We have a solution which uses the Apache Ignite-provided In-Memory Data Grid as a distributed cache. For newer projects, we ended up using Spring, and as such we wished homogenize our software ecosystem and using Spring for the first solution as well. In addition, we do not use all the features of Ignite to excuse its use (discovery, caching).
Since we currently only use a limited subset of features from Ignite, we are basically looking for a self-managed application-level distributed cache solution (similar to what Ignite provides). This means that dedicated caching infrastructure like Redis, Memcached, etc. is not what we want.
I've researched the topic somewhat and found that there are some possible alternatives like:
Tayzgrid - Last update seems to be quite some time ago, not sure if still actively maintained
Druid - Still incubating, and I have also read that new releases being somewhat broken was not that uncommon
Hazelcast - Seems like the best choice given its maturity and the existence of Spring Data Hazelcast, though I am unsure what the level of support is here.
Has anyone has experience with integrating one of the above IMDGs (aside from Ignite) with Spring Cache? Any pointers in the right direction would be greatly appreciated.
You can use Redisson - Redis Java client with features of
In-Memory Data Grid. It also implements Spring Data support. Here is the documentation.
Hazelcast has official support for Spring Data Hazelcast and also this module has many users as now. I can also suggest you to have a look at the resources below:
Using Hazelcast with Spring Data
Getting Started with Microservices Using Hazelcast IMDG and Spring Boot
Related
I am trying to implement cache mechanism provide by Spring Data GemFire. Has anyone implemented a solution? I need to check on performance and ease to implement it.
Sonal-
First, you can find plenty of examples in the Spring User Guides, here, for example...
Accessing Data with GemFire,
Caching Data with GemFire, and ...
Accessing GemFire Data with REST
Additionally, there is a Spring GemFire Examples project here.
I have also started work on building a "Reference Implementation" (RI) for Spring Data GemFire/Geode, here. I have much work to do with this project yet, like documentation (READMEs) in the Repo, but I do plan to keep it up-to-date with my latest developments since I use the code as a basis for all my conference talks. Anyway, there is plenty of code examples and tests in this GitHub project to keep you busy for awhile.
Then, the Spring Data GemFire and Spring Data Geode GitHub projects themselves, have plenty of tests to show you how to address different application concerns (Configuration, Data Access, Function Execution, etc, etc).
Of particular interests might be the new Annotation-based configuration model for SDG^2 that I am working on. This is currently a WIP and I am also working on User Guide documentation for this feature/functionality, but it is established and even inspired by the auto-configuration features and Annotations provided by Spring and Spring Boot (e.g. #EnableXYZ).
Users have even started using the Annotation-based configuration model without significant documentation in place since it builds on concepts already available and familiar in Spring Boot. In fact combining these SDG specific Annotations with Spring Boot makes for a very powerful combination while preserving simple/easy nature to get started, 1 of my primary goals.
Given the lack of documentation yet, you can find more out in the Spring IO blog, where I first blogged about it here. Then I expanded on this article in a second blog, talking specifically about security.
And if you are really curious, you can follow the latest developments of the Annotation configuration model in my testing efforts.
Finally, of course, as I have already alluded to, as any good developer knows, getting started is as easy following the examples and reviewing Spring Data GemFire Reference Guide and Javadoc.
Don't forget to familiarize yourself with Pivotal GemFire as well! Javadoc here.
Hope this helps!
-John
I've got an application that uses Spring Cache (Ehcache), but now we need to add a 2nd node (same application). Can the cache be shared between the nodes or each with their own instance but synched?
Or do I need to look at a different solution?
Thanks.
That depends on your cache implementation - not on Spring, which only provides an abstract caching API. You are using EhCache as your caching implementation, which comes with a Terracotta server for basic clustering support and is open source. See http://www.ehcache.org/documentation/3.1/clustered-cache.html#clustering-concepts for more details
I want to cluster EHCache in Play Framework 2.x web application in several node. Why everyone recommend to avoid to use EHCache as a distributed cache in Play 2.x clustered web application?
I use nginx proxy to serve request across Play node and i want to make default EHCache of each node share its content.
Well according to this EHCache page, using EHCache in distributed mode is a commercial product. So if you want to use a free distributed cache, you need something different like Memcached or Redis.
My experience deploying a (Java)Play 2.2.3 to Amazon EC2 was terrible with EHCache. It requires a few workarounds with the localhost resolve (going su for each of your nodes - hard work when you have a few dozens of servers) and regardless, being free only for standalone version without ostensively letting us know upfront is a big no-no for me. I'm done with EHCache.
