This part of the documentation website is obsolete. Please see the new Solution Hub.

Distributed Mirror

Author XAP Version Last Updated Reference Download
Shay Hassidim 12.0 March 2017 Asynchronous Persistence Example


By default a single mirror instance used to perform write-behind activity, persisting data from the space to the enterprise backend database. For most systems this will provide sufficient throughput to address the activity a single clustered space generating. There are cases with large space clusters or with systems that produce large volume of activity where the amount of activity performed by a clustered space would require a distributed (multi-instance) mirror setup. The solution described here allows each partition (primary and backup instances) to perform write-behind activity via a dedicated mirror. This forms an architecture where each partition using a separate mirror instance that may run on a different machine, utilizing its full CPU and network bandwidth. This approach reducing the potential for redolog accumulation generating a lag between the space data state and the persistency backend state as a result of a single mirror.


With the example below we will run a partitioned space (2 partitions) and 2 mirror instances, both writing into a single database.


The Example

Download the example and extract its contents into an empty folder. You will find 3 zip files:

  • – A Mirror PU configured to support multiple mirror instances
  • - A Space PU configured to support multiple mirror instances
  • – A PU writing objects into the space

Start the Database and its UI


java -cp hsqldb-2.3.2.jar org.hsqldb.Server -database.0 file:testDB -dbname.0 testDB

Run SQLDB Manager:

java -cp hsqldb-2.3.2.jar org.hsqldb.util.DatabaseManager

Connect to the database:


You can find the hsqldb-2.3.2.jar within the lib folder.

Start Agent

Start an agent with 7 GSCs. This will allow the GSM to deploy each instance into a dedicated GSC. It will allow you to track the activity easily by monitoring the GSC log file each PU instance using.

gs-agent gsa.gsc 7

Deploying Multiple Mirror Instances

To scale the mirror activity deploy multiple mirror instances , one per partition. You should deploy each separately. Each can use the same PU library with different mirror-service_id value – see below example:

gs deploy -properties embed://mirror-service_id=1 -override-name mirror1

gs deploy -properties embed://mirror-service_id=2 -override-name mirror2

You can create a script that will loop and deploy multiple mirror instances each with its own unique ID.

Deploying the Space

To deploy the space:

gs deploy -cluster schema=partitioned total_members=2,1 -override-name space

Deploying the Feeder

Deploy the feeder via the following:

gs deploy

This will write objects into the space. The mirrors will persist these into the database.

View the Space and the Mirrors Status

Start the GS-Web UI. You should see the space and the different mirror instances:


Or you can start the Management console and view the space and the different mirror instances:



You may access the database and check the amount of rows inserted – this should match the amount of objects within the space:


Space pu.xml configuration

The cluster-config.mirror-service.url should include the ${clusterInfo.instanceId} as demonstrated below:

<os-core:space id="space" url="/./space" mirror="true" >
                <prop key="cluster-config.mirror-service.url">jini://*/mirror-service${clusterInfo.instanceId}_container/mirror-service${clusterInfo.instanceId}</prop>

Mirror pu.xml configuration

The url mirror bean property should include the mirror service id together with the mirror name as demonstrated below:

<os-core:mirror id="mirror" url="/./mirror-service${mirror-service_id}" space-sync-endpoint="hibernateSpaceSynchronizationEndpoint" operation-grouping="group-by-space-transaction">
        <os-core:source-space name="space" partitions="2" backups="1"/>


  • Distributed transactions are not supported. Local transactions are supported.