{"id":170875,"date":"2011-11-21T13:31:30","date_gmt":"2011-11-21T13:31:30","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/project\/streams\/"},"modified":"2017-06-19T10:26:41","modified_gmt":"2017-06-19T17:26:41","slug":"streams","status":"publish","type":"msr-project","link":"https:\/\/www.microsoft.com\/en-us\/research\/project\/streams\/","title":{"rendered":"Streams"},"content":{"rendered":"
In the streams research project, we propose novel architectures, efficient processing techniques, models, and applications to support time-oriented queries over real-time and offline data streams. Our current focus in the project centers around Trill, a high-performance streaming analytics engine that is now used across Microsoft. Our currect focus areas include efficient query processing, scale-out, resiliency, streaming state management, and unstructured data support.<\/div>\n

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In the streams research project, we propose novel architectures, efficient processing techniques, models, and applications to support time-oriented queries over real-time and offline data streams. Our current focus in the project centers around Trill, a high-performance streaming analytics engine that is now used across Microsoft. Our currect focus areas include efficient query processing, scale-out, resiliency, […]<\/p>\n","protected":false},"featured_media":0,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"_classifai_error":"","footnotes":""},"research-area":[13555,13547],"msr-locale":[268875],"msr-impact-theme":[],"msr-pillar":[],"class_list":["post-170875","msr-project","type-msr-project","status-publish","hentry","msr-research-area-search-information-retrieval","msr-research-area-systems-and-networking","msr-locale-en_us","msr-archive-status-active"],"msr_project_start":"2011-11-21","related-publications":[167653,161997,162047,163577,164964,165116,165416,165420,166281,161985,244505,245552,266391,319952,345572,160426,157952,157953,159592,159593,160094,160249,160417,160425,153171,160917,160918,160919,161365,161408,161550,161984],"related-downloads":[],"related-videos":[],"related-groups":[],"related-events":[],"related-opportunities":[],"related-posts":[],"related-articles":[],"tab-content":[],"slides":[],"related-researchers":[{"type":"user_nicename","value":"badrishc","display_name":"Badrish Chandramouli","author_link":"Badrish Chandramouli<\/a>","is_active":false,"user_id":31166,"last_first":"Chandramouli, Badrish","people_section":0,"alias":"badrishc"}],"msr_research_lab":[199565],"msr_impact_theme":[],"_links":{"self":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-project\/170875","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-project"}],"about":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/types\/msr-project"}],"version-history":[{"count":2,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-project\/170875\/revisions"}],"predecessor-version":[{"id":391496,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-project\/170875\/revisions\/391496"}],"wp:attachment":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/media?parent=170875"}],"wp:term":[{"taxonomy":"msr-research-area","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/research-area?post=170875"},{"taxonomy":"msr-locale","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-locale?post=170875"},{"taxonomy":"msr-impact-theme","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-impact-theme?post=170875"},{"taxonomy":"msr-pillar","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-pillar?post=170875"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}