Edit: moved to Redis in 2015 (thanks #Traveler)
I am not aware of any Play Framework issues here, but the use of ehcache 2.x should fine as you can set it up with JGroups (faster than RMI) and use invalidation mode (infinispan slang).
Invalidation is a clustered mode that does not actually share any data at all, but simply aims to remove data that may be stale from remote caches. This cache mode only makes sense if you have another, permanent store for your data.
In ehcache 2.x you can set up invalidation mode with replicatePuts=false in your jgroups config.
In ehcache 3.x they do not have such a mode. You have to set up a commercial Terracotta server which is a distributed cache. So all date is moved between nodes and the terracotta server.
We tried it once and failed terribly.
As ehcache2.x is no longer active we just switched to Infinispan which has all features of ehcache2.x and a lot more.
So my recommendation: Use ehcache 2.x or infinispan. Do not use ehcache 3.x
I am putting together a regular Java EE application on jboss7 that will use JPA in the data tier. I would like to make this application such that it scales up with load. While it is pretty clear how to scale up the web tier: create more machines and throw them behind a load balancer, scaling up the data tier is less so.
I can probably cluster my database (MySQL). Stil, that leaves the JPA layer unclustered. Ideally, JPA will scale up by using in (clustered) memory caching backed by MySQL.
When I look around, all information around JPA scaling seems to be 3-4 years old. People talk about ehcache, memcached and infinispan. I am not sure if this is still current.
Can someone tell me the state of the art in Java EE clustering and scaling, especially in the data tier.
Various caching strategies are still the way to scale JPA/Hibernate (you basically named the most popular options in your question). Nothing extraordinary happend since 4-5 years in this field, as far as I know. One more option you haven't mentioned is JBoss Cache. So the Second Level Cache for JPA/Hibernate still rules in this area.
Why no progress here? My wild guess is that first of all people, who need scalable application tend to ignore JPA and Hibernate in areas where high performance is needed. Usually people go with SQL dressed in Spring Framework JDBCTemplate helpers and transaction management. Then scalability is the matter of database capabilities in this area.
The other trend is to use No-SQL databases. There is plany of solutions: MongoDB, CouchoDB, Cassandra, Redis, to name a few. These are usually Google BigTable like key-value storages (this is oversimplification, but it is more or less the idea behind that approach) and they scale as hell, if you accept their limitations (relations are no longer managed easily, etc.).
There are many solutions, the two main categories of solutions are:
scaling the database
using a clustered cache to reduce database load
EclipseLink supports data partitioning for sharding data across a set of database instances,
see:
http://java-persistence-performance.blogspot.com/2011/05/data-partitioning-scaling-database.html
You can also use MySQL Cluster,
see:
http://www.mysql.com/products/cluster/
Oracle TopLink Grid provides EclipseLink JPA support for integration with Oracle Coherence as a distributed cache,
see:
http://www.oracle.com/technetwork/middleware/ias/tl-grid-097210.html
EclipseLink's cache supports clustering through cache coordination,
see:
http://wiki.eclipse.org/EclipseLink/Examples/JPA/CacheCoordination
Does anybody has an experience with Spring Integration project as embedded ESB?
I'm highly interesting in such use cases as:
Reading files from directory on schedule basis
Getting data from JDBC data source
Modularity and possibility to start/stop/redeploy module on the fly (e.g. one module can scan directory on schedule basis, another call query from jdbc data source etc.)
repeat/retry policy
UPDATE:
I found answers on all my questions except "Getting data from JDBC data source". Is it technically possible?
Remember, "ESB" is just a marketing term designed to sell more expensive software, it's not a magic bullet. You need to consider the specific jobs you need your software to do, and pick accordingly. If Spring Integration seems to fit the bill, I wouldn't be too concerned if it doesn't look much like an uber-expensive server installation.
The Spring Integration JDBC adapters are available in 2.0, and we just released GA last week. Here's the relevant section from the reference manual: http://static.springsource.org/spring-integration/docs/latest-ga/reference/htmlsingle/#jdbc
This link describes the FileSucker with Spring Integration. Read up on your Enterprise Integration patterns for more info I think.
I kinda think you need to do a bit more investigation your self, or do a couple of tries on some of your usecases. Then we can discuss whats good and bad
JDBC Adapters appear to be a work in progress.
Even if there is no specific adapter available, remember that Spring Integration is a thin wrapper around POJOs. You'll be able to access JDBC in any component e.g. your service activators.
See here for a solution based on a polling inbound channel adapter too.