Abstract: Certain example embodiments relate to a distributed computing system including servers organized in a cluster and clients. One server is elected leader and is responsible for maintaining consensus information among the other servers. Each server is configured to determine whether a new leader election is to take place. If so, the respective server requests votes for a new leader from the other server(s) and determines whether it has won by a clear majority. Depending on the implementation, votes from eligible client devices are counted, either in a main election together with server votes, or in a tie-break election (if needed) after server votes. Once a server has won, the other servers are informed accordingly. It therefore is possible to maintain a highly-available, consistent, partition-tolerant cluster in the distributed computing systems, using client voters.

Abstract: Certain example embodiments relate to a distributed computing system including servers organized in a cluster and clients. One server is elected leader and is responsible for maintaining consensus information among the other servers. Each server is configured to determine whether a new leader election is to take place. If so, the respective server requests votes for a new leader from the other server(s) and determines whether it has won by a clear majority. Depending on the implementation, votes from eligible client devices are counted, either in a main election together with server votes, or in a tie-break election (if needed) after server votes. Once a server has won, the other servers are informed accordingly. It therefore is possible to maintain a highly-available, consistent, partition-tolerant cluster in the distributed computing systems, using client voters.

Abstract: Certain example embodiments relate to a distributed computing system including servers organized in a cluster and clients. One server is elected leader and is responsible for maintaining consensus information among the other servers. Each server is configured to determine whether a new leader election is to take place. If so, the respective server requests votes for a new leader from the other server(s) and determines whether it has won by a clear majority. Depending on the implementation, votes from eligible client devices are counted, either in a main election together with server votes, or in a tie-break election (if needed) after server votes. Once a server has won, the other servers are informed accordingly. It therefore is possible to maintain a highly-available, consistent, partition-tolerant cluster in the distributed computing systems, using client voters.

Abstract: Certain example embodiments relate to a distributed computing system including servers organized in a cluster and clients. One server is elected leader and is responsible for maintaining consensus information among the other servers. Each server is configured to determine whether a new leader election is to take place. If so, the respective server requests votes for a new leader from the other server(s) and determines whether it has won by a clear majority. Depending on the implementation, votes from eligible client devices are counted, either in a main election together with server votes, or in a tie-break election (if needed) after server votes. Once a server has won, the other servers are informed accordingly. It therefore is possible to maintain a highly-available, consistent, partition-tolerant cluster in the distributed computing systems, using client voters.

Abstract: Certain example embodiments provide a single pass, reverse chronological approach to write-ahead log recovery, enabling space- and time-efficient the recovery of stored data from large write-ahead logs to a transient storage medium. The techniques described herein can in certain instances enable fast and efficient recovery, even in scenarios where at the time of a failure requiring such a recovery the live log is potentially multiple terabytes or larger in size. Certain example embodiments make use of a filtering mechanism (e.g., involving potentially stateful delete, skip, and/or transaction filters), a key/value property (allowing a live set of data, once identified, to be applied in any arbitrary order), etc. A simplified environment with a small closed set of mutative operations allows for the performing of recovery backwards by scanning the log from the most recent written record backwards in time (and, in other words, finishing with the oldest record).