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| e-docs > WebLogic Server > Using WebLogic Server Clusters > Load Balancing in a Cluster |
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Using WebLogic Server Clusters
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This section describes the load balancing support that a WebLogic Server cluster provides for different types of objects, and related planning and configuration considerations for architects and administrators. It contains the following information:
Load Balancing for Servlets and JSPs
Load balancing of servlets and JSPs can be accomplished with the built-in load balancing capabilities of a WebLogic proxy plug-in or with separate load balancing hardware.
Note: In addition to distributing HTTP traffic, external load balancers can distribute initial context requests that come from Java clients over t3 and the default channel. See Load Balancing for EJBs and RMI Objects for a discussion of object-level load balancing in WebLogic Server.
Load Balancing with a Proxy Plug-in
The WebLogic proxy plug-in maintains a list of WebLogic Server instances that host a clustered servlet or JSP, and forwards HTTP requests to those instances using a round-robin strategy. This load balancing method is described below in Round Robin Load Balancing.
The plug-in also provides the logic necessary to locate the replica of a client's HTTP session state if a WebLogic Server instance should fail.
WebLogic Server supports the following Web servers and associated proxy plug-ins:
For instructions on setting up proxy plug-ins, see Configure Proxy Plug-Ins.
How Session Connection and Failover Work with a Proxy Plug-in
For a description of connection and failover for HTTP sessions in a cluster with proxy plug-ins, see Accessing Clustered Servlets and JSPs Using a Proxy.
Load Balancing HTTP Sessions with an External Load Balancer
Clusters that utilize a hardware load balancing solution can use any load balancing algorithm supported by the hardware. These can include advanced load-based balancing strategies that monitor the utilization of individual machines.
Load Balancer Configuration Requirements
If you choose to use load balancing hardware instead of a proxy plug-in, it must support a compatible passive or active cookie persistence mechanism, and SSL persistence.
Passive cookie persistence enables WebLogic Server to write a cookie containing session parameter information through the load balancer to the client. For information about the session cookie and how a load balancer uses session parameter data to maintain the relationship between the client and the primary WebLogic Server hosting a HTTP session state, see Load Balancers and the WebLogic Session Cookie.
Certain active cookie persistence mechanisms can be used with WebLogic Server clusters, provided the load balancer does not modify the WebLogic Server cookie. WebLogic Server clusters do not support active cookie persistence mechanisms that overwrite or modify the WebLogic HTTP session cookie. If the load balancer's active cookie persistence mechanism works by adding its own cookie to the client session, no additional configuration is required to use the load balancer with a WebLogic Server cluster.
When SSL persistence is used, the load balancer performs all encryption and decryption of data between clients and the WebLogic Server cluster. The load balancer then uses the plain text cookie that WebLogic Server inserts on the client to maintain an association between the client and a particular server in the cluster.
Load Balancers and the WebLogic Session Cookie
A load balancer that uses passive cookie persistence can use a string in the WebLogic session cookie to associate a client with the server hosting its primary HTTP session state. The string uniquely identifies a server instance in the cluster. You must configure the load balancer with the offset and length of the string. The correct values for the offset and length depend on the format of the session cookie.
The format of a session cookie is:
sessionid!primary_server_id!secondary_server_id
Notes: For sessions using non-replicated memory, cookie, JDBC, or file-based session persistence, the secondary_server_id is not present. For sessions that use in-memory replication, if the secondary session does not exist, the secondary_server_id is "NONE".
For general instructions on configuring load balancers, see Configuring Load Balancers that Support Passive Cookie Persistence. Vendor-specific instructions are provided in Configuring BIG-IPTM Hardware with Clusters
Related Programming Considerations
For key programming constraints and recommendations for clustered servlets and JSPs see Programming Considerations for Clustered Servlets and JSPs.
How Session Connection and Failover Works with a Load Balancer
For a description of connection and failover for HTTP sessions in a cluster with load balancing hardware, see Accessing Clustered Servlets and JSPs with Load Balancing Hardware.
Load Balancing for EJBs and RMI Objects
WebLogic Server clusters support several algorithms for load balancing clustered EJBs and RMI objects: round-robin, weight-based, and random. By default, a WebLogic Server cluster will use the round-robin method. You can configure a cluster to use one of the other methods using the Administration Console. The method you select is maintained within the replica-aware stub obtained for clustered objects.
