In general, when a secondary server fails, there is no effect on Oracle Stream Analytics application operation as Figure 17-3 shows. Regardless of the quality of service you choose, there are no missed or duplicate events.

When a primary server fails, as Figure 17-4 shows, Oracle Stream Analytics performs a failover that can cause missed or duplicate events, depending on the quality of service you choose.

During failover, Oracle Stream Analytics selects a new primary and the new primary transitions from the SECONDARY state to the BECOMING_PRIMARY state. Depending on the quality of service you choose, the new primary does not transition to PRIMARY state until a configurable readiness threshold is met. For details, see the specific quality of service option in Choose a Quality of Service Option.

When a new Oracle Stream Analytics server is added to an Oracle Stream Analytics high availability multiserver domain or an existing failed server restarts, the server does not fully join the Oracle Stream Analytics high availability deployment and notification groups until all applications deployed to it have fully joined. The type of application determines when it can fully join.

If the application must generate exactly the same sequence of output events as existing secondaries (a Type 1 application), then it must be able to rebuild its internal state by processing input streams for some finite period of time (the warm-up-window-length period). This warm-up-window-length time determines the minimum time it takes for the application to fully join the Oracle Stream Analytics high availability deployment and notification groups.

If the application does not need to generate exactly the same sequence of output events as existing secondaries (a Type 2 application), then it does not require a warm-up-window-length time and fully joins the Oracle Stream Analytics high availability deployment and notification groups when it deploys.

For more information, see Choose an Adequate warm-up-window-length Time.

Each event is associated with a point in time at which the event occurred. There are two different approaches to generating event timestamps: application timestamps and system timestamps (see Channels for information about application and system time stamps). Application time means that a time value is assigned to each event externally by the application before the event enters a CQL processor. System time means that a time value is associated with an event automatically by Oracle Stream Analytics when it arrives at a CQL processor.

Application time is generally the best approach for applications that need to be highly available. The application time is associated with an event before the event is sent to Oracle Stream Analytics, so it is consistent across active primary and secondary instances. System time can cause application instances to generate different results because the time value associated with an event can be different on each instance due to system clocks not being synchronized.

Using system time is not a problem for applications whose CQL queries do not use time-based windows. Applications that use only event-based windows depend only on the arrival order of events rather than the arrival time, so system time can be used in this case.

For applications that use time-based windows and do not have externally generated (application) time stamps, the optional Oracle Stream Analytics high availability input adapter can be used to provide a consistent time value across all servers. The input adapter instance on the primary server assigns a time (in nanoseconds) to events as they arrive at the adapter and forwards the time values assigned for each event to all secondary servers.

Because a time value is assigned to each event before the event reaches any downstream channels in the EPN, downstream channels should be configured to use application time so that they do not assign a new time value to events as they arrive at the channel.

Input events must have a key that uniquely identifies each event in order to use this adapter.

You can configure the Oracle Stream Analytics high availability input adapter to send heartbeat events.

The Oracle Stream Analytics high availability input adapter is applicable to all high availability quality of service options. However, because the high availability input adapter increases performance overhead, it is not appropriate for some high availability quality of service options (such as Simple Failover and Simple Failover with Buffering). For these options, you should instead consider using application time with some incoming event property.

For more information, see:

• Light-Weight Queue Trimming

• Precise Recovery with JMS

• Configure the High Availability Input Adapter.

The Oracle Stream Analytics high availability buffering output adapter implements a buffered queue trimming strategy. The buffer is a sliding window of output events from the stream. The size of the window is measured in milliseconds.

The Oracle Stream Analytics high availability buffering output adapter applies to simple failover, and simple failover with buffering high availability quality of service options.

For more information, see:

• Simple Failover

• Simple Failover with Buffering

• Configure the Buffering Output Adapter.

The Oracle Stream Analytics high availability broadcast output adapter implements a distributed queue trimming strategy. The active primary instance broadcasts messages to the active secondary instances in the notification group telling them when to trim their local representation of the queue.

The Oracle Stream Analytics high availability broadcast output adapter applies to the light-weight queue trimming high availability quality of service option.

For more information, see:

• Light-Weight Queue Trimming

• Configure the Broadcast Output Adapter.

The Oracle Stream Analytics high availability correlating output adapter correlates two event streams, usually from JMS. This adapter correlates an inbound buffer of events with a second source of the same event stream, outputting the buffer if correlation fails after a configurable time interval. Correlated events are trimmed from the queue. Correlated events are assumed to be in-order.

The Oracle Stream Analytics high availability correlating output adapter applies to precise recovery with JMS high availability quality of service option.

For more information, see:

• Precise Recovery with JMS

• Configure the Correlating Output Adapter.

The simple failover high availability quality of service is characterized by the lowest performance overhead (fastest recovery time) and the least data integrity (both missed events and duplicate events are possible during failover).

The primary server outputs events and secondary servers discard their output events because they do not buffer output events. If the current active primary fails, a new active primary is chosen and begins sending output events once it is notified.

During failover, many events can be missed or duplicated by the new primary depending on whether it is running ahead of or behind the old primary, respectively.

During the failover window, events can be missed. For example, if you process 100 events per second and failover takes 10 seconds, then you miss 1000 events

The new primary server enters the PRIMARY state immediately. There is no configurable readiness threshold that must be met before the new primary server transitions out of the BECOMING_PRIMARY state. When an Oracle Event Processing server rejoins the multiserver domain, it is immediately available as a secondary.

To implement this high availability quality of service, you configure your EPN with a high availability buffering output adapter (with a sliding window of size zero) before each output adapter. To reduce performance overhead, rather than use a high availability input adapter, use application time with some incoming event property.

