{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,9,4]],"date-time":"2024-09-04T19:45:39Z","timestamp":1725479139896},"reference-count":47,"publisher":"Association for Computing Machinery (ACM)","issue":"9","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Proc. VLDB Endow."],"published-print":{"date-parts":[[2022,5]]},"abstract":"The continued emergence of large social network applications has introduced a scale of data and query volume that challenges the limits of existing data stores. However, few benchmarks accurately simulate these request patterns, leaving researchers in short supply of tools to evaluate and improve upon these systems. In this paper, we present a new benchmark, TAOBench, that captures the social graph workload at Meta. We open source workload configurations along with a benchmark that leverages these request features to both accurately model production workloads and generate emergent application behavior. We ensure the integrity of TAOBench's workloads by validating them against their production counterparts. We also describe several benchmark use cases at Meta and report results for five popular distributed database systems to demonstrate the benefits of using TAOBench to evaluate system tradeoffs as well as identify and address performance issues. Our benchmark fills a gap in the available tools and data that researchers and developers have to inform system design decisions.<\/jats:p>","DOI":"10.14778\/3538598.3538616","type":"journal-article","created":{"date-parts":[[2022,7,27]],"date-time":"2022-07-27T17:12:31Z","timestamp":1658941951000},"page":"1965-1977","source":"Crossref","is-referenced-by-count":6,"title":["TAOBench"],"prefix":"10.14778","volume":"15","author":[{"given":"Audrey","family":"Cheng","sequence":"first","affiliation":[{"name":"UC Berkeley"}]},{"given":"Xiao","family":"Shi","sequence":"additional","affiliation":[{"name":"Meta"}]},{"given":"Aaron","family":"Kabcenell","sequence":"additional","affiliation":[{"name":"Meta"}]},{"given":"Shilpa","family":"Lawande","sequence":"additional","affiliation":[{"name":"Meta"}]},{"given":"Hamza","family":"Qadeer","sequence":"additional","affiliation":[{"name":"UC Berkeley"}]},{"given":"Jason","family":"Chan","sequence":"additional","affiliation":[{"name":"UC Berkeley"}]},{"given":"Harrison","family":"Tin","sequence":"additional","affiliation":[{"name":"UC Berkeley"}]},{"given":"Ryan","family":"Zhao","sequence":"additional","affiliation":[{"name":"UC Berkeley"}]},{"given":"Peter","family":"Bailis","sequence":"additional","affiliation":[{"name":"Sisu Data"}]},{"given":"Mahesh","family":"Balakrishnan","sequence":"additional","affiliation":[{"name":"Meta"}]},{"given":"Nathan","family":"Bronson","sequence":"additional","affiliation":[{"name":"Rockset"}]},{"given":"Natacha","family":"Crooks","sequence":"additional","affiliation":[{"name":"UC Berkeley"}]},{"given":"Ion","family":"Stoica","sequence":"additional","affiliation":[{"name":"UC Berkeley"}]}],"member":"320","published-online":{"date-parts":[[2022,7,27]]},"reference":[{"key":"e_1_2_1_1_1","unstructured":"2013. Epinions.com Benchmark in OLTP-Bench. https:\/\/github.com\/oltpbenchmark\/oltpbench\/tree\/master\/src\/com\/oltpbenchmark\/benchmarks\/epinions\/ 2013. Epinions.com Benchmark in