{"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00161710","sets":["6504:8672:8729"]},"path":["8729"],"owner":"6748","recid":"161710","title":["低更新頻度データを対象としたSQL-on-Hadoopエンジンの時空間効率の比較と評価"],"pubdate":{"attribute_name":"公開日","attribute_value":"2016-03-10"},"_buckets":{"deposit":"d530765b-f834-461f-832f-3c600aa5e881"},"_deposit":{"id":"161710","pid":{"type":"depid","value":"161710","revision_id":0},"owners":[6748],"status":"published","created_by":6748},"item_title":"低更新頻度データを対象としたSQL-on-Hadoopエンジンの時空間効率の比較と評価","author_link":["314639"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"低更新頻度データを対象としたSQL-on-Hadoopエンジンの時空間効率の比較と評価"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"データとウェブ","subitem_subject_scheme":"Other"}]},"item_type_id":"22","publish_date":"2016-03-10","item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"jpn"}]},"item_22_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"NHN comico 株式会社"}]},"item_publisher":{"attribute_name":"出版者","attribute_value_mlt":[{"subitem_publisher":"情報処理学会","subitem_publisher_language":"ja"}]},"publish_status":"0","weko_shared_id":-1,"item_file_price":{"attribute_name":"Billing file","attribute_type":"file","attribute_value_mlt":[{"url":{"url":"https://ipsj.ixsq.nii.ac.jp/record/161710/files/IPSJ-Z78-3B-02.pdf","label":"IPSJ-Z78-3B-02.pdf"},"date":[{"dateType":"Available","dateValue":"2016-05-18"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-Z78-3B-02.pdf","filesize":[{"value":"521.9 kB"}],"mimetype":"application/pdf","priceinfo":[{"tax":["include_tax"],"price":"0","billingrole":"6"},{"tax":["include_tax"],"price":"0","billingrole":"8"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"9ae939c7-c332-4faa-88cb-95623281dc53","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2016 by the Information Processing Society of Japan"}]},"item_22_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"趙, 漢哲"}],"nameIdentifiers":[{}]}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourceuri":"http://purl.org/coar/resource_type/c_5794","resourcetype":"conference paper"}]},"item_22_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AN00349328","subitem_source_identifier_type":"NCID"}]},"item_22_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"Hadoopの登場は今まで不可能だった大規模のデータの蓄積と分析を可能にした。特にHiveのようなSQL-on-Hadoopエンジンを利用することでSQLに慣れているデータ分析家であれば特別なトレーニングを受けなくても容易にHadoopのパワーを活かすことができた。しかし、既存のRDBMSとは違ってHadoopではデータ更新や遅延挿入が困難な問題点も存在する。本論文では商品マスターテーブルのように更新頻度が低いデータを対象として複数のSQL-on-Hadoopエンジンの時空間効率を比較する。幅広く使われているがデータ更新や遅延挿入ができないHiveとそれらが可能になったHive-on-HBase、Phoenixを比較することで扱うデータの特性によってどのアプローチを取ることがデータの蓄積と処理に有利なのかを判断することが可能である。","subitem_description_type":"Other"}]},"item_22_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"480","bibliographic_titles":[{"bibliographic_title":"第78回全国大会講演論文集"}],"bibliographicPageStart":"479","bibliographicIssueDates":{"bibliographicIssueDate":"2016-03-10","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"1","bibliographicVolumeNumber":"2016"}]},"relation_version_is_last":true,"weko_creator_id":"6748"},"id":161710,"updated":"2025-01-20T11:46:19.598543+00:00","links":{},"created":"2025-01-19T00:34:25.988203+00:00"}