gigaspaces

Data Distribution is usually used in high-performance computing (HPC. There are two main data distribution topologies: Replication and partitioning. In a Data Replication environment, a data item usually has several copies, but data consistency should be ensured to a certain extent, so that the end user can only have one copy of data globally. The biggest challenge to using data replication is to make a correct balance between data consistency and Performance Based on business needs. To achieve

Thanks to Li Zhi, who edited the cloud computing channel of the csdn website, my csdn blog has been put on the csdn homepage and has been addicted to "blog Star. It is also a shame. My csdn blog (http://blog.csdn.net/babyfacer/) is I in learning computer, write some notes, reprint some articles, basically don't take care of, there is no serious original, and the big bull are far away. It is only a personal technical memorandum. Some time ago, I was a bit confused about the agent's cloud computin

latest 3.5 reference documents do not mention how to use the new caching method. For the following reasons, we will continue to focus on the old approach: only JBoss Cache 2, Infinispan 4 and Ehcache 2 are supported by all popular hibernate level two cache providers. Oscache, Swarmcache, coherence and gigaspaces Xap-data Grid only support old methods. Both methods share the same 4.8.1 caching mechanism based on Cacheprovider Understanding the mechani

, that is, the message is received in the order sent. The benefit of a session is that it supports transactions. If the user chooses transaction support, the session context saves a set of messages until the transaction is committed. The user can use a rollback operation to cancel these messages before committing the transaction. A session allows a user to create a message producer to send a message, creating a message consumer to receive the message. JMS flowchart JMS provider implementation

caching system provides a graphical management console, easy to unified maintenance;5) Distributed Code Execution (distributed code Execution): Transfer the task code to the data nodes to execute in parallel, and the client aggregation returns the result, thus effectively avoiding the movement and transmission of the cached data. Latest Java Data grid specification JSR-347 has added distributed code execution and Map/reduce API support to mainstream distributed cache products such as IBM WebSph

provides NoSQL performance for applications that require a large number of unstructured data stores. Tables can be automatically scaled to terabytes and accessed through the rest and managed APIs.· Other columns store the database.In-memory data grid· hazelcast: Hazelcast CE is an open source data distribution platform that allows developers to share and split data on top of a DB cluster.· Oracle Coherence: Oracle's in-memory data grid solution provides fast access to common data, consistent su

Gigaspaces), which leverages the memory of the application and the middle tier to reduce the workload of the database system. These caches are becoming more complex and have database features such as transactions, scope indexes, and queries (such as Gigaspaces already has these features). At the same time, database systems have caching capabilities, such as high-performance hash indexes and extensions acro

object itself in memory and guarantees extensibility. Common business and open source products such as the following:? hazelcast? Terracotta Enterprise Suite? VMware Gemfire? Oracle Coherence? gigaspaces XAP Elastic Caching Edition? IBM eXtreme Scale? JBoss Infinispan2ArchitectureIMDG the two core issues that need to be overcome are: capacity constraints and reliability. Typically,IMDG is designed to overcome limits on memory

NDatabase PicoLisp Acid-state ObjectDB Cloud database solution GigaSpaces Popular SpaceBased Grid Solution. GemFire GemFire provides memory-based Global Distributed Database Management with dynamic scalability, high performance, and fine-grained control. It is well integrated with Spring Framework, allowing developers to quickly and easily provide complex data management. Infinispan Scalable Java programming, highly available grid data management, op

from any previous database Grid database Source: Research on data grids and metadata sets. Data Model: space-based architecture Example: GigaSpaces, Coherence Advantage: suitable for high performance and high scalability of Transaction Processing What should your application use? The key is to realize that different applications require different data models and products. Select an appropriate data model and product. To understand What data models yo

