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Gorilla: A Fast, Scalable, In-Memory Time Series Database
Manage episode 487366652 series 3670304
A tartalmat a The Binary Breakdown biztosítja. Az összes podcast-tartalmat, beleértve az epizódokat, grafikákat és podcast-leírásokat, közvetlenül a The Binary Breakdown vagy a podcast platform partnere tölti fel és biztosítja. Ha úgy gondolja, hogy valaki az Ön engedélye nélkül használja fel a szerzői joggal védett művét, kövesse az itt leírt folyamatot https://hu.player.fm/legal.
The provided text describes the architecture and functionality of Gorilla, Facebook's in-memory time series database. Gorilla was developed to address the challenges of monitoring and analyzing massive amounts of time series data generated by Facebook's vast infrastructure. The system prioritizes high availability for writes and reads, even in the face of failures, by using compression techniques, a unique data structure, and replication across geographically distributed datacenters. Gorilla achieves high performance through compression and in-memory data structures, enabling the development of new tools for time series correlation, visualization, and aggregation. The paper highlights the importance of prioritizing recent data over historical data in this context, and the trade-offs made to achieve high availability. https://www.vldb.org/pvldb/vol8/p1816-teller.pdf
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