Many organizations develop a combination of .NET and Java web and SOA applications. And, many of these applications need to share data with one another at run time. Often, they're all working on common business data that's stored in a database. Or, they might be dealing with continuous streams of data (for example, financial trading applications), and need to process it and share results with other applications, again all at run time. Learn how to share data across multiple .NET to .NET and Java applications at runtime with the help of a distributed cache. This webinar covers: 1. .NET to .NET and Java application data sharing techniques 2. How distributed cache event notifications are used 3. How does Continuous Query help 4. Read-through and Write-through handlers 5. Caching strategies for different relationship types 6. Sharing data through database synchronization 7. High availability and scalability of distributed cache

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Runtime Data Sharing
through
a Distributed Cache
Iqbal Khan
iqbal@alachisoft.com Ph: +1 (925) 236-2125
Alachisoft
.NET Performance Solutions

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What is Runtime Data Sharing?
1. Server Apps Sharing Application Data Changes
 Connected to a relational database
 Data changed in the database and then shared
2. Server Apps Sharing Transient Data
 This data is never stored in the database
 Data is created at runtime, shared, and then destroyed
3. Server Apps Mix of .NET and Java
 Data sharing may be between .NET and Java apps as well

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Traditional Data Sharing Mechanisms
1. Relational Databases
 Polling
 Database notifications (SQL Server Query Notifications or Oracle Database
Change Notifications)
 Performance and scalability issues
2. Message Queues
 Message focused (not data focused)
 Not intended for large data sets
 Performance and scalability issues
3. Web Services or Remote Procedure Calls
 Too complicated to develop and manage
 Weakness: sender and receiver not decoupled

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Use
Fast & Scalable
Distributed Cache
The Solution
NCache

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What is a Distributed Cache?
1. Cluster of cache servers
 Pools their memory and CPU
2. Synchronizes cache across all servers
 Updates immediately visible
3. Linearly scales transaction & memory capacity
 Add servers to grow capacity
4. Replicates data for reliability
 Without compromising performance & scalability

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Distributed Cache Deployment Architecture
Filesystem Database Servers Mainframe
Distributed Cache Cluster
Windows 2008/2012 (64-bit)
Scale Horizontally
Memory pooled from all cache servers
Grid Computing Apps
(.NET/Java)
Web Services (.NET/Java) Server Apps (.NET/Java)Web Apps (.NET/Java)

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Following Apps use Distributed Cache
1. Web Apps (.NET & Java)
 To handle millions of users
2. Web Services (.NET & Java)
 To handle millions of requests
3. Big Data Apps (.NET & Java)
 To quickly process very large amounts of data thru distribution
4. Grid Computing Apps (.NET & Java)
 To process very large computations thru distribution
5. Other Server Apps (.NET & Java)
 To handle millions of requests

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Three Common Uses of Distributed Cache
1. App Data Caching (for Database Bottlenecks)
 In-memory cache faster than database
 Cache linearly scalable which database is not
2. Reliable & Scalable Cache for ASP.NET Specific Data
 ASP.NET Session State storage (most common)
 ASP.NET View State cache
 ASP.NET Output Cache provider
3. Scalable Runtime Data Sharing
 Faster & more scalable than traditional message queues
 Async data sharing in producer/consumer model
 Powerful event notifications & continuous queries for app coordination

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Scalable Event Notifications for Data Sharing

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Event Notification Types for Data Sharing
1. Event Notifications between .NET and Java Apps
 .NET and Java apps can send event notifications to each other
2. Data Focused Event Notifications
 Whenever some data in the cache changes
3. Message Based Event Notifications
 Publish/subscribe model
 Message sent to one or more subscribers

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.NET and Java App Event Notifications
1. Binary Portable Format
 Data and messages in the cache can use Binary Portable Format
 .NET objects can be read back as Java objects and vice versa
 No XML based costly transformations needed
2. Events Notifications between .NET & Java Apps
 .NET and Java apps can send event notifications to each other

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Data Focused Event Notifications
1. Item Level Event Notifications
 When specific cached items change (update/remove)
2. Group Level Event Notifications
 When any data in a group changes (add/update/remove)
 NCache 4.6 will have this feature
3. Cache Level Event Notifications
 When any data in the cache changes (add/update/remove)
4. Continuous Query Event Notifications
 When any data in a dataset in the cache changes (add/update/remove)
 Dataset defined through SQL-like criteria

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Item Level Event Notifications
// Define and item level event handler function
static void OnCacheDataModification (string key, CacheEventArg args)
{
switch(args.EventType)
{
case EventType.ItemRemoved:
break;
case EventType.ItemUpdated:
break;
}
}
// Register item level event handler function with a “key”
CacheDataNotificationCallback dataNotificationCallback
= new CacheDataNotificationCallback( OnCacheDataModification );
CacheEventDescriptor EventDescriptor
= cache.RegisterCacheNotification (key, dataNotificationCallback,
EventType.ItemRemoved | EventType.ItemUpdated,
EventDataFilter.DataWithMetadata);

