{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,4,21]],"date-time":"2025-04-21T01:06:47Z","timestamp":1745197607007,"version":"3.40.3"},"publisher-location":"Singapore","reference-count":19,"publisher":"Springer Nature Singapore","isbn-type":[{"type":"print","value":"9789819998920"},{"type":"electronic","value":"9789819998937"}],"license":[{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024]]},"DOI":"10.1007\/978-981-99-9893-7_10","type":"book-chapter","created":{"date-parts":[[2024,1,22]],"date-time":"2024-01-22T18:03:08Z","timestamp":1705946588000},"page":"128-138","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["A Design of\u00a0Hybrid Transactional and\u00a0Analytical Processing Database for\u00a0Energy Efficient Big Data Queries"],"prefix":"10.1007","author":[{"given":"Wenmin","family":"Lin","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,1,23]]},"reference":[{"issue":"3","key":"10_CR1","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3447032","volume":"17","author":"X Xu","year":"2021","unstructured":"Xu, X., Fang, Z., Zhang, J., et al.: Edge content caching with deep spatiotemporal residual network for IoV in smart city. ACM Trans. Sens. Netw. 17(3), 1\u201333 (2021)","journal-title":"ACM Trans. Sens. Netw."},{"issue":"1","key":"10_CR2","doi-asserted-by":"publisher","first-page":"120","DOI":"10.1109\/69.273032","volume":"6","author":"G Graefe","year":"1994","unstructured":"Graefe, G.: Volcano - an extensible and parallel query evaluation system. IEEE Trans. Knowl. Data Eng. 6(1), 120\u2013135 (1994)","journal-title":"IEEE Trans. Knowl. Data Eng."},{"doi-asserted-by":"crossref","unstructured":"Lyu, Z., Zhang, H.H., Xiong, G., et al.: Greenplum: a hybrid database for transactional and analytical workloads. arXiv arXiv:2103.11080 (2021)","key":"10_CR3","DOI":"10.1145\/3448016.3457562"},{"doi-asserted-by":"crossref","unstructured":"Arnold, J., Glavic, B., Raicu, I.: A high-performance distributed relational database system for scalable OLAP processing. In: 2019 IEEE International Parallel and Distributed Processing Symposium (IPDPS), pp. 738\u2013748 (2019)","key":"10_CR4","DOI":"10.1109\/IPDPS.2019.00083"},{"doi-asserted-by":"crossref","unstructured":"Sirin, U., Dwarkadas, S., Ailamaki, A.: Performance characterization of HTAP workloads. In: 2021 IEEE 37th International Conference on Data Engineering (ICDE), pp. 1829\u20131834 (2021)","key":"10_CR5","DOI":"10.1109\/ICDE51399.2021.00162"},{"doi-asserted-by":"crossref","unstructured":"Sikka, V., F\u00e4rber, F., Lehner, W., Cha, S.K., Peh, T., Bornh\u00f6vd, C.: Efficient transaction processing in SAP HANA database: the end of a column store myth. In: ACM SIGMOD International Conference on Management of Data, pp. 731\u2013742 (2012)","key":"10_CR6","DOI":"10.1145\/2213836.2213946"},{"doi-asserted-by":"publisher","unstructured":"Skidanov, A., Papito, A.J., Prout, A.: A column store engine for real-time streaming analytics. In: IEEE 32nd International Conference on Data Engineering (ICDE) (2016). https:\/\/doi.org\/10.1109\/ICDE.2016.7498332","key":"10_CR7","DOI":"10.1109\/ICDE.2016.7498332"},{"doi-asserted-by":"crossref","unstructured":"Chang, L., et al.: HAWQ: a massively parallel processing SQL engine in hadoop. In: SIGMOD, pp. 1223\u20131234 (2014)","key":"10_CR8","DOI":"10.1145\/2588555.2595636"},{"doi-asserted-by":"crossref","unstructured":"Thusoo, A., et al.: Hive-aware housing solution over a map-reduce framework. In: Proceedings of the VLDB Endowment, pp. 1626\u20131629 (2009)","key":"10_CR9","DOI":"10.14778\/1687553.1687609"},{"doi-asserted-by":"crossref","unstructured":"Sirin, U., Dwarkadas, S., Ailamaki, A.: Performance characterization of HTAP workloads. In: 2021 IEEE 37th International Conference on Data Engineering (ICDE), pp. 1829\u20131834 (2021)","key":"10_CR10","DOI":"10.1109\/ICDE51399.2021.00162"},{"doi-asserted-by":"crossref","unstructured":"Makreshanski, D., Giceva, J., Barthels, C., Alonso, G.: BatchDB: efficient isolated execution of hybrid OLTP+OLAP workloads for interactive applications. In: 2017 IEEE 33nd International Conference on Data Engineering (ICDE), pp. 37\u201350. 