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For this deployment, both nodes should be configured to receive all events. To achieve this, clients can either send all the requests to both the nodes or each request to any one of the two nodes (i.e., using load balancing or failover mechanisms). If clients send all the requests to both nodes, the user has to specify that events are duplicated in the cluster (i.e., the same event comes to all the members of the cluster). Alternatively, if a client sends a request to one node, internally it sends that particular request to the other node as well. This way, even if the clients send requests to only one node, both DAS API-M Analytics nodes receive all the requests.

In this scenario, one DAS API-M Analytics node works in active mode and the other works in passive mode. However, both nodes process all the data.

If the active node fails, the other node becomes active and receives all the requests.

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When the failed node is up again, it fetches all the internal states of the current active node via synching.

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The newly arrived node then becomes the passive node and starts processing all the incoming messages to keep its state synched with the active node so that it can become active if the current active node fails.

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Before you configure a minimum high availability DAS API-M Analytics cluster, the following needs to be carried out.

Download and install WSO2 DAS from here.the WSO2 API-M Analytics distribution. Click DOWNLOAD ANALYTICS in the WSO2 API Manager page.
Take the following steps to install WSO2 APIM Analytics. Because this procedure is identical to installing WSO2 Data Analytics Server (DAS), these steps take you to the DAS documentation for details.
1. Ensure that you have met the Installation Prerequisites.
2. Go to the installation instructions relevant to your operating system:

Follow the steps below to set up MySQL.

Download and install MySQL Server.
Download the MySQL JDBC driver.
Unzip the downloaded MySQL driver zipped archive, and copy the MySQL JDBC driver JAR (mysql-connector-java-x.x.xx-bin.jar) into the <APIM Analytics_HOME>/repository/components/lib directory of all the nodes in the cluster.
Enter the following command in a terminal/command window, where username is the username you want to use to access the databases.
mysql -u username -p
When prompted, specify the password that will be used to access the databases with the username you specified.

Create two databases named userdb and regdb.

Info

title	About using MySQL in different operating systems

For users of Microsoft Windows, when creating the database in MySQL, it is important to specify the character set as latin1. Failure to do this may result in an error (error code: 1709) when starting your cluster. This error occurs in certain versions of MySQL (5.6.x) and is related to the UTF-8 encoding. MySQL originally used the latin1 character set by default, which stored characters in a 2-byte sequence. However, in recent versions, MySQL defaults to UTF-8 to be friendlier to international users. Hence, you must use latin1 as the character set as indicated below in the database creation commands to avoid this problem. Note that this may result in issues with non-latin characters (like Hebrew, Japanese, etc.). The following is how your database creation command should look.

mysql> create database <DATABASE_NAME> character set latin1;

For users of other operating systems, the standard database creation commands will suffice. For these operating systems, the following is how your database creation command should look.

mysql> create database <DATABASE_NAME>;

Execute the following script for the two databases you created in the previous step.
mysql> source <APIM Analytics_HOME>/dbscripts/mysql.sql;

Note
From WSO2 Carbon Kernel 4.4.6 onwards there are two MySQL DB scripts available in the product distribution. Click here to identify as to which version of the MySQL script to use.

Expand

title	Click here to view the commands for performing steps f and g

Code Block

mysql> create database userdb;
mysql> use userdb;
mysql> source <APIM Analytics_HOME>/dbscripts/mysql.sql;
mysql> grant all on userdb.* TO username@localhost identified by "password";
 
 
mysql> create database regdb;
mysql> use regdb;
mysql> source <APIM Analytics_HOME>/dbscripts/mysql.sql;
mysql> grant all on regdb.* TO username@localhost identified by "password";

Create the following databases in MySQL.

WSO2_ANALYTICS_EVENT_STORE_DB
WSO2_ANALYTICS_PROCESSED_DATA_STORE_DB

Info

It is recommended to create the databases with the same names given above because they are the default JNDI names that are included in the <APIM Analytics_HOME>/repository/conf/analytics/analytics-conf.xml file as shown in the extract below. If you change the name, the analytics-conf.xml file should be updated with the changed name.

