WSO2 Message Broker Scalable persistent Messaging System Outline - PowerPoint PPT Presentation

WSO2 Message Broker Scalable persistent Messaging System

Outline  Messaging  Scalable Messaging  Distributed Message Brokers  WSO2 MB Architecture o Distributed Pub/sub architecture o Distributed Queues architecture  User Story  Conclusion

What is Messaging ?  We often program and design distributed systems with RPC style communication o E.g. Web Services, Thrift, REST  RPC communication is o Request/Response (there is always a response) o Synchronous (client waits for response) o Non-persistent (message is lot if something failed)  But there are other 7 possibilities o Under messaging we support those o Build on top of single message, with flexibility (users can choose) in other dimensions WSO2 Inc. 3

Messaging Systems in Real World  There are many types of message systems in the real word o Sensor networks o Monitoring/ Surveillance o Business Activity Monitoring o Job Scheduling systems o Social Networks WSO2 Inc. 4

Why Messaging?  More reliability o E.g. via persistence, transactions  Decupling o Space o Time o Synchronization WSO2 Inc. 5

Messaging Server Models  Messaging is implemented with a broker (or brokers in the middle)  Participants send messages, and broker delivers them to recipients  There are two main models o Queues - A message is delivered only once to a single consumer. o Publish/Subscribe: Broadcast a message to many message consumers WSO2 Inc. 6

Distributed Queues  A queue in the “Cloud”  Supports Operations o Put(M) – put a message o Get() – get a message (dqueue) o Subscribe() – send me a message when there is one  E.g. SQS (Amazon Queuing Service)  Usecases o Job Queues o Sored and process 7

Publish/ Subscribe  There is a topic space based on interest  Publishers send messages to brokers  Subscribers registers their interest  Brokers matches events (messages) and delivers to all interested parties  Usecases o Surveillance o Monitoring WSO2 Inc. 8

What is JMS ?  JMS – Java Message Service  A specification that define a standard API for java programmer to perform messaging by interacting with a message broker  Support both o Distributed Queue o Publish/Subscribe  It does not define the message format or how java API interacts with the message broker WSO2 Inc. 9

What is AMQP ?  Advanced Message Queuing Protocol (AMQP)  Open standard for passing business messages between applications or organizations.  JMS does not define the message format, and AMQP fills that gap  AMQP let different systems (e.g. .NET and Java) to interact with each other by agreeing the message format at the wire level just like Web Services. WSO2 Inc. 10

Brokers  Message broker support messaging  Some brokers can be setup as a network or a cluster  Some of well known brokers o Apache Qpid - http://qpid.apache.org/ o Storm MQ - http://stormmq.com/ o Active MQ - http://activemq.apache.org/ o HornetQ - http://www.jboss.org/hornetq o Rabbit MQ - http://www.rabbitmq.com/ o IBM WebSphere MQ - http://www- 01.ibm.com/software/integration/wmq/ WSO2 Inc. 11

Scaling  There a several dimensions of Scale  Number of messages  Number of Queues  Size of messages  Scaling Pub/Sub is relatively easy  E.g. Consider cluster of brokers. If all node know about all subscriptions, all publish messages can be delivered  E.g. Narada Broker, Padres  Scaling Distributed Queues is harder WSO2 Inc. 12

Scaling Distributed Queues WSO2 Inc. 13

Scaling Distributed Queues (Contd.) Topology Pros Cons Supporting Systems Master Salve Support HA No Scalability Qpid, ActiveMQ, RabbitMQ Queue Distribution Scale to large Does not scale for RabbitMQ number of Queues large number of messages for a queue Cluster Connections Support HA Might not support HorentMQ in-order delivery Logic runs in the client side takes local decisions. Broker/Queue Load balancing and Fair load balancing ActiveMQ Networks distribution is hard WSO2 Inc. 14

Alternative Message Broker Design  Most persistent message brokers use a per-node DB to store messages with message routing.  But with large messages, cost of routing messages over the network is very high  With availability of scalable storage and distributed coordination middleware we propose an alternative architecture for scalable message brokers  Main idea o Avoid message routing o Use scalable storage to share messages between nodes o Use distributed coordination to control the behavior

Cassandra and Zookeeper  Cassandra o NoSQL Highly scalable new data model (column family) o Highly scalable (multiple Nodes), available and no Single Point of Failure. o SQL like query language (from 0.8) and support search through secondary indexes (well no JOINs, Group By etc. ..). o Tunable consistency and replication o Very high write throughput and good read throughput. It is pretty fast.  Zookeeper o Scalable, fault tolerant distributed coordination framework

WSO2 Message Broker  Use Apache Zookeeper for coordination when needed  Support for AMQP JMS and WS-Eventing while enabling interoperability between protocols  Built by extending Apache Qpid Code base

WSO2 MB Architecture WSO2 Inc. 18

How Distributed Queues Works ? WSO2 Inc. 19

How Distributed Queues Works Contd.. WSO2 Inc. 20

How Distributed Queues Works Contd..  Each node contains a node queue. Message meta data are stored in this queue. A Queue Delivery Worker running in each node and consume messages in the above node queue. Destination is extracted from this consumed message and delivered to the endpoint.  MB stores message content separately  Delivery logic works with message IDs written to queue representation in Cassandra and it only reads the messages at delivery WSO2 Inc. 21

Distributed Queues  Strict ordering means there can be one message being delivered at a give time. o Say we receive messages m1, m2 for Queue Q. o Say we deliver messages m1 and m2 to client c1 and c2 for Queue Q in parallel o Say m1->c1 failed, but by then m2->c2 is done. o If there is no other subscribers, now m1 has to be delivered out of order.  Two implementation o Strict ordering support - using a distributed shared lock with Zookeeper o Best effort implementation

How Pub/Sub Works ? WSO2 Inc. 23

How Pub/Sub Works Contd …  There is a node queue for each of the brokers.  When published message to a topic, broker get the list of nodes where subscriptions available for the topic and write the message id to each of the node queue connected to brokers.  A worker thread running in each of these brokers to consume messages from the above node queue and deliver the message to subscriber. WSO2 Inc. 24

MB2 JMS Support Feature Yes No √ Pub / Sub √ Durable Subscriptions √ Hierarchical Topics √ Queues √ Message Selectors √ Transactions WSO2 Inc. 25

How does it Make a difference?  Scale up in all 3 dimensions  Create only one copy of message while delivery  High Availability and Fault Tolerance  Large message transfers in pub/sub (asynchronous style)  Let users choose between strict and best effort messages  Replication of stored messages in the storage

Conclusion and Future Work  Provides an alternative architecture for scalable message brokers using Cassandra and Zookeeper  It provides o A publish/subscribe model that does not need any coordination between broker nodes o A strict mode for distributed queues that provides in order delivery o A best-effort mode for distributed queue  Future work o Further Scalability Tests o Testing with large messages o Fault Tolerance Tests

Integrating with WSO2 ESB  JMS Transport o JMS endpoints and JMS proxy services  Message Stores and Processors WSO2 Inc. 28

Integrating with WSO2 DSS  JMS Transport o JMS transport enabled data services WSO2 Inc. 29

User Story  An SAP system need to distribute IDOCs to their point of sales which are distributed Island wide. IDOCs are sending out from SAP as batches issued within small amount of time period. These IDOCs need to transform in to SOAP messages and need to inject some properties. Finally these messages need to update the data bases in Point of Sales. WSO2 Inc. 30

User Story Contd.. WSO2 Inc. 31

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