MERAL Myanmar Education Research and Learning Portal
Item
{"_buckets": {"deposit": "a42d7044-2b75-4e4b-aabe-c2fee8d0132e"}, "_deposit": {"id": "5017", "owners": [], "pid": {"revision_id": 0, "type": "recid", "value": "5017"}, "status": "published"}, "_oai": {"id": "oai:meral.edu.mm:recid/5017", "sets": ["user-ucsy"]}, "communities": ["ucsy"], "item_1583103067471": {"attribute_name": "Title", "attribute_value_mlt": [{"subitem_1551255647225": "A Platform for Big Data Analytics on Distributed Scale-out Storage System", "subitem_1551255648112": "en"}]}, "item_1583103085720": {"attribute_name": "Description", "attribute_value_mlt": [{"interim": "Big data analytics is the process of examining large amounts of data of a varietyof types to uncover hidden patterns, unknown correlations and other useful information.Hadoop-based platform emerges to deal with big data. In Hadoop NameNode is used to store metadata in a single system’s memory, which is a performance bottleneck for scale-out. Gluster file system has no performance bottlenecks related to metadata. To achieve massive performance, scalability and fault tolerance for big data analytics, a big data platform is proposed. The proposed big data platform consists of big data storage and big data processing. The Hadoop big data platform and the proposed big data platform are implemented on commodity Linux virtual machines clusters and performance evaluations are conducted. According to the evaluation analysis, the proposed big data platform provides better scalability, fault tolerance, and faster query response time than the Hadoop platform."}]}, "item_1583103108160": {"attribute_name": "Keywords", "attribute_value_mlt": [{"interim": "big data"}, {"interim": "big data analytics"}, {"interim": "big data platform"}, {"interim": "Hadoop MapReduce"}, {"interim": "Gluster File System"}, {"interim": "Apache Pig"}, {"interim": "Apache Hive"}, {"interim": "Jaql"}]}, "item_1583103120197": {"attribute_name": "Files", "attribute_type": "file", "attribute_value_mlt": [{"accessrole": "open_access", "date": [{"dateType": "Available", "dateValue": "2019-07-16"}], "displaytype": "preview", "download_preview_message": "", "file_order": 0, "filename": "ijbdi2015.pdf", "filesize": [{"value": "762 Kb"}], "format": "application/pdf", "future_date_message": "", "is_thumbnail": false, "licensetype": "license_free", "mimetype": "application/pdf", "size": 762000.0, "url": {"url": "https://meral.edu.mm/record/5017/files/ijbdi2015.pdf"}, "version_id": "4615b268-c181-487c-b272-4f292d4b4cfa"}]}, "item_1583103131163": {"attribute_name": "Journal articles", "attribute_value_mlt": [{"subitem_issue": "", "subitem_journal_title": "International Journal of Big Data Intelligence (IJBDI)", "subitem_pages": "", "subitem_volume": ""}]}, "item_1583103147082": {"attribute_name": "Conference papers", "attribute_value_mlt": [{"subitem_acronym": "", "subitem_c_date": "", "subitem_conference_title": "", "subitem_part": "", "subitem_place": "", "subitem_session": "", "subitem_website": ""}]}, "item_1583103211336": {"attribute_name": "Books/reports/chapters", "attribute_value_mlt": [{"subitem_book_title": "", "subitem_isbn": "", "subitem_pages": "", "subitem_place": "", "subitem_publisher": ""}]}, "item_1583103233624": {"attribute_name": "Thesis/dissertations", "attribute_value_mlt": [{"subitem_awarding_university": "", "subitem_supervisor(s)": [{"subitem_supervisor": ""}]}]}, "item_1583105942107": {"attribute_name": "Authors", "attribute_value_mlt": [{"subitem_authors": [{"subitem_authors_fullname": "Aye, Kyar Nyo"}, {"subitem_authors_fullname": "Thein, Thandar"}]}]}, "item_1583108359239": {"attribute_name": "Upload type", "attribute_value_mlt": [{"interim": "Publication"}]}, "item_1583108428133": {"attribute_name": "Publication type", "attribute_value_mlt": [{"interim": "Article"}]}, "item_1583159729339": {"attribute_name": "Publication date", "attribute_value": "2015"}, "item_1583159847033": {"attribute_name": "Identifier", "attribute_value": "2053-1389"}, "item_title": "A Platform for Big Data Analytics on Distributed Scale-out Storage System", "item_type_id": "21", "owner": "1", "path": ["1597824175385"], "permalink_uri": "http://hdl.handle.net/20.500.12678/0000005017", "pubdate": {"attribute_name": "Deposited date", "attribute_value": "2019-07-16"}, "publish_date": "2019-07-16", "publish_status": "0", "recid": "5017", "relation": {}, "relation_version_is_last": true, "title": ["A Platform for Big Data Analytics on Distributed Scale-out Storage System"], "weko_shared_id": -1}
A Platform for Big Data Analytics on Distributed Scale-out Storage System
http://hdl.handle.net/20.500.12678/0000005017
http://hdl.handle.net/20.500.12678/0000005017b59bbf1d-413d-4a89-a380-7b4dbd7d1a93
a42d7044-2b75-4e4b-aabe-c2fee8d0132e
Name / File | License | Actions |
---|---|---|
![]() |
|
Publication type | ||||||
---|---|---|---|---|---|---|
Article | ||||||
Upload type | ||||||
Publication | ||||||
Title | ||||||
Title | A Platform for Big Data Analytics on Distributed Scale-out Storage System | |||||
Language | en | |||||
Publication date | 2015 | |||||
Authors | ||||||
Aye, Kyar Nyo | ||||||
Thein, Thandar | ||||||
Description | ||||||
Big data analytics is the process of examining large amounts of data of a varietyof types to uncover hidden patterns, unknown correlations and other useful information.Hadoop-based platform emerges to deal with big data. In Hadoop NameNode is used to store metadata in a single system’s memory, which is a performance bottleneck for scale-out. Gluster file system has no performance bottlenecks related to metadata. To achieve massive performance, scalability and fault tolerance for big data analytics, a big data platform is proposed. The proposed big data platform consists of big data storage and big data processing. The Hadoop big data platform and the proposed big data platform are implemented on commodity Linux virtual machines clusters and performance evaluations are conducted. According to the evaluation analysis, the proposed big data platform provides better scalability, fault tolerance, and faster query response time than the Hadoop platform. | ||||||
Keywords | ||||||
big data, big data analytics, big data platform, Hadoop MapReduce, Gluster File System, Apache Pig, Apache Hive, Jaql | ||||||
Identifier | 2053-1389 | |||||
Journal articles | ||||||
International Journal of Big Data Intelligence (IJBDI) | ||||||
Conference papers | ||||||
Books/reports/chapters | ||||||
Thesis/dissertations |