{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,25]],"date-time":"2026-04-25T08:36:06Z","timestamp":1777106166426,"version":"3.51.4"},"reference-count":99,"publisher":"Association for Computing Machinery (ACM)","issue":"11","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Proc. VLDB Endow."],"published-print":{"date-parts":[[2022,7]]},"abstract":"<jats:p>\n            Today's large-scale services (\n            <jats:italic>e.g.<\/jats:italic>\n            , video streaming platforms, data centers, sensor grids) need diverse real-time summary statistics across multiple subpopulations of multidimensional datasets. However, state-of-the-art frameworks do not offer general and accurate analytics in real time at reasonable costs. The root cause is the combinatorial explosion of data subpopulations and the diversity of summary statistics we need to monitor simultaneously. We present Hydra, an efficient framework for multidimensional analytics that presents a novel combination of using a \"sketch of sketches\" to avoid the overhead of monitoring exponentially-many subpopulations and universal sketching to ensure accurate estimates for multiple statistics. We build Hydra as an Apache Spark plugin and address practical system challenges to minimize overheads at scale. Across multiple real-world and synthetic multidimensional datasets, we show that Hydra can achieve robust error bounds and is an order of magnitude more efficient in terms of operational cost and memory footprint than existing frameworks (e.g., Spark, Druid) while ensuring interactive estimation times.\n          <\/jats:p>","DOI":"10.14778\/3551793.3551867","type":"journal-article","created":{"date-parts":[[2022,9,29]],"date-time":"2022-09-29T22:25:03Z","timestamp":1664490303000},"page":"3249-3262","source":"Crossref","is-referenced-by-count":8,"title":["Enabling efficient and general subpopulation analytics in multidimensional data streams"],"prefix":"10.14778","volume":"15","author":[{"given":"Antonis","family":"Manousis","sequence":"first","affiliation":[{"name":"Carnegie Mellon University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhuo","family":"Cheng","sequence":"additional","affiliation":[{"name":"Carnegie Mellon University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ran Ben","family":"Basat","sequence":"additional","affiliation":[{"name":"University College London"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zaoxing","family":"Liu","sequence":"additional","affiliation":[{"name":"Boston University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Vyas","family":"Sekar","sequence":"additional","affiliation":[{"name":"Carnegie Mellon University"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2022,9,29]]},"reference":[{"key":"e_1_2_1_1_1","volume-title":"Spark treeAggregate and treeReduce. https:\/\/github.com\/apache\/spark\/pull\/1110. (2014). [Online","year":"2022","unstructured":"2014. Spark treeAggregate and treeReduce. https:\/\/github.com\/apache\/spark\/pull\/1110. (2014). [Online ; accessed 16- July - 2022 ]. 2014. Spark treeAggregate and treeReduce. https:\/\/github.com\/apache\/spark\/pull\/1110. (2014). [Online; accessed 16-July-2022]."},{"key":"e_1_2_1_2_1","volume-title":"Kafka tops 1 trillion messages per day at linkedin. https:\/\/www.datanami.com\/2015\/09\/02\/kafka-tops-1-trillion-messages-per-day-at-linkedin\/. (2015). [Online","year":"2022","unstructured":"2015. Kafka tops 1 trillion messages per day at linkedin. https:\/\/www.datanami.com\/2015\/09\/02\/kafka-tops-1-trillion-messages-per-day-at-linkedin\/. (2015). [Online ; accessed 16- July - 2022 ]. 