Welcome!

Java IoT Authors: Liz McMillan, Elizabeth White, Pat Romanski, Jamie Maidson, Yakov Fain

Related Topics: Java IoT, Microservices Expo

Java IoT: Article

Scaling Java and JSP Apps with Distributed Caching

Keeping up with the high volume of transactions in JSP applications

Java is the technology of choice for high-end enterprise applications. The most common applications that developers are involved with are JavaServer Pages web applications, also known as JSP applications. JSP has become one of the two standards for developing high traffic web applications, the other being Microsoft ASP.NET. Being part of Java, JSP has been popular for a long time and is highly instrumental in promoting Web technologies for developing high-traffic applications. Millions of people are using JSP applications and those numbers keep growing.

These JSP applications are endowed with an architecture that scales very nicely. You can handle more and more users by adding more web servers to a load-balanced Web farm. As you have an increasing amount of transaction load, you just keep adding more servers to the Web farm. That way you can handle more transactions and more concurrent users.

However, all good things come to an end, and in this case data storage and data access are not able to keep up with the increasingly higher volume of transactions in JSP applications. Therefore, data storage and data access become a bottleneck in JSP applications. As the saying goes, "The strength of a chain is only as strong as its weakest link". While JSP architecture is very scalable, data storage starts to bring it down and thus a bottleneck is created.

There are two types of data primarily used in JSP applications. One is Servlet Session data. The other is normal application data that comes from the application database. This application database could be a relational database, a mainframe, or it could come from a Web services call. Both types of data storage incur scalability bottlenecks for high transaction loads.

Figure 1: JSP Application Facing Data Storage Bottlenecks

How do you address this issue and remove these scalability bottlenecks? The goal is not only to improve the performance although that is always nice, but rather to improve scalability. Scalability here is defined as the ability to maintain good performance even under peak transaction load. In effect, if you have five users, your Web application is probably very fast. If you have 500,000 users, it's probably going to not only slow down but actually choke. If you have good scalability, your 500,000 user performance would be very similar to a five-user performance.

Distributed Cache Eliminates Data Storage Bottlenecks
In-memory Distributed cache is the way to remove these scalability bottlenecks in JSP applications and improve scalability. It lets you cache application data and reduce those expensive database trips that are causing these bottlenecks. A distributed cache spans across multiple inexpensive cache servers and brings together their memory and CPU power to provide a very scalable architecture. It permits you to keep adding more cache servers to the distributed cache cluster as your transaction load increases. This gives you a linear scalability for handling transactions in JSP applications.

Figure 2: Distributed Cache Removing Bottlenecks in a JSP Application

A shown in Figure 2 a distributed cache efficiently fits into JSP application architecture; it provides the essential scalability and reduces pressure on the database. As a further note, it is important to know that unlike a database that uses persistent storage, a distributed cache uses volatile memory as its store. Therefore, a distributed cache ensures data reliability through data replication across multiple cache servers to warrant that all data is kept on at least two cache servers. Then, if any one server goes down, no data is lost.

There are two ways you can use distributed caching in JSP applications. One is for HTTP Session persistence. The second is application data caching that is also called object caching. Both of these help improve JSP application scalability in their own ways.

Using Distributed Cache for HTTP Session Persistence
Just like any regular Web application, JSP also uses HTTP Session to keep track of a user's session across multiple HTTP requests. By default, there are five persistence options provided for HTTP Session. They are:

  1. Memory (single server without replication): This doesn't work in a multi-server load balanced Web farm running a JSP application and therefore is not scalable at all.
  2. File system persistence: This has performance and scalability issues because all session are being persisted on a single file server and disk-based access is not as fast as in-memory access.
  3. JDBC persistence: This also has serious performance and scalability issues because a database server is unable to scale linearly whereas a load balanced Web farm can.
  4. Cookie-based persistence: This is very limiting because the entire session has to be sent to the user's browser and then returned back to the Web server at the time of next HTTP request. It consumes a lot of bandwidth as well and also slows down the response time because of it.
  5. Clustered session persistence (replicated) by a Servlet Engine: Each Servlet Engine has implemented its own scheme for replicating HTTP Session. These schemes at least support multi-server load-balanced Web farms with Session replication to ensure that no data loss occurs. But, the clustering and replication in all the leading Servlet engines (Apache Tomcat, JBoss, WebLogic, and WebSphere) are not very optimized for a high-transaction environment. As a result, you quickly run into scalability bottlenecks.