OLTP-Bench. https:\/\/github.com\/oltpbenchmark\/oltpbench\/tree\/master\/src\/com\/oltpbenchmark\/benchmarks\/epinions\/"},{"key":"e_1_2_1_2_1","unstructured":"2013. Twitter Benchmark in OLTP-Bench. https:\/\/github.com\/oltpbenchmark\/oltpbench\/tree\/master\/src\/com\/oltpbenchmark\/benchmarks\/twitter\/ 2013. Twitter Benchmark in OLTP-Bench. https:\/\/github.com\/oltpbenchmark\/oltpbench\/tree\/master\/src\/com\/oltpbenchmark\/benchmarks\/twitter\/"},{"key":"e_1_2_1_3_1","unstructured":"2014. Manhattan our real-time multi-tenant distributed database for Twitter scale. https:\/\/blog.twitter.com\/engineering\/en_us\/a\/2014\/manhattan-our-realtime-multi-tenant-distributed-database-for-twitter-scale.html 2014. Manhattan our real-time multi-tenant distributed database for Twitter scale. https:\/\/blog.twitter.com\/engineering\/en_us\/a\/2014\/manhattan-our-realtime-multi-tenant-distributed-database-for-twitter-scale.html"},{"key":"e_1_2_1_4_1","unstructured":"2015. HBaseCon 2015 General Session: Zen - A Graph Data Model on HBase. https:\/\/www.slideshare.net\/HBaseCon\/keynote-3-pinterest-49043320 2015. HBaseCon 2015 General Session: Zen - A Graph Data Model on HBase. https:\/\/www.slideshare.net\/HBaseCon\/keynote-3-pinterest-49043320"},{"key":"e_1_2_1_5_1","unstructured":"2020. MySQL Transactional and Locking Statements. https:\/\/dev.mysql.com\/doc\/refman\/8.0\/en\/sql-transactional-statements.html 2020. MySQL Transactional and Locking Statements. https:\/\/dev.mysql.com\/doc\/refman\/8.0\/en\/sql-transactional-statements.html"},{"key":"e_1_2_1_6_1","unstructured":"2022. Apache HBase. https:\/\/hbase.apache.org\/ 2022. Apache HBase. https:\/\/hbase.apache.org\/"},{"key":"e_1_2_1_7_1","unstructured":"2022. Cloud Spanner. https:\/\/cloud.google.com\/spanner 2022. Cloud Spanner. https:\/\/cloud.google.com\/spanner"},{"key":"e_1_2_1_8_1","unstructured":"2022. Cloud Spanner best practices. https:\/\/cloud.google.com\/spanner\/docs\/best-practice-list 2022. Cloud Spanner best practices. https:\/\/cloud.google.com\/spanner\/docs\/best-practice-list"},{"key":"e_1_2_1_9_1","unstructured":"2022. DGraph. https:\/\/github.com\/dgraph-io\/dgraph 2022. DGraph. https:\/\/github.com\/dgraph-io\/dgraph"},{"key":"e_1_2_1_10_1","unstructured":"2022. PlanetScale. https:\/\/planetscale.com\/ 2022. PlanetScale. https:\/\/planetscale.com\/"},{"key":"e_1_2_1_11_1","unstructured":"2022. TAOBench. https:\/\/github.com\/audreyccheng\/taobench 2022. TAOBench. https:\/\/github.com\/audreyccheng\/taobench"},{"key":"e_1_2_1_12_1","unstructured":"2022. Yugabyte DB. https:\/\/www.yugabyte.com 2022. Yugabyte DB. https:\/\/www.yugabyte.com"},{"key":"e_1_2_1_13_1","unstructured":"2022. YugabyteDB Postgres Monitoring Issue. https:\/\/github.com\/yugabyte\/yugabyte-db\/issues\/10805 2022. YugabyteDB Postgres Monitoring Issue. https:\/\/github.com\/yugabyte\/yugabyte-db\/issues\/10805"},{"key":"e_1_2_1_14_1","unstructured":"2022. YugabyteDB Row Comparison Issue. https:\/\/github.com\/yugabyte\/yugabyte-db\/issues\/11463 2022. YugabyteDB Row Comparison Issue. https:\/\/github.com\/yugabyte\/yugabyte-db\/issues\/11463"},{"key":"e_1_2_1_15_1","unstructured":"Atul Adya Barbara Liskov and Patrick O'Neil. 2000. Generalized Isolation Level Definitions. (2000) 67--78. Atul Adya Barbara Liskov and Patrick O'Neil. 2000. Generalized Isolation Level Definitions. (2000) 67--78."