A general fragments allocation method for join query in distributed database
The quality of fragments allocation is key for improving performance of join query in distributed database. Current strategies concentrate on using heuristic rules to allocate fragments to corresponding locations, such as picking the location with maximum required data or with greedy algorithm. Notw...
Uloženo v:
| Vydáno v: | Information sciences Ročník 512; s. 1249 - 1263 |
|---|---|
| Hlavní autoři: | , , , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
| Vydáno: |
Elsevier Inc
01.02.2020
|
| Témata: | |
| ISSN: | 0020-0255, 1872-6291 |
| On-line přístup: | Získat plný text |
| Tagy: |
Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
|
| Abstract | The quality of fragments allocation is key for improving performance of join query in distributed database. Current strategies concentrate on using heuristic rules to allocate fragments to corresponding locations, such as picking the location with maximum required data or with greedy algorithm. Notwithstanding their benefits, under distributed environment, facing various query plans, different data distributions and expensive network cost, their scene-sensitive character may easily generate low quality allocation plan due to lack of generalization ability.
In this paper, for breaking this limitation, we propose a general strategy for allocating fragments(AlCo, Allocate fragments based on Cost). AlCo evaluates multiple candidate allocation plans based on cost, which is realized by a modified genetic algorithm employed from PostgreSQL. Our fitness function (cost model) synthetically considers various changeable factors to support generalization ability. For reducing the risks caused by randomization of genetic algorithm, AlCo provides an upper bound computed through current heuristic methods to improve the robustness of our genetic algorithm. We implement AlCo in a distributed database system, and the experiments show that, on TPC-H benchmark, AlCo is up to 2x–4x better on performance than existing strategies and performs well in robustness and scalability. |
|---|---|
| AbstractList | The quality of fragments allocation is key for improving performance of join query in distributed database. Current strategies concentrate on using heuristic rules to allocate fragments to corresponding locations, such as picking the location with maximum required data or with greedy algorithm. Notwithstanding their benefits, under distributed environment, facing various query plans, different data distributions and expensive network cost, their scene-sensitive character may easily generate low quality allocation plan due to lack of generalization ability.
In this paper, for breaking this limitation, we propose a general strategy for allocating fragments(AlCo, Allocate fragments based on Cost). AlCo evaluates multiple candidate allocation plans based on cost, which is realized by a modified genetic algorithm employed from PostgreSQL. Our fitness function (cost model) synthetically considers various changeable factors to support generalization ability. For reducing the risks caused by randomization of genetic algorithm, AlCo provides an upper bound computed through current heuristic methods to improve the robustness of our genetic algorithm. We implement AlCo in a distributed database system, and the experiments show that, on TPC-H benchmark, AlCo is up to 2x–4x better on performance than existing strategies and performs well in robustness and scalability. |