As you can see, none of the above options are ideal for a high-transaction multi-server environment. Although clustered session persistence by a Servlet Engine handles a multi-server environment, it still can't cope with the extreme transaction load that your JSP application needs to handle.

The best option is to use a distributed cache for JSP Session persistence. The reason is because unlike the Servlet Engine implementation of Session clustering and replication, a distributed cache scales very nicely in a linear fashion. This allows you to keep adding more cache servers to the mix as your transaction load increases. As a result, you never run into any scalability bottlenecks. In addition, a distributed cache usually provides various caching topologies including an intelligent combination of data partitioning and data replication so along with scalability you would also get reliability through data replication.

Depending on the distributed caching vendor you use, you may already have a plug-in HTTP Filter. This automatically intercepts your HTTP calls and reads the JSP Session from the distributed cache before your JSP page is executed. Then, after the JSP page is done and it is sending a response back to the user, this HTTP Filter takes the JSP Session object and saves it back to the distributed cache. This means you don't have to write any special code for JSP Session persistence. You only make a configuration change.

Just plug in the HTTP filter and make changes in your configuration files and your JSP Sessions are automatically persisted in a distributed cache. However, you have to make sure that any object that you store in the JSP Session is serializable. Serialization is needed for shipping data across process boundaries and a distributed cache usually resides in its own process either on the Web server or on a separate dedicated server.

Using Distributed Cache for Application Data Caching
Just like a typical Web application, most JSP applications deal with data that is coming from an application database. This database could be a relational database like Oracle, IBM DB2, SQL Server, or MySQL. It could also be a mainframe or a Web service call to cloud-based storage. Either way, the data store is typically not able to handle a growing number of transactions and quickly slows down and even grinds to a halt if you put too much pressure on the database.

The second use of distributed cache is for application data caching. By deploying this particular caching, you significantly cut down on those expensive database trips for reading the same data over again, which is overwhelming the database server. This frees up the application database to handle writes more efficiently and handle a larger number of users. Another key benefit is that you cache transactional or read-write data in addition to caching read-only data. Transactional data is one that changes frequently, even as frequently as every 20 to 30 seconds. It's a good idea to cache this type of data because even during this short time, your application ends up reading this data many times. When you multiply this with the total number of users and transactions, you immediately realize that the overall traffic to the database reduces dramatically.

In caching application data, the goal is to reduce those application database trips by about 70 to 90%. This means 70 to 90% of the time you should not even be going to the database. Instead, you should just be getting your data from the distributed cache.

While you are reducing those expensive database trips, you are also eliminating scalability bottlenecks in your application database. Most often you modify your application source code to make calls to a distributed cache API. The following is an example of how you can use a distributed cache in a JSP application for caching application data.

<[email protected] import="com.alachisoft.ncache.web.caching.*" %>
...
<%
String cacheId = "mycache";
Cache _cache;

//Initializing the cache object ...

try {
_cache = DistCache.initializeCache(cacheId);
}
catch (Exception e){}

//Adding key (cache item name) and val (object) into the cache ...

try {
_cache.add(key, val, null, Cache.NoAbsoluteExpiration,

Cache.NoSlidingExpiration, CacheItemPriority.Default);

}
catch (Exception e){}

//Getting the object against a given key ...

try {
obj = _cache.get(key);
}
catch (Exception e){}
%>

Listing 1: Example of using a Distributed Cache in a JSP application

Using Distributed Cache Topologies
Let's now go back to what was earlier said about a distributed cache being highly scalable while at the same time providing data replication intelligently to ensure data reliability. A distributed cache usually provides multiple caching topologies to meet your environment. A caching topology consists of data storage and a client/server connection strategy.

A typical distributed cache would provide the following topologies to you:

  1. Mirrored Cache: This topology consists of two cache servers. One is active and the other is passive. All clients connect to the active server to do their reads and writes. All writes are asynchronously backed up to the passive cache server. If the active cache server goes down at runtime, the passive one becomes active and all clients connect to it automatically. You would use this normally if you only have one dedicated cache server and you use your database server or another server as the passive mirror. This topology handles reads and writes very efficiently but is limited in terms of storage capacity and transaction capacity since it cannot have more than two servers.
  2. Replicated Cache: This topology can have more than two servers. All are active and all contain an entire copy of the cache. Reads are super fast but writes are not as fast because they're made synchronously throughout the cache cluster. Also, adding more servers does not increase storage capacity. This topology is good when you're not making changes to cached data very frequently.
  3. Partitioned Cache: This topology can have more than two servers. All servers are active. The cache is broken down into partitions and each server contains one partition. As you add more servers, you grow storage capacity and also transaction capacity. This topology offers linear scalability but doesn't provide the data reliability as there is no replication of data.
  4. Partitioned-Replicated Cache: This topology is similar to the Partitioned Cache except that it also provides data replication at the partition level. Doing this allows it to scale linearly just like the Partitioned Cache while at the same time providing data reliability through replication.
  5. Client Cache (aka Near Cache): This topology works with any of the above four topologies. It is basically a local cache near your application and sits on your Web/application server. However, it's not a standalone cache and is in fact connected to the cache cluster. It gets informed by the cache cluster whenever there is any data change so it can update itself automatically. Client Cache provides further scalability to your applications because you reduce trips even to the cache cluster.

