{"id":"W2148682126","doi":"10.1109/ipdps.2012.85","title":"Query Optimization and Execution in a Parallel Analytics DBMS","year":2012,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Online analytical processing; Computer science; Scalability; Query optimization; Sargable; Data warehouse; View; Database; Search engine indexing; NoSQL; Analytics; Big data; Query expansion; Parallel database; Relational database management system; Relational database; Web search query; Information retrieval; Data mining; Search engine; Database design","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001498508,0.00004954937,0.00006696945,0.00005502203,0.00002857869,0.00001744197,0.00005097883,0.00002223375,0.000005555333],"category_scores_gemma":[0.00001531275,0.00004094202,0.000008085194,0.0001553533,0.00001416065,0.001150602,0.00007138067,0.00003011236,0.000004522166],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001559314,"about_ca_system_score_gemma":0.000008600919,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000665111,"about_ca_topic_score_gemma":0.00002760806,"domain_scores_codex":[0.999567,0.00002054846,0.0001089085,0.0001031941,0.00006569612,0.0001346779],"domain_scores_gemma":[0.9997345,0.0000186358,0.0000289608,0.0001568543,0.00001477781,0.00004623367],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000003023926,0.00004310605,0.01382883,0.00001457598,0.000003574416,0.000002109757,0.000570766,0.03620121,0.00007484523,0.9449817,0.0002779482,0.003998292],"study_design_scores_gemma":[0.0003365183,0.00002354998,0.008944859,0.00002470866,0.000002374675,0.00002212052,0.0001883744,0.9792344,0.0001652456,0.0004506246,0.01040832,0.0001989028],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002868293,0.0002077138,0.9954628,0.000122625,0.00008542362,0.00005999778,8.663143e-7,0.00004111148,0.001151197],"genre_scores_gemma":[0.35576,0.00006378595,0.6438128,0.0001029898,0.00003329831,0.000006429548,0.000005182934,0.000002499696,0.0002129985],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9445311,"threshold_uncertainty_score":0.1669567,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01738522641094388,"score_gpt":0.2463153529283406,"score_spread":0.2289301265173967,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}