For more information, see Configure a Simple Failover.

The simple failover with buffering high availability quality of service is characterized by a low performance overhead (faster recovery time) and increased data integrity (no missed events but many duplicate events are possible during failover).

The primary server outputs events and the secondary servers buffer their output events. If the current active primary fails, a new active primary is chosen and begins sending output events once it is notified.

During the failover window, events might be missed. For example, if you are processing 100 events per second and failover takes 10 seconds, then you miss 1000 events. If the secondary buffers are large, a significant number of duplicates can be output. On the other hand, a larger buffer reduces the chances of missed messages.

When an Oracle Stream Analytics server rejoins the multiserver domain, if your application is an Oracle Stream Analytics high availability Type 1 application (the application must generate exactly the same sequence of output events as existing secondaries), then it must wait the warm-up-window-length time you configure for the Oracle Stream Analytics high availability output adapter before it is available as a secondary.

To implement this high availability quality of service, you configure your EPN with a high availability buffering output adapter with a sliding window of size greater than zero before each output adapter. To reduce performance overhead, rather than use a high availability input adapter, use application time with some incoming event property.

For more information, see:

• Choose an Adequate warm-up-window-length Time

• Configure Simple Failover With Buffering.

This high availability quality of service is characterized by a low performance overhead (faster recovery time) and increased data integrity (no missed events but a few duplicate events are possible during failover).

The active primary communicates to the secondaries the events that it has actually processed. This enables the secondaries to trim their buffer of output events so that it contains only those events that have not been sent by the primary at a particular point in time. Because events are only trimmed after they have been sent by the current primary, this allows the secondary to avoid missing any output events when there is a failover.

The frequency with which the active primary sends queue trimming messages to active secondaries is configurable:

• Every n events (n>0)

  This limits the number of duplicate output events to at most n events at failover.

• Every n milliseconds (n>0)

The queue trimming adapter requires a way to identify events consistently among the active primary and secondaries. The recommended approach is to use application time to identify events, but any key value that uniquely identifies events works.

The advantage of queue trimming is that output events are never lost. There is a slight performance overhead at the active primary, however, for sending the trimming messages that need to be communicated. This overhead increases as the frequency of queue trimming messages increases.

During failover, the new primary enters the BECOMING_PRIMARY state and does not transition into the PRIMARY state until its event queue (that it was accumulating as a secondary) has been flushed. During this transition, new input events are buffered and some duplicate events can be output.

When an Oracle Stream Analytics server rejoins the multiserver domain, if your application is an Oracle Stream Analytics high availability Type 1 application (an application that must generate exactly the same sequence of output events as existing secondaries), then it must wait the warm-up-window-length time you configure for the Oracle Stream Analytics high availability output adapter before it is available as a secondary.

To implement this high availability quality of service, you configure your EPN with a high availability input adapter after each input adapter and a high availability broadcast output adapter before each output adapter.

For more information, see Configure Light-Weight Queue Trimming.

The precise recovery with JMS high availability quality of service is characterized by a high performance overhead (slower recovery time) and maximum data integrity (no missed events and no duplicate events during failover). This high availability quality of service is compatible with only JMS input and output adapters.

In the precise recovery with JMS high availability quality of service, the focus is not on transactional guarantees along the event path for a single-server, but on guaranteeing a single output from a set of servers. To achieve guarantee, secondary servers listen over JMS to the event stream being published by the primary. As Figure 17-7 shows, this incoming event stream is a source of reliable queue-trimming messages that the secondaries use to trim their output queues. If JMS is configured for reliable delivery, we can be sure that the stream of events seen by the secondary is precisely the stream of events output by the primary and so failover allows the new primary server to output precisely those events not delivered by the old primary server.

During failover, the new primary server enters the BECOMING_PRIMARY state and does not transition into the PRIMARY state in its event queue (that was accumulating as a secondary) has been flushed. During this transition, new input events are buffered and no duplicate events are output.

When an Oracle Stream Analytics server rejoins the multiserver domain, if your application is an Oracle Stream Analytics high availability Type 1 application (the application must generate exactly the same sequence of output events as existing secondaries), it must wait the warm-up-window-length time you configure for the Oracle Stream Analytics high availability output adapter before it is available as a secondary server.

To implement the precise recovery with JMS high availability quality of service, you configure your EPN with a high availability input adapter after each input adapter and a high availability correlating output adapter before each output adapter.

To increase scalability, you can also use the cluster groups bean with high availability quality of service.

For more information, see:

• Configure Precise Recovery With JMS

• Partition an Incoming JMS Event Stream.

You can adapt high availability options to various Oracle Stream Analytics application designs but in general, Oracle Stream Analytics high availability is designed for the following use case:

• An application receives input events from one or more external systems.

• The external systems are publish-subscribe style systems that allow multiple instances of the application to connect simultaneously and receive the same stream of messages.

• The application does not update any external systems in a way that would cause conflicts when multiple copies of the application run concurrently.

• The application sends output events to an external downstream system. Multiple instances of the application can connect to the downstream system simultaneously, although only one instance of the application can send messages at any one time.

Within these constraints, the following different cases are of interest:

• The application is allowed to skip sending some output events to the downstream system when there is a failure. Duplicates are also allowed. Use the "Simple Failover" high availability quality of service option.

• The application is allowed to send duplicate events to the downstream system, but must not skip any events when there is a failure. Use the Simple Failover with Buffering and Light-Weight Queue Trimming high availability quality of service options.

• The application must send exactly the same stream of messages/events to the downstream system when there is a failure, modulo a brief pause during which events may not be sent when there is a failure. Use the Precise Recovery with JMS high availability quality of service option.

