How sparse histograms can improve efficiency, precision, and mergeability in Prometheus TSDB

Grafana Labs, in collaboration with Björn Rabenstein, developed a prototype for incorporating sparse high-resolution histograms into Prometheus TSDB, aiming to enhance efficiency, precision, and mergeability. This innovation addresses the limitations of the current histogram implementation, which requires manual bucket definition and struggles with compatibility and precision issues. The sparse histograms prototype allows for dynamic bucket allocation, reducing storage space and memory usage while improving precision from 43% to 4.3%. The prototype has demonstrated significant operational cost reductions, including a 93% decrease in index size, making it feasible for more extensive data partitioning. Future work will focus on integrating sparse histograms with PromQL and developing a compatibility layer to bridge conventional and sparse histograms.

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