Abstract: In a distributed computing environment comprising a frontend system with a search platform having a cache of pre-computed search results and a backend system with one or more data-bases and a validation instance, a request is received at the search platform from a client comprising one or more first key-values indicating a first data record and at least a first pre-computed search result and a second pre-computed search result for the first data record is retrieved from the cache. The validation instance evaluates a current validity of the first pre-computed search result and the second pre-computed search result retrieved from the cache and returns the first pre-computed search result to the client device, or in response to evaluating that the first pre-computed search result is invalid and the second pre-computed search result is valid, returns the second pre-computed search result to the client.

Abstract: Pre-computed query results stored at a database server are re-computed by a computation machine. The pre-computed query results are composed of a plurality of shares. Each share includes a certain number of pre-computed query results. The computation resources of the computation machine needed to re-compute a pre-computed query result of a first share depend on whether or not other pre-computed query results of the first share are re-computed during a given time interval forming a current re-computation cycle. The computation machine receives a request to re-compute pre-computed query results of at least a first share, determines a number of pre-computed query results in the first share to be re-computed in the current re-computation cycle based on a Reinforcement Learning algorithm, and re-computes the determined number of pre-computed query results in the first share.

Abstract: In a distributed computing environment comprising a frontend system with a search platform having a cache of pre-computed search results and a backend system with one or more data-bases and a validation instance, a request is received at the search platform from a client comprising one or more first key-values indicating a first data record and at least a first pre-computed search result and a second pre-computed search result for the first data record is retrieved from the cache. The validation instance evaluates a current validity of the first pre-computed search result and the second pre-computed search result retrieved from the cache and returns the first pre-computed search result to the client device, or in response to evaluating that the first pre-computed search result is invalid and the second pre-computed search result is valid, returns the second pre-computed search result to the client.

Abstract: Pre-computed query results stored at a database server are re-computed by a computation machine. The pre-computed query results are composed of a plurality of shares. Each share includes a certain number of pre-computed query results. The computation resources of the computation machine needed to re-compute a pre-computed query result of a first share depend on whether or not other pre-computed query results of the first share are re-computed during a given time interval forming a current re-computation cycle. The computation machine receives a request to re-compute pre-computed query results of at least a first share, determines a number of pre-computed query results in the first share to be re-computed in the current re-computation cycle based on a Reinforcement Learning algorithm, and re-computes the determined number of pre-computed query results in the first share.

Abstract: The method according to a preferred embodiment of the present invention allows an improved travel request service to end-users who request proposals for a trip from a Global Distribution System (GDS). This uses a new travel request which comprises a wider range for each search parameter than previous travel requests from the prior art. The new travel request includes many different ranges of parameters in the same travel request whereas the prior art travel request has to be repeated for each different requested value for each search parameter. The method according to a preferred embodiment of the present invention provides a combination of two modules, a master module and a worker module, to carry out the improved travel request service.