2015. Kafka tops 1 trillion messages per day at linkedin. https:\/\/www.datanami.com\/2015\/09\/02\/kafka-tops-1-trillion-messages-per-day-at-linkedin\/. (2015). [Online; accessed 16-July-2022]."},{"key":"e_1_2_1_3_1","volume-title":"SURUS - Anomaly detection at Netflix. https:\/\/netflixtechblog.com\/radoutlier-detection-on-big-data-d6b0494371cc. (2015). [Online","year":"2022","unstructured":"2015. SURUS - Anomaly detection at Netflix. https:\/\/netflixtechblog.com\/radoutlier-detection-on-big-data-d6b0494371cc. (2015). [Online ; accessed 16- July - 2022 ]. 2015. SURUS - Anomaly detection at Netflix. https:\/\/netflixtechblog.com\/radoutlier-detection-on-big-data-d6b0494371cc. (2015). [Online; accessed 16-July-2022]."},{"key":"e_1_2_1_4_1","volume-title":"Approximate Algorithms in Apache spark: Hyperloglog and Quantiles. https:\/\/databricks.com\/blog\/2016\/05\/19\/approximate-algorithms-in-apache-spark-hyperloglog-and-quantiles.html. (2016). [Online","year":"2022","unstructured":"2016. Approximate Algorithms in Apache spark: Hyperloglog and Quantiles. https:\/\/databricks.com\/blog\/2016\/05\/19\/approximate-algorithms-in-apache-spark-hyperloglog-and-quantiles.html. (2016). [Online ; accessed 16- July - 2022 ]. 2016. Approximate Algorithms in Apache spark: Hyperloglog and Quantiles. https:\/\/databricks.com\/blog\/2016\/05\/19\/approximate-algorithms-in-apache-spark-hyperloglog-and-quantiles.html. (2016). [Online; accessed 16-July-2022]."},{"key":"e_1_2_1_5_1","volume-title":"https:\/\/kafka.apache.org\/documentation\/streams\/. (2017). [Online","author":"Streams Kafka","year":"2022","unstructured":"2017. Kafka Streams . https:\/\/kafka.apache.org\/documentation\/streams\/. (2017). [Online ; accessed 16- July - 2022 ]. 2017. Kafka Streams. https:\/\/kafka.apache.org\/documentation\/streams\/. (2017). [Online; accessed 16-July-2022]."},{"key":"e_1_2_1_6_1","volume-title":"EC2 DNS Resolution Issues in the Asia Pacific Region. https:\/\/aws.amazon.com\/message\/74876\/. (2018). [Online","year":"2022","unstructured":"2018. EC2 DNS Resolution Issues in the Asia Pacific Region. https:\/\/aws.amazon.com\/message\/74876\/. (2018). [Online ; accessed 16- July - 2022 ]. 2018. EC2 DNS Resolution Issues in the Asia Pacific Region. https:\/\/aws.amazon.com\/message\/74876\/. (2018). [Online; accessed 16-July-2022]."},{"key":"e_1_2_1_7_1","volume-title":"https:\/\/www.caida.org\/catalog\/datasets\/monitors\/passive-equinix-nyc\/. (2019). [Online","author":"Trace CAIDA","year":"2022","unstructured":"2019. CAIDA Trace . https:\/\/www.caida.org\/catalog\/datasets\/monitors\/passive-equinix-nyc\/. (2019). [Online ; accessed 16- July - 2022 ]. 2019. CAIDA Trace. https:\/\/www.caida.org\/catalog\/datasets\/monitors\/passive-equinix-nyc\/. (2019). [Online; accessed 16-July-2022]."},{"key":"e_1_2_1_8_1","volume-title":"Druid Ingestion Performance. https:\/\/stackoverflow.com\/questions\/54578482\/druid-parquet-poor-ingestion-performance#54580535. (2019). [Online","year":"2022","unstructured":"2019. Druid Ingestion Performance. https:\/\/stackoverflow.com\/questions\/54578482\/druid-parquet-poor-ingestion-performance#54580535. (2019). [Online ; accessed 16- July - 2022 ]. 2019. Druid Ingestion Performance. https:\/\/stackoverflow.com\/questions\/54578482\/druid-parquet-poor-ingestion-performance#54580535. (2019). [Online; accessed 16-July-2022]."},{"key":"e_1_2_1_9_1","volume-title":"EBS Service Event in the Tokyo Region. https:\/\/aws.amazon.com\/message\/56489\/. (2019). [Online","year":"2022","unstructured":"2019. EBS Service Event in the Tokyo Region. https:\/\/aws.amazon.com\/message\/56489\/. (2019). [Online ; accessed 16- July - 2022 ]. 