The most popular caching topology is a partitioned-replicated cache. As the name implies, this hybrid topology provides the benefits of partitioned cache, which is in terms of scalability. Simultaneously, it hands you the benefits of a replicated cache, which is reliability. This means all data is copied to two different servers. Other topologies are partitioned, replicated, and client cache. For the time being, let's focus on partitioned-replicated, and the others we will discuss later.

Figure 3: Example of a Partitioned-Replicated Caching Topology

Important Application Data Caching Features
There are several major and important features associated with a highly efficient distributed cache for application data caching. They are:

  • Absolute and sliding expirations
  • Cache dependency for managing relational data in the cache
  • Synchronize cache with a database
  • Read-through and write-through
  • Groups and tags
  • SQL-like Cache Query Language
  • Event Notifications

Absolute and sliding expirations allow you to specify when individual cache items should expire and be automatically removed from the cache. You can either specify an absolute date-time or an interval of inactivity as criteria. Cache dependency is particularly useful for managing data relationships. The majority of cached data comes from relational databases hence it has relationships. When keeping track of this data in the cache, you rely on the cache to manage data integrity and simplify your application.

Database synchronization also plays a big role in application data caching. Consider that the cache keeps a copy of the data that is in the database. If it changes in the database, it's more effective if the cache can automatically learn about it and synchronize itself. It can do that by removing that item from the cache o reloading a new copy from the database.

As far as read-through and write-through, at times, your application directly reads data from the database and caches it. Other times, you want the cache to read the data for you because this simplifies your application code and also provides other benefits. For this latter case, you need both read-through and write-through. Groups and tags come into play for grouping multiple cached items in various ways. That way you can easily locate them. Here, a group allows each item to relate to only one group. Conversely, with tags, you are provided with a many-to-many grouping with cached items. Both distributed cache traits provide you with great flexibility for fetching data and keeping track of it in the cache.

The last two major distributed caching attributes you should seek are SQL-like cache query event notifications. A typical cache fetch is based on a key since every cached item has a key. However, on certain occasions, you want to search for items based on other criteria. A cache query allows you to provide an SQL-like query to search the cache based on object attributes rather than the key.

In the area of event notifications, your application often wants to be notified when some data changes in the cache. An efficient cache provides various event propagation mechanisms. One is key-based event notification, which is triggered by an individual cached item update. Second is a general-purpose event triggered whenever anything in the cache is updated or removed. Third is a continuous query that is triggered whenever an item in a criteria-based data set in the cache is updated or removed. All of these allow your applications to make full use of the cache.

High Availability of Distributed Cache
A rule of thumb to remember is that you're using a distributed cache because you are anticipating a high transaction environment for your application. This usually means your JSP application has a greater impact on your business. Therefore, you can't afford any unscheduled downtimes for your application and even the scheduled downtimes should be very short and very infrequent.

Therefore, since a distributed cache runs in your data center as part of your JSP application, it must provide high availability in itself. One critical aspect of this high availability is that the cache cluster must be self-healing and totally dynamically configurable. Some caches provide a manually fixed cache cluster (so your application code creates and manages the cluster). Some other caches use master/slave architecture where if the master node goes down, all the slaves either stop working or become read-only. Both architectures are severely limiting and inflexible.

A highly efficient distributed cache has a peer-to-peer cache clustering that corrects itself automatically at runtime, thus self-healing if you add or remove cache servers from the cache cluster or if a cache server crashes for some reason. This is a highly important characteristic of a good distributed cache.

Conclusion
You should seriously consider incorporating a distributed cache both for application data caching and for session state storage if you are developing a JSP application targeted for a high transaction environment.