| Author | Shen, Li Liu, Wenjie Zhang, Jian Gao, Jintao Li, Zhanhuai |
| Author_xml | – sequence: 1 givenname: Jintao orcidid: 0000-0003-3262-8946 surname: Gao fullname: Gao, Jintao email: gaojintao@mail.nwpu.edu.cn organization: Northwestern Polytechnical University, Xi’an 710072, China – sequence: 2 givenname: Wenjie surname: Liu fullname: Liu, Wenjie organization: Northwestern Polytechnical University, Xi’an 710072, China – sequence: 3 givenname: Zhanhuai surname: Li fullname: Li, Zhanhuai organization: Northwestern Polytechnical University, Xi’an 710072, China – sequence: 4 givenname: Jian surname: Zhang fullname: Zhang, Jian organization: PingCAP Ltd., Beijing 100096, China – sequence: 5 givenname: Li surname: Shen fullname: Shen, Li organization: PingCAP Ltd., Beijing 100096, China |
| BookMark | eNp9kMtKQzEQhoNUsK0-gLu8wDkmac8luCrFGxTc6DrkMqk5nCaapELf3tS6ctHVzPzwDfzfDE188IDQLSU1JbS9G2rnU80I5eWuyXJxgaa071jVMk4naEoIIxVhTXOFZikNhJBl17ZTtFnhLXiIcsQ2yu0OfE5YjmPQMrvg8Q7yRzDYhoiH4Dz-2kM84LIYl3J0ap_BYCOzVDLBNbq0ckxw8zfn6P3x4W39XG1en17Wq02lGe9yZTtDqW16LRU3lFleAsZUS1puLOs4KE6XjDVaNrxXnFOm1EJpwiSYXiu9mCN6-qtjSCmCFZ_R7WQ8CErEUYcYRNEhjjqOUdFRmO4fo13-7ZijdONZ8v5EQqn07SCKpB14DcZF0FmY4M7QP0Ooffk |
| CitedBy_id | crossref_primary_10_1016_j_ins_2022_09_003 crossref_primary_10_1142_S0219649222400196 crossref_primary_10_1002_dac_5458 crossref_primary_10_1155_2022_4417998 crossref_primary_10_1109_ACCESS_2025_3547623 |
| Cites_doi | 10.1016/j.ins.2013.01.020 10.14778/3137628.3137650 10.14778/3137628.3137639 10.1109/69.273032 10.14778/3231751.3231761 10.14778/2850578.2850582 10.14778/3137628.3137636 10.14778/3007263.3007277 10.1109/TEVC.2016.2634625 10.14778/3025111.3025125 10.14778/3115404.3115415 10.14778/3055540.3055551 10.1109/TCYB.2019.2951520 |
| ContentType | Journal Article |
| Copyright | 2019 |
| Copyright_xml | – notice: 2019 |
| DBID | AAYXX CITATION |
| DOI | 10.1016/j.ins.2019.10.043 |
| DatabaseName | CrossRef |
| DatabaseTitle | CrossRef |
| DatabaseTitleList | |
| DeliveryMethod | fulltext_linktorsrc |
| Discipline | Engineering Library & Information Science |
| EISSN | 1872-6291 |
| EndPage | 1263 |
| ExternalDocumentID | 10_1016_j_ins_2019_10_043 S0020025519310114 |
| GroupedDBID | --K --M --Z -~X .DC .~1 0R~ 1B1 1OL 1RT 1~. 1~5 29I 4.4 457 4G. 5GY 5VS 7-5 71M 8P~ 9JN 9JO AAAKF AAAKG AABNK AACTN AAEDT AAEDW AAIAV AAIKJ AAKOC AALRI AAOAW AAQFI AAQXK AARIN AAXUO AAYFN ABAOU ABBOA ABEFU ABFNM ABJNI ABMAC ABTAH ABUCO ABXDB ABYKQ ACAZW ACDAQ ACGFS ACNNM ACRLP ACZNC ADBBV ADEZE ADGUI ADJOM ADMUD ADTZH AEBSH AECPX AEKER AENEX AFFNX AFKWA AFTJW AGHFR AGUBO AGYEJ AHHHB AHJVU AHZHX AIALX AIEXJ AIGVJ AIKHN AITUG AJBFU AJOXV ALMA_UNASSIGNED_HOLDINGS AMFUW AMRAJ AOUOD APLSM ARUGR ASPBG AVWKF AXJTR AZFZN BJAXD BKOJK BLXMC CS3 DU5 EBS EFJIC EFLBG EJD EO8 EO9 EP2 EP3 F5P FDB FEDTE FGOYB FIRID FNPLU FYGXN G-Q GBLVA GBOLZ HAMUX HLZ HVGLF HZ~ H~9 IHE J1W JJJVA KOM LG9 LY1 M41 MHUIS MO0 MS~ N9A O-L O9- OAUVE OZT P-8 P-9 P2P PC. Q38 R2- RIG ROL RPZ SBC SDF SDG SDP SDS SES SEW SPC SPCBC SSB SSD SST SSV SSW SSZ T5K TN5 TWZ UHS WH7 WUQ XPP YYP ZMT ZY4 ~02 ~G- 77I 9DU AATTM AAXKI AAYWO AAYXX ABWVN ACLOT ACRPL ACVFH ADCNI ADNMO ADVLN AEIPS AEUPX AFJKZ AFPUW AGQPQ AIGII AIIUN AKBMS AKRWK AKYEP ANKPU APXCP CITATION EFKBS ~HD |