2019. EBS Service Event in the Tokyo Region. https:\/\/aws.amazon.com\/message\/56489\/. (2019). [Online; accessed 16-July-2022]."},{"key":"e_1_2_1_10_1","volume-title":"CAIDA Network Flow Traces. https:\/\/www.caida.org\/catalog\/datasets\/overview\/. (2021). [Online","year":"2022","unstructured":"2021. CAIDA Network Flow Traces. https:\/\/www.caida.org\/catalog\/datasets\/overview\/. (2021). [Online ; accessed 16- July - 2022 ]. 2021. CAIDA Network Flow Traces. https:\/\/www.caida.org\/catalog\/datasets\/overview\/. (2021). [Online; accessed 16-July-2022]."},{"key":"e_1_2_1_11_1","volume-title":"Amazon AWS EC2 pricing. https:\/\/aws.amazon.com\/ec2\/pricing\/on-demand\/. (2022). [Online","year":"2022","unstructured":"2022. Amazon AWS EC2 pricing. https:\/\/aws.amazon.com\/ec2\/pricing\/on-demand\/. (2022). [Online ; accessed 16- July - 2022 ]. 2022. Amazon AWS EC2 pricing. https:\/\/aws.amazon.com\/ec2\/pricing\/on-demand\/. (2022). [Online; accessed 16-July-2022]."},{"key":"e_1_2_1_12_1","volume-title":"Conviva - Real-time Streaming Video Intelligence. https:\/\/www.conviva.com\/. (2022). [Online","year":"2022","unstructured":"2022. Conviva - Real-time Streaming Video Intelligence. https:\/\/www.conviva.com\/. (2022). [Online ; accessed 16- July - 2022 ]. 2022. Conviva - Real-time Streaming Video Intelligence. https:\/\/www.conviva.com\/. (2022). [Online; accessed 16-July-2022]."},{"key":"e_1_2_1_13_1","volume-title":"HYDRA repository. https:\/\/github.com\/antonis-m\/HYDRA_VLDB. (2022). [Online","year":"2022","unstructured":"2022. HYDRA repository. https:\/\/github.com\/antonis-m\/HYDRA_VLDB. (2022). [Online ; accessed 16- July - 2022 ]. 2022. HYDRA repository. https:\/\/github.com\/antonis-m\/HYDRA_VLDB. (2022). [Online; accessed 16-July-2022]."},{"key":"e_1_2_1_14_1","volume-title":"https:\/\/www.ibm.com\/cloud\/streaming-analytics. (2022). [Online","author":"Streams IBM","year":"2022","unstructured":"2022. IBM Streams . https:\/\/www.ibm.com\/cloud\/streaming-analytics. (2022). [Online ; accessed 16- July - 2022 ]. 2022. IBM Streams. https:\/\/www.ibm.com\/cloud\/streaming-analytics. (2022). [Online; accessed 16-July-2022]."},{"key":"e_1_2_1_15_1","first-page":"277","article-title":"The design of the borealis stream processing engine","volume":"5","author":"Abadi Daniel J","year":"2005","unstructured":"Daniel J Abadi , Yanif Ahmad , Magdalena Balazinska , Ugur Cetintemel , Mitch Cherniack , Jeong-Hyon Hwang , Wolfgang Lindner , Anurag Maskey , Alex Rasin , Esther Ryvkina , 2005 . The design of the borealis stream processing engine .. In Cidr , Vol. 5. 277 -- 289 . Daniel J Abadi, Yanif Ahmad, Magdalena Balazinska, Ugur Cetintemel, Mitch Cherniack, Jeong-Hyon Hwang, Wolfgang Lindner, Anurag Maskey, Alex Rasin, Esther Ryvkina, et al. 2005. The design of the borealis stream processing engine.. In Cidr, Vol. 5. 277--289.","journal-title":"Cidr"},{"key":"e_1_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.14778\/2536222.2536231"},{"key":"e_1_2_1_17_1","volume-title":"Congressional samples for approximate answering of group-by queries. In Proceedings of the 2000 ACM SIGMOD international conference on Management of data. 487--498","author":"Acharya Swarup","year":"2000","unstructured":"Swarup Acharya , Phillip B Gibbons , and Viswanath Poosala . 2000 . Congressional samples for approximate answering of group-by queries. In Proceedings of the 2000 ACM SIGMOD international conference on Management of data. 487--498 . Swarup Acharya, Phillip B Gibbons, and Viswanath Poosala. 