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OODIDA (On-board/Off-board Distributed Data Analytics) is a platform fordistributed real-time analytics, targeting fleets of reference vehicles in theautomotive industry. Its users are data analysts. The bulk of the dataanalytics tasks are performed by clients (on-board), while a central cloudserver performs supplementary tasks (off-board). OODIDA can be automaticallypackaged and deployed, which necessitates restarting parts of the system, orall of it. As this is potentially disruptive, we added the ability to executeuser-defined Python modules on clients as well as the server. These modules canbe replaced without restarting any part of the system; they can even bereplaced between iterations of an ongoing assignment. This feature is referredto as active-code replacement. It facilitates use cases such as iterative A/Btesting of machine learning algorithms or modifying experimental algorithmson-the-fly. Consistency of results is achieved by majority vote, which preventstainted state. Active-code replacement can be done in less than a second in anidealized setting whereas a standard deployment takes many orders of magnitudemore time. The main contribution of this paper is the description of arelatively straightforward approach to active-code replacement that is veryuser-friendly. It enables a data analyst to quickly execute custom code on thecloud server as well as on client devices. Sensible safeguards and designdecisions ensure that this feature can be used by non-specialists who are notfamiliar with the implementation of OODIDA in general or this feature inparticular. As a consequence of adding the active-code replacement feature,OODIDA is now very well-suited for rapid prototyping.

Facilitating Rapid Prototyping in the OODIDA Data Analytics Platform via Active-Code Replacement