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Cache Level Event Notifications
// Define the event handler function
static void OnCacheDataModification (string key, CacheEventArg args)
{
switch(args.EventType)
{
case EventType.ItemAdded:
break;
case EventType.ItemRemoved:
break;
case EventType.ItemUpdated:
break;
}
}
// Register event handler function
CacheDataNotificationCallback dataNotificationCallback
= new CacheDataNotificationCallback ( OnCacheDataModification );
CacheEventDescriptor EventDescriptor = cache.RegisterCacheNotification (
dataNotificationCallback,
EventType.ItemAdded |
EventType.ItemRemoved |
EventType.ItemUpdated,
EventDataFilter.DataWithMetadata );

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Continuous Query Event Notifications
string queryStr = "Select ClassLibrary.Product WHERE this.supplier = ?";
Hashtable values = new Hashtable();
values.Add("supplier", "Carlos Diaz");
ContinuousQuery cq = new ContinuousQuery(queryStr, values);
cq.RegisterNotification (
new QueryDataNotificationCallback (ItemAddedCallBack),
EventType.ItemAdded, EventDataFilter.None );
cq.RegisterNotification (
new QueryDataNotificationCallback(QueryItemCallBack),
EventType.ItemUpdated | EventType.ItemRemoved , EventDataFilter.None);
cq.RegisterClearNotification (
new ContinuousQueryClearCallback(CacheClear));
cache.RegisterCQ ( cq );

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Message Based Event Notifications
1. App Generated Custom Event Notifications
 Publish/subscribe model
 App fires a notification into cache cluster, other apps receive it
2. Topic Based Event Notifications
 Publish/subscribe model
 Publisher sends a message against a topic to multiple subscribers
 NCache 4.6 will have this feature
3. Queue Based Event Notifications
 Publish/subscribe model
 Publisher sends a message to any one subscriber through cache cluster
 NCache 4.6 will have this feature

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App Generated Event Notifications
// Define a callback function
void CacheCustomEvent(object eventId, object data) { }
Product product = new Product();
// Registering custom event callback function
cache.CustomEvent += new CustomEventCallback(CacheCustomEvent);
//Raise custom event when needed
cache.RaiseCustomEvent("custom event id", product);

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Hands on Demo

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NCache Architecture
1. High Availability (100% Uptime)
 Peer to peer cluster
 Dynamic configuration
2. Scalability: Caching Topologies
 Mirrored, Replicated, Partitioned, and Partition-Replica Cache

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High Availability (100% Uptime)
Dynamic Cache Cluster
Cache Cluster
NCache Srv
Add
Server
At
Runtime
Remove
Server
At
Runtime
NCache Srv NCache Srv
Remote Clients (Web/App Servers) TCP based Cache Cluster
 Does not use Windows Clustering
 Peer to peer architecture
 No single point of failure
 Add/remove servers at runtime
 Without stopping cache or your app
 Data adjusted automatically based
on caching topology
 Hot Apply config changes
 Change config properties while
cache is running

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High Availability (100% Uptime)
Dynamic Configuration
 Cluster membership info
 Propagate to clients at runtime
 Cache topology info
 Propagate to clients at runtime
 Connection strategy at runtime
 Connection failover
 Clients auto-connect to other servers
Dynamic Cache Cluster
NCache Srv
Remote Clients (Web/App Servers)
NCache SrvNCache Srv
Cluster
Membership Info
Cache
Topology Info

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Caching Topologies
Mirrored Cache (2-node active/passive)
Server 1 Server 2
Mirrored Cache
1 2
3 4
5 6
Active
1 2
3 4
5 6
Passive
(Backup)
Async Backup
Remote Clients (Web/App Servers)
 All clients connect to active node
 Passive node becomes active if
active node goes down. Clients
also automatically connect to new
active node
 Mirroring to passive node done
asynchronously
 Recommended use:
 Up to 10 app servers
 2 cache server cluster

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Caching Topologies
Replicated Cache
 Each server has the entire cache
 Cache updates done to all servers
synchronously. So, they’re slower.
 Each clients connects to only one
cache server. All servers active.
 Good for read-intensive scenarios Server 1 Server 2
Replicated Cache
1 2
3 4
5 6
Active
Synchronous Updates
Remote Clients (Web/App Servers)
1 2
3 4
5 6
Active

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Caching Topologies
Partitioned Cache
 Extremely scalable
 Location transparency
 Good for large cache clusters
 Distribution map sent to all clients
at runtime
 No replication available
Server 1 Server 2
Partitioned Cache
Remote Clients (Web/App Servers)
21
Partition 1
43
Partition 2
Distribution
Map
Distribution
Map

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Caching Topologies
Partition-Replica Cache
 Each partition has one replica on a
different server. All created
automatically.
 Async & Sync replication options
 Extremely fast & scalable
 Reliability due to replicas
Server 1 Server 2
Partition-Replica Cache
Remote Clients (Web/App Servers)
21
Partition 1
43
Replica 2
43
Partition 2
21
Replica 1
Distribution
Map
Distribution
Map

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Conclusion
1. Distributed Cache is Better for Runtime Data Sharing
 Faster and more scalable
 Likely to be already available for your app
2. NCache is the leading distributed cache for .NET
 More feature rich product in the market

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Next Steps
 Download NCache 60-Day Trial (Fully Working)
 http://www.alachisoft.com/download.html
 Contact us for Personalized Architectural Demo
 Email: sales@alachisoft.com. Phone: +1 (925) 236-3830