2000. Congressional samples for approximate answering of group-by queries. In Proceedings of the 2000 ACM SIGMOD international conference on Management of data. 487--498."},{"key":"e_1_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1145\/304182.304581"},{"key":"e_1_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1145\/2500128"},{"key":"e_1_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.1145\/2465351.2465355"},{"key":"e_1_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.14778\/2536222.2536229"},{"key":"e_1_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.1145\/237814.237823"},{"key":"e_1_2_1_23_1","volume-title":"Stream: The stanford data stream management system. In Data Stream Management","author":"Arasu Arvind","year":"2016","unstructured":"Arvind Arasu , Brian Babcock , Shivnath Babu , John Cieslewicz , Mayur Datar , Keith Ito , Rajeev Motwani , Utkarsh Srivastava , and Jennifer Widom . 2016 . Stream: The stanford data stream management system. In Data Stream Management . Springer , 317--336. Arvind Arasu, Brian Babcock, Shivnath Babu, John Cieslewicz, Mayur Datar, Keith Ito, Rajeev Motwani, Utkarsh Srivastava, and Jennifer Widom. 2016. Stream: The stanford data stream management system. In Data Stream Management. Springer, 317--336."},{"key":"e_1_2_1_24_1","doi-asserted-by":"publisher","DOI":"10.1145\/2723372.2742797"},{"key":"e_1_2_1_25_1","volume-title":"Observability at Twitter: technical overview, part i","author":"Asta A","year":"2016","unstructured":"A Asta . 2016. Observability at Twitter: technical overview, part i , 2016 . (2016). A Asta. 2016. Observability at Twitter: technical overview, part i, 2016. (2016)."},{"key":"e_1_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.1145\/3035918.3035928"},{"key":"e_1_2_1_27_1","doi-asserted-by":"publisher","DOI":"10.1145\/1066157.1066160"},{"key":"e_1_2_1_28_1","doi-asserted-by":"publisher","DOI":"10.1109\/INFOCOM41043.2020.9155340"},{"key":"e_1_2_1_29_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDE51399.2021.00080"},{"key":"e_1_2_1_30_1","doi-asserted-by":"publisher","DOI":"10.1145\/3098822.3098832"},{"key":"e_1_2_1_31_1","doi-asserted-by":"publisher","DOI":"10.1145\/2723372.2742783"},{"key":"e_1_2_1_32_1","volume-title":"Universal sketches for the frequency negative moments and other decreasing streaming sums. arXiv preprint arXiv:1408.5096","author":"Braverman Vladimir","year":"2014","unstructured":"Vladimir Braverman and Stephen R Chestnut . 2014. Universal sketches for the frequency negative moments and other decreasing streaming sums. arXiv preprint arXiv:1408.5096 ( 2014 ). Vladimir Braverman and Stephen R Chestnut. 2014. Universal sketches for the frequency negative moments and other decreasing streaming sums. arXiv preprint arXiv:1408.5096 (2014)."},{"key":"e_1_2_1_33_1","doi-asserted-by":"publisher","DOI":"10.1145\/1806689.1806729"},{"key":"e_1_2_1_34_1","doi-asserted-by":"crossref","unstructured":"Chiranjeeb Buragohain and Subhash Suri. 2009. Quantiles on Streams. (2009).  Chiranjeeb Buragohain and Subhash Suri. 2009. Quantiles on Streams. (2009).","DOI":"10.1007\/978-0-387-39940-9_290"},{"key":"e_1_2_1_35_1","volume-title":"Apache flink: Stream and batch processing in a single engine. Bulletin of the IEEE Computer Society Technical Committee on Data Engineering 36, 4","author":"Carbone Paris","year":"2015","unstructured":"Paris Carbone , Asterios Katsifodimos , Stephan Ewen , Volker Markl , Seif Haridi , and Kostas Tzoumas . 