This article will introduce the basic concepts of JGroups and then implement a task java,spring boot,errror response,http,tutorial,customize. JGroups is a library for reliable one-to-one or one-to-many communication written in the Java language. It can be used to create groups of processes whose. JGroup is the corner stone for clustering. It is a reliable multicast system. As we know, using IP multicasting we can set a group of computers to.
|Published (Last):||6 February 2004|
|PDF File Size:||2.38 Mb|
|ePub File Size:||8.74 Mb|
|Price:||Free* [*Free Regsitration Required]|
This article will introduce the basic concepts of JGroups and tutoorial implement a task distribution system on top of JGroupswhere tasks can be placed into the cluster and ngroups executed by worker nodes. I’ll show that worker nodes can be added at run time to add more processing power, or taken down when we don’t have much load. Plus, tasks assigned to workers who subsequently crash are automatically reassigned to live nodes.
We could have implemented this with JMS queues. However, when we have jjgroups lot of load, the JMS server tends to become the bottleneck. In our decentralized solution, every node in the cluster can be both a master who submits tasks and a slave who executes the tasks and returns the tutorual. JGroups is a clustering library.
Applications tutoria use JGroups to join a cluster, send messages to the cluster nodes, get notifications when other nodes join or leave including crashesand leave a cluster. Its task is the reliable sending of messages within a cluster.
Its scope is much smaller than JMS; JGroups doesn’t know about queues, topics and transactions, but only about message sending. The main feature of JGroups is the protocol stack and the resulting configuration jgriups. Applications can pick the properties they would like in a cluster by simply editing an XML file. Another application might add encryption and tutprial, so messages are encrypted and only nodes which present a tutroial X.
Applications are even free to write their own protocols or extend an existing oneand add them to the configuration. It might be useful for example, to add a protocol which keeps track of all messages sent and received over a cluster, for auditing or statistics purposes.
The architecture of JGroups is shown in fig. The main API for clients is a Channel see below which is used to send and receive messages. When a message is sent, jgroupx is passed down the protocol stack. The stack is a list of protocols, and each protocol gets a chance to do something with the message.
For example, a fragmentation protocol might check the size of the message. If the message is greater than the configured size, it might fragment it into multiple smaller messages and send those down the stack. On the receive side, the fragmentation protocol would queue the fragments, until all have been received, then assemble them into the original message and pass it up.
The protocols shipped with JGroups can be divided into the following categories: This is done through assigning sequence numbers to each message and through retransmission in case of a missing message. The stability protocol makes sure that periodically or based on accumulated sizemessages that have been received by all cluster nodes are purged so they can be garbage collected. This is necessary to prevent out-of-memory situations. Flow control is a counter part to stability.
If an application needs different properties, it would modify udp. Then we set a Receiver, which has callbacks that are invoked when messages are received.
Jgtoups channels with the same configuration and the same cluster name argument of tutorila will join the same cluster. A node can send and receive messages once it has joined a cluster.
The Receiver interface has 2 methods we’re interested in:. The receive callback is invoked whenever a message is received Note that receive can be invoked concurrently, when we receive messages from different senders it therefore needs to be reentrant.
Jgrousp argument is an org. An Address is an opaque class identifying a node uniquely within a cluster2. A destination address of null means that the message is to be jgrohps to all cluster nodes a multicasta non-null destination address means to send the message to a single receiver a unicast. When receiving a message, the application can call getBuffer to retrieve the byte buffer and then unmarshal it into data meaningful to the application.
The viewAccepted callback is invoked when a node joins or leaves. Its only parameter is a View, which is essentially a list of addresses. As we can see, the nodes in a view are ordered according to join time.
The oldest node is always first. The current view can also be retrieved from a channel by calling Channel. The send method takes a Message and sends it to all cluster nodes if the message’s destination is null, or to a single node if the destination is non-null.
The application needs to marshal their data to a byte buffer and set place it into the message via Message. To retrieve the current view, we can use Channel.