In a high availability application, Oracle CQL queries have the following restrictions.

1. Create a multiserver domain using Oracle Coherence.
2. Create an Oracle Stream Analytics application.
3. Edit the MANIFEST.MF file to add the following Import-Package entries:

   • com.bea.wlevs.ede.api.cluster

   • com.oracle.cep.cluster.hagroups

   • com.oracle.cep.cluster.ha.adapter

   • com.oracle.cep.cluster.ha.api

4. Configure your Oracle Stream Analytics application EPN assembly file to add an Oracle Stream Analytics high availability buffering output adapter as the following assembly file entries show.

   • Add a wlevs:adapter element with provider set to ha-buffering after channel helloworldOutputChannel.

   • Update the wlevs:listener element in channel helloworldOutputChannel to reference the ha-buffering adapter by its id.

   • Add a wlevs:listener element to the ha-buffering adapter that references the HelloWorldBean class.

   <wlevs:event-type-repository>
     <wlevs:event-type type-name="HelloWorldEvent">            <wlevs:class>com.bea.wlevs.event.example.helloworld.HelloWorldEvent
       </wlevs:class>
     </wlevs:event-type>
   </wlevs:event-type-repository>
   
   <wlevs:adapter id="helloworldAdapter" 
     class="com.bea.wlevs.adapter.example.helloworld.HelloWorldAdapter" >
   <wlevs:instance-property name="message" value="HelloWorld - 
     the current time is:"/>
   </wlevs:adapter>
   
   <wlevs:channel id="helloworldInputChannel" event-type="HelloWorldEvent" >
     <wlevs:listener ref="helloworldProcessor"/>
   </wlevs:channel>
   
   <wlevs:processor id="helloworldProcessor" />
   
   <wlevs:channel id="helloworldOutputChannel" event-type="HelloWorldEvent"
     advertise="true">
     <wlevs:listener ref="myHaSlidingWindowAdapter"/>
     <wlevs:source ref="helloworldProcessor"/>
    </wlevs:channel>
   
    <wlevs:adapter id="myHaSlidingWindowAdapter" provider="ha-buffering" >
      <wlevs:listener>
        <bean class="com.bea.wlevs.example.helloworld.HelloWorldBean"/>
      </wlevs:listener>
    </wlevs:adapter>
   

5. Optionally, configure the channel downstream from the input adapter (helloworldInputChannel) to configure an application time stamp based on an appropriate event property as assembly file entries show.

   For simple failover, you can use system time stamps because events are not correlated between servers. However, it is possible that slightly different results might be output from the buffer if application time stamps are not used.

   In this example, event property arrivalTime is used.

   The wlevs:expression should be set to this event property.

   <wlevs:channel id="helloworldInputChannel" event-type="HelloWorldEvent" >
      <wlevs:listener ref="helloworldProcessor"/>
      <wlevs:source ref="myHaInputAdapter"/>
      <wlevs:application-timestamped>
         <wlevs:expression>arrivalTime</wlevs:expression>
      </wlevs:application-timestamped>
    </wlevs:channel>
   

6. Configure the Oracle Stream Analytics high availability buffering output adapter.

   Set the instance property windowLength to zero (0) as shown.

   <wlevs:adapter id="myHaSlidingWindowAdapter" provider="ha-buffering" >
      <wlevs:listener>
        <bean class="com.bea.wlevs.example.helloworld.HelloWorldBean"/>
      </wlevs:listener>
      <wlevs:instance-property name="windowLength" value="0"/>
   </wlevs:adapter>

7. Optionally, configure the component configuration file to include the Oracle Stream Analytics high availability buffering output adapter as shown.

   <processor>
     <name>helloworldProcessor</name>
     <rules>
       <query id="helloworldRule">
         <![CDATA[ select * from helloworldInputChannel [Now] >
       </query>
     </rules>
   </processor>
   
   <ha:ha-buffering-adapter >
     <name>myHaSlidingWindowAdapter</name>
     <window-length>0</window-length>
   </ha:ha-buffering-adapter >

8. Deploy your application to the deployment group you created in step 1.

   Oracle Stream Analytics automatically selects one of the Oracle Stream Analytics servers as the primary.

1. Create a multiserver domain using Oracle Coherence.
2. Create an Oracle Stream Analytics application.
3. Edit the MANIFEST.MF file to add the following Import-Package entries:

   • com.bea.wlevs.ede.api.cluster

   • com.oracle.cep.cluster.hagroups

   • com.oracle.cep.cluster.ha.adapter

   • com.oracle.cep.cluster.ha.api

4. Configure your Oracle Stream Analytics application EPN assembly file to add an Oracle Stream Analytics high availability buffering output adapter as the following assembly file entries show.

   • Add a wlevs:adapter element with provider set to ha-buffering after channel helloworldOutputChannel.

   • Update the wlevs:listener element in channel helloworldOutputChannel to reference the ha-buffering adapter by its id.

   • Add a wlevs:listener element to the ha-buffering adapter that references the HelloWorldBean class.