| ID | FETCH-LOGICAL-c297t-f7d11f58cab9d12f9f7d22b6069df279eb914225ca598b9912bb3bc02aed8cbc3 |
| ISICitedReferencesCount | 8 |
| ISICitedReferencesURI | http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000504778300076&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| ISSN | 0020-0255 |
| IngestDate | Sat Nov 29 07:25:58 EST 2025 Tue Nov 18 21:55:37 EST 2025 Fri Feb 23 02:46:22 EST 2024 |
| IsPeerReviewed | true |
| IsScholarly | true |
| Keywords | Fragments allocation Robustness Distributed database Genetic algorithm Query optimization |
| Language | English |
| LinkModel | OpenURL |
| MergedId | FETCHMERGED-LOGICAL-c297t-f7d11f58cab9d12f9f7d22b6069df279eb914225ca598b9912bb3bc02aed8cbc3 |
| ORCID | 0000-0003-3262-8946 |
| PageCount | 15 |
| ParticipantIDs | crossref_primary_10_1016_j_ins_2019_10_043 crossref_citationtrail_10_1016_j_ins_2019_10_043 elsevier_sciencedirect_doi_10_1016_j_ins_2019_10_043 |
| PublicationCentury | 2000 |
| PublicationDate | February 2020 2020-02-00 |
| PublicationDateYYYYMMDD | 2020-02-01 |
| PublicationDate_xml | – month: 02 year: 2020 text: February 2020 |
| PublicationDecade | 2020 |
| PublicationTitle | Information sciences |
| PublicationYear | 2020 |
| Publisher | Elsevier Inc |
| Publisher_xml | – name: Elsevier Inc |
| References | Olma, Karpathiotakis, Alagiannis, Athanassoulis, Ailamaki (bib0015) 2017; 10 Sun, Franklin, Krishnan, Xin (bib0012) 2014 Sharma, Singh, Singh (bib0029) 2018; 8 Gong, Sun, Miao (bib0025) 2018; 22 Tpc-h. the home page of tpc-h Ding, Das, Wu, Chaudhuri, Narasayya (bib0011) 2018; 11 Thusoo, Sarma, Jain, Zheng, Chakka, Ning, Anthony, Hao, Murthy (bib0005) 2010 Gong, Jing, Ji (bib0026) 2013; 233 Li, Xu, Tang, Wang (bib0020) 2018; 11 (6) Sun, Miao, Gong, Zeng, Li, Wang (bib0028) 2019 Serafini, Taft, Elmore, Pavlo, Aboulnaga, Stonebraker (bib0014) 2016; 10 Tidb. source code of tidb Yang (bib0036) 2014; 2014 Ammar, Mcsherry, Salihoglu, Joglekar (bib0022) 2018; 11 (6) Apache drill. join planning guidelines Sharma, Singh, Singh (bib0032) 2016; 17 Jing, Gong, Zeng, Na (bib0027) 2018; 436 Rupprecht, Culhane, Pietzuch (bib0024) 2017; 10 Hasan, Motwani (bib0008) 1994 Lin, Ooi, Wang, Yu (bib0001) 2015 Yi, Shanbhag, Jindal, Madden (bib0019) 2017; 10 Graefe (bib0034) 2002; 6 Apache calcite. the home page of apache calcite Zaharia, Chowdhury, Das, Dave, Ma, Mccauley, Franklin, Shenker, Stoica (bib0018) 2012 Katsipoulakis, Labrinidis, Chrysanthis (bib0038) 2017; 10 . Graefe (bib0009) 1995; 18 Shankar, Nehme, Aguilar-Saborit, Chung, Elhemali, Halverson, Robinson, Subramanian, Dewitt (bib0017) 2012 Kloudas, Mamede, Rodrigues (bib0023) 2015; 9 Wiki. genetic algorithm Tpc benchmark h. the tool to generate tpc-h data sets Zamanian, Binnig, Salama (bib0013) 2015 Sharma, Singh, Singh (bib0031) 2018 Postgresql. genetic query optimizer Sevin, Coar (bib0030) 2011; 54 Soliman, Lyublena Antova, Amr El-Helw, Gu, George, Caragea, Foyzur Rahman, Petropoulos, Sivaramakrishnan Narayanan, Baldwin (bib0006) 2014 Chen, Jindel, Walzer, Sen, Andrews (bib0007) 2016; 9 Kabiljo, Karrer, Pundir, Pupyrev, Shalita, Presta, Akhremtsev (bib0021) 2017; 10 Mysql cluster.join pushdown Olma (10.1016/j.ins.2019.10.043_bib0015) 2017; 10 Kloudas (10.1016/j.ins.2019.10.043_bib0023) 2015; 9 Gong (10.1016/j.ins.2019.10.043_bib0026) 2013; 233 Sun (10.1016/j.ins.2019.10.043_bib0012) 2014 Yi (10.1016/j.ins.2019.10.043_bib0019) 2017; 10 Katsipoulakis (10.1016/j.ins.2019.10.043_bib0038) 2017; 10 10.1016/j.ins.2019.10.043_bib0004 Soliman (10.1016/j.ins.2019.10.043_bib0006) 2014 Sharma (10.1016/j.ins.2019.10.043_bib0029) 2018; 8 Sharma (10.1016/j.ins.2019.10.043_bib0031) 2018 Graefe (10.1016/j.ins.2019.10.043_bib0034) 2002; 6 10.1016/j.ins.2019.10.043_bib0003 10.1016/j.ins.2019.10.043_bib0002 Thusoo (10.1016/j.ins.2019.10.043_bib0005) 2010 Ding (10.1016/j.ins.2019.10.043_bib0011) 2018; 11 Kabiljo (10.1016/j.ins.2019.10.043_bib0021) 2017; 10 Jing (10.1016/j.ins.2019.10.043_bib0027) 2018; 436 Sharma (10.1016/j.ins.2019.10.043_bib0032) 2016; 17 Shankar (10.1016/j.ins.2019.10.043_bib0017) 2012 Graefe (10.1016/j.ins.2019.10.043_bib0009) 1995; 18 Ammar (10.1016/j.ins.2019.10.043_bib0022) 2018; 11 (6) Sevin (10.1016/j.ins.2019.10.043_bib0030) 2011; 54 Lin (10.1016/j.ins.2019.10.043_bib0001) 2015 10.1016/j.ins.2019.10.043_bib0016 10.1016/j.ins.2019.10.043_bib0037 Hasan (10.1016/j.ins.2019.10.043_bib0008) 1994 Rupprecht (10.1016/j.ins.2019.10.043_bib0024) 2017; 10 10.1016/j.ins.2019.10.043_bib0010 Yang (10.1016/j.ins.2019.10.043_bib0036) 2014; 2014 Sun (10.1016/j.ins.2019.10.043_bib0028) 2019 Zaharia (10.1016/j.ins.2019.10.043_bib0018) 2012 Li (10.1016/j.ins.2019.10.043_bib0020) 2018; 11 (6) Zamanian (10.1016/j.ins.2019.10.043_bib0013) 2015 Gong (10.1016/j.ins.2019.10.043_bib0025) 2018; 22 10.1016/j.ins.2019.10.043_bib0035 Serafini (10.1016/j.ins.2019.10.043_bib0014) 2016; 10 Chen (10.1016/j.ins.2019.10.043_bib0007) 2016; 9 10.1016/j.ins.2019.10.043_bib0033 |
| References_xml | – reference: Mysql cluster.join pushdown, – start-page: 17 year: 2015 end-page: 30 ident: bib0013 article-title: Locality-aware partitioning in parallel database systems publication-title: The 2015 ACM SIGMOD International Conference – volume: 2014 start-page: 141 year: 2014 end-page: 148 ident: bib0036 article-title: The architecture of oceanbase relational database system publication-title: J. East China Normal Univ. – start-page: 767 year: 2012 end-page: 776 ident: bib0017 article-title: Query optimization in microsoft SQL server PDW publication-title: ACM SIGMOD International Conference on Management of Data – volume: 233 start-page: 141 year: 2013 end-page: 161 ident: bib0026 article-title: Evolutionary algorithms with preference polyhedron for interval multi-objective optimization problems publication-title: Inf. Sci. – volume: 10 start-page: 1286 year: 2017 end-page: 1297 ident: bib0038 article-title: A holistic view of stream partitioning costs publication-title: Proc. VLDB Endow. – start-page: 2 year: 2012 ident: bib0018 article-title: Resilient distributed datasets: a fault-tolerant abstraction for in-memory cluster computing publication-title: Usenix Conference on Networked Systems Design and Implementation – start-page: 1 year: 2019 end-page: 14 ident: bib0028 article-title: Interval multiobjective optimization with memetic algorithms publication-title: IEEE Trans. Cybern. – year: 2018 ident: bib0031 article-title: Clinical decision support system query optimizer using hybrid firefly and controlled genetic algorithm publication-title: J. King Saud Univ. Comput. Inf. Sci. – volume: 8 start-page: 1 year: 2018 end-page: 18 ident: bib0029 article-title: A review of different cost-based distributed query optimizers publication-title: Prog. Artif. Intell. – reference: Tidb. source code of tidb, – volume: 9 start-page: 1401 year: 2016 end-page: 1412 