One last point - Caveat Emptor. Currently, there are a number of free distributed caches available. However, you must seriously consider the old tried and true saying, "there is no free lunch." Sure, you might think of not forking over any money for a free distributed cache. But, in the long run, the cost becomes exorbitant. If your JSP application is business-critical then you must consider the total cost of ownership and not just the price of a distributed cache or that it's free.

More Stories By Iqbal Khan

Iqbal Khan is the President and Technology Evangelist of Alachisoft. Alachisoft provides NCache, a Java and .NET distributed cache for boosting performance and scalability in enterprise applications. Iqbal received his MS in Computer Science from Indiana University, Bloomington, in 1990. You can reach him at [email protected]

Comments (0)

Share your thoughts on this story.

Add your comment
You must be signed in to add a comment. Sign-in | Register

In accordance with our Comment Policy, we encourage comments that are on topic, relevant and to-the-point. We will remove comments that include profanity, personal attacks, racial slurs, threats of violence, or other inappropriate material that violates our Terms and Conditions, and will block users who make repeated violations. We ask all readers to expect diversity of opinion and to treat one another with dignity and respect.


@ThingsExpo Stories
In his session at 18th Cloud Expo, Bruce Swann, Senior Product Marketing Manager at Adobe, will discuss how the Adobe Marketing Cloud can help marketers embrace opportunities for personalized, relevant and real-time customer engagement across offline (direct mail, point of sale, call center) and digital (email, website, SMS, mobile apps, social networks, connected objects). Bruce Swann has more than 15 years of experience working with digital marketing disciplines like web analytics, social med...
SYS-CON Events announced today that Enzu, a leading provider of cloud hosting solutions, will exhibit at SYS-CON's 18th International Cloud Expo®, which will take place on June 7-9, 2016, at the Javits Center in New York City, NY. Enzu’s mission is to be the leading provider of enterprise cloud solutions worldwide. Enzu enables online businesses to use its IT infrastructure to their competitive advantage. By offering a suite of proven hosting and management services, Enzu wants companies to foc...
Customer experience has become a competitive differentiator for companies, and it’s imperative that brands seamlessly connect the customer journey across all platforms. With the continued explosion of IoT, join us for a look at how to build a winning digital foundation in the connected era – today and in the future. In his session at @ThingsExpo, Chris Nguyen, Group Product Marketing Manager at Adobe, will discuss how to successfully leverage mobile, rapidly deploy content, capture real-time d...
A strange thing is happening along the way to the Internet of Things, namely far too many devices to work with and manage. It has become clear that we'll need much higher efficiency user experiences that can allow us to more easily and scalably work with the thousands of devices that will soon be in each of our lives. Enter the conversational interface revolution, combining bots we can literally talk with, gesture to, and even direct with our thoughts, with embedded artificial intelligence, wh...
IoT generates lots of temporal data. But how do you unlock its value? How do you coordinate the diverse moving parts that must come together when developing your IoT product? What are the key challenges addressed by Data as a Service? How does cloud computing underlie and connect the notions of Digital and DevOps What is the impact of the API economy? What is the business imperative for Cognitive Computing? Get all these questions and hundreds more like them answered at the 18th Cloud Expo...
As cloud and storage projections continue to rise, the number of organizations moving to the cloud is escalating and it is clear cloud storage is here to stay. However, is it secure? Data is the lifeblood for government entities, countries, cloud service providers and enterprises alike and losing or exposing that data can have disastrous results. There are new concepts for data storage on the horizon that will deliver secure solutions for storing and moving sensitive data around the world. ...
What a difference a year makes. Organizations aren’t just talking about IoT possibilities, it is now baked into their core business strategy. With IoT, billions of devices generating data from different companies on different networks around the globe need to interact. From efficiency to better customer insights to completely new business models, IoT will turn traditional business models upside down. In the new customer-centric age, the key to success is delivering critical services and apps wit...
The IoT is changing the way enterprises conduct business. In his session at @ThingsExpo, Eric Hoffman, Vice President at EastBanc Technologies, discuss how businesses can gain an edge over competitors by empowering consumers to take control through IoT. We'll cite examples such as a Washington, D.C.-based sports club that leveraged IoT and the cloud to develop a comprehensive booking system. He'll also highlight how IoT can revitalize and restore outdated business models, making them profitable...