585 (2017)","key":"10_CR11","DOI":"10.1145\/3035918.3035959"},{"unstructured":"Appuswamy, R., Karpathiotakis, M., Porobic, D., Ailamaki, A.: The case for heterogeneous HTAP. In: CIDR, pp. 1041\u20131052 (2017)","key":"10_CR12"},{"doi-asserted-by":"crossref","unstructured":"Raza, A., Chrysogelos, P., Anadiotis, A.C., Ailamaki, A.: Adaptive HTAP through elastic resource scheduling. In: 2020 ACM International Conference on Management of Data, pp. 2043\u20132054 (2020)","key":"10_CR13","DOI":"10.1145\/3318464.3389783"},{"unstructured":"Oracle Exadata. https:\/\/www.oracle.com\/technetwork\/database\/exadata\/exadata-storage-technical-overview-128045.pdf","key":"10_CR14"},{"doi-asserted-by":"crossref","unstructured":"Verbitski, A., Gupta, A., et al.: Amazon Aurora: design considerations for high throughput cloud-native relational databases. In: Proceedings of the 2017 ACM International Conference on Management of Data, pp. 1041\u20131052 (2017)","key":"10_CR15","DOI":"10.1145\/3035918.3056101"},{"issue":"2","key":"10_CR16","doi-asserted-by":"publisher","first-page":"338","DOI":"10.1109\/TCC.2015.2511764","volume":"8","author":"L Qi","year":"2020","unstructured":"Qi, L., Dou, W., Chunhua, H., Zhou, Y., Jiguo, Yu.: A context-aware service evaluation approach over Big Data for cloud applications. IEEE Trans. Cloud Comput. 8(2), 338\u2013348 (2020)","journal-title":"IEEE Trans. Cloud Comput."},{"key":"10_CR17","doi-asserted-by":"publisher","first-page":"522","DOI":"10.1016\/j.future.2018.12.055","volume":"95","author":"X Xu","year":"2019","unstructured":"Xu, X., et al.: A computation offloading method over Big Data for IoT-enabled cloud-edge computing. Futur. Gener. Comput. Syst. 95, 522\u2013533 (2019)","journal-title":"Futur. Gener. Comput. Syst."},{"key":"10_CR18","doi-asserted-by":"publisher","DOI":"10.1109\/TBDATA.2017.2787661","author":"X Zhang","year":"2017","unstructured":"Zhang, X., et al.: MRMondrian: scalable multidimensional anonymisation for Big Data privacy preservation. IEEE Trans. Big Data (2017). https:\/\/doi.org\/10.1109\/TBDATA.2017.2787661","journal-title":"IEEE Trans. Big Data"},{"unstructured":"TPC-H. http:\/\/www.tpc.org\/tpch\/","key":"10_CR19"}],"container-title":["Lecture Notes in Computer Science","Green, Pervasive, and Cloud Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-99-9893-7_10","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,1,22]],"date-time":"2024-01-22T18:04:26Z","timestamp":1705946666000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-99-9893-7_10"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"ISBN":["9789819998920","9789819998937"],"references-count":19,"URL":"https:\/\/doi.org\/10.1007\/978-981-99-9893-7_10","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2024]]},"assertion":[{"value":"23 January 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"GPC","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Green, Pervasive, and Cloud Computing","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Harbin","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"China","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2023","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"23 September 2023","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"24 September 2023","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"18","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"gpc2023","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Double-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Easy Chair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"111","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":"38","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":"1","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":"34% - 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":"3","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":"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":"No","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}