},{"key":"e_1_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1145\/2463676.2465296"},{"key":"e_1_2_1_17_1","volume-title":"BG: A Benchmark to Evaluate Interactive Social Networking Actions. In CIDR. Citeseer.","author":"Barahmand Sumita","year":"2013","unstructured":"Sumita Barahmand and Shahram Ghandeharizadeh . 2013 . BG: A Benchmark to Evaluate Interactive Social Networking Actions. In CIDR. Citeseer. Sumita Barahmand and Shahram Ghandeharizadeh. 2013. BG: A Benchmark to Evaluate Interactive Social Networking Actions. In CIDR. Citeseer."},{"key":"e_1_2_1_18_1","volume-title":"Concurrency Control and Recovery in Database Systems","author":"Bernstein Philip A.","unstructured":"Philip A. Bernstein , Vassos Hadzilacos , and Nathan Goodman . 1987. Concurrency Control and Recovery in Database Systems . Addison-Wesley . Philip A. Bernstein, Vassos Hadzilacos, and Nathan Goodman. 1987. Concurrency Control and Recovery in Database Systems. Addison-Wesley."},{"key":"e_1_2_1_19_1","unstructured":"ByteDance Official Tech Blog. 2020. Design and Implementation of ByteDance's Trillion-Edge 10M+ QPS Graph Database and Computation System. https:\/\/blog.csdn.net\/ByteDanceTech\/article\/details\/104509642 ByteDance Official Tech Blog. 2020. Design and Implementation of ByteDance's Trillion-Edge 10M+ QPS Graph Database and Computation System. https:\/\/blog.csdn.net\/ByteDanceTech\/article\/details\/104509642"},{"key":"e_1_2_1_20_1","volume-title":"2013 USENIX Annual Technical Conference (USENIX ATC '13)","author":"Bronson Nathan","year":"2013","unstructured":"Nathan Bronson , Zach Amsden , George Cabrera , Prasad Chakka , Peter Dimov , Hui Ding , Jack Ferris , Anthony Giardullo , Sachin Kulkarni , Harry Li , 2013 . TAO: Facebook's Distributed Data Store for the Social Graph . In 2013 USENIX Annual Technical Conference (USENIX ATC '13) . 49--60. Nathan Bronson, Zach Amsden, George Cabrera, Prasad Chakka, Peter Dimov, Hui Ding, Jack Ferris, Anthony Giardullo, Sachin Kulkarni, Harry Li, et al. 2013. TAO: Facebook's Distributed Data Store for the Social Graph. In 2013 USENIX Annual Technical Conference (USENIX ATC '13). 49--60."},{"key":"e_1_2_1_21_1","volume-title":"Gryff: Unifying Consensus and Shared Registers. In 17th USENIX Symposium on Networked Systems Design and Implementation (NSDI '20)","author":"Burke Matthew","year":"2020","unstructured":"Matthew Burke , Audrey Cheng , and Wyatt Lloyd . 2020 . Gryff: Unifying Consensus and Shared Registers. In 17th USENIX Symposium on Networked Systems Design and Implementation (NSDI '20) . 591--617. Matthew Burke, Audrey Cheng, and Wyatt Lloyd. 2020. Gryff: Unifying Consensus and Shared Registers. In 17th USENIX Symposium on Networked Systems Design and Implementation (NSDI '20). 591--617."},{"key":"e_1_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.5555\/3386691.3386712"},{"key":"e_1_2_1_23_1","doi-asserted-by":"publisher","DOI":"10.1145\/2764947.2764954"},{"key":"e_1_2_1_24_1","volume-title":"Proceedings of the International AAAI Conference on Web and Social Media 4, 1 (May","author":"Cha Meeyoung","year":"2010","unstructured":"Meeyoung Cha , Hamed Haddadi , Fabricio Benevenuto , and Krishna Gummadi . 