   <wlevs:event-type-repository>
     <wlevs:event-type type-name="HelloWorldEvent">
        <wlevs:class>com.bea.wlevs.event.example.helloworld.HelloWorldEvent</wlevs:class>
     </wlevs:event-type>
   </wlevs:event-type-repository>
   
   <wlevs:adapter id="helloworldAdapter" 
     class="com.bea.wlevs.adapter.example.helloworld.HelloWorldAdapter" >
     <wlevs:instance-property name="message" value="HelloWorld - the current time is:"/>
   </wlevs:adapter>
   
   <wlevs:channel id="helloworldInputChannel" event-type="HelloWorldEvent" >
     <wlevs:listener ref="helloworldProcessor"/>
   </wlevs:channel>
   
   <wlevs:processor id="helloworldProcessor" />
   
   <wlevs:channel id="helloworldOutputChannel" event-type="HelloWorldEvent" advertise="true">
      <wlevs:listener ref="myHaSlidingWindowAdapter"/>
      <wlevs:source ref="helloworldProcessor"/>
   </wlevs:channel>
   
   <wlevs:adapter id="myHaSlidingWindowAdapter" provider="ha-buffering" >
     <wlevs:listener>
        <bean class="com.bea.wlevs.example.helloworld.HelloWorldBean"/>
     </wlevs:listener>
   </wlevs:adapter>
   

5. Optionally, configure the channel downstream from the input adapter (helloworldInputChannel) to configure an application time stamp based on an appropriate event property as shown.

   For simple failover with buffering, you can use system time stamps because events are not correlated between servers. However, it is possible that slightly different results might be output from the buffer if application time stamps are not used.

   In this example, event property arrivalTime is used.

   The wlevs:expression should be set to this event property.

   <wlevs:channel id="helloworldInputChannel" event-type="HelloWorldEvent" >
     <wlevs:listener ref="helloworldProcessor"/>
     <wlevs:source ref="myHaInputAdapter"/>
     <wlevs:application-timestamped>
       <wlevs:expression>arrivalTime</wlevs:expression>
     </wlevs:application-timestamped>
   </wlevs:channel>
   

6. Configure the Oracle Stream Analytics high availability buffering output adapter.

   Set the instance property windowLength to a value greater than zero (0) as shown.

   <wlevs:adapter id="myHaSlidingWindowAdapter" provider="ha-buffering" >
     <wlevs:listener>
       <bean class="com.bea.wlevs.example.helloworld.HelloWorldBean"/>
     </wlevs:listener>
        <wlevs:instance-property name="windowLength" value="15000"/>
   </wlevs:adapter>
   

7. Optionally, configure the component configuration file to include the Oracle Stream Analytics high availability buffering output adapter as shown.

   <processor>
     <name>helloworldProcessor</name>
     <rules>
       <query id="helloworldRule">
         <![CDATA[ select * from helloworldInputChannel [Now] >
       </query>
     </rules>
   </processor>
   
   <ha:ha-buffering-adapter >
     <name>myHaSlidingWindowAdapter</name>
     <window-length>15000</window-length>
   </ha:ha-buffering-adapter >

8. If your application is an Oracle Stream Analytics high availability Type 1 application where the application must generate exactly the same sequence of output events as existing secondaries) configure the warm-up-window-length for the buffering output adapter.

   For more information, see Choose an Adequate warm-up-window-length Time

9. Deploy your application to the deployment group you created in step 1.

   Oracle Stream Analytics automatically selects one of the Oracle Stream Analytics servers as the primary.

1. Create a multiserver domain using Oracle Coherence.
2. Create an Oracle Stream Analytics application.
3. Edit the MANIFEST.MF file to add the following Import-Package entries:

   • com.bea.wlevs.ede.api.cluster

   • com.oracle.cep.cluster.hagroups

   • com.oracle.cep.cluster.ha.adapter

   • com.oracle.cep.cluster.ha.api

4. Configure your Oracle Stream Analytics application EPN assembly file to add an Oracle Stream Analytics high availability input adapter as the following example shows.

   • Add a wlevs:adapter element with provider set to ha-inbound after the regular input adapter helloworldAdapter.

   • Add a wlevs:listener element to the regular input adapter helloworldAdapter that references the ha-inbound adapter by its id.

   • Add a wlevs:source element to the helloworldInputChannel that references the ha-inbound adapter by its id.

       <wlevs:event-type-repository>
           <wlevs:event-type type-name="HelloWorldEvent">
               <wlevs:class>com.bea.wlevs.event.example.helloworld.HelloWorldEvent</wlevs:class>
     </wlevs:event-type>
   </wlevs:event-type-repository>
   
   <wlevs:adapter id="helloworldAdapter" 
     class="com.bea.wlevs.adapter.example.helloworld.HelloWorldAdapter" >
   <wlevs:instance-property name="message" value="HelloWorld - 
     the current time is:"/>
      <wlevs:listener ref="myHaInputAdapter"/>
   </wlevs:adapter>
   
   <wlevs:adapter id="myHaInputAdapter" provider="ha-inbound" >
   </wlevs:adapter>
   
   <wlevs:channel id="helloworldInputChannel" event-type="HelloWorldEvent" >
     <wlevs:listener ref="helloworldProcessor"/>
     <wlevs:source ref="myHaInputAdapter"/>
   </wlevs:channel>
   
   <wlevs:processor id="helloworldProcessor" />
   
   <wlevs:channel id="helloworldOutputChannel" event-type="HelloWorldEvent"
     advertise="true">
     <wlevs:listener>
       <bean class="com.bea.wlevs.example.helloworld.HelloWorldBean"/>
     </wlevs:listener>
       <wlevs:source ref="helloworldProcessor"/>
     </wlevs:channel>
   

5. Configure your Oracle Stream Analytics application EPN assembly file to add an Oracle Stream Analytics high availability broadcast output adapter as shown.

   • Add a wlevs:adapter element with provider set to ha-broadcast after channel helloworldOutputChannel.

   • Update the wlevs:listener element in channel helloworldOutputChannel to reference the ha-broadcast adapter by its id.

   • Add a wlevs:listener element to the ha-broadcast adapter that references the HelloWorldBean class.

