This presentation talks about the Splitter and Aggregator integration pattern

1. Integration Pattern
Splitter and Aggregators

2. Introduction
• Messages passing through an integration solution consist of multiple elements.
• E.g. an order placed by a customer typically consists of more than just a single items like Address, Product
details , Mode Of Payment etc.
• We should process a complete order but treat each order item contained in the order
individually
• How can we process a message having multiple elements, each of which may have to
be processed in a different way?
• Publish Subscriber Model ????
Page 2

3. Publish Subscriber an alternative to Splitter ?
• Publish a message having Multiple Orders to All Subscribers
• Each Subscriber would process the required/supported Order and discard other orders
• Inefficient
• Each subscriber needs to implement logic to divide whole message and process supported one
• Increase Network Traffic
• Implement extra logic for lost / duplicate message handling
Page 3

4. Splitter
• Use a Splitter to break out the composite message into a series of individual messages, each containing
data related to one item.
• To avoid sending the complete message multiple times
• Split them into multiple
• Each message would then contain only one items
• The Splitter publishes one message for each single element
Page 4

5. Splitter -Handling Common Elements
• In many cases, we repeat some common elements in each resulting message
• These extra elements might be required to make the resulting child message self-contained and enable stateless
processing of each child message
• It also allows reconciliation of associated child messages later on
• Common Element can be Some ID or Timestamp
Page 5

6. Iterative Splitter
• When Data in Message is stored in a Data Structure like Lists , Tree Or Map
• Then Splitter iterates over each records/Node and constructs the output
• Generic Splitter can be worked with any number of child elements
• Also Called Sequencer Splitter
Page 6

7. Static Splitter
• Customized Splitter
• Used to split a large message into smaller messages based on some criteria e.g.
subtype
• Usually it splits into Fixed number of messages
• The strategy of splitting is fixed hence its called static Splitter
Page 7

8. Splitter -Input Message
• <order>
<date>7/18/2002</date>
<ordernumber>3825968</ordernumber>
<customer>
<id>12345</id>
<name>Joe Doe</name>
</customer>
<orderitems>
<item>
<quantity>3.0</quantity>
<itemno>W1234</itemno>
<description>A Widget</description>
</item>
<item>
<quantity>2.0</quantity>
<itemno>G2345</itemno>
<description>A Gadget</description>
</item>
</orderitems>
</order>
Page 8

9. Splitter – Output Messages
• <orderitem>
<date>7/18/2002</date>
<ordernumber>3825968</ordernumber>
<customerid>12345</customerid>
<quantity>3.0</quantity>
<itemno>W1234</itemno>
<description>A Widget</description>
</orderitem>
<orderitem>
<date>7/18/2002</date>
<ordernumber>3825968</ordernumber>
<customerid>12345</customerid>
<quantity>2.0</quantity>
<itemno>G2345</itemno>
<description>A Gadget</description>
</orderitem>
Page 9

10. Aggregator
• Splitter splits single message into sequence of individual messages
• How can we combine results of individual but related messages ?
• Asynchronous behavior
• Unknown number of recipients
• Response of individual message may be out of sequence
• How long should we wait ?
• Wait for too long ?
• Set timeout
• What should we do when response of few message is pending
• Should we send incomplete information ?
Page
10

11. Aggregator
• A separate component which sends a single message Once all individual message response is
ready
• Its called Aggregator because it collects individual messages until it receives a complete set and
then it combines and sends a single message
• Special filter
• which receives stream of messages It identifies the related messages . Once a complete set is arrived it sends
to output channel
Page
11

12. • Stateful component
• It needs to store all incoming messages(some information)
• Design
1. Correlation: Which incoming messages belong together
 ID, Timestamp etc
2. Completeness Condition: When are we ready to publish the result message?
3. Aggregation Algorithm: How do we combine the received messages into a single result
message ?
Page
12
Aggregator

13. Aggregator Implementation
Page
13
Message
First
Message
?
Aggregator
Yes
Message
Correlatio
n exists
No
Aggregator
No
Create
Aggregator and
add message
Add Message to
Existing
Aggregator
Create
Aggregator and
add message
Complete
Set
Received
Yes
Aggregate and
Construct
Single Message
No
Wait till all messages received
System
Send
message

14. References
• Enterprise Integration Patterns a Book by Gregor Hohpe