Code Block

language	xml

<analytics-record-store name="EVENT_STORE">
   <implementation>org.wso2.carbon.analytics.datasource.rdbms.RDBMSAnalyticsRecordStore</implementation>
   <properties>
      <property name="datasource">WSO2_ANALYTICS_EVENT_STORE_DB</property>
      <property name="category">read_write_optimized</property>
   </properties>
</analytics-record-store>
<analytics-record-store name="EVENT_STORE_WO">
   <implementation>org.wso2.carbon.analytics.datasource.rdbms.RDBMSAnalyticsRecordStore</implementation>
   <properties>
      <property name="datasource">WSO2_ANALYTICS_EVENT_STORE_DB</property>
      <property name="category">write_optimized</property>
   </properties>
</analytics-record-store>
<analytics-record-store name="PROCESSED_DATA_STORE">
   <implementation>org.wso2.carbon.analytics.datasource.rdbms.RDBMSAnalyticsRecordStore</implementation>
   <properties>
      <property name="datasource">WSO2_ANALYTICS_PROCESSED_DATA_STORE_DB</property>
      <property name="category">read_write_optimized</property>
   </properties>
</analytics-record-store>

...

Do the following database-related configurations.

Follow the steps below to configure the <APIM Analytics_HOME>/repository/conf/datasources/master-datasources.xml file as required

Enable the all the nodes to access the users database by configuring a datasource to be used by user manager as shown below.

Code Block

language	xml

<datasource>
	<name>WSO2UM_DB</name>
	<description>The datasource used by user manager</description>
	<jndiConfig>
  	<name>jdbc/WSO2UM_DB</name>
	</jndiConfig>
	<definition type="RDBMS">
  	<configuration>
    	<url>jdbc:mysql://[MySQL DB url]:[port]/userdb</url>
    	<username>[user]</username>
    	<password>[password]</password>
    	<driverClassName>com.mysql.jdbc.Driver</driverClassName>
    	<maxActive>50</maxActive>
    	<maxWait>60000</maxWait>
    	<testOnBorrow>true</testOnBorrow>
    	<validationQuery>SELECT 1</validationQuery>
    	<validationInterval>30000</validationInterval>
  	</configuration>
	</definition>
</datasource>

Enable the nodes to access the registry database by configuring the WSO2REG_DB data source as follows.

Code Block

language	xml

<datasource>
	<name>WSO2REG_DB</name>
	<description>The datasource used by the registry</description>
	<jndiConfig>
  	<name>jdbc/WSO2REG_DB</name>
	</jndiConfig>
	<definition type="RDBMS">
  	<configuration>
    	<url>jdbc:mysql://[MySQL DB url]:[port]/regdb</url>
    	<username>[user]</username>
    	<password>[password]</password>
    	<driverClassName>com.mysql.jdbc.Driver</driverClassName>
    	<maxActive>50</maxActive>
    	<maxWait>60000</maxWait>
    	<testOnBorrow>true</testOnBorrow>
    	<validationQuery>SELECT 1</validationQuery>
    	<validationInterval>30000</validationInterval>
  	</configuration>
	</definition>
</datasource>

For detailed information about registry sharing strategies, see the library article Sharing Registry Space across Multiple Product Instances.

Point to WSO2_ANALYTICS_EVENT_STORE_DB and WSO2_ANALYTICS_PROCESSED_DATA_STORE_DB in the <APIM Analytics_HOME>/repository/conf/datasources/analytics-datasources.xml file as shown below.

Code Block

language	xml

<datasources-configuration>
    <providers>
        <provider>org.wso2.carbon.ndatasource.rdbms.RDBMSDataSourceReader</provider>
    </providers>

    <datasources>
        <datasource>
            <name>WSO2_ANALYTICS_EVENT_STORE_DB</name>
            <description>The datasource used for analytics record store</description>
            <definition type="RDBMS">
                <configuration>
                    <url>jdbc:mysql://[MySQL DB url]:[port]/WSO2_ANALYTICS_EVENT_STORE_DB</url>
                    <username>[username]</username>
                    <password>[password]</password>
                    <driverClassName>com.mysql.jdbc.Driver</driverClassName>
                    <maxActive>50</maxActive>
                    <maxWait>60000</maxWait>
                    <testOnBorrow>true</testOnBorrow>
                    <validationQuery>SELECT 1</validationQuery>
                    <validationInterval>30000</validationInterval>
                    <defaultAutoCommit>false</defaultAutoCommit>
                </configuration>
            </definition>
        </datasource>
        <datasource>
            <name>WSO2_ANALYTICS_PROCESSED_DATA_STORE_DB</name>
            <description>The datasource used for analytics record store</description>
            <definition type="RDBMS">
                <configuration>
                    <url>jdbc:mysql://[MySQL DB url]:[port]/WSO2_ANALYTICS_PROCESSED_DATA_STORE_DB</url>
                    <username>[username]</username>
                    <password>[password]</password>
                    <driverClassName>com.mysql.jdbc.Driver</driverClassName>
                    <maxActive>50</maxActive>
                    <maxWait>60000</maxWait>
                    <testOnBorrow>true</testOnBorrow>
                    <validationQuery>SELECT 1</validationQuery>
                    <validationInterval>30000</validationInterval>
                    <defaultAutoCommit>false</defaultAutoCommit>
                </configuration>
            </definition>
        </datasource>
    </datasources>
</datasources-configuration>

