(window.webpackJsonp=window.webpackJsonp||[]).push([[1347],{1920:function(n,a,e){"use strict";e.r(a);var t=e(71),r=Object(t.a)({},(function(){var n=this,a=n.$createElement,e=n._self._c||a;return e("ContentSlotsDistributor",{attrs:{"slot-key":n.$parent.slotKey}},[e("h1",{attrs:{id:"研究论文"}},[e("a",{staticClass:"header-anchor",attrs:{href:"#研究论文"}},[n._v("#")]),n._v(" 研究论文")]),n._v(" "),e("p",[n._v("Apache IoTDB 始于清华大学软件学院。IoTDB是一个用于管理大量时间序列数据的数据库，它采用了列式存储、数据编码、预计算和索引技术，具有类SQL的接口，可支持每秒每节点写入数百万数据点，可以秒级获得超过数万亿个数据点的查询结果。它还可以很容易地与 ApacheHadoop、MapReduce 和 ApacheSpark 集成以进行分析。")]),n._v(" "),e("p",[n._v("相关研究论文如下：")]),n._v(" "),e("ul",[e("li",[e("a",{attrs:{href:"https://dl.acm.org/citation.cfm?id=2983775&dl=ACM&coll=DL",target:"_blank",rel:"noopener noreferrer"}},[n._v("PISA: An Index for Aggregating Big Time Series Data"),e("OutboundLink")],1),n._v(", Xiangdong Huang and Jianmin Wang and Raymond K. Wong and Jinrui Zhang and Chen Wang. CIKM 2016.")]),n._v(" "),e("li",[e("a",{attrs:{href:"https://link.springer.com/chapter/10.1007/978-3-319-96893-3_8",target:"_blank",rel:"noopener noreferrer"}},[n._v("Matching Consecutive Subpatterns over Streaming Time Series"),e("OutboundLink")],1),n._v(", Rong Kang and Chen Wang and Peng Wang and Yuting Ding and Jianmin Wang. APWeb/WAIM 2018.")]),n._v(" "),e("li",[e("a",{attrs:{href:"https://www.semanticscholar.org/paper/KV-match%3A-A-Subsequence-Matching-Approach-and-Time-Wu-Wang/9ed84cb15b7e5052028fc5b4d667248713ac8592",target:"_blank",rel:"noopener noreferrer"}},[n._v("KV-match: A Subsequence Matching Approach Supporting Normalization and Time Warping"),e("OutboundLink")],1),n._v(", Jiaye Wu and Peng Wang and Chen Wang and Wei Wang and Jianmin Wang. ICDE 2019.")]),n._v(" "),e("li",[n._v("我们还研发了面向时间序列数据库的Benchmark工具： "),e("a",{attrs:{href:"https://github.com/thulab/iotdb-benchmark",target:"_blank",rel:"noopener noreferrer"}},[n._v("https://github.com/thulab/iotdb-benchmark"),e("OutboundLink")],1)])])])}),[],!1,null,null,null);a.default=r.exports}}]);