   <wlevs:event-type-repository>
     <wlevs:event-type type-name="HelloWorldEvent">
       <wlevs:class>com.bea.wlevs.event.example.helloworld.HelloWorldEvent
       </wlevs:class>
     </wlevs:event-type>
   </wlevs:event-type-repository>
   
   <wlevs:adapter id="helloworldAdapter" 
      class="com.bea.wlevs.adapter.example.helloworld.HelloWorldAdapter" >
    <wlevs:instance-property name="message" value="HelloWorld - 
       the current time is:"/>
     <wlevs:listener ref="myHaInputAdapter"/>
   </wlevs:adapter>
   
   <wlevs:adapter id="myHaInputAdapter" provider="ha-inbound" >
   </wlevs:adapter>
   
   <wlevs:channel id="helloworldInputChannel" event-type="HelloWorldEvent" >
     <wlevs:listener ref="helloworldProcessor"/>
     <wlevs:source ref="myHaInputAdapter"/>
   </wlevs:channel>
   
   <wlevs:processor id="helloworldProcessor" />
   
   <wlevs:channel id="helloworldOutputChannel" event-type="HelloWorldEvent" 
     advertise="true">
     <wlevs:listener ref="myHaBroadcastAdapter"/>
     <wlevs:source ref="helloworldProcessor"/>
   </wlevs:channel>
   
   <wlevs:adapter id="myHaBroadcastAdapter" provider="ha-broadcast" >
     <wlevs:listener>
       <bean class="com.bea.wlevs.example.helloworld.HelloWorldBean"/>
     </wlevs:listener>
   </wlevs:adapter>
   

6. Configure the Oracle Stream Analytics high availability input adapter.

   Consider using one of the following example configurations.

   This example shows a high availability input adapter configuration using all defaults. The mandatory key is based on all event properties and the event property that the high availability input adapter assigns a time value to is an event property named arrivalTime.

   <wlevs:adapter id="myHaInputAdapter" provider="ha-inbound" >
     <wlevs:instance-property name="timeProperty" value="arrivalTime"/>
   </wlevs:adapter>

   This example shows a high availability input adapter configuration using all defaults. The mandatory key is based on all event properties and the event property that the high availability input adapter assigns a time value to is an event property named arrivalTime. Because the events are tuple-based events, you must specify the event type (MyEventType) using the eventType property.

   <wlevs:adapter id="myHaInputAdapter" provider="ha-inbound" >
      <wlevs:instance-property name="timeProperty" value="arrivalTime"/>
      <wlevs:instance-property name="eventType" value="MyEventType"/>
   </wlevs:adapter>

   This example shows a high availability input adapter configuration where the mandatory key is based on one event property (named id) and the event property that the high availability input adapter assigns a time value to is an event property named arrivalTime.

   <wlevs:adapter id="myHaInputAdapter" provider="ha-inbound" >
     <wlevs:instance-property name="keyProperties" value="id"/>
     <wlevs:instance-property name="timeProperty" value="arrivalTime"/>
   </wlevs:adapter>

   This example shows a high availability input adapter configuration where the mandatory key is based on more than one event property (properties orderID and accountID) and the event property that the high availability input adapter assigns a time value to is an event property named arrivalTime.

   <wlevs:adapter id="myHaInputAdapter" provider="ha-inbound" >
     <wlevs:instance-property name="timeProperty" value="arrivalTime"/>
     <wlevs:instance-property name="keyClass" value="com.acme.MyCompoundKeyClass"/>
   </wlevs:adapter>
   

   A compound key Java class (com.acme.MyCompoundKeyClass) is mandatory and its implementation is shown. The hashCode and equals methods are required. When you specify a keyClass, the keyProperties instance property is ignored: Oracle Stream Analytics assumes that the compound key is based on all the getter methods in the keyClass.

   package com.acme;
   
   public class MyCompoundKeyClass {
       private int orderID;
       private int accountID;
   
       public MyCompoundKeyClass() {}
   
       public int getOrderID() {
           return orderID;
       }
       public setOrderID(int orderID) {
           this.orderID = orderID;
       }
       public int getAccountID() {
           return accountID;
       }
       public setOrderID(int accountID) {
           this.accountID = accountID;
       }
   
       public int hashCode() {
       int hash = 1;
       hash = hash * 31 + orderID.hashCode();
       hash = hash * 31 + (accountID == null ? 0 : accountID.hashCode());
       return hash;
       }
   
       public boolean equals(Object obj) {
           if (obj == this) return true;
           if (obj == null) return false;
           if (!(obj instanceof MyCompoundKeyClass)) return false;
           MyCompoundKeyClass k = (MyCompoundKeyClass) obj;
           return k.accountID == accountID && k.orderID == orderID;
       }
   }

7. Configure the channel downstream from the high availability input adapter (helloworldInputChannel) to configure an application time stamp based on the high availability input adapter timeProperty setting as the following example shows.

   The wlevs:expression should be set to the timeProperty value.

   <wlevs:adapter id="myHaInputAdapter" provider="ha-inbound" >
      <wlevs:instance-property name="keyProperties" value="id"/>
      <wlevs:instance-property name="eventType" value="HelloWorldEvent"/>
      <wlevs:instance-property name="timeProperty" value="arrivalTime"/>
   </wlevs:adapter>
   
   <wlevs:channel id="helloworldInputChannel" event-type="HelloWorldEvent" >
     <wlevs:listener ref="helloworldProcessor"/>
     <wlevs:source ref="myHaInputAdapter"/>
     <wlevs:application-timestamped>
       <wlevs:expression>arrivalTime</wlevs:expression>
     </wlevs:application-timestamped>
   </wlevs:channel>
   

8. Configure the Oracle Stream Analytics high availability broadcast output adapter.

   Consider using one of the following example configurations:

   This example shows a broadcast output adapter configuration using all defaults. The mandatory key is based on all event properties, key values are non-monotonic (do not increase continually) and total order (unique).