For more information, see Datasources in DAS documentation.

To share the user store among the nodes, open the <APIM Analytics_HOME>/repository/conf/user-mgt.xmlfile and modify the dataSource property of the <configuration> element as follows.
Code Block
language xml
<configuration> ... <Property name="dataSource">jdbc/WSO2UM_DB</Property> </configuration>
Info
The datasource name specified in this configuration should be the same as the datasource used by user manager that you configured in sub step a, i.

In the <APIM Analytics_HOME>/repository/conf/registry.xml file, add or modify the dataSource attribute of the <dbConfig name="govregistry"> element as follows.

Code Block

language	xml

<dbConfig name="govregistry">
	<dataSource>jdbc/WSO2REG_DB</dataSource>
</dbConfig>
<remoteInstance url="https://localhost:9443/registry"> 
	<id>gov</id>
	<cacheId>user@jdbc:mysql://localhost:3306/regdb</cacheId>
	<dbConfig>govregistry</dbConfig>
	<readOnly>false</readOnly>
	<enableCache>true</enableCache>
	<registryRoot>/</registryRoot>
</remoteInstance>
<mount path="/_system/governance" overwrite="true">
	<instanceId>gov</instanceId>
	<targetPath>/_system/governance</targetPath>
</mount>
<mount path="/_system/config" overwrite="true">
	<instanceId>gov</instanceId>
	<targetPath>/_system/config</targetPath>
</mount>

Note

Do not replace the following configuration when adding in the mounting configurations. The registry mounting configurations mentioned in the above steps should be added in addition to the following.

Code Block

language	xml

<dbConfig name="wso2registry">
    <dataSource>jdbc/WSO2CarbonDB</dataSource>
</dbConfig>

Update the <APIM Analytics_HOME>/repository/conf/axis2/axis2.xml file as follows to enable Hazlecast clustering for both nodes.

Set clustering class="org.wso2.carbon.core.clustering.hazelcast.HazelcastClusteringAgent" to true as shown below to enable Hazlecast clustering.
Code Block
language xml
<clustering class="org.wso2.carbon.core.clustering.hazelcast.HazelcastClusteringAgent" enable="true">
Enable wka mode on both nodes as shown below. See For more information on wka mode, see About Membership Schemes for more information on wka mode.
Code Block
language xml
<parameter name="membershipScheme">wka</parameter>

Add both the DAS nodes nodes as well known members in the cluster under the members tag in each node as shown in the example below.

Code Block

language	xml

<members>
    <member>
        <hostName>[node1 IP]</hostName>
        <port>[node1 port]</port>
    </member>
    <member>
        <hostName>[node2 IP]</hostName>
        <port>[node2 port]</port>
    </member>
</members>

For each node, enter the respective server IP address as the value for the localMemberHost property as shown below.
Code Block
language xml
<parameter name="localMemberHost">[Server_IP_Address]</parameter>

Expand

title	Click here to view the complete clustering section of the axis2.xml file. with the changes mentioned above.

