A new data grid JSR
Following up on my previous response to Antonio Goncalves' blog post, I have submitted a JSR to the JCP on a data grid standard, titled "Java Data Grids". It has yet to be assigned a number by the JCP, but I thought I’d talk about it a little here anyway.
Here is the description of the JSR that I have submitted:
This specification proposes to provide an API for accessing, storing, and managing data in a distributed data grid. The primary API will build upon and extend JSR-107 (JCACHE) API. In addition to it’s genericized Map-like API to access a Cache, JSR-107 defines SPIs for spooling in-memory data to persistent storage, an API for obtaining a named Cache from a CacheManager and an API to register event listeners. Above and beyond JSR-107, this JSR will define characteristics and expectations from eviction, replication and distribution, and transactions (via the JTA specification). Further, it would define an asynchronous, non-blocking API as an alternative to JSR-107’s primary API, as non-blocking access to data becomes a concern when an implementation needs to perform remote calls, as in the case of a data grid. This specification builds upon JSR-107, which is not yet complete. We intend to work with the JSR-107 EG to ensure that their schedule is compatible with the schedule for this JSR. If JSR-107 is unable to complete, we propose merging the last available draft into this specification.
Data grids are gaining prominence and importance in enterprise Java, particularly as cloud-style deployments gain popularity:
-
Characteristics such as high availability, along with removal of single points of failure become increasingly important, since cloud infrastructure is inherently unreliable and can be re-provisioned with minimal notice; applications deployed on cloud need to be resilient to this.
-
Further, one of the major benefits of cloud-style deployments is elasticity. The ability to scale out (and back in) quickly and easily. Again, data grids have a role to play here.
-
Finally, with scalable middleware comes additional stress on the data tier (traditionally an RDBMS), as middleware nodes scale out to cope with load. Data grids - used as a distributed cache - can help with mitigating database bottlenecks.
With one of Java EE 7’s stated goals being "cloud-friendliness", the above are powerful arguments for the inclusion of a distributed data grid standard in Java EE 7.
What about JSR-107? JSR-107 - the temporary caching API proposed in 2001 - certainly has a role to play in Java EE too. Temporary caches are an important part of enterprise middleware, but yet a standard has been sadly missing from a Java EE umbrella specification for far too long. Spring, having identified the need as well, has a temporary caching abstraction in their current development versions. Several other non-Java frameworks define temporary caching APIs too (Ruby on Rails, Django for Python, .NET). There is no denying JSR-107 is necessary, and necessary as a part of Java EE.
But JSR-107 isn’t a data grid. JSR-107 falls short as a standard for data grids, specifically as it doesn’t take into account characteristics of distribution and replication of data, and doesn’t define a contract that implementations would have to adhere to when it comes to moving data around a cluster. Crucial things for a data grid that, if not baked into a specification, will hinder portability and render the standard itself useless and impotent.
Further, with remote capabilities in mind, a data grid should also expose a non-blocking API, since network calls can be a limiting factor. Invoking methods that involve remote calls should be able to be done in an asynchronous fashion. Stuff that is irrelevant to a temporary caching API like JSR-107.
So with all that in mind, I’d love to hear your thoughts on the data grid JSR. In addition to Red Hat, the JSR is currently backed by a major Java EE and data grid vendor which cannot be named at this stage, along with independent JCP members with relevant interest and background.
Cheers Manik
Get it, Use it, Ask us!
We’re hard at work on new features, improvements and fixes, so watch this space for more announcements!Please, download and test the latest release.
The source code is hosted on GitHub. If you need to report a bug or request a new feature, look for a similar one on our JIRA issues tracker. If you don’t find any, create a new issue.
If you have questions, are experiencing a bug or want advice on using Infinispan, you can use GitHub discussions. We will do our best to answer you as soon as we can.
The Infinispan community uses Zulip for real-time communications. Join us using either a web-browser or a dedicated application on the Infinispan chat.