   <wlevs:adapter id="myHaSlidingWindowAdapter" provider="ha-broadcast" >
      <wlevs:listener>
         <bean class="com.bea.wlevs.example.helloworld.HelloWorldBean"/>
      </wlevs:listener>
   </wlevs:adapter>

   This example shows a broadcast output adapter configuration where the mandatory key is based on one event property (named timeProperty), key values are monotonic (they do increase continually) and not total order (not unique).

   <wlevs:adapter id="myHaSlidingWindowAdapter" provider="ha-broadcast" >
      <wlevs:listener>
        <bean class="com.bea.wlevs.example.helloworld.HelloWorldBean"/>
      </wlevs:listener>
        <wlevs:instance-property name="keyProperties" value="timeProperty"/>
        <wlevs:instance-property name="monotonic" value="true"/>
        <wlevs:instance-property name="totalOrder" value="false"/>
     </wlevs:adapter>

   This example shows a broadcast output adapter configuration where the mandatory key is based on more than one event property (properties timeProperty and accountID), key values are monotonic (they do increase continually) and total order (unique).

   <wlevs:adapter id="myHaSlidingWindowAdapter" provider="ha-broadcast" >
    <wlevs:listener>
       <bean class="com.bea.wlevs.example.helloworld.HelloWorldBean"/>
     </wlevs:listener>
     <wlevs:instance-property name="keyClass" value="com.acme.MyCompoundKeyClass"/>
     <wlevs:instance-property name="monotonic" value="true"/>
     <wlevs:instance-property name="totalOrder" value="true"/>
   </wlevs:adapter>
   

   A compound key Java class (com.acme.MyCompoundKeyClass) is mandatory and its implementation is shown in the following example. The hashCode and equals methods are required. When you specify a keyClass, the keyProperties instance property is ignored: Oracle Stream Analytics assumes that the compound key is based on all the getter methods in the keyClass.

   package com.acme;
   
   public class MyCompoundKeyClass {
       private int timeProperty;
       private int accountID;
   
       public MyCompoundKeyClass() {}
   
       public int getTimeProperty() {
           return orderID;
       }
       public setTimeProperty(int timeProperty) {
           this.timeProperty = timeProperty;
       }
       public int getAccountID() {
           return accountID;
       }
       public setOrderID(int accountID) {
           this.accountID = accountID;
       }
   
       public int hashCode() {
       int hash = 1;
       hash = hash * 31 + timeProperty.hashCode();
       hash = hash * 31 + (accountID == null ? 0 : accountID.hashCode());
       return hash;
       }
   
       public boolean equals(Object obj) {
           if (obj == this) return true;
           if (obj == null) return false;
           if (!(obj instanceof MyCompoundKeyClass)) return false;
           MyCompoundKeyClass k = (MyCompoundKeyClass) obj;
           return k.accountID == accountID && k.orderID == orderID;
       }
   }
   

9. Optionally, configure the component configuration file to include the Oracle Stream Analytics high availability input adapter and buffering output adapter as shown.

   <processor>
     <name>helloworldProcessor</name>
     <rules>
       <query id="helloworldRule">
         <![CDATA[ select * from helloworldInputChannel [Now] >
       </query>
     </rules>
   </processor>
   
   <ha:ha-inbound-adapter>
    <name>myHaInputAdapter</name>
   </ha:ha-inbound-adapter>
    
   <ha:ha-broadcast-adapter>
     <name>myHaBroadcastAdapter</name>
     <trimming-interval units="events">10</trimming-interval>
   </ha:ha-broadcast-adapter>
   

10. If your application is an Oracle Stream Analytics high availability Type 1 application where the application must generate exactly the same sequence of output events as existing secondaries, configure the warm-up-window-length for the broadcast output adapter.
11. Oracle Stream Analytics automatically selects one of the Oracle Stream Analytics servers as the primary.

1. Create a multiserver domain using Oracle Coherence.
2. Create an Oracle Stream Analytics application.
3. Edit the MANIFEST.MF file to add the following Import-Package entries:

   • com.bea.wlevs.ede.api.cluster

   • com.oracle.cep.cluster.hagroups

   • com.oracle.cep.cluster.ha.adapter

   • com.oracle.cep.cluster.ha.api

4. Configure your Oracle Stream Analytics application EPN assembly file to add an Oracle Stream Analytics high availability input adapter as shown:

   • Add a wlevs:adapter element with provider set to ha-inbound after the regular input adapter JMSInboundAdapter.

   • Add a wlevs:listener element to the regular input adapter JMSInboundAdapter that references the ha-inbound adapter by its id.

   • Add a wlevs:source element to the channel channel1 that references the ha-inbound adapter by its id.

       <wlevs:event-type-repository>
           <wlevs:event-type type-name="StockTick">
               <wlevs:properties>
                   <wlevs:property name="lastPrice" type="double" />
                   <wlevs:property name="symbol" type="char" />
               </wlevs:properties>
           </wlevs:event-type>
       </wlevs:event-type-repository>
   
       <wlevs:adapter id="JMSInboundAdapter" provider="jms-inbound">
           <wlevs:listener ref="myHaInputAdapter"/>
       </wlevs:adapter>
   
       <wlevs:adapter id="myHaInputAdapter" provider="ha-inbound" >
       </wlevs:adapter>
   
       <wlevs:channel id="channel1" event-type="StockTick">
           <wlevs:listener ref="processor1" />
           <wlevs:source ref="myHaInputAdapter"/>
       </wlevs:channel>
   

5. Configure your Oracle Stream Analytics application EPN assembly file to add an Oracle Stream Analytics high availability correlating output adapter as shown.