Code Block

language	xml

    <clustering class="org.wso2.carbon.core.clustering.hazelcast.HazelcastClusteringAgent"
                enable="true">

        <!--
           This parameter indicates whether the cluster has to be automatically initalized
           when the AxisConfiguration is built. If set to "true" the initialization will not be
           done at that stage, and some other party will have to explictly initialize the cluster.
        -->
        <parameter name="AvoidInitiation">true</parameter>

        <!--
           The membership scheme used in this setup. The only values supported at the moment are
           "multicast" and "wka"

           1. multicast - membership is automatically discovered using multicasting
           2. wka - Well-Known Address based multicasting. Membership is discovered with the help
                    of one or more nodes running at a Well-Known Address. New members joining a
                    cluster will first connect to a well-known node, register with the well-known node
                    and get the membership list from it. When new members join, one of the well-known
                    nodes will notify the others in the group. When a member leaves the cluster or
                    is deemed to have left the cluster, it will be detected by the Group Membership
                    Service (GMS) using a TCP ping mechanism.
        -->
        
        <parameter name="membershipScheme">wka</parameter>

        <!--<parameter name="licenseKey">xxx</parameter>-->
        <!--<parameter name="mgtCenterURL">http://localhost:8081/mancenter/</parameter>-->

        <!--
         The clustering domain/group. Nodes in the same group will belong to the same multicast
         domain. There will not be interference between nodes in different groups.
        -->
        <parameter name="domain">wso2.carbon.domain</parameter>

        <!-- The multicast address to be used -->
        <!--<parameter name="mcastAddress">228.0.0.4</parameter>-->

        <!-- The multicast port to be used -->
        <parameter name="mcastPort">45564</parameter>

        <parameter name="mcastTTL">100</parameter>

        <parameter name="mcastTimeout">60</parameter>

        <!--
           The IP address of the network interface to which the multicasting has to be bound to.
           Multicasting would be done using this interface.
        -->
        <!--
            <parameter name="mcastBindAddress">10.100.5.109</parameter>
        -->
        <!-- The host name or IP address of this member -->

        <parameter name="localMemberHost">[node IP]</parameter>

        <!--
            The bind adress of this member. The difference between localMemberHost & localMemberBindAddress
            is that localMemberHost is the one that is advertised by this member, while localMemberBindAddress
            is the address to which this member is bound to.
        -->
        <!--
        <parameter name="localMemberBindAddress">[node IP]</parameter>
        -->

        <!--
        The TCP port used by this member. This is the port through which other nodes will
        contact this member
         -->
        <parameter name="localMemberPort">[node port]</parameter>

        <!--
            The bind port of this member. The difference between localMemberPort & localMemberBindPort
            is that localMemberPort is the one that is advertised by this member, while localMemberBindPort
            is the port to which this member is bound to.
        -->
        <!--
        <parameter name="localMemberBindPort">4001</parameter>
        -->

        <!--
        Properties specific to this member
        -->
        <parameter name="properties">
            <property name="backendServerURL" value="https://${hostName}:${httpsPort}/services/"/>
            <property name="mgtConsoleURL" value="https://${hostName}:${httpsPort}/"/>
            <property name="subDomain" value="worker"/>
        </parameter>

        <!--
        Uncomment the following section to load custom Hazelcast data serializers.
        -->
        <!--
        <parameter name="hazelcastSerializers">
            <serializer typeClass="java.util.TreeSet">org.wso2.carbon.hazelcast.serializer.TreeSetSerializer
            </serializer>
            <serializer typeClass="java.util.Map">org.wso2.carbon.hazelcast.serializer.MapSerializer</serializer>
        </parameter>
        -->

        <!--
           The list of static or well-known members. These entries will only be valid if the
           "membershipScheme" above is set to "wka"
        -->
        <members>
            <member>
                <hostName>[node1 IP]</hostName>
                <port>[node1 port]</port>
            </member>
            <member>
                <hostName>[node2 IP]</hostName>
                <port>[node2 port]</port>
            </member>
        </members>

        <!--
        Enable the groupManagement entry if you need to run this node as a cluster manager.
        Multiple application domains with different GroupManagementAgent implementations
        can be defined in this section.
        -->
        <groupManagement enable="false">
            <applicationDomain name="wso2.as.domain"
                               description="AS group"
                               agent="org.wso2.carbon.core.clustering.hazelcast.HazelcastGroupManagementAgent"
                               subDomain="worker"
                               port="2222"/>
        </groupManagement>
    </clustering>

Configure the <APIM Analytics_HOME>/repository/conf/event-processor.xml file as follows to cluster DAS API-M Analytics in the Receiver.

Anchor

	EventProcessor
	EventProcessor

Enable the HA mode by setting the following property.
Code Block
language xml
<mode name="HA" enable="true">
Disable the Distributed mode by setting the following property.
Code Block
language xml
<mode name="Distributed" enable="false">

For each node, enter the respective server IP address under the HA mode Config section as shown in the example below.