2010 . Measuring User Influence in Twitter: The Million Follower Fallacy . Proceedings of the International AAAI Conference on Web and Social Media 4, 1 (May 2010), 10--17. Meeyoung Cha, Hamed Haddadi, Fabricio Benevenuto, and Krishna Gummadi. 2010. Measuring User Influence in Twitter: The Million Follower Fallacy. Proceedings of the International AAAI Conference on Web and Social Media 4, 1 (May 2010), 10--17."},{"key":"e_1_2_1_25_1","doi-asserted-by":"publisher","DOI":"10.14778\/3476311.3476379"},{"key":"e_1_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.1145\/1807128.1807152"},{"key":"e_1_2_1_27_1","unstructured":"The Transaction Processing Performance Council. 2010. TPC-C. http:\/\/www.tpc.org\/tpcc\/ The Transaction Processing Performance Council. 2010. TPC-C. http:\/\/www.tpc.org\/tpcc\/"},{"key":"e_1_2_1_28_1","doi-asserted-by":"publisher","DOI":"10.14778\/2732240.2732246"},{"key":"e_1_2_1_29_1","doi-asserted-by":"publisher","DOI":"10.1145\/2723372.2742786"},{"key":"e_1_2_1_30_1","volume-title":"Operating Systems: An Advanced Course","author":"Gray J. N.","unstructured":"J. N. Gray . 1978. Notes on Data Base Operating Systems . In Operating Systems: An Advanced Course , R. Bayer, R. M. Graham, and G. Seegm\u00fcller (Eds.). Springer Berlin Heidelberg , Berlin, Heidelberg , 393--481. J. N. Gray. 1978. Notes on Data Base Operating Systems. In Operating Systems: An Advanced Course, R. Bayer, R. M. Graham, and G. Seegm\u00fcller (Eds.). Springer Berlin Heidelberg, Berlin, Heidelberg, 393--481."},{"key":"e_1_2_1_31_1","doi-asserted-by":"publisher","DOI":"10.14778\/3055540.3055548"},{"key":"e_1_2_1_32_1","doi-asserted-by":"publisher","DOI":"10.14778\/3415478.3415535"},{"key":"e_1_2_1_33_1","doi-asserted-by":"publisher","DOI":"10.1145\/1773912.1773922"},{"key":"e_1_2_1_34_1","first-page":"18","article-title":"Paxos Made Simple","volume":"32","author":"Leslie Lamport","year":"2001","unstructured":"Leslie Lamport et al. 2001 . Paxos Made Simple . ACM Sigact News 32 , 4 (2001), 18 -- 25 . Leslie Lamport et al. 2001. Paxos Made Simple. ACM Sigact News 32, 4 (2001), 18--25.","journal-title":"ACM Sigact News"},{"key":"e_1_2_1_35_1","doi-asserted-by":"publisher","DOI":"10.14778\/3415478.3415546"},{"key":"e_1_2_1_36_1","unstructured":"Meta. 2022. Meta Reports First Quarter 2022 Results. https:\/\/investor.fb.com\/investor-news\/press-release-details\/2022\/Meta-Reports-First-Quarter-2022-Results\/default.aspx Meta. 2022. Meta Reports First Quarter 2022 Results. https:\/\/investor.fb.com\/investor-news\/press-release-details\/2022\/Meta-Reports-First-Quarter-2022-Results\/default.aspx"},{"key":"e_1_2_1_37_1","volume-title":"2014 USENIX Annual Technical Conference (USENIX ATC '14)","author":"Ongaro Diego","year":"2014","unstructured":"Diego Ongaro and John Ousterhout . 2014 . In Search of an Understandable Consensus Algorithm . In 2014 USENIX Annual Technical Conference (USENIX ATC '14) . 305--319. Diego Ongaro and John Ousterhout. 2014. In Search of an Understandable Consensus Algorithm. In 2014 USENIX Annual Technical Conference (USENIX ATC '14). 305--319."},{"key":"e_1_2_1_38_1","doi-asserted-by":"publisher","DOI":"10.1145\/2463676.2465298"},{"key":"e_1_2_1_39_1","volume-title":"14th USENIX Symposium on Operating Systems Design and Implementation (OSDI 20)","author":"Shi Xiao","year":"2020","unstructured":"Xiao Shi , Scott Pruett , Kevin Doherty , Jinyu Han , Dmitri Petrov , Jim Carrig , John Hugg , and Nathan Bronson . 