Tutorial
Speed up user programs
Tutorial 1-1: Run a user program as a RaSC service
- Explains how to reduce overhead of startup of user programs and call the programs on remote computers.
- Overviews the basic settings of a RaSC service.
Tutorial 1-2: Execute a user program in parallel
- Explains how to execute user programs in parallel on one computer, using a multi-core CPU.
- Explains parallel execution inside RaSC and usecases.
Tutorial 1-3: Call a user program from various programming languages
- Provides some examples of calling a RaSC service from Perl, Python and Ruby.
Tutorial 1-4: Run your analysis tool as an RaSC service (in preparation)
- Explains how to define interface tailored to the function of a user program.
Improve usability and compatibility
Tutorial 2-1: Work with various network protocols
- Explains how to use various network protocols, JSON RPC, ProtocolBuffers, and SOAP in additon to MessagePack RPC.
- Shows usage of JSON RPC through command line or the Web browser interface.
Tutorial 2-2: Call through ProtocolBuffers
- Explains how to use ProtocolBuffers, a high-speed binary protocol developed by Google.
- Shows a Java client program to call a RaSC service through ProtocolBuffers.
Tutorial 2-3: Call by SOAP
- Explains how to a call RaSC service with SOAP, which is the major protocol for SOA (service-oriented architecture).
- Shows the SOAP standalone client soapUI to call a RaSC service.
Distributed execution using multiple computers
Tutorial 3-1: Distributed execution with load balancing
- Executes RaSC services on multiple nodes to process large scale data, and aggregates the results.
- Introduces load balancing using a round robin.
Tutorial 3-2: Monitor distributed execution (in preparation)
- Explains monitoring over RaSC services in a distributed environment, using Fluentd and growthforecast.