ident: bib0007 article-title: The MemSQL query optimizer: a modern optimizer for real-time analytics in a distributed database publication-title: Proc. VLDB Endow. – start-page: 1115 year: 2014 end-page: 1126 ident: bib0012 article-title: Fine-grained partitioning for aggressive data skipping publication-title: ACM SIGMOD International Conference on Management of Data – volume: 9 start-page: 72 year: 2015 end-page: 83 ident: bib0023 article-title: PIXIDA: optimizing data parallel jobs in wide-area data analytics publication-title: Proc. VLDB Endow. – reference: Postgresql. genetic query optimizer, – volume: 10 start-page: 1250 year: 2017 end-page: 1261 ident: bib0024 article-title: Squirreljoin: network-aware distributed join processing with lazy partitioning publication-title: Proc. VLDB Endow. – reference: Wiki. genetic algorithm, – volume: 436 start-page: 146 year: 2018 end-page: 161 ident: bib0027 article-title: An ensemble framework for assessing solutions of interval programming problems publication-title: Inf. Sci. – start-page: 337 year: 2014 end-page: 348 ident: bib0006 article-title: Orca: a modular query optimizer architecture for big data publication-title: ACM SIGMOD International Conference on Management of Data – volume: 11 (6) start-page: 691 year: 2018 end-page: 704 ident: bib0022 article-title: Distributed evaluation of subgraph queries using worstcase optimal lowmemory dataflows publication-title: Proceedings of the VLDB Endowment – volume: 6 start-page: 120 year: 2002 end-page: 135 ident: bib0034 article-title: Volcano/spl minus/an extensible and parallel query evaluation system publication-title: IEEE Trans. Knowl. Data Eng. – volume: 22 start-page: 47 year: 2018 end-page: 60 ident: bib0025 article-title: A set-based genetic algorithm for interval many-objective optimization problems publication-title: IEEE Trans. Evol. Comput. – volume: 11 (6) start-page: 705 year: 2018 end-page: 718 ident: bib0020 article-title: Model-free control for distributed stream data processing using deep reinforcement learning publication-title: Proceedings of the VLDB Endowment – start-page: 996 year: 2010 end-page: 1005 ident: bib0005 article-title: Hive - a petabyte scale data warehouse using hadoop publication-title: Proceedings-International Conference on Data Engineering – volume: 54 start-page: 147 year: 2011 end-page: 152 ident: bib0030 article-title: An evolutionary genetic algorithm for optimization of distributed database queries publication-title: International Symposium on Computer & Information Sciences – reference: . – volume: 18 start-page: 19 year: 1995 end-page: 29 ident: bib0009 article-title: The cascades framework for query optimization publication-title: Data Eng. Bull. – reference: Apache calcite. the home page of apache calcite, – start-page: 36 year: 1994 end-page: 47 ident: bib0008 article-title: Optimization algorithms for exploiting the parallelism-communication tradeoff in pipelined parallelism publication-title: Proceedings of 20th International Conference on Very Large Data Bases – reference: Tpc-h. the home page of tpc-h, – volume: 10 start-page: 589 year: 2017 end-page: 600 ident: bib0019 article-title: AdaptDB: adaptive partitioning for distributed joins publication-title: Proc. VLDB Endow. – reference: Apache drill. join planning guidelines, – start-page: 811 year: 2015 end-page: 825 ident: bib0001 article-title: Scalable distributed stream join processing publication-title: ACM Sigmod International Conference – volume: 10 start-page: 445 year: 2016 end-page: 456 ident: bib0014 article-title: Clay: fine-grained adaptive partitioning for general database schemas publication-title: Proc. VLDB Endow. – volume: 10 start-page: 1106 year: 2017 end-page: 1117 ident: bib0015 article-title: Slalom: coasting through raw data via adaptive partitioning and indexing publication-title: Proc. VLDB Endow. – reference: Tpc benchmark h. the tool to generate tpc-h data sets, – volume: 11 start-page: 1123 year: 2018 end-page: 1136 ident: bib0011 article-title: Plan stitch: harnessing the best of many plans publication-title: Proc. VLDB Endow. – volume: 17 start-page: 161 year: 2016 end-page: 173 ident: bib0032 article-title: Design and analysis of stochastic DSS query optimizers in a distributed database system publication-title: Egypt. Inf. J. – volume: 10 year: 2017 ident: bib0021 article-title: Social hash partitioner: a scalable distributed hypergraph partitioner publication-title: Proc. VLDB Endow. – volume: 54 start-page: 147 year: 2011 ident: 10.1016/j.ins.2019.10.043_bib0030 article-title: An evolutionary genetic algorithm for optimization of distributed database queries – start-page: 36 year: 1994 ident: 10.1016/j.ins.2019.10.043_bib0008 article-title: Optimization algorithms for exploiting the parallelism-communication tradeoff in pipelined parallelism – volume: 233 start-page: 141 issue: 2 year: 2013 ident: 10.1016/j.ins.2019.10.043_bib0026 article-title: Evolutionary algorithms with preference polyhedron for interval multi-objective optimization problems publication-title: Inf. Sci. doi: 10.1016/j.ins.2013.01.020 – volume: 10 issue: 11 year: 2017 ident: 10.1016/j.ins.2019.10.043_bib0021 article-title: Social hash partitioner: a scalable distributed hypergraph partitioner publication-title: Proc. VLDB Endow. doi: 10.14778/3137628.3137650 – ident: 10.1016/j.ins.2019.10.043_bib0037 – ident: 10.1016/j.ins.2019.10.043_bib0016 – volume: 436 start-page: 146 year: 2018 ident: 10.1016/j.ins.2019.10.043_bib0027 article-title: An ensemble framework for assessing solutions of interval programming problems publication-title: Inf. Sci. – volume: 10 start-page: 1286 issue: 11 year: 2017 ident: 10.1016/j.ins.2019.10.043_bib0038 article-title: A holistic view of stream partitioning costs publication-title: Proc. VLDB Endow. doi: 10.14778/3137628.3137639 – volume: 11 (6) start-page: 705 year: 2018 ident: 10.1016/j.ins.2019.10.043_bib0020 article-title: Model-free control for distributed stream data processing using deep reinforcement learning – volume: 8 start-page: 1 year: 2018 ident: 10.1016/j.ins.2019.10.043_bib0029 article-title: A review of different cost-based distributed query optimizers publication-title: Prog. Artif. Intell. – volume: 6 start-page: 120 issue: 1 year: 2002 ident: 10.1016/j.ins.2019.10.043_bib0034 article-title: Volcano/spl minus/an extensible and parallel query evaluation system publication-title: IEEE Trans. Knowl. Data Eng. doi: 10.1109/69.273032 – ident: 10.1016/j.ins.2019.10.043_bib0010 – volume: 11 start-page: 1123 issue: 10 year: 2018 ident: 10.1016/j.ins.2019.10.043_bib0011 article-title: Plan stitch: harnessing the best of many plans publication-title: Proc. VLDB Endow. doi: 10.14778/3231751.3231761 – volume: 2014 start-page: 141 year: 2014 ident: 