{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,25]],"date-time":"2025-03-25T19:56:53Z","timestamp":1742932613057,"version":"3.40.3"},"publisher-location":"Cham","reference-count":14,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030276140"},{"type":"electronic","value":"9783030276157"}],"license":[{"start":{"date-parts":[[2019,1,1]],"date-time":"2019-01-01T00:00:00Z","timestamp":1546300800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2019]]},"DOI":"10.1007\/978-3-030-27615-7_1","type":"book-chapter","created":{"date-parts":[[2019,8,18]],"date-time":"2019-08-18T23:02:41Z","timestamp":1566169361000},"page":"3-17","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Optimization of Row Pattern Matching over Sequence Data in Spark SQL"],"prefix":"10.1007","author":[{"given":"Kosuke","family":"Nakabasami","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hiroyuki","family":"Kitagawa","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuya","family":"Nasu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2019,8,3]]},"reference":[{"key":"1_CR1","unstructured":"19075-5:2016(E), I.T.: Information technology - database languages - sql technical reports - part 5: row pattern recognition in sql. technical report. Technical report, ISO copyright office (2016)"},{"key":"1_CR2","doi-asserted-by":"crossref","unstructured":"Agrawal, J., Diao, Y., Gyllstrom, D., Immerman, N.: Efficient pattern matching over event streams. In: Proceedings of the 2008 ACM SIGMOD International Conference on Management of Data, pp. 147\u2013160 (2008)","DOI":"10.1145\/1376616.1376634"},{"key":"1_CR3","doi-asserted-by":"crossref","unstructured":"Armbrust, M., et al.: Spark SQL: relational data processing in spark. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pp. 1383\u20131394 (2015)","DOI":"10.1145\/2723372.2742797"},{"key":"1_CR4","doi-asserted-by":"crossref","unstructured":"Cadonna, B., Gamper, J., B\u00f6hlen, M.H.: Efficient event pattern matching with match windows. In: Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD2012), pp. 471\u2013479 (2012)","DOI":"10.1145\/2339530.2339607"},{"key":"1_CR5","unstructured":"Demers, A., Gehrke, J., Panda, B., Riedewald, M., Sharma, V., White, W.: Cayuga: a general purpose event monitoring system. In: CIDR 2007, pp. 412\u2013422 (2007)"},{"key":"1_CR6","unstructured":"Foundation, T.A.S.: Hadoop (2018). http:\/\/hadoop.apache.org\/"},{"key":"1_CR7","unstructured":"Foursquare: Foursquare (2018). https:\/\/foursquare.com"},{"key":"1_CR8","unstructured":"Laker, K.: A technical deep dive into pattern matching using match$$\\_$$recognize (2016). http:\/\/www.oracle.com\/technetwork\/database\/bi-datawarehousing\/mr-deep-dive-3769287.pdf"},{"key":"1_CR9","doi-asserted-by":"crossref","unstructured":"Mei, Y., Madden, S.: ZStream: a cost-based query processor for adaptively detecting composite events. In: Proceedings of the 2009 ACM SIGMOD International Conference on Management of Data, pp. 193\u2013206 (2009)","DOI":"10.1145\/1559845.1559867"},{"key":"1_CR10","doi-asserted-by":"crossref","unstructured":"Thusoo, A., et al.: Hive - a petabyte scale data warehouse using Hadoop. In: Proceedings of the 26th International Conference on Data Engineering (ICDE2010) (2010)","DOI":"10.1109\/ICDE.2010.5447738"},{"key":"1_CR11","doi-asserted-by":"crossref","unstructured":"Wu, E., Diao, Y., Rizvi, S.: High-performance complex event processing over streams. In: SIGMOD 2006, pp. 407\u2013418 (2006)","DOI":"10.1145\/1142473.1142520"},{"key":"1_CR12","doi-asserted-by":"publisher","first-page":"170","DOI":"10.1016\/j.jnca.2015.05.010","volume":"55","author":"D Yang","year":"2015","unstructured":"Yang, D., Zhang, D., Chen, L., Qu, B.: NationTelescope: monitoring and visualizing large-scale collective behavior in LBSNs. J. Netw. Comput. Appl. (JNCA) 55, 170\u2013180 (2015)","journal-title":"J. Netw. Comput. Appl. (JNCA)"},{"key":"1_CR13","doi-asserted-by":"crossref","unstructured":"Yang, D., Zhang, D., Qu, B.: Participatory cultural mapping based on collective behavior data in location based social networks. In: ACM Trans. on Intelligent Systems and Technology (TIST) (2015)","DOI":"10.1145\/2814575"},{"key":"1_CR14","unstructured":"Zaharia, M., Chowdhury, M., Franklin, M.J., Shenker, S., Stonica, I.: Spark: cluster computing with working sets. In: Proceedings of the 2nd USENIX Conference on Hot Topics in Cloud Computing (HotCloud2010), vol. 55, p. 10 (2010)"}],"container-title":["Lecture Notes in Computer Science","Database and Expert Systems Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-27615-7_1","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,12]],"date-time":"2024-03-12T13:12:05Z","timestamp":1710249125000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-27615-7_1"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019]]},"ISBN":["9783030276140","9783030276157"],"references-count":14,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-27615-7_1","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2019]]},"assertion":[{"value":"3 August 2019","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"DEXA","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Database and Expert Systems Applications","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Linz","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Austria","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2019","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"26 August 2019","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"29 August 2019","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"30","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"dexa2019a","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.dexa.org\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Mixed (Single-blind and Double-blind)","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"ConfDriver","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"157","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"32","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"34","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"20% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"4-6","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3-4","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}