren has to be called to retrieve the new list of children. Similarly, in order to discover the new data for a NodeDataChanged event, getdata has to be called.

ZooKeeper provides a set of guarantees from its data model perspectives and watch infrastructure built on top of it, which enables the easy, fast, and scalable building of other distributed coordination primitives: Sequential consistency: This ensures that the updates from clients are always applied in a FIFO order. This ensures that the updates either succeed or fail, so there is no partial commit.

Single system image: A client sees the same view of the ZooKeeper service, which doesn't depend on which ZooKeeper server in the ensemble it connects to. This ensures that the updates will persist once they are applied. This is until they are overwritten by some clients. The clients' view of the system is guaranteed to be up-to-date within a certain time bound. This is known as eventual consistency.

While creating a znode, the ACLs determine the permissions with respect to the various operations that you can perform on the znodes. ACLs are determined on the basis of the authentication mechanism of the client and the ZooKeeper service.

ZooKeeper provides the following built-in authentication mechanisms based on ACLs: This represents anyone who is connecting to the ZooKeeper service Auth: This represents any authenticated user, but doesn't use any ID Digest: This represents the username and password way of authentication IP address: This represents authentication with the IP address of the client In addition to the authentication schemes mentioned in the preceding list, ZooKeeper also supports a pluggable authentication mechanism, which makes it possible to integrate third-party authentication schemes if needed.

Any authentication schemes in ZooKeeper consist of the following two main authentication operations: Firstly, the authentication framework in ZooKeeper authenticates the client. The client authentication occurs when the client connects to the ZooKeeper service by validating client information. Secondly, the authentication framework finds the entries in the ACL, which correspond to the client.

An important point about znode ACLs is that the ACL associated with a particular znode doesn't propagate to its children. A client's authentication with ZooKeeper is optional; if the ACLs associated with a znode require a client to authenticate, then it must authenticate using any of the previously mentioned authentication mechanisms.

An ACL is the combination of an authentication mechanism, an identity for that mechanism, and a set of permissions. This exist operation is permission-free, which allows to retrieve the stat structure of a znode. We will read about the stat structure of ZooKeeper in the next section.

The fields in the stat structure of a znode are shown as follows with their respective meanings: This is the transaction ID of the change that caused this znode to be created.

This is the transaction ID of the change that last modified this znode. This is the transaction ID for a znode change that pertains to adding or removing children. This denotes the creation time of a znode in milliseconds from epoch.

This denotes the last modification time of a znode in milliseconds from epoch. This denotes the number of changes made to the data of this znode. This denotes the number of changes made to the children of this znode. This denotes the number of changes made to the ACL of this znode.

This is the session ID of the znode's owner if the znode is an ephemeral node. If the znode is not an ephemeral node, this field is set to zero. This is the length of the data field of this znode. This denotes the number of children of this znode. In the ZooKeeper Java shell, the stat structure of a znode can be viewed using the stat or ls2 command. One way to look at this is: If you have 3 ZKs you can afford to lose one, if you have 5 you can afford to lose two.

If your IT is aggressively applying security patches and other upgrades, like firmware, kernel, Java, other packages used by Hadoop tools, and taking nodes down to do the job, then during those upgrades with 3 ZKs, you ZK runs with only two nodes, and if you are unlucky and one of them goes down, then your whole cluster will go down.

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So, in this case 5 are better. Warning: the more ZK nodes you have, the slower the ZK becomes for writes. Placement Zookeeper is a master node, as such it can be collocated with other master services. Ideally, you would not want to collocate it with an HA service. Storage Requirements In general, Zookeeper doesn't actually require huge drives because it will only store metadata information for many services, It is common to use G to G for zookeeper data directory and logs which is fine of many cluster deployments.

Moreover, it is recommended to set configuration for automatic purging policy of snapshots and logs directories so that it doesn't end up by filling all the local storage. Dedicated or Shared? At Yahoo! The driving force for physical hardware or at least for the dedicated disk is the transaction log and the high throughput nature of Kafka and Storm. Put the Zookeeper on the Storm nodes. Caution Rather than going to larger clusters of ZKs, it is better to split out certain services to their own ZKs when they're putting more pressure on an otherwise fairly quiet ZK cluster.

Challenge is that more hardware is needed and more administration, but it pays off. Be careful where you put that transaction log. The most performance-critical part of ZooKeeper is the transaction log.

ZooKeeper must sync transactions to media before it returns a response.The client that created the next higher sequence node will be notified and hold the lock. The cost can be in the form of CPU cycles spent to actual dollars being paid to network service providers. This book assumes you to have some prior knowledge of distributed systems and high-level programming knowledge of C, Java, or Python, but no experience with Apache ZooKeeper is required. A service discovery system provides a seamless mechanism to guarantee service continuity in the case of failures and is an indispensable part of building a robust and scalable distributed platform.

For example, an application can store the configuration data in a persistent znode. Update operations in ZooKeeper, such as a delete or setdata operation, have to specify the version number of the znode that is being updated.