2015. Apache flink: Stream and batch processing in a single engine. Bulletin of the IEEE Computer Society Technical Committee on Data Engineering 36, 4 ( 2015 ). Paris Carbone, Asterios Katsifodimos, Stephan Ewen, Volker Markl, Seif Haridi, and Kostas Tzoumas. 2015. Apache flink: Stream and batch processing in a single engine. Bulletin of the IEEE Computer Society Technical Committee on Data Engineering 36, 4 (2015)."},{"key":"e_1_2_1_36_1","doi-asserted-by":"publisher","DOI":"10.14778\/1454159.1454166"},{"key":"e_1_2_1_37_1","doi-asserted-by":"publisher","DOI":"10.1145\/1541880.1541882"},{"key":"e_1_2_1_38_1","doi-asserted-by":"publisher","DOI":"10.1145\/1242524.1242526"},{"key":"e_1_2_1_39_1","doi-asserted-by":"publisher","DOI":"10.1145\/3035918.3056097"},{"key":"e_1_2_1_40_1","doi-asserted-by":"publisher","DOI":"10.1145\/3387514.3405865"},{"key":"e_1_2_1_41_1","doi-asserted-by":"publisher","DOI":"10.1145\/1508857.1508863"},{"key":"e_1_2_1_42_1","doi-asserted-by":"publisher","DOI":"10.1561\/1900000004"},{"key":"e_1_2_1_43_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jalgor.2003.12.001"},{"key":"e_1_2_1_44_1","doi-asserted-by":"publisher","DOI":"10.1145\/872757.872838"},{"key":"e_1_2_1_45_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-540-39658-1_55"},{"key":"e_1_2_1_46_1","doi-asserted-by":"publisher","DOI":"10.1109\/90.929850"},{"key":"e_1_2_1_47_1","doi-asserted-by":"publisher","DOI":"10.1016\/0022-0000(85)90041-8"},{"key":"e_1_2_1_48_1","volume-title":"A Survey on the Evolution of Stream Processing Systems. arXiv preprint arXiv:2008.00842","author":"Fragkoulis Marios","year":"2020","unstructured":"Marios Fragkoulis , Paris Carbone , Vasiliki Kalavri , and Asterios Katsifodimos . 2020. A Survey on the Evolution of Stream Processing Systems. arXiv preprint arXiv:2008.00842 ( 2020 ). Marios Fragkoulis, Paris Carbone, Vasiliki Kalavri, and Asterios Katsifodimos. 2020. A Survey on the Evolution of Stream Processing Systems. arXiv preprint arXiv:2008.00842 (2020)."},{"key":"e_1_2_1_49_1","doi-asserted-by":"publisher","DOI":"10.14778\/3407790.3407817"},{"key":"e_1_2_1_50_1","volume-title":"Vatsal Sharan, and Peter Bailis.","author":"Gan Edward","year":"2018","unstructured":"Edward Gan , Jialin Ding , Kai Sheng Tai , Vatsal Sharan, and Peter Bailis. 2018 . Moment-based quantile sketches for efficient high cardinality aggregation queries. arXiv preprint arXiv:1803.01969 (2018). Edward Gan, Jialin Ding, Kai Sheng Tai, Vatsal Sharan, and Peter Bailis. 2018. Moment-based quantile sketches for efficient high cardinality aggregation queries. arXiv preprint arXiv:1803.01969 (2018)."},{"key":"e_1_2_1_51_1","doi-asserted-by":"publisher","DOI":"10.1145\/945445.945450"},{"key":"e_1_2_1_52_1","volume-title":"Data cube: A relational aggregation operator generalizing group-by, cross-tab, and sub-totals. Data mining and knowledge discovery 1, 1","author":"Gray Jim","year":"1997","unstructured":"Jim Gray , Surajit Chaudhuri , Adam Bosworth , Andrew Layman , Don Reichart , Murali Venkatrao , Frank Pellow , and Hamid Pirahesh . 1997. Data cube: A relational aggregation operator generalizing group-by, cross-tab, and sub-totals. Data mining and knowledge discovery 1, 1 ( 1997 ), 29--53. Jim Gray, Surajit Chaudhuri, Adam Bosworth, Andrew Layman, Don Reichart, Murali Venkatrao, Frank Pellow, and Hamid Pirahesh. 1997. Data cube: A relational aggregation operator generalizing group-by, cross-tab, and sub-totals. Data mining and knowledge discovery 1, 1 (1997), 29--53."