, final consistency (non-acid), bulk data, etc. It's a wide variety, such as a column database (Hadoop/hbase, Cassandra, hypertable, Amazon simpledb, etc.), a document-type database (MongoDB, CouchDB, Orientdb, and so on), a key-value database (Azure Table Storage, Membase, Redis, Berkeley DB, memcachedb, etc.), graphics database (neo4j, Infinite graph, sones, bigdata, etc.), object-oriented database (DB4O, Versant, objectivity, starcounter, etc.), grid and cloud Database (

such as pattern ownership, easy replication support, simple APIs, final consistency (non-acid), bulk data, etc. It's a wide variety, such as a column database (Hadoop/hbase, Cassandra, hypertable, Amazon simpledb, etc.), a document-type database (MongoDB, CouchDB, Orientdb, and so on), a key-value database (Azure Table Storage, Membase, Redis, Berkeley DB, memcachedb, etc.), graphics database (neo4j, Infinite graph, sones, bigdata, etc.), object-oriented database (DB4O, Versant, objectivity, st

are already a number of available products, including IBM? Websphere? EXtreme scale,oracle Coherence and gigaspaces, both of which support the free memory of a cluster of JVMs as a cache rather than a single JVM. This makes the larger the number of merged JVMs, the greater the size of the cache support. If these JVMs are additional servers with CPUs, storage, and networks, the service for read requests is scalable. By using Write-behind technology, t

programming. BigTable databases Source: Google's paper BigTable. Data Model: column clusters. each row is theoretically different. Example: HBase, Hypertable, Cassandra Advantages: it processes a large amount of data, responds to extremely high write loads, and is highly available. it supports cross-data centers and MapReduce. Data structure Service Source :? Data Model: Dictionary operations, lists, sets, and string values Example: Redis Advantage: different from any previous databas

in memory and guarantees extensibility. Common business and open source products are as follows:? hazelcast? Terracotta Enterprise Suite? VMware Gemfire? Oracle Coherence? gigaspaces XAP Elastic Caching Edition? IBM eXtreme Scale? JBoss Infinispan2ArchitectureIMDG the two core issues that need to be overcome are: capacity constraints and reliability. Typically,IMDG is designed to overcome limits on memory capacity through hori

least a separate column configuration. Example: HBase, Hypertable, Cassandra Advantages: proper size control, good at dealing with large-scale write loads, high availability, support for multiple data centers, support for simplified ing Data Structure services Inheritance: Unknown Instance: Redis Data Model: the execution process is based on indexes, lists, sets, and string values. Advantage: bringing unprecedented fresh blood to database applications Grid database Inheritance: research on data

code to each data node in parallel execution, the client aggregation returns results, thus effectively avoiding the movement and transmission of the cached data. Latest Java The data grid specification JSR-347 has been added to the API support for distributed code execution and Map/reduce, and mainstream distributed cache products such as IBM WebSphere EXtreme scale,vmware gemfire,gigaspaces XAP and Red Hat Infinispan also supports this new programmi

: only JBoss Cache 2, Infinispan 4 and Ehcache 2 are supported by all popular hibernate level two cache providers. Oscache, Swarmcache, coherence and gigaspaces Xap-data grid only support old methods. Both methods share the same 3.1 caching mechanism based on Cacheprovider Understanding the mechanism is the key to making reasonable choices. The key class/interface is cacheconcurrencystrategy and its implementation classes for different caches in 4, as

scale,vmware gemfire,gigaspaces XAP and Red Hat Infinispan also supports this new programming model. 3.2 Typical scenarios for distributed caching can be grouped into the following categories: Page caching. A fragment of content used to cache Web pages, including HTML, CSS, and images, for social networking sites; Application object caching. The caching system serves as a level two cache of ORM framework to reduce the load pressure of the database an

Recently, people are thinking about how to use Java to implement cloud computing, and I see two trends. They overlap rather than repel each other, but in general they have very different performance in terms of projects: Re-ui (Heavy UI oriented) This type of application or framework typically provides a UI-based console, administrative usefulness, plug-ins, and so on, providing the only way to manage resources in the cloud, such as starting and stopping images. The key feature of this approac