{"id":{"repo_id":"siu-theses","oai_identifier":"oai:opensiuc.lib.siu.edu:dissertations-2514"},"canonical_url":"https://search.dev.ndltd.org/etd/siu-theses/oai:opensiuc.lib.siu.edu:dissertations-2514","repository":{"repo_id":"siu-theses","name":"Southern Illinois University","base_url":"https://opensiuc.lib.siu.edu/do/oai/"},"display":{"title":"Answering Join Queries Instantly","abstract":"This research presents an innovative way to process queries without having to perform expensive join and set operations. We propose to store the equi-join relationships of tuples on mass storage devices, such as disks, to facilitate query processing. The equi-join relationships are captured, grouped, and stored as various tables on disks, which are collectively called the Join Core. Queries involving arbitrary legitimate sequences of equi-joins, semi-joins, outer-joins, anti-joins, unions, differences, and intersections can all be answered quickly by merely merging these tables. Without having to performing joins, memory consumptions are dramatically reduced. The Join Core can also be updated dynamically. Preliminary experimental results showed that all test queries began to generate results instantly, and many completed instantly too. The proposed methodology can be very useful for queries with complex joins of large relations, and can be even more advantageous to distributed query processing, as there are fewer or even no relations or intermediate results needed to be retrieved, generated or transferred over the networks.","abstract_html":"This research presents an innovative way to process queries without having to perform expensive join and set operations. We propose to store the equi-join relationships of tuples on mass storage devices, such as disks, to facilitate query processing. The equi-join relationships are captured, grouped, and stored as various tables on disks, which are collectively called the Join Core. Queries involving arbitrary legitimate sequences of equi-joins, semi-joins, outer-joins, anti-joins, unions, differences, and intersections can all be answered quickly by merely merging these tables. Without having to performing joins, memory consumptions are dramatically reduced. The Join Core can also be updated dynamically. Preliminary experimental results showed that all test queries began to generate results instantly, and many completed instantly too. The proposed methodology can be very useful for queries with complex joins of large relations, and can be even more advantageous to distributed query processing, as there are fewer or even no relations or intermediate results needed to be retrieved, generated or transferred over the networks.","abstract_has_math":false,"creators":["Hamdi, Mohammed"],"institution":null,"degree_name":"Doctor of Philosophy","degree_level":"Campus Only Dissertation","degree_discipline":"Computer Science","degree_department":null,"school":null,"contributors":["Hou, Wen-Chi"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2018,"date_issued":"2018-05-01T07:00:00Z","date_published":"2018-05-01T07:00:00Z","updated_at":"2026-07-24T04:35:34Z","subjects":[],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://opensiuc.lib.siu.edu/dissertations/1510","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Hou, Wen-Chi"]},{"key":"dc:creator","label":"Author","values":["Hamdi, Mohammed"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.available","label":"Dc Date Available","values":["2020-09-05T07:00:00Z"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Computer Science"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Campus Only Dissertation"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Doctor of Philosophy"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://opensiuc.lib.siu.edu/dissertations/1510"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["This research presents an innovative way to process queries without having to perform expensive join and set operations. We propose to store the equi-join relationships of tuples on mass storage devices, such as disks, to facilitate query processing. The equi-join relationships are captured, grouped, and stored as various tables on disks, which are collectively called the Join Core. Queries involving arbitrary legitimate sequences of equi-joins, semi-joins, outer-joins, anti-joins, unions, differences, and intersections can all be answered quickly by merely merging these tables. Without having to performing joins, memory consumptions are dramatically reduced. The Join Core can also be updated dynamically. Preliminary experimental results showed that all test queries began to generate results instantly, and many completed instantly too. The proposed methodology can be very useful for queries with complex joins of large relations, and can be even more advantageous to distributed query processing, as there are fewer or even no relations or intermediate results needed to be retrieved, generated or transferred over the networks."]},{"key":"dc:title","label":"Title","values":["Answering Join Queries Instantly"]}]}],"canonical_facts":{"dc:contributor":["Hou, Wen-Chi"],"dc:creator":["Hamdi, Mohammed"],"dc:date.available":["2020-09-05T07:00:00Z"],"dc:description.abstract":["This research presents an innovative way to process queries without having to perform expensive join and set operations. We propose to store the equi-join relationships of tuples on mass storage devices, such as disks, to facilitate query processing. The equi-join relationships are captured, grouped, and stored as various tables on disks, which are collectively called the Join Core. Queries involving arbitrary legitimate sequences of equi-joins, semi-joins, outer-joins, anti-joins, unions, differences, and intersections can all be answered quickly by merely merging these tables. Without having to performing joins, memory consumptions are dramatically reduced. The Join Core can also be updated dynamically. Preliminary experimental results showed that all test queries began to generate results instantly, and many completed instantly too. The proposed methodology can be very useful for queries with complex joins of large relations, and can be even more advantageous to distributed query processing, as there are fewer or even no relations or intermediate results needed to be retrieved, generated or transferred over the networks."],"dc:identifier":["https://opensiuc.lib.siu.edu/dissertations/1510"],"dc:title":["Answering Join Queries Instantly"],"thesis:degree_discipline":["Computer Science"],"thesis:degree_level":["Campus Only Dissertation"],"thesis:degree_name":["Doctor of Philosophy"]},"updated_at":"2026-07-24T04:35:34Z"}