},{"key":"e_1_2_1_53_1","doi-asserted-by":"publisher","DOI":"10.1145\/376284.375670"},{"key":"e_1_2_1_54_1","doi-asserted-by":"publisher","DOI":"10.1145\/3230543.3230555"},{"key":"e_1_2_1_55_1","unstructured":"Alex Hall Alexandru Tudorica Filip Buruiana Reimar Hofmann Silviu-Ionut Ganceanu and Thomas Hofmann. 2016. Trading off accuracy for speed in PowerDrill. (2016).  Alex Hall Alexandru Tudorica Filip Buruiana Reimar Hofmann Silviu-Ionut Ganceanu and Thomas Hofmann. 2016. Trading off accuracy for speed in PowerDrill. (2016)."},{"key":"e_1_2_1_56_1","doi-asserted-by":"publisher","DOI":"10.1145\/375663.375664"},{"key":"e_1_2_1_57_1","doi-asserted-by":"publisher","DOI":"10.1145\/235968.233333"},{"key":"e_1_2_1_58_1","doi-asserted-by":"publisher","DOI":"10.1145\/253260.253291"},{"key":"e_1_2_1_59_1","doi-asserted-by":"publisher","DOI":"10.1145\/3097983.3098184"},{"key":"e_1_2_1_60_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDE.2005.72"},{"key":"e_1_2_1_61_1","doi-asserted-by":"publisher","DOI":"10.1145\/1272996.1273005"},{"key":"e_1_2_1_62_1","volume-title":"Building wavelet histograms on large data in mapreduce. arXiv preprint arXiv:1110.6649","author":"Jestes Jeffrey","year":"2011","unstructured":"Jeffrey Jestes , Ke Yi , and Feifei Li. 2011. Building wavelet histograms on large data in mapreduce. arXiv preprint arXiv:1110.6649 ( 2011 ). Jeffrey Jestes, Ke Yi, and Feifei Li. 2011. Building wavelet histograms on large data in mapreduce. arXiv preprint arXiv:1110.6649 (2011)."},{"key":"e_1_2_1_63_1","volume-title":"Proceedings of the 13th Usenix Conference on Networked Systems Design and Implementation (NSDI'16)","author":"Jiang Junchen","year":"2016","unstructured":"Junchen Jiang , Vyas Sekar , Henry Milner , Davis Shepherd , Ion Stoica , and Hui Zhang . 2016 . CFA: A Practical Prediction System for Video QoE Optimization . In Proceedings of the 13th Usenix Conference on Networked Systems Design and Implementation (NSDI'16) . USENIX Association, Berkeley, CA, USA, 137--150. http:\/\/dl.acm.org\/citation.cfm?id=2930611.2930621 Junchen Jiang, Vyas Sekar, Henry Milner, Davis Shepherd, Ion Stoica, and Hui Zhang. 2016. CFA: A Practical Prediction System for Video QoE Optimization. In Proceedings of the 13th Usenix Conference on Networked Systems Design and Implementation (NSDI'16). USENIX Association, Berkeley, CA, USA, 137--150. http:\/\/dl.acm.org\/citation.cfm?id=2930611.2930621"},{"key":"e_1_2_1_64_1","doi-asserted-by":"publisher","DOI":"10.1145\/2535372.2535394"},{"key":"e_1_2_1_65_1","doi-asserted-by":"publisher","DOI":"10.1145\/3097983.3097992"},{"key":"e_1_2_1_66_1","doi-asserted-by":"publisher","DOI":"10.14778\/1920841.1921032"},{"key":"e_1_2_1_67_1","doi-asserted-by":"publisher","DOI":"10.1007\/11841036_42"},{"key":"e_1_2_1_68_1","first-page":"9","article-title":"Impala: A Modern, Open-Source SQL Engine for Hadoop","volume":"1","author":"Kornacker Marcel","year":"2015","unstructured":"Marcel Kornacker , Alexander Behm , Victor Bittorf , Taras Bobrovytsky , Casey Ching , Alan Choi , Justin Erickson , Martin Grund , Daniel Hecht , Matthew Jacobs , 2015 . Impala: A Modern, Open-Source SQL Engine for Hadoop .. In Cidr , Vol. 1. 9 . Marcel Kornacker, Alexander Behm, Victor Bittorf, Taras Bobrovytsky, Casey Ching, Alan Choi, Justin Erickson, Martin Grund, Daniel Hecht, Matthew Jacobs, et al. 2015. Impala: A Modern, Open-Source SQL Engine for Hadoop.. In Cidr, Vol. 1. 