Note: WebLogic Server does not always perform load balancing for an object's method calls. To understand why, see Optimization for Collocated Objects.
For instructions on how to specify the load balancing algorithm to be used in your cluster, see Configure Load Balancing Method for EJBs and RMIs.
To understand the supported load balancing algorithms, see:
WebLogic Server also supports custom parameter-based routing. For more information, see Parameter-Based Routing for Clustered Objects.
Load Balancing Algorithms for RMI Objects and EJBs
This following sections describes the standard load balancing methods available in a WebLogic Server cluster.
WebLogic Server uses the round-robin algorithm as the default load balancing strategy for clustered object stubs when no algorithm is specified. This algorithm is supported for RMI objects and EJBs. It is also the method used by WebLogic proxy plug-ins.
The round-robin algorithm cycles through a list of WebLogic Server instances in order. For clustered objects, the server list consists of WebLogic Server instances that host the clustered object. For proxy plug-ins, the list consists of all WebLogic Server instances that host the clustered servlet or JSP.
The advantages of the round-robin algorithm are that it is simple, cheap and very predictable. The primary disadvantage is that there is some chance of convoying. Convoying occurs when one server is significantly slower than the others. Because replica-aware stubs or proxy plug-ins access the servers in the same order, one slow server can cause requests to "synchronize" on the server, then follow other servers in order for future requests.
This algorithm applies only to EJB and RMI object clustering.
Weight-based load balancing improves on the round-robin algorithm by taking into account a pre-assigned weight for each server. You can use the Server -> Configuration -> Cluster tab in the Administration Console to assign each server in the cluster a numerical weight between 1 and 100, in the Cluster Weight field. This value determines what proportion of the load the server will bear relative to other servers. If all servers have the same weight, they will each bear an equal proportion of the load. If one server has weight 50 and all other servers have weight 100, the 50-weight server will bear half as much as any other server. This algorithm makes it possible to apply the advantages of the round-robin algorithm to clusters that are not homogeneous.
If you use the weight-based algorithm, carefully determine the relative weights to assign to each server instance. Factors to consider include:
If you change the specified weight of a server and reboot it, the new weighting information is propagated throughout the cluster via the replica-aware stubs. For related information see Cluster-Wide JNDI Naming Service.
Notes: In this version of WebLogic Server, weight-based load balancing is not supported for objects that communicate using the RMI/IIOP protocol.
The random method of load balancing applies only to EJB and RMI object clustering.
In random load balancing, requests are routed to servers at random. Random load balancing is recommended only for homogeneous cluster deployments, where each server instance runs on a similarly configured machine. A random allocation of requests does not allow for differences in processing power among the machines upon which server instances run. If a machine hosting servers in a cluster has significantly less processing power than other machines in the cluster, random load balancing will give the less powerful machine as many requests as it gives more powerful machines.
Random load balancing distributes requests evenly across server instances in the cluster, increasingly so as the cumulative number of requests increases. Over a small number of requests the load may not be balanced exactly evenly.
Disadvantages of random load balancing include the slight processing overhead incurred by generating a random number for each request, and the the possibility that the load may not be evenly balanced over a small number of requests.
Parameter-Based Routing for Clustered Objects
Parameter-based routing allows you to control load balancing behavior at a lower level. Any clustered object can be assigned a CallRouter. This is a class that is called before each invocation with the parameters of the call. The CallRouter is free to examine the parameters and return the name server to which the call should be routed. For information about creating custom CallRouter classes, see "Appendix A - WebLogic Cluster API".
Optimization for Collocated Objects
Although a replica-aware stub contains the load-balancing logic for a clustered EJB or RMI object, WebLogic Server does not always perform load balancing for an object's method calls. In most cases, it is more efficient to use a replica that is collocated with the stub itself, rather than using a replica that resides on a remote server. The following figure illustrates this
Figure 4-1 Collocation Optimization Overrides Load Balancer Logic for Method Calls
In the above example, a client connects to a servlet hosted by the first WebLogic Server instance in the cluster. In response to client activity, the servlet obtains a replica-aware stub for Object A. Because a replica of Object A is also available on the same server instance, the object is said to be collocated with the client's stub.
