Weblogic error unmarshaller failed relationship

java - omarcafini.infoptorException: Unmarshaller failed - Stack Overflow

directory is less than 1 GB, the Hub Server installation might fail. . If the MDM Hub runs with a WebLogic application server and multiple Process Servers When you create a relationship between two timeline-enabled base objects, .. SIP Error unmarshalling the XML string to object using the. When I deploy my Seam-JPA application onto WebLogic , I get the [exec] Error> failed to unmarshal class omarcafini.info .. The really interesting thing is this: this inability to deploy only occurs when I set my join relationships to. package omarcafini.info; import omarcafini.infoller. so that your application does not fail if you change JAXB implementations. .. One of reasons for shorter release cycles of the JDK is the ability to roll out faster security bug fixes and enhancements. . Difference Between C++ and Java.

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It exposes a JSR compatible Cache interface which in turn extends java. Map in which you can store objects. While Infinispan can be run in local mode, its real value is in distributed mode where caches cluster together and expose a large memory heap. Distributed mode is more powerful than simple replication since each data entry is spread out only to a fixed number of replicas thus providing resilience to server failures as well as scalability since the work done to store each entry is constant in relation to a cluster size.

So, why would you use it? Massive heap and high availability - If you have blade servers, and each node has 2GB of space to dedicate to a replicated cache, you end up with 2 GB of total data. Every server is just a copy. On the other hand, with a distributed grid - assuming you want 1 copy per data item - you get a GB memory backed virtual heap that is efficiently accessible from anywhere in the grid.

If a server fails, the grid simply creates new copies of the lost data, and puts them on other servers. Scalability - Since data is evenly distributed there is essentially no major limit to the size of the grid, except group communication on the network - which is minimised to just discovery of new nodes. All data access patterns use peer-to-peer communication where nodes directly speak to each other, which scales very well. Infinispan does not require entire infrastructure shutdown to allow scaling up or down.

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Data distribution - Infinispan uses consistent hash algorithm to determine where keys should be located in the cluster. Consistent hashing allows for cheap, fast and above all, deterministic location of keys with no need for further metadata or network traffic.

The goal of data distribution is to maintain enough copies of state in the cluster so it can be durable and fault tolerant, but not too many copies to prevent Infinispan from being scalable. This means that Infinispan is not just useful to Java. Any major website or application that wants to take advantage of a fast data grid will be able to do so.

Support for Compute Grids - Infinispan 5 adds the ability to pass a Runnable around the grid. This allows you to push complex processing towards the server where data is local, and pull back results using a Future.

Also see this page on the Infinispan website. What would I use Infinispan for? Most people use Infinispan for one of two reasons. Firstly, as a distributed cache. Putting Infinispan in front of your database, disk-based NoSQL store or any part of your system that is a bottleneck can greatly help improve performance. A distributed cache can greatly help here. The other major use-case is as a NoSQL data store.

In addition to being in memory, Infinispan can also persist data to a more permanent store. We call this a cache store. Cache stores are pluggable, you can easily write your own, and many already exist for you to use. A less common use case is adding clusterability and high availability to frameworks.

Since Infinispan exposes a distributed data structure, frameworks and libraries that also need to be clustered can easily achieve this by embedding Infinispan and delegating all state management to Infinispan. This way, any framework can easily be clustered by letting Infinispan do all the heavy lifting. How is Infinispan related to JBoss Cache?

Certain design ideas and indeed some code have been borrowed from JBoss Cache 3. Infinispan is a complete, separate and standalone project. Some may consider this a fork, but the people behind Infinispan and JBoss Cache see it as an evolution, since all future effort will be on Infinispan and not JBoss Cache. What version of Java does Infinispan need to run? Does Infinispan need an application server to run?

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All that is needed is a Java 8 compatible JVM. An application server is not a requirement. Yes, and this is called Hibernate OGM. How come Infinispan's first release is 4. A lot of the code, designs and ideas in Infinispan are from JBoss Cache, and has been tried and tested, proven in high stress environments.

Infinispan should thus be viewed as a mature and stable platform and not a new, experimental one. Infinispan core engineers are on the JSR expert group and starting with version 7. Can I use Infinispan with Hibernate? Yes, you can combine one or more of these integrations in the same application: Using Infinispan as a database replacement: For more details see Hibernate OGM. Hibernate can cache frequently loaded entities and queries in Infinispan, taking advantage of state of the art eviction algorithms, and clustering if needed but it provides a good performance boost in non-clustered deployments too.

You can store the index in Infinispan: Using full-text queries on Infinispan: A combination of multiple such integrations: What APIs does Infinispan offer? Cache - extends java. ConcurrentMap and closely resembles javax. Cache from JSR This is the most performant API to use, and should be used for all new projects. Note that the similarities end at the interface though, since internal implementation and representation of the tree is completely different, using a much more efficient flat structure.

TreeCache should be considered as a compatibility API, if you are migrating from JBoss Cache and cannot invest the time in rewriting your application, or your application specifically relies on a tree structure. Infinispan is developed and primarily tested against Oracle Java SE 8.

Does Infinispan store data by value or by reference? By default, Infinispan stores data by reference.

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So once clients store some data, clients can still modify entries via original object references. The way store-by-value is enabled is by enabling Infinispan to store data in binary format and forcing it to do these binary transformations eagerly. The reason Infinispan stores data by-reference instead of by-value is performance. Storing data by reference is quicker than doing it by value because it does not have the penalty of having to transform keys and values into their binary format.

Can I use Infinispan with Groovy? Cache Loader and Cache Store questions 2. Please read Persistence for information about the persistence SPI. Are modifications to asynchronous cache stores coalesced or aggregated? Modifications are coalesced or aggregated for the interval that the modification processor thread is currently applying.

What does the passivation flag do? Passivation is a mode of storing entries in the cache store only when they are evicted from memory. The benefit of this approach is to prevent a lot of expensive writes to the cache store if an entry is hot frequently used and hence not evicted from memory. The reverse process, known as activation, occurs when a thread attempts to access an entry which is not in memory but is in the store i. Activation involves loading the entry into memory, and then removing it from the cache store.

With passivation enabled, the cache uses the cache store as an overflow tank, akin to swapping memory pages to disk in virtual memory implementations in operating systems. If passivation is disabled, the cache store behaves as a write-through or write-behind if asynchronous cache, where all entries in memory are also maintained in the cache store.

The effect of this is that the cache store will always contain a superset of what is in memory. See the setDataColumnType javadoc for more details. This optimization skips a cache store read and can have very significant performance improvement effects. For more information, check out our Performance Guide.