9.","journal-title":"Cidr"},{"key":"e_1_2_1_69_1","doi-asserted-by":"publisher","DOI":"10.1016\/B978-155860869-6\/50074-3"},{"key":"e_1_2_1_70_1","doi-asserted-by":"publisher","DOI":"10.1145\/2882903.2915235"},{"key":"e_1_2_1_71_1","volume-title":"Proceedings of the Thirtieth international conference on Very large data bases-Volume 30","author":"Li Xiaolei","year":"2004","unstructured":"Xiaolei Li , Jiawei Han , and Hector Gonzalez . 2004 . High-dimensional OLAP: A minimal cubing approach . In Proceedings of the Thirtieth international conference on Very large data bases-Volume 30 . 528--539. Xiaolei Li, Jiawei Han, and Hector Gonzalez. 2004. High-dimensional OLAP: A minimal cubing approach. In Proceedings of the Thirtieth international conference on Very large data bases-Volume 30. 528--539."},{"key":"e_1_2_1_72_1","doi-asserted-by":"publisher","DOI":"10.1145\/2934872.2934906"},{"key":"e_1_2_1_73_1","doi-asserted-by":"publisher","DOI":"10.1145\/3299869.3324958"},{"key":"e_1_2_1_74_1","doi-asserted-by":"publisher","DOI":"10.14778\/1920841.1920886"},{"key":"e_1_2_1_75_1","doi-asserted-by":"publisher","DOI":"10.5555\/2634074.2634125"},{"key":"e_1_2_1_76_1","doi-asserted-by":"publisher","DOI":"10.1145\/2517349.2522738"},{"key":"e_1_2_1_77_1","unstructured":"Hun Namkung Zaoxing Liu Daehyeok Kim Vyas Sekar Peter Steenkiste Guyue Liu Ao Li Christopher Canel Adithya Abraham Philip Ranysha Ware et al. Sketchlib: Enabling efficient sketch-based monitoring on programmable switches. NSDI.  Hun Namkung Zaoxing Liu Daehyeok Kim Vyas Sekar Peter Steenkiste Guyue Liu Ao Li Christopher Canel Adithya Abraham Philip Ranysha Ware et al. Sketchlib: Enabling efficient sketch-based monitoring on programmable switches. NSDI."},{"key":"e_1_2_1_78_1","unstructured":"Christopher Olston Edward Bortnikov Khaled Elmeleegy Flavio Junqueira and Benjamin Reed. 2009. Interactive Analysis of Web-Scale Data.. In CIDR. Citeseer.  Christopher Olston Edward Bortnikov Khaled Elmeleegy Flavio Junqueira and Benjamin Reed. 2009. Interactive Analysis of Web-Scale Data.. In CIDR. Citeseer."},{"key":"e_1_2_1_79_1","doi-asserted-by":"publisher","DOI":"10.1145\/1376616.1376726"},{"key":"e_1_2_1_80_1","doi-asserted-by":"publisher","DOI":"10.14778\/3402707.3402748"},{"key":"e_1_2_1_81_1","doi-asserted-by":"publisher","DOI":"10.1145\/3183713.3196905"},{"key":"e_1_2_1_82_1","doi-asserted-by":"publisher","DOI":"10.14778\/2824032.2824078"},{"key":"e_1_2_1_83_1","volume-title":"11th {USENIX} Symposium on Networked Systems Design and Implementation ({NSDI} 14). 275--288.","author":"Rabkin Ariel","unstructured":"Ariel Rabkin , Matvey Arye , Siddhartha Sen , Vivek S Pai , and Michael J Freedman . 2014. Aggregation and degradation in jetstream: Streaming analytics in the wide area . In 11th {USENIX} Symposium on Networked Systems Design and Implementation ({NSDI} 14). 275--288. Ariel Rabkin, Matvey Arye, Siddhartha Sen, Vivek S Pai, and Michael J Freedman. 2014. Aggregation and degradation in jetstream: Streaming analytics in the wide area. In 11th {USENIX} Symposium on Networked Systems Design and Implementation ({NSDI} 14). 275--288."},{"key":"e_1_2_1_84_1","doi-asserted-by":"publisher","DOI":"10.1145\/1452520.1452551"},{"key":"e_1_2_1_85_1","doi-asserted-by":"publisher","DOI":"10.1109\/MSST.2010.5496972"},{"key":"e_1_2_1_86_1","first-page":"296","article-title":"Sciborq: scientific data management with bounds on runtime and quality","volume":"11","author":"Sidirourgos Lefteris","year":"2011","unstructured":"Lefteris Sidirourgos , Martin L Kersten , Peter A Boncz , 2011 . Sciborq: scientific data management with bounds on runtime and quality .. In CIDR , Vol. 11. 296 -- 301 . Lefteris Sidirourgos, Martin L Kersten, Peter A Boncz, et al. 2011. Sciborq: scientific data management with bounds on runtime and quality.. In CIDR, Vol. 11. 