WebLogic Server always uses the local, collocated copy of Object A, rather than distributing the client's calls to other replicas of Object A in the cluster. It is more efficient to use the local copy, because doing so avoids the network overhead of establishing peer connections to other servers in the cluster.
This optimization is often overlooked when planning WebLogic Server clusters. The collocation optimization is also frequently confusing for administrators or developers who expect or require load balancing on each method call. If your Web application is deployed to a single cluster, the collocation optimization overrides any load balancing logic inherent in the replica-aware stub.
If you require load balancing on each method call to a clustered object, see Recommended Multi-Tier Architecture for information about how to plan your WebLogic Server cluster accordingly.
As an extension to the basic collocation strategy, WebLogic Server attempts to collocate clustered objects that are enlisted as part of the same transaction. When a client creates a UserTransaction object, WebLogic Server attempts to use object replicas that are collocated with the transaction. This optimization is depicted in the figure below.
Figure 4-2 Collocation Optimization Extends to Other Objects in Transaction
In this example, a client attaches to the first WebLogic Server instance in the cluster and obtains a UserTransaction object. After beginning a new transaction, the client looks up Objects A and B to do the work of the transaction. In this situation WebLogic Server always attempts to use replicas of A and B that reside on the same server as the UserTransaction object, regardless of the load balancing strategies in the stubs for A and B.
This transactional collocation strategy is even more important than the basic optimization described in Optimization for Collocated Objects. If remote replicas of A and B were used, added network overhead would be incurred for the duration of the transaction, because the peer connections for A and B would be locked until the transaction committed. Furthermore, WebLogic Server would need to employ a multi-tiered JDBC connection to commit the transaction, incurring even further network overhead.
By collocating clustered objects in a transactional context, WebLogic Server reduces the network load for accessing the individual objects. The server also can make use of a single-tiered JDBC connection, rather than a multi-tiered connection, to do the work of the transaction.
A system administrator can establish load balancing of JMS destinations across multiple servers in a cluster by configuring multiple JMS servers and using targets to assign them to the defined WebLogic Servers. Each JMS server is deployed on exactly one WebLogic Server and handles requests for a set of destinations. During the configuration phase, the system administrator enables load balancing by specifying targets for JMS servers. For instructions on setting up targets, see Configure Migratable Targets for Pinned Services. For instructions on deploying a JMS server to a migratable target, see Deploying JMS to a Migratable Target Server Instance.
A system administrator can establish cluster-wide, transparent access to destinations from any server in the cluster by configuring multiple connection factories and using targets to assign them to WebLogic Servers. Each connection factory can be deployed on multiple WebLogic Servers. Connection factories are described in more detail in "ConnectionFactory" in Programming WebLogic JMS.
The application uses the Java Naming and Directory Interface (JNDI) to look up a connection factory and create a connection to establish communication with a JMS server. Each JMS server handles requests for a set of destinations. Requests for destinations not handled by a JMS server are forwarded to the appropriate server.
Server Affinity for Distributed JMS Destinations
Server affinity is supported for JMS applications that use the distributed destination feature; this feature is not supported for standalone destinations. If you configure server affinity for JMS connection factories, a server instance that is load balancing consumers or producers across multiple members of a distributed destination will first attempt to load balance across any destination members that are also running on the same server instance.
For detailed information on how the JMS connection factory's Server Affinity Enabled option affects the load balancing preferences for distributed destination members, see "How Distributed Destination Load Balancing Is Affected When Using the Server Affinity Enabled Attribute" in Programming WebLogic JMS.
For instructions to configure server affinity for distributed destinations, see "Tuning Distributed Destinations" in the Administration Guide.
Load Balancing for JDBC Connections
Load balancing of JDBC connection requires the use of a multipool configured for load balancing. Load balancing support is an option you can choose when configuring a multipool.
A load balancing multipool provides the high available behavior described in Failover and JDBC Connections, and in addition, balances the load among the connection pools in the multipool. A multipool has an ordered list of connection pools it contains. If you do not configure the multipool for load balancing, it always attempts to obtain a connection from the first connection pool in the list. In a load-balancing multipool, the connection pools it contains are accessed using a round-robin scheme. In each successive client request for a multipool connection, the list is rotated so the first pool tapped cycles around the list.
For instructions on clustering JDBC objects, see Configure Clustered JDBC.
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