Info

When you enable the HA mode for WSO2 DASWSO2 API-M Analytics, the following are enabled by default:

State persistence: If there is no real time use case that requires any state information after starting the cluster, you should disable event persistence by setting the persistence attribute to false in the <APIM Analytics_HOME>/repository/conf/event-processor.xml file as shown below.

Code Block

language	xml

<persistence enable="false">
    <persistenceIntervalInMinutes>15</persistenceIntervalInMinutes>
    <persisterSchedulerPoolSize>10</persisterSchedulerPoolSize>
    <persister class="org.wso2.carbon.event.processor.core.internal.persistence.FileSystemPersistenceStore">
        <property key="persistenceLocation">cep_persistence</property>
    </persister>
</persistence>

Tip

When state persistence is enabled for WSO2 DASAPI-M Analytics, the internal state of DAS API-M Analytics is persisted in files. These files are not automatically deleted. Therefore, if you want to save space in your DAS API-M Analytics pack, you need to delete them manually.

These files are created in the <APIM Analytics_HOME>/cep_persistence/<tenant-id> directory. This directory has a separate sub-directory for each execution plan. Each execution plan can have multiple files. The format of each file name is <TIMESTAMP>_<EXECUTION_PLAN_NAME> (e.g, 1493101044948_MyExecutionPlan). If you want to clear files for a specific execution plan, you need to leave the two files with the latest timestamps and delete the rest.

Event synchronization: However, if you set the event.duplicated.in.cluster=true property for an event receiver configured in a node, DAS API-M Analytics does not perform event synchronization for that receiver.

Code Block

language	xml

    <!-- HA Mode Config -->
    <mode name="HA" enable="true">
       ...
        <eventSync>
            <hostName>[Server_IP_Address]</hostName>

Expand

title	Click here to view the complete event-processor.xml file with the changes mentioned above.

Code Block

language	xml

<eventProcessorConfiguration>
    <mode name="SingleNode" enable="false">
        <persistence enable="false">
            <persistenceIntervalInMinutes>15</persistenceIntervalInMinutes>
            <persisterSchedulerPoolSize>10</persisterSchedulerPoolSize>
            <persister class="org.wso2.carbon.event.processor.core.internal.persistence.FileSystemPersistenceStore">
                <property key="persistenceLocation">cep_persistence</property>
            </persister>
        </persistence>
    </mode>

    <!-- HA Mode Config -->
    <mode name="HA" enable="true">
        <nodeType>
            <worker enable="true"/>
            <presenter enable="false"/>
        </nodeType>
        <checkMemberUpdateInterval>10000</checkMemberUpdateInterval>
        <eventSync>
            <hostName>172.18.1.217</hostName>
            <port>11224</port>
            <reconnectionInterval>20000</reconnectionInterval>
            <serverThreads>20000</serverThreads>
            <!--Size of TCP event publishing client's send buffer in bytes-->
            <publisherTcpSendBufferSize>5242880</publisherTcpSendBufferSize>
            <!--Character encoding of TCP event publishing client-->
            <publisherCharSet>UTF-8</publisherCharSet>
            <publisherBufferSize>1024</publisherBufferSize>
            <publisherConnectionStatusCheckInterval>30000</publisherConnectionStatusCheckInterval>
            <!--Number of events that could be queued at receiver before they are synced between CEP/DAS nodes-->
            <receiverQueueSize>1000000</receiverQueueSize>
            <!--Max total size of events that could be queued at receiver before they are synced between CEP/DAS nodes-->
            <receiverQueueMaxSizeMb>10</receiverQueueMaxSizeMb>
            <!--Number of events that could be queued at publisher to sync output between CEP/DAS nodes-->
            <publisherQueueSize>1000000</publisherQueueSize>
            <!--Max total size of events that could be queued at publisher to sync output between CEP/DAS nodes-->
            <publisherQueueMaxSizeMb>10</publisherQueueMaxSizeMb>
        </eventSync>
        <management>
            <hostName>172.18.1.217</hostName>
            <port>10005</port>
            <tryStateChangeInterval>15000</tryStateChangeInterval>
            <stateSyncRetryInterval>10000</stateSyncRetryInterval>
        </management>
        <presentation>
            <hostName>0.0.0.0</hostName>
            <port>11000</port>
            <!--Size of TCP event publishing client's send buffer in bytes-->
            <publisherTcpSendBufferSize>5242880</publisherTcpSendBufferSize>
            <!--Character encoding of TCP event publishing client-->
            <publisherCharSet>UTF-8</publisherCharSet>
            <publisherBufferSize>1024</publisherBufferSize>
            <publisherConnectionStatusCheckInterval>30000</publisherConnectionStatusCheckInterval>
        </presentation>
    </mode>

