Marc Nunkesser
Authored Publications
Google Publications
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Quantifying the sustainability impact of Google Maps: A case study of Salt Lake City
Theophile Cabannes
Yechen Li
Preston McAfee
2021 (2021) (to appear)
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Google Maps uses current and historical traffic trends to provide routes to drivers. In this paper, we use microscopic traffic simulation to quantify the improvements to both travel time and CO2 emissions from Google Maps real-time navigation. A case study in Salt Lake City shows that Google Maps users are, on average, saving 1.7% of CO2 emissions and 6.5% travel time. If we restrict to the users for which Google Maps finds a different route than their original route, the average savings are 3.4% of CO2 emissions and 12.5% of travel time. These results are based on traffic conditions observed during the Covid-19 pandemic. As congestion gradually builds back up to pre-pandemic levels, it is expected to lead to even greater savings in emissions.
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HyperLogLog in Practice: Algorithmic Engineering of a State of The Art Cardinality Estimation Algorithm
Stefan Heule
Alex Hall
Proceedings of the EDBT 2013 Conference, ACM, Genoa, Italy (to appear)
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Cardinality estimation has a wide range of applications and
is of particular importance in database systems. Various
algorithms have been proposed in the past, and the HyperLogLog algorithm is one of them. In this paper, we
present a series of improvements to this algorithm that reduce its memory requirements and significantly increase its
accuracy for an important range of cardinalities. We have
implemented our proposed algorithm for a system at Google
and evaluated it empirically, comparing it to the original
HyperLogLog algorithm. Like HyperLogLog, our improved algorithm parallelizes perfectly and computes the
cardinality estimate in a single pass.
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Processing a Trillion Cells per Mouse Click
Alex Hall
Olaf Bachmann
Robert Buessow
Silviu-Ionut Ganceanu
PVLDB, vol. 5 (2012), pp. 1436-1446
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Column-oriented database systems have been a real game changer for the industry in recent years. Highly tuned and performant systems have evolved that provide users with the possibility of answering ad hoc queries over large datasets in an interactive manner.
In this paper we present the column-oriented datastore developed as one of the central components of PowerDrill. It combines the advantages of columnar data layout with other known techniques (such as using composite range partitions) and extensive algorithmic engineering on key data structures. The main goal of the latter being to reduce the main memory footprint and to increase the efficiency in processing typical user queries. In this combination we achieve large speed-ups. These enable a highly interactive Web UI where it is common that a single mouse click leads to processing a trillion values in the underlying dataset.
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