10.1016/j.ins.2019.10.043_bib0036 article-title: The architecture of oceanbase relational database system publication-title: J. East China Normal Univ. – ident: 10.1016/j.ins.2019.10.043_bib0003 – start-page: 2 year: 2012 ident: 10.1016/j.ins.2019.10.043_bib0018 article-title: Resilient distributed datasets: a fault-tolerant abstraction for in-memory cluster computing – start-page: 1115 year: 2014 ident: 10.1016/j.ins.2019.10.043_bib0012 article-title: Fine-grained partitioning for aggressive data skipping – volume: 18 start-page: 19 issue: 5 year: 1995 ident: 10.1016/j.ins.2019.10.043_bib0009 article-title: The cascades framework for query optimization publication-title: Data Eng. Bull. – volume: 9 start-page: 72 issue: 2 year: 2015 ident: 10.1016/j.ins.2019.10.043_bib0023 article-title: PIXIDA: optimizing data parallel jobs in wide-area data analytics publication-title: Proc. VLDB Endow. doi: 10.14778/2850578.2850582 – start-page: 811 year: 2015 ident: 10.1016/j.ins.2019.10.043_bib0001 article-title: Scalable distributed stream join processing – start-page: 767 year: 2012 ident: 10.1016/j.ins.2019.10.043_bib0017 article-title: Query optimization in microsoft SQL server PDW – volume: 10 start-page: 1250 issue: 11 year: 2017 ident: 10.1016/j.ins.2019.10.043_bib0024 article-title: Squirreljoin: network-aware distributed join processing with lazy partitioning publication-title: Proc. VLDB Endow. doi: 10.14778/3137628.3137636 – volume: 17 start-page: 161 issue: 2 year: 2016 ident: 10.1016/j.ins.2019.10.043_bib0032 article-title: Design and analysis of stochastic DSS query optimizers in a distributed database system publication-title: Egypt. Inf. J. – ident: 10.1016/j.ins.2019.10.043_bib0033 – ident: 10.1016/j.ins.2019.10.043_bib0035 – start-page: 337 year: 2014 ident: 10.1016/j.ins.2019.10.043_bib0006 article-title: Orca: a modular query optimizer architecture for big data – volume: 9 start-page: 1401 issue: 13 year: 2016 ident: 10.1016/j.ins.2019.10.043_bib0007 article-title: The MemSQL query optimizer: a modern optimizer for real-time analytics in a distributed database publication-title: Proc. VLDB Endow. doi: 10.14778/3007263.3007277 – volume: 11 (6) start-page: 691 year: 2018 ident: 10.1016/j.ins.2019.10.043_bib0022 article-title: Distributed evaluation of subgraph queries using worstcase optimal lowmemory dataflows – volume: 22 start-page: 47 issue: 1 year: 2018 ident: 10.1016/j.ins.2019.10.043_bib0025 article-title: A set-based genetic algorithm for interval many-objective optimization problems publication-title: IEEE Trans. Evol. Comput. doi: 10.1109/TEVC.2016.2634625 – start-page: 996 year: 2010 ident: 10.1016/j.ins.2019.10.043_bib0005 article-title: Hive - a petabyte scale data warehouse using hadoop – volume: 10 start-page: 445 issue: 4 year: 2016 ident: 10.1016/j.ins.2019.10.043_bib0014 article-title: Clay: fine-grained adaptive partitioning for general database schemas publication-title: Proc. VLDB Endow. doi: 10.14778/3025111.3025125 – year: 2018 ident: 10.1016/j.ins.2019.10.043_bib0031 article-title: Clinical decision support system query optimizer using hybrid firefly and controlled genetic algorithm publication-title: J. King Saud Univ. Comput. Inf. Sci. – volume: 10 start-page: 1106 issue: 10 year: 2017 ident: 10.1016/j.ins.2019.10.043_bib0015 article-title: Slalom: coasting through raw data via adaptive partitioning and indexing publication-title: Proc. VLDB Endow. doi: 10.14778/3115404.3115415 – ident: 10.1016/j.ins.2019.10.043_bib0004 – volume: 10 start-page: 589 issue: 5 year: 2017 ident: 10.1016/j.ins.2019.10.043_bib0019 article-title: AdaptDB: adaptive partitioning for distributed joins publication-title: Proc. VLDB Endow. doi: 10.14778/3055540.3055551 – ident: 10.1016/j.ins.2019.10.043_bib0002 – start-page: 17 year: 2015 ident: 10.1016/j.ins.2019.10.043_bib0013 article-title: Locality-aware partitioning in parallel database systems – start-page: 1 year: 2019 ident: 10.1016/j.ins.2019.10.043_bib0028 article-title: Interval multiobjective optimization with memetic algorithms publication-title: IEEE Trans. Cybern. doi: 10.1109/TCYB.2019.2951520 |
| SSID | ssj0004766 |
| Score | 2.350528 |
| Snippet | The quality of fragments allocation is key for improving performance of join query in distributed database. Current strategies concentrate on using heuristic... |
| SourceID | crossref elsevier |
| SourceType | Enrichment Source Index Database Publisher |
| StartPage | 1249 |
| SubjectTerms | Distributed database Fragments allocation Genetic algorithm Query optimization Robustness |
| Title | A general fragments allocation method for join query in distributed database |
| URI | https://dx.doi.org/10.1016/j.ins.2019.10.043 |
| Volume | 512 |
| WOSCitedRecordID | wos000504778300076&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| hasFullText | 1 |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| journalDatabaseRights | – providerCode: PRVESC databaseName: Elsevier SD Freedom Collection Journals 2021 customDbUrl: eissn: 1872-6291 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0004766 issn: 0020-0255 databaseCode: AIEXJ dateStart: 19950101 isFulltext: true titleUrlDefault: https://www.sciencedirect.com providerName: Elsevier |
| link | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwtV1Nb9QwELWg5QAHBAVEW4p8QBxYpUqcZB0fV6h8VFXFoUh7i-zYpokqb7XdRf35zMR2Nm0BARKXKLLi3cjzPPHMvJkh5I0UUy5twRKhM5kUmmWJYjJNZC711NjS2KJPFD7hp6fVfC6-hHDBVd9OgDtXXV-Ly_8qahgDYWPq7F-Ie_hRGIB7EDpcQexw_SPBz7ArMnqaJnYpv_kMNoyue99caBndswu7Resm8F1Y9rl_GkvoYvcrOIIib1TFuE0Xye5DouMkfDeH8_hH6QM4rVvJxcDxadc9g8-4rjWbwT4cci7d-Vq2d9zWxxGtwREBVmd6g9QxZMjcIHCm_kFfivfQeCVbcZZMme_SFbVwGdjUXo9iS-zRNzljXgve0ffe9dCBkYKl1zNxiEw9X_fpVhltjEr3BhScWDO0Au-TbcZLAcp8e_b5aH68yablPsId3zzGwntW4K0_-vlpZnRCOXtCHgfTgs48JJ6Se8btkEejgpM75CCkqdC3dCROGhT8M3IyowE8dAAP3YCHevBQmEkRPLQHD4WbEXhoBM9z8vXD0dn7T0not5E0TPBVYrnOMltWjVSwc5kVMMCYAhNXaMu4MEqgx7BsZCkqBYYFUypXTcqk0VWjmvwF2XILZ14Smtt8WhldZprLQhaFUExzZaw2kiHheZekcd3qJhSjx54oF3VkHXY1LHWNS41DsNS75N0w5dJXYvndw0UURh22hD8i1oCcX0_b-7dp--ThZkO8Ilur5dockAfN91V7tXwd8PUDud-Y8Q |
| linkProvider | Elsevier |
| openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=A+general+fragments+allocation+method+for+join+query+in+distributed+database&rft.jtitle=Information+sciences&rft.au=Gao%2C+Jintao&rft.au=Liu%2C+Wenjie&rft.au=Li%2C+Zhanhuai&rft.au=Zhang%2C+Jian&rft.date=2020-02-01&rft.pub=Elsevier+Inc&rft.issn=0020-0255&rft.eissn=1872-6291&rft.volume=512&rft.spage=1249&rft.epage=1263&rft_id=info:doi/10.1016%2Fj.ins.2019.10.043&rft.externalDocID=S0020025519310114 |
| thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=0020-0255&client=summon |
| thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=0020-0255&client=summon |
| thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=0020-0255&client=summon |