The disconnect method leaves a cluster and close destroys the channel. A closed channel cannot be opened again. Invoking close also disconnects a channel if not already disconnected. Calling disconnect will install a new view in all cluster nodes, and viewAccepted will be invoked in all receivers.
As we will see in building our task distribution system, the use of JGroups allows us to focus on the system at hand, and not have to worry about clustering issues, as JGroups does the heavy lifting.
The main features used in our system are membership management we need to know who the cluster nodes are, and when a node joins or leaves and reliable messaging for task sending. Plus, by modifying the protocol configuration, we can adapt the transport to our needs. The idea is very simple: So every node is a peer, in the sense that it can both submit and handle tasks.
In a real life application, clients would connect to any of the nodes, e. When submitting a task, we choose a random integer which is then mapped to the rank of a node in the cluster int mod N where N is the cluster size.
The rank is the position of a node in the view, and since the view is the same in all nodes, the rank identifies the node uniquely. Every node adds the task to a hash map consisting of tasks and their submitters’ JGroups addresses. Every node now compares the rank shipped with the task to its own rank.
It it doesn’t match, nothing is done. If it matches, the node needs to process the task. It does so and returns the result to the submitter.
A Simple Clustered Task Distribution System
If a node X crashes or leaves gracefullywe know which tasks were assigned to it by looking up the tasks in the hash map, keyed by X. All tasks which are still present in the hash map have not yet been processed and need to be re-executed, this time by a different node.
This is done by comparing the rank shipped with the task to the node’s rank and executing it if a node’s own rank matches it. If a master M crashes after having submitted a few tasks but not yet having received the results, the slaves remove all tasks submitted by M, because M won’t need the results anymore3.
The cluster jgrooups of nodes A, B, C and D.
Clients can access any one of them. A task submitted for example to B by a client might assign 23 to the task. Had A crashed during processing of task 23, some other node would have taken over, processed the result and sent it back to B. Let’s look at how we implement this4. We’ll write a Server class which has the main loop and accepts requests which are to be distributed across the cluster.
This mimics real clients sending requests tutoial any cluster node. We can then start a number of Tktorial processes, across the cluster or on the same host for the demo.
First, we need an ID ClusterID which is unique across the cluster and which is used to determine whether a node accepts a task. An instance of ClusterID is created for every task. The class looks as follows:. Implementations of Streamable let JGroups marshal and unmarshal objects more efficiently. A ClusterID has the address of the node which created it and an ID which ttutorial incremented on each create call.
If we only used IDs, because every node could potentially submit tasks, we might end up with node A submitting task 23 and node C submitting task tutorrial, and this would lead to issues with task entries getting overwritten in the cache hash map Prefixing the ID with its creator would yield A:: Then, jgroupw define the Master and Slaves interfaces:.
These interfaces are implemented by our Server class which does the bulk of the work. The submit method takes a task see below and a timeout. It can throw an exception or return tutorisl result. Note that both the Task subclasses and the result have to be serializable or Streamable, because they are potentially sent across the network to get executed. The handle Task t method is invoked at the slave, which is the worker node which decides that it will handle the task.
It typically uses the data shipped with a task subclass and returns an object which needs to be serializable because in most cases, it will be sent back to the submitter via the network.
Next, we define the Task:. A task contains all of the necessary data that is shipped to a slave. The execute method then uses that data to perform the processing and returns a result which is sent back to the master who submitted that task. Now that we’ve defined all the ancillary classes and interfaces, let’s start writing the Server:.
Server implements the Master and Slave interfaces, which means that a Server can act both as a client Master and server Slave.
tutogial Next, we need a few instance variables. For instance, we need a JGroups channel ch which needs to be configured with properties props defining the configuration of the protocol stack. Here, we chose the a simple pool which creates new threads when needed and removes threads that have been idle for more than 60 seconds. The ‘tasks’ hash map is the cache for received tasks. It is keyed by ClusterId and the values are Entry instances see below. More tutorrial this later.
In startwe create a JChannel based on the properties passed to server and connect it, which causes it to join the cluster.