   • Add a wlevs:adapter element with provider set to ha-correlating after channel channel2.

   • Update the wlevs:listener element in channel channel2 to reference the ha-correlating adapter by its id.

   • Add a wlevs:listener element to the ha-correlating adapter that references the regular output adapter JMSOutboundAdapter.

   <wlevs:event-type-repository>
     <wlevs:event-type type-name="StockTick">
       <wlevs:properties>
         <wlevs:property name="lastPrice" type="double" />
         <wlevs:property name="symbol" type="char" />
       </wlevs:properties>
     </wlevs:event-type>
   </wlevs:event-type-repository>
   
   <wlevs:adapter id="JMSInboundAdapter" provider="jms-inbound">
     <wlevs:listener ref="myHaInputAdapter"/>
   </wlevs:adapter>
   
   <wlevs:adapter id="myHaInputAdapter" provider="ha-inbound" >
   </wlevs:adapter>
   
   <wlevs:channel id="channel1" event-type="StockTick">
     <wlevs:listener ref="processor1" />
     <wlevs:source ref="myHaInputAdapter"/>
   </wlevs:channel>
   
   <wlevs:processor id="processor1">
     <wlevs:listener ref="channel2" />
   </wlevs:processor>
   
   <wlevs:channel id="channel2" event-type="StockTick">
     <wlevs:listener ref="myHaCorrelatingAdapter" />
   </wlevs:channel>
   
   <wlevs:adapter id="myHaCorrelatingAdapter" provider="ha-correlating" >
     <wlevs:listener ref="JMSOutboundAdapter"/>
   </wlevs:adapter>
   
   <wlevs:adapter id="JMSOutboundAdapter" provider="jms-outbound">
   </wlevs:adapter>
   

6. Configure the Oracle Stream Analytics high availability input adapter.

   Consider using one of the following example configurations:

   This example shows a high availability input adapter configuration using all defaults. The mandatory key is based on all event properties and the event property that the high availability input adapter assigns a time value to is an event property named arrivalTime.

   <wlevs:adapter id="myHaInputAdapter" provider="ha-inbound" >
     <wlevs:instance-property name="timeProperty" value="arrivalTime"/>
   </wlevs:adapter>

   This example shows a high availability input adapter configuration using all defaults. The mandatory key is based on all event properties and the event property that the high availability input adapter assigns a time value to is an event property named arrivalTime. Because the events are tuple-based events, you must specify the event type (MyEventType) using the eventType property.

   <wlevs:adapter id="myHaInputAdapter" provider="ha-inbound" >
     <wlevs:instance-property name="timeProperty" value="arrivalTime"/>
     <wlevs:instance-property name="eventType" value="MyEventType"/>
   </wlevs:adapter>

   This example shows a high availability input adapter configuration where the mandatory key is based on one event property (named sequenceNo) and the event property that the high availability input adapter assigns a time value to is an event property named inboundTime.

   <wlevs:adapter id="myHaInputAdapter" provider="ha-inbound" >
     <wlevs:instance-property name="keyProperties" value="sequenceNo"/>
     <wlevs:instance-property name="timeProperty" value="inboundTime"/>
   </wlevs:adapter>

   This example shows a high availability input adapter configuration where the mandatory key is based on more than one event property (properties orderID and accountID) and the event property that the high availability input adapter assigns a time value to is an event property named arrivalTime.

   A compound key Java class (com.acme.MyCompoundKeyClass) is mandatory and its implementation is shown. The hashCode and equals methods are required. When you specify a keyClass, the keyProperties instance property is ignored: Oracle Stream Analytics assumes that the compound key is based on all the getter methods in the keyClass.

   <wlevs:adapter id="myHaInputAdapter" provider="ha-inbound" >
     <wlevs:instance-property name="timeProperty" value="arrivalTime"/>
     <wlevs:instance-property name="keyClass" value="com.acme.MyCompoundKeyClass"/>
   </wlevs:adapter>

   package com.acme;
   
   public class MyCompoundKeyClass {
       private int orderID;
       private int accountID;
   
       public MyCompoundKeyClass() {}
   
       public int getOrderID() {
           return orderID;
       }
       public setOrderID(int orderID) {
           this.orderID = orderID;
       }
       public int getAccountID() {
           return accountID;
       }
       public setOrderID(int accountID) {
           this.accountID = accountID;
       }
   
       public int hashCode() {
       int hash = 1;
       hash = hash * 31 + orderID.hashCode();
       hash = hash * 31 + (accountID == null ? 0 : accountID.hashCode());
       return hash;
       }
   
       public boolean equals(Object obj) {
           if (obj == this) return true;
           if (obj == null) return false;
           if (!(obj instanceof MyCompoundKeyClass)) return false;
           MyCompoundKeyClass k = (MyCompoundKeyClass) obj;
           return k.accountID == accountID && k.orderID == orderID;
       }
   }
   

7. Configure the channel downstream from the high availability input adapter (channel1) to configure an application time stamp based on the high availability input adapter timeProperty setting as the following example shows.

   The wlevs:expression should be set to the timeProperty value.