The essence of data analysis involves setting up data pipelines that consist of several operations that are chained together – starting from data collection, data quality checks, data integration, data analysis and data visualization (including the setting up of interaction paths in that visualization). In our opinion, the challenges stem from the technology diversity at each stage of the data pipeline as well as the lack of process around the analysis.
Designing IoT applications is complex, but deploying them in a scalable fashion is even more complex. A scalable, API first IaaS cloud is a good start, but in order to understand the various components specific to deploying IoT applications, one needs to understand the architecture of these applications and figure out how to scale these components independently. In his session at @ThingsExpo, Nara Rajagopalan is CEO of Accelerite, will discuss the fundamental architecture of IoT applications, ...
SYS-CON Events announced today that ContentMX, the marketing technology and services company with a singular mission to increase engagement and drive more conversations for enterprise, channel and SMB technology marketers, has been named “Sponsor & Exhibitor Lounge Sponsor” of SYS-CON's 18th Cloud Expo, which will take place on June 7-9, 2016, at the Javits Center in New York City, New York. “CloudExpo is a great opportunity to start a conversation with new prospects, but what happens after the...
SYS-CON Events announced today that MangoApps will exhibit at SYS-CON's 18th International Cloud Expo®, which will take place on June 7-9, 2016, at the Javits Center in New York City, NY. MangoApps provides modern company intranets and team collaboration software, allowing workers to stay connected and productive from anywhere in the world and from any device. For more information, please visit https://www.mangoapps.com/.
SYS-CON Events announced today that 24Notion has been named “Bronze Sponsor” of SYS-CON's 18th Cloud Expo, which will take place on June 7-9, 2016, at the Javits Center in New York, New York. 24Notion is full-service global creative digital marketing, technology and lifestyle agency that combines strategic ideas with customized tactical execution. With a broad understand of the art of traditional marketing, new media, communications and social influence, 24Notion uniquely understands how to con...
WebRTC is bringing significant change to the communications landscape that will bridge the worlds of web and telephony, making the Internet the new standard for communications. Cloud9 took the road less traveled and used WebRTC to create a downloadable enterprise-grade communications platform that is changing the communication dynamic in the financial sector. In his session at @ThingsExpo, Leo Papadopoulos, CTO of Cloud9, will discuss the importance of WebRTC and how it enables companies to fo...
SYS-CON Events announced today TechTarget has been named “Media Sponsor” of SYS-CON's 18th International Cloud Expo, which will take place on June 7–9, 2016, at the Javits Center in New York City, NY, and the 19th International Cloud Expo, which will take place on November 1–3, 2016, at the Santa Clara Convention Center in Santa Clara, CA. TechTarget is the Web’s leading destination for serious technology buyers researching and making enterprise technology decisions. Its extensive global networ...
Korean Broadcasting System (KBS) will feature the upcoming 18th Cloud Expo | @ThingsExpo in a New York news documentary about the "New IT for the Future." The documentary will cover how big companies are transmitting or adopting the new IT for the future and will be filmed on the expo floor between June 7-June 9, 2016, at the Javits Center in New York City, New York. KBS has long been a leader in the development of the broadcasting culture of Korea. As the key public service broadcaster of Korea...
With major technology companies and startups seriously embracing IoT strategies, now is the perfect time to attend @ThingsExpo 2016 in New York and Silicon Valley. Learn what is going on, contribute to the discussions, and ensure that your enterprise is as "IoT-Ready" as it can be! Internet of @ThingsExpo, taking place Nov 3-5, 2015, at the Santa Clara Convention Center in Santa Clara, CA, is co-located with 17th Cloud Expo and will feature technical sessions from a rock star conference faculty ...
The 19th International Cloud Expo has announced that its Call for Papers is open. Cloud Expo, to be held November 1-3, 2016, at the Santa Clara Convention Center in Santa Clara, CA, brings together Cloud Computing, Big Data, Internet of Things, DevOps, Containers, Microservices and WebRTC to one location. With cloud computing driving a higher percentage of enterprise IT budgets every year, it becomes increasingly important to plant your flag in this fast-expanding business opportunity. Submit y...
There are several IoTs: the Industrial Internet, Consumer Wearables, Wearables and Healthcare, Supply Chains, and the movement toward Smart Grids, Cities, Regions, and Nations. There are competing communications standards every step of the way, a bewildering array of sensors and devices, and an entire world of competing data analytics platforms. To some this appears to be chaos. In this power panel at @ThingsExpo, moderated by Conference Chair Roger Strukhoff, panelists will discuss the vast to...
Internet of @ThingsExpo, taking place November 1-3, 2016, at the Santa Clara Convention Center in Santa Clara, CA, is co-located with the 19th International Cloud Expo and will feature technical sessions from a rock star conference faculty and the leading industry players in the world and ThingsExpo New York Call for Papers is now open.