Cluster Selection

When you create a new record and specify the class to which it belongs, OrientDB automatically selects a cluster, where it stores the physical data of the record. There are a number of configuration strategies available for you to use in determining how OrientDB selects the appropriate cluster for the new record.

• default It selects the cluster using the defaultClusterId property from the class. Prior to version 1.7, this was the default method.

• round-robin It arranges the configured clusters for the class into sequence and assigns each new record to the next cluster in order.

• balanced It checks the number of records in the configured clusters for the class and assigns the new record to whichever is the smallest at the time. To avoid latency issues on data insertions, OrientDB calculates cluster size every five seconds or longer.

• local When the database is run in distributed mode, it selects the master cluster on the current node. This helps to avoid conflicts and reduce network latency with remote calls between nodes.

In distributed mode the local cluster strategy is always selected automatically and can't be changed. The local strategy acts as a wrapper for the underlying strategy (round-robin by default) by filtering the allowed clusters by selecting only those the local server is a master.

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Whichever cluster selection strategy works best for your application, you can assign it through the ALTER CLASS...CLUSTERSELECTION command. For example,

orientdb> ALTER CLASS Account CLUSTERSELECTION round-robin

When you run this command, it updates the Account class to use the round-robin selection strategy. It cycles through available clusters, adding new records to each in sequence.

Custom Cluster Selection Strategies

In addition to the cluster selection strategies listed above, you can also develop your own select strategies through the Java API. This ensures that the strategies that are available by default do not meet your particular needs, you can develop one that does.

1. Using your preferred text editor, create the implementation in Java. In order to use a custom strategy, the class must implement the OClusterSelectionStrategy interface.

   package mypackage;
   public class RandomSelectionStrategy implements OClusterSelectionStrategy {
      public int getCluster(final OClass iClass, final ODocument doc) {
         final int[] clusters = iClass.getClusterIds();
   
         // RETURN A RANDOM CLUSTER ID IN THE LIST
         int r = new Random().nextInt(clusters.length);
           return clusters[r];
      }
   
      public String getName(){ return "random"; }
   }
   

   Bear in mind that the method getCluster() also receives the ODocument cluster to insert. You may find this useful, if you want to assign the clusterId variable, based on the Document content.

2. Register the implementation as a service. You can do this by creating a new file under META-INF/services. Use the filename com.orientechnologies.orient.core.metadata.schema.clusterselection.OClusterSelectionStrategy. For its contents, code your class with the full package. For instance,

   mypackage.RandomSelectionStrategy
   

   This adds to the default content in the OrientDB core:

   com.orientechnologies.orient.core.metadata.schema.clusterselection.ORoundRobinClusterSelectionStrategy
   com.orientechnologies.orient.core.metadata.schema.clusterselection.ODefaultClusterSelectionStrategy
   com.orientechnologies.orient.core.metadata.schema.clusterselection.OBalancedClusterSelectionStrategy
   

3. From the database console, assign the new selection strategy to your class with the ALTER CLASS...CLUSTERSELECTION command.

   orientdb> ALTER CLASS Employee CLUSTERSELECTION random
   

The class Employee now selects clusters using random, your custom strategy.