Colocated Code

When client apps need to update Space Where GigaSpaces data is stored. It is the logical cache that holds data objects in memory and might also hold them in layered in tiering. Data is hosted from multiple SoRs, consolidated as a unified data model. data, they don't have to fetch the data and then update it. Instead, they specify what changes they want to make and for which objects using SQLQuery. These changes are then carried out within the JVM Java Virtual Machine. A virtual machine that enables a computer to run Java programs as well as programs written in other languages that are also compiled to Java bytecode. that stores the data. There are standard ways to make changes, like increasing a value 'increment' or setting a new one 'set value' or a property. You can also write custom code to define specific changes. This custom code can be updated while the program is running as it supports versioning.

This should be used when there is no need to bring the entire object to the client, when there is a need to simply send an instruction (via a query) from the client application to change specifically chosen objects in the Space.

Initiate a predefined service from the client side that operates embedded within the JVM which stores the data. For example, you have a code that performs calculations, but you just want to get the results of those calculations that will be performed in the partitions.

Allow the client to send dynamic code on-the-fly to run within the stored data. This is different from the remote service, which declared the service in advance, whereas this is not done in this case.

Information is gathered from all partitions of the data and an action is performed on it from the client's side to allow reducing it (MapReduce An associated implementation for processing and generating big data sets with a parallel, distributed algorithm on a cluster. A MapReduce program is composed of a map procedure, which performs filtering and sorting, and a reduce method, which performs a summary operation). For instance, if you want to take the top objects (for instance, orders that were the most expensive), you will get the most expensive orders from each partition and in the client they will be sorted to get the highest one. Different versions of the code can run in parallel.  

As this is a more efficient way of performing operations. This should be used when several operations are required and we want to avoid multiple remoting calls.

The difference between Task and Aggregation is that Tasks is performing whatever you want with different types and calculations on different classes.

Aggregations

An API which allows the client to ask for data aggregation. The request is automatically sent to each data node that performs the aggregation and the results are sent to the client. The client then retrieves the results from all nodes and reduces them to provide the required answer. This API can handle common types of combining data, like sum, average, min and max. Plus, you can even write your own way of combining data if you want. It's flexible too, supporting different versions of code running at the same time and letting you change the code without causing any downtime.

Use when aggregated data is required out of one table type

The difference between Aggregation and Task is that Aggregation only iterates over one type of an actual in-memory representation of the object. Using aggregations should be preferred over executing as a task when applicable. This will increase performance as t will not necessitate the creation of an object.

This API lets you run logic embedded with your data whenever that data changes.

Allows definition of custom Java beans that will run together with the data. These beans can then trigger actions on the data based on whether they're the main source (primary) or a backup.

Space Mode Context Loader

The Space Notification

Supports ANSI SQL which is implemented in a way that filters required data in each partition. Then, only the required data is supplied to the client for further reducing on the client side.

When a client needs nearby data, it can define a local view that replicates data based on specifically defined (at the time) filters. This allows the client's code to run using local data. Additionally, a local cache will store data based on how often it is used.

Local View

Local Cache