2020 . FlightTracker: Consistency across Read-Optimized Online Stores at Facebook . In 14th USENIX Symposium on Operating Systems Design and Implementation (OSDI 20) . USENIX Association, 407--423. Xiao Shi, Scott Pruett, Kevin Doherty, Jinyu Han, Dmitri Petrov, Jim Carrig, John Hugg, and Nathan Bronson. 2020. FlightTracker: Consistency across Read-Optimized Online Stores at Facebook. In 14th USENIX Symposium on Operating Systems Design and Implementation (OSDI 20). USENIX Association, 407--423."},{"key":"e_1_2_1_40_1","doi-asserted-by":"publisher","DOI":"10.5555\/2208461.2208479"},{"key":"e_1_2_1_41_1","doi-asserted-by":"publisher","DOI":"10.1145\/3318464.3386134"},{"key":"e_1_2_1_42_1","unstructured":"The H-Store team. 2013. AuctionMark: An OLTP Benchmark for Shared-Nothing Database Management Systems. https:\/\/hstore.cs.brown.edu\/projects\/auctionmark\/ The H-Store team. 2013. AuctionMark: An OLTP Benchmark for Shared-Nothing Database Management Systems. https:\/\/hstore.cs.brown.edu\/projects\/auctionmark\/"},{"key":"e_1_2_1_43_1","unstructured":"The H-Store team. 2013. SEATS Benchmark. https:\/\/hstore.cs.brown.edu\/projects\/seats\/ The H-Store team. 2013. SEATS Benchmark. https:\/\/hstore.cs.brown.edu\/projects\/seats\/"},{"key":"e_1_2_1_44_1","unstructured":"The H-Store team. 2013. SmallBank Benchmark. http:\/\/hstore.cs.brown.edu\/documentation\/deployment\/benchmarks\/smallbank\/ The H-Store team. 2013. SmallBank Benchmark. http:\/\/hstore.cs.brown.edu\/documentation\/deployment\/benchmarks\/smallbank\/"},{"key":"e_1_2_1_45_1","volume-title":"Benchmarking Online Social Networks. 2016 IEEE\/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)","author":"Terevinto Pablo Nicolas","year":"2016","unstructured":"Pablo Nicolas Terevinto , Miguel P\u00e9rez-Francisco , Josep Domenech , Jos\u00e9 A. Gil , and Ana Pont . 2016 . Benchmarking Online Social Networks. 2016 IEEE\/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) (2016), 164--169. Pablo Nicolas Terevinto, Miguel P\u00e9rez-Francisco, Josep Domenech, Jos\u00e9 A. Gil, and Ana Pont. 2016. Benchmarking Online Social Networks. 2016 IEEE\/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) (2016), 164--169."},{"key":"e_1_2_1_46_1","doi-asserted-by":"publisher","DOI":"10.1109\/HPCA.2014.6835958"},{"key":"e_1_2_1_47_1","doi-asserted-by":"publisher","DOI":"10.14778\/3137765.3137778"}],"container-title":["Proceedings of the VLDB Endowment"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.14778\/3538598.3538616","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,12,28]],"date-time":"2022-12-28T09:31:04Z","timestamp":1672219864000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.14778\/3538598.3538616"}},"subtitle":["an end-to-end benchmark for social network workloads"],"short-title":[],"issued":{"date-parts":[[2022,5]]},"references-count":47,"journal-issue":{"issue":"9","published-print":{"date-parts":[[2022,5]]}},"alternative-id":["10.14778\/3538598.3538616"],"URL":"https:\/\/doi.org\/10.14778\/3538598.3538616","relation":{},"ISSN":["2150-8097"],"issn-type":[{"value":"2150-8097","type":"print"}],"subject":[],"published":{"date-parts":[[2022,5]]}}}