   <wlevs:adapter id="myHaInputAdapter" provider="ha-inbound" >
     <wlevs:instance-property name="eventType" value="HelloWorldEvent"/>
     <wlevs:instance-property name="keyProperties" value="sequenceNo"/>
     <wlevs:instance-property name="timeProperty" value="inboundTime"/>
   </wlevs:adapter>
   
   <wlevs:channel id="channel1" event-type="StockTick">
     <wlevs:listener ref="processor1" />
     <wlevs:source ref="myHaInputAdapter"/>
     <wlevs:application-timestamped>
       <wlevs:expression>inboundTime</wlevs:expression>
     </wlevs:application-timestamped>
   </wlevs:channel>
   

8. Configure the Oracle Stream Analytics high availability correlating output adapter failOverDelay.

   The following example shows a correlating output adapter configuration where the failOverDelay is 2000 milliseconds.

   <wlevs:adapter id="myHaCorrelatingAdapter" provider="ha-correlating" >
     <wlevs:listener ref="JMSOutboundAdapter"/>
     <wlevs:instance-property name="failOverDelay" value="2000"/>
   </wlevs:adapter>
   

9. Create a second regular JMS input adapter.

   The following example shows a JMS adapter named JMSInboundAdapter2.

       <wlevs:adapter id="JMSInboundAdapter2" provider="jms-inbound">
       </wlevs:adapter>
   

   The following JMS input adapter must be configured identically to the first JMS input adapter (in this example, JMSInboundAdapter). The following example shows the component configuration file for both the JMS input adapters. Note that both have exactly the same configuration, including the same provider.

       <jms-adapter>
           <name>JMSInboundAdapter</name>
           <jndi-provider-url>t3://localhost:7001</jndi-provider-url>
           <destination-jndi-name>./Topic1</destination-jndi-name>
           <user>weblogic</user>
           <password>weblogic</password>
           <work-manager>JettyWorkManager</work-manager>
           <concurrent-consumers>1</concurrent-consumers>
       </jms-adapter>
   
       <jms-adapter>
           <name>JMSInboundAdapter2</name>
           <jndi-provider-url>t3://localhost:7001</jndi-provider-url>
           <destination-jndi-name>./Topic2</destination-jndi-name>
           <user>weblogic</user>
           <password>weblogic</password>
           <work-manager>JettyWorkManager</work-manager>
           <concurrent-consumers>1</concurrent-consumers>
       </jms-adapter>
       ...
   </wlevs:config>
   

10. Create a channel to function as the correlated source.

    You must configure this channel with the second regular JMS input adapter as its source.

    The following example shows a correlated source named clusterCorrelatingOutstream whose source is JMSInboundAdapter2.

        <wlevs:adapter id="JMSInboundAdapter2" provider="jms-inbound">
        </wlevs:adapter>
    
        <wlevs:channel id="clusterCorrelatingOutstream" event-type="StockTick" advertise="true">
            <wlevs:source ref="JMSInboundAdapter2"/>
        </wlevs:channel> 
    

11. Configure the Oracle Stream Analytics high availability correlating output adapter with the correlatedSource.

    The following example shows a correlating output adapter configuration where the correlatedSource is clusterCorrelatingOutstream.

    <wlevs:adapter id="myHaCorrelatingAdapter" provider="ha-correlating" >
      <wlevs:listener ref="JMSOutboundAdapter"/>
      <wlevs:instance-property name="failOverDelay" value="2000"/>
      <wlevs:instance-property name="correlatedSource"       ref="clusterCorrelatingOutstream"/>
    </wlevs:adapter>
    

12. If your application is an Oracle Stream Analytics high availability Type 1 application where the application must generate exactly the same sequence of output events as existing secondaries, configure the warm-up-window-length for the correlating output adapter.
13. Configure the component configuration file to enable session-transacted for both inbound JMS adapters and the outbound JMS adapter as the following example shows:

        <jms-adapter>
            <name>JMSInboundAdapter</name>
            <jndi-provider-url>t3://localhost:7001</jndi-provider-url>
            <destination-jndi-name>./Topic1</destination-jndi-name>
            <user>weblogic</user>
            <password>weblogic</password>
            <work-manager>JettyWorkManager</work-manager>
            <concurrent-consumers>1</concurrent-consumers>
            <session-transacted>true</session-transacted>
        </jms-adapter>
    
        <jms-adapter>
            <name>JMSInboundAdapter2</name>
            <jndi-provider-url>t3://localhost:7001</jndi-provider-url>
            <destination-jndi-name>./Topic2</destination-jndi-name>
            <user>weblogic</user>
            <password>weblogic</password>
            <work-manager>JettyWorkManager</work-manager>
            <concurrent-consumers>1</concurrent-consumers>
            <session-transacted>true</session-transacted>
        </jms-adapter>
        ...
        <jms-adapter>
            <name>JMSOutboundAdapter</name>
            <event-type>JMSEvent</event-type>
            <jndi-provider-url>t3://localhost:7001</jndi-provider-url>
            <destination-jndi-name>./Topic2</destination-jndi-name>
            <delivery-mode>nonpersistent</delivery-mode>
            <session-transacted>true</session-transacted>
        </jms-adapter>
        ...
    </wlevs:config>

14. Optionally, configure the component configuration file to include the Oracle Stream Analytics high availability input adapter and correlating output adapter as shown.

        <ha:ha-inbound-adapter>
            <name>myHaInputAdapter</name>
        </ha:ha-inbound-adapter>
        ...
        <ha:ha-correlating-adapter>
            <name>myHaBroadcastAdapter</name>
            <fail-over-delay>2000</fail-over-delay>
        </ha:ha-correlating-adapter>

15. Optionally, add an ActiveActiveGroupBean to your EPN to improve scalability.

    For more information, see Partition an Incoming JMS Event Stream.

16. Oracle Stream Analytics automatically selects one of the Oracle Stream Analytics servers as the primary.