Getting started: SampleApp

Learn about SampleApp.

Synchronous IBM Spectrum Symphony C++ client tutorial
This tutorial guides you through the process of building, packaging, deploying, and running the hello grid sample client and service. It also walks you through the sample client application code. You learn the minimum amount of code that you need to create a client.
SampleApp: Developing an asynchronous IBM Spectrum Symphony C++ client
The purpose of an asynchronous client is to get the output as soon as it is available. The client thread does not need to be blocked once the input data is sent and can perform other actions. In this tutorial, you learn how to convert a synchronous client into asynchronous.
SampleApp: Your first IBM Spectrum Symphony C++ service
This tutorial guides you through the process of building and running a service, then walks you through the sample service code. You learn the minimum amount of code that you need to create a service.
SoamDataBlock binary container
SoamDataBlock is a C++ SDK binary container that is handled more efficiently than the binary container within IBM® Spectrum Symphony. It uses reference counting to the data and eliminates internal data copying. The data in the container is not duplicated during the serialization, so you must not modify it until the message is sent. During message serialization, group SoamDataBlocks together at the end of the message for efficient serialization. You can also use SoamDataBlock as a IBM Spectrum Symphony message and serialize your data inside this container.
Customizing a MapReduce service for lifecycle events
This tutorial walks you through a sample service code, then guides you through the process of customizing the default MapReduce service.
Demonstrating memory shared between tasks in the MapReduce framework
This tutorial guides you through the process of using the shared memory sample to demonstrate how memory is shared between tasks in the MapReduce framework, so as to significantly reduce the service footprint.
Using mixed data sources
This tutorial guides you through the process of using different data sources and destinations for input and output within the MapReduce framework in IBM Spectrum Symphony.
Using hash-based grouping for data aggregation
This tutorial guides you through the process of using hash-based grouping to implement aggregation in the reducer class code.

Parent topic: Developing applications for IBM Spectrum Symphony