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Developing
Develop stream applications with the Streams Processing Language (SPL), Java, and Python.
Performance improvements for stream applications
You can improve the processing of your stream application by following these guidelines and tips.
Performance recommendations for SPL application programmers
You can use these performance options and recommendations to improve your stream application.

Welcome
Learn about the core capabilities of Teracloud® Streams, its architecture, and key concepts.
Installing
Use this information to install, upgrade, and uninstall the Teracloud® Streams product.
Configuring
Create a basic or an enterprise domain which is a single point for configuring and managing common resources, security, and instances.
Administering
Administer the product by using the Teracloud® Streams graphical user interface, APIs, or the streamtool command-line interface.
Developing
Develop stream applications with the Streams Processing Language (SPL), Java, and Python.
- Development concepts
  Development of stream applications consists of several components such as operators, streams, tuples, Streams Processing Language, toolkits, and more.
- Writing stream applications
  Teracloud® Streams provides features and functions to help you write your applications to fulfill your business needs.
- Enabling Streams data exchange
  Teracloud® Streams provides a data exchange REST API for inserting and retrieving Streams job data. You can add one or more endpoint operators to your Streams application to enable Streams data exchange. Providing a standard REST interface for Streams data exchange eases the integration of Streams data with other data services and externally hosted applications.
- Compiling stream applications
  The Streams Processing Language (SPL) Compiler is called sc and is included with the Teracloud® Streams installation package. You compile SPL to create files to run on your Teracloud Streams instance.
- Performance improvements for stream applications
  You can improve the processing of your stream application by following these guidelines and tips.
  - Performance recommendations for SPL application programmers
    You can use these performance options and recommendations to improve your stream application.
    - Attribute on streams
      A common operation on a stream is to add an attribute.
    - Operations on Collective Types
      Temporary objects are sometimes introduced when you use mapped operators. If those temporary objects affect performance, you can write the code in a way that does not introduce temporary objects.
    - Loop Invariants
      When you initialize a tuple in a loop, some attributes might be invariant.
    - Runtime invariants
      Some computations are runtime invariant. They can be computed on startup and remain constant throughout the execution of the program.
    - Operator Merging
      Going from one operator to the next is not free, even if the operators are in the same PE. You can merge two or more operators to improve performance.
    - Load Splitting
      You can split the computation load to improve performance if more processing power is available.
  - Performance recommendations for primitive operator implementors
    These tips help you to improve performance of your primitive operators in C++.
- Debugging stream applications
  The Streams Processing Language (SPL) Streams Debugger (sdb) provides a command line-based interactive debugger for debugging stream applications.
- Developing toolkits and operators
  You can create custom toolkits and operators for your applications.
Troubleshooting
Resolve problems with Teracloud® Streams using the troubleshooting tools provided with the product as well as the resources offered by Teracloud Support.
Reference
Find details on the SPL language, toolkits, APIs, commands, and more.
Glossary
Use this glossary to find terms and definitions for Teracloud® Streams.

Performance recommendations for SPL application programmers

You can use these performance options and recommendations to improve your stream application.

Important Notice

As the SPL compiler evolves, new optimizations are added. The recommendations for SPL application programmers might change in future releases as they might be implemented as automatic optimizations in the compiler.

Note: The first step for any of the optimizations is to check whether it does, in fact, fix a bottleneck. If it does not, hand-optimizing the code can make it harder to maintain.