296--301.","journal-title":"CIDR"},{"key":"e_1_2_1_87_1","doi-asserted-by":"publisher","DOI":"10.14778\/1687553.1687609"},{"key":"e_1_2_1_88_1","doi-asserted-by":"publisher","DOI":"10.1145\/3219819.3219975"},{"key":"e_1_2_1_89_1","doi-asserted-by":"publisher","DOI":"10.1145\/3299869.3319897"},{"key":"e_1_2_1_90_1","volume-title":"Proceedings of the VLDB Endowment International Conference on Very Large Data Bases","volume":"8","author":"Vartak Manasi","year":"2015","unstructured":"Manasi Vartak , Sajjadur Rahman , Samuel Madden , Aditya Parameswaran , and Neoklis Polyzotis . 2015 . Seedb: Efficient data-driven visualization recommendations to support visual analytics . In Proceedings of the VLDB Endowment International Conference on Very Large Data Bases , Vol. 8 . NIH Public Access, 2182. Manasi Vartak, Sajjadur Rahman, Samuel Madden, Aditya Parameswaran, and Neoklis Polyzotis. 2015. Seedb: Efficient data-driven visualization recommendations to support visual analytics. In Proceedings of the VLDB Endowment International Conference on Very Large Data Bases, Vol. 8. NIH Public Access, 2182."},{"key":"e_1_2_1_91_1","doi-asserted-by":"publisher","DOI":"10.1145\/304181.304199"},{"key":"e_1_2_1_92_1","doi-asserted-by":"publisher","DOI":"10.14778\/2850583.2850584"},{"key":"e_1_2_1_93_1","doi-asserted-by":"publisher","DOI":"10.1145\/2723372.2749443"},{"key":"e_1_2_1_94_1","doi-asserted-by":"publisher","DOI":"10.1145\/2745844.2745870"},{"key":"e_1_2_1_95_1","volume-title":"2005 IEEE Symposium on Security and Privacy (S&P'05)","author":"Xie Yinglian","year":"2005","unstructured":"Yinglian Xie , Vyas Sekar , David A Maltz , Michael K Reiter , and Hui Zhang . 2005 . Worm origin identification using random moonwalks . In 2005 IEEE Symposium on Security and Privacy (S&P'05) . IEEE, 242--256. Yinglian Xie, Vyas Sekar, David A Maltz, Michael K Reiter, and Hui Zhang. 2005. Worm origin identification using random moonwalks. In 2005 IEEE Symposium on Security and Privacy (S&P'05). IEEE, 242--256."},{"key":"e_1_2_1_96_1","doi-asserted-by":"publisher","DOI":"10.1145\/2588555.2595631"},{"key":"e_1_2_1_97_1","doi-asserted-by":"publisher","DOI":"10.1145\/3372224.3419204"},{"key":"e_1_2_1_98_1","volume-title":"10th {USENIX} Symposium on Networked Systems Design and Implementation ({NSDI} 13). 29--42.","author":"Yu Minlan","unstructured":"Minlan Yu , Lavanya Jose , and Rui Miao . 2013. Software Defined Traffic Measurement with OpenSketch . In 10th {USENIX} Symposium on Networked Systems Design and Implementation ({NSDI} 13). 29--42. Minlan Yu, Lavanya Jose, and Rui Miao. 2013. Software Defined Traffic Measurement with OpenSketch. In 10th {USENIX} Symposium on Networked Systems Design and Implementation ({NSDI} 13). 29--42."},{"key":"e_1_2_1_99_1","doi-asserted-by":"publisher","DOI":"10.1145\/2934664"}],"container-title":["Proceedings of the VLDB Endowment"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.14778\/3551793.3551867","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,12,28]],"date-time":"2022-12-28T10:57:01Z","timestamp":1672225021000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.14778\/3551793.3551867"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,7]]},"references-count":99,"journal-issue":{"issue":"11","published-print":{"date-parts":[[2022,7]]}},"alternative-id":["10.14778\/3551793.3551867"],"URL":"https:\/\/doi.org\/10.14778\/3551793.3551867","relation":{},"ISSN":["2150-8097"],"issn-type":[{"value":"2150-8097","type":"print"}],"subject":[],"published":{"date-parts":[[2022,7]]}}}