    <!-- Distributed Mode Config -->
    <mode name="Distributed" enable="false">
        <nodeType>
            <worker enable="true"/>
            <manager enable="true">
                <hostName>0.0.0.0</hostName>
                <port>8904</port>
            </manager>
            <presenter enable="false">
                <hostName>0.0.0.0</hostName>
                <port>11000</port>
            </presenter>
        </nodeType>
        <management>
            <managers>
                <manager>
                    <hostName>localhost</hostName>
                    <port>8904</port>
                </manager>
                <manager>
                    <hostName>localhost</hostName>
                    <port>8905</port>
                </manager>
            </managers>
            <!--Connection re-try interval to connect to Storm Manager service in case of a connection failure-->
            <reconnectionInterval>20000</reconnectionInterval>
            <!--Heart beat interval (in ms) for event listeners in "Storm Receivers" and "CEP Publishers" to acknowledge their
            availability for receiving events"-->
            <heartbeatInterval>5000</heartbeatInterval>
            <!--Storm topology re-submit interval in case of a topology submission failure-->
            <topologyResubmitInterval>10000</topologyResubmitInterval>
        </management>
        <transport>
            <!--Port range to be used for events listener servers in "Storm Receiver Spouts" and "CEP Publishers"-->
            <portRange>
                <min>15000</min>
                <max>15100</max>
            </portRange>
            <!--Connection re-try interval (in ms) for connection failures between "CEP Receiver" to "Storm Receiver" connections
            and "Storm Publisher" to "CEP Publisher" connections-->
            <reconnectionInterval>20000</reconnectionInterval>
            <!--Size of the output queue of each "CEP Receiver" which stores events to be published into "Storm Receivers" .
            This must be a power of two-->
            <cepReceiverOutputQueueSize>8192</cepReceiverOutputQueueSize>
            <!--Size of the output queue of each "Storm Publisher" which stores events to be published into "CEP Publisher" .
            This must be a power of two-->
            <stormPublisherOutputQueueSize>8192</stormPublisherOutputQueueSize>
            <!--Size of TCP event publishing client's send buffer in bytes-->
            <tcpEventPublisherSendBufferSize>5242880</tcpEventPublisherSendBufferSize>
            <!--Character encoding of TCP event publishing client-->
            <tcpEventPublisherCharSet>UTF-8</tcpEventPublisherCharSet>
            <!--Size of the event queue in each storm spout which stores events to be processed by storm bolts -->
            <stormSpoutBufferSize>10000</stormSpoutBufferSize>
            <connectionStatusCheckInterval>20000</connectionStatusCheckInterval>
        </transport>
        <presentation>
            <presentationOutputQueueSize>1024</presentationOutputQueueSize>
            <!--Size of TCP event publishing client's send buffer in bytes-->
            <tcpEventPublisherSendBufferSize>5242880</tcpEventPublisherSendBufferSize>
            <!--Character encoding of TCP event publishing client-->
            <tcpEventPublisherCharSet>UTF-8</tcpEventPublisherCharSet>
            <connectionStatusCheckInterval>20000</connectionStatusCheckInterval>
        </presentation>
        <statusMonitor>
            <lockTimeout>60000</lockTimeout>
            <updateRate>60000</updateRate>
        </statusMonitor>
        <stormJar>org.wso2.cep.storm.dependencies.jar</stormJar>
        <distributedUIUrl></distributedUIUrl>
        <memberUpdateCheckInterval>20000</memberUpdateCheckInterval>
    </mode>
</eventProcessorConfiguration>

Info

The following node types are configured for the HA deployment mode in the <APIM Analytics_HOME>/repository/conf/event-processor.xml file.

eventSync: Both the active and the passive nodes in this setup are event synchronizing nodes as explained in the introduction. Therefore, each node should have the host and the port on which it is operating specified under the <eventSync> element.
Info
Note that the eventSync port is not automatically updated to the port in which each node operates via port offset.
management: In this setup, both the nodes carry out the same tasks, and therefore, both nodes are considered manager nodes. Therefore, each node should have the host and the port on which it is operating specified under the <management> element.
Info
Note that the management port is not automatically updated to the port in which each node operates via port offset.
presentation: You can optionally specify only one of the two nodes in this setup as the presenter node. The dashboards in which processed information is displayed are configured only in the presenter node. Each node should have the host and the port on which the assigned presenter node is operating specified under the <presentation> element. The host and the port as well as the other configurations under the <presentation> element are effective only when the presenter enable="false property is set under the  section.

Update the <APIM Analytics_HOME>/repository/conf/analytics/spark/spark-defaults.conf file as follows to use the Spark cluster embedded within DASAPI-M Analytics.

Keep the carbon.spark.master configuration as local. This instructs Spark to create a Spark cluster using the Hazelcast cluster.
Enter 2 as the value for the carbon.spark.master.count configuration. This specifies that there should be two masters in the Spark cluster. One master serves as an active master and the other serves as a stand-by master.

The following example shows the <APIM Analytics_HOME>/repository/conf/analytics/spark/spark-defaults.conf file with changes mentioned above.

Code Block
carbon.spark.master local carbon.spark.master.count 2

For more information, see Spark Configurations in DAS documentation.

Warning

Important: If the path to <APIM Analytics_HOME> is different in the two nodes, please do the following.

Localtabgroup

Localtab

active	true
title	UNIX environment

Create a symbolic link to <APIM Analytics_HOME> in both nodes, where paths of those symbolic links are identical. This ensures that if we use the symbolic link to access the DAS serverAPI-M Analytics, we can use a common path. To do this, set the following property in the
<APIM Analytics_HOME>/repository/conf/analytics/spark/spark-defaults.conf file.

carbon.das.symbolic.link /home/ubuntu/das/das_symlink/

Localtab

title	Windows environment

In the Windows environment there is a strict requirement to have both DAS API-M Analytics distributions in a common path.

In order to share the C-Apps deployed among the nodes, configure the SVN-based deployment synchronizer. For detailed instructions, see Configuring SVN-Based Deployment Synchronizer.

Tip
DAS API-M Analytics Minimum High availability Deployment set up does not use a manager and a worker. For the purpose of configuring the deployment synchronizer, you can add the configurations relevant to the manager for the node of your choice, and add the configurations relating to the worker for the other node.

Info
If you do not configure the deployment synchronizer, you are required to deploy any C-App you use in the DAS API-M Analytics Minimum High Availability Deployment set up to both the nodes.

If the physical DAS API-M Analytics server has multiple network interfaces with different IPs, and if you want Spark to use a specific Interface IP, open either the <APIM Analytics_HOME>/bin/load-spark-env-vars.sh file (for Linux) or <APIM Analytics_HOME>/bin/load-spark-env-vars.bat file (for Windows), and add the following parameter to configure the Spark IP address.
Code Block
export SPARK_LOCAL_IP=<IP_Address>
Note that if you are deploying in an environment where file systems do not get persisted automatically, it's required to persist and share some directories under <APIM_ANALYTICS_HOME> directory. Please see APIM Analytics section in the Common Runtime and Configuration Artifacts page.

Starting the cluster

Once you complete the configurations mentioned above, start the two DAS API-M Analytics nodes. If the cluster is successfully configured, the following CLI logs are generated.

...

Access the Spark UIs of the active master and the stand-by master using < node ip>:8081 in each node.
- Information relating to the active master is displayed as shown in the example below.
- Information relating to the stand-by master is displayed as shown in the example below.
Click the links under Running Applications in the Spark UI of the active master to check the Spark application UIs of those applications. A working application is displayed as shown in the following example.
Click the Environment tab of a Spark application UI to check whether all the configuration parameters are correctly set. You can also check whether the class path variables in this tab can be accessed manually.
Check the Spark UIs of workers to check whether they have running executors. If a worker UI does not have running executors or if it is continuously creating executors, it indicates an issue in the Spark cluster configuration. The following example shows a worker UI with a running executor.
Check the symbolic parameter, and check if you could manually access it via a cd <directory> command in the CLI.
Log into the DAS API-M Analytics Management Console and navigate to Main => Manage => Batch Analytics => Console to open the Interactive Analytics Console. Run a query in this console.

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Starting the cluster