{
    "article_id": 546,
    "public_id": "68f55e86-ce87-45a1-b804-d54cda688a63",
    "internal_identifier": null,
    "source_identifier": "5:193",
    "status": "published",
    "type": "research_article",
    "title": "Analysis Of Server Logs To Determine The Right Timing For Server Maintenance Using A Single Node And Multi-Node Hadoop Environment",
    "title_secondary": null,
    "abstract": "The log files that are continuously recorded are one of the most important information generated by web\r\nservers.Hadoop is an open source application platform that works on large amounts of data using hardware clusters. Web server\r\nlogs are large-volume plain text files that are meaningfully structured. The servers use customized operating systems for resource\r\nsharing. It is extremely important that, some precautions like security updates are formerly planned by monitoring the load status\r\nof the servers over time. Therefore, it is necessary to determine when the server workload is minimal. In the Hadoop environment,\r\nthe Hadoop file system is used to store the log files and the results are appreciated using the map and reduce functions. In this\r\nstudy, the Hadoop MapReduce programming model was used with two mode for analyzing weblogs. These modes are single\r\nnode environment mode and distributed environment mode. By using our approach, we have determined how many connections\r\nmade to the server during the day and we have tried to find the best time for maintenance.  ",
    "language": "en",
    "english_title": null,
    "english_abstract": null,
    "doi": null,
    "doi_url": null,
    "resource_url": "https://www.set-science.com/a/68f55e86-ce87-45a1-b804-d54cda688a63",
    "pdf_url": "https://www.set-science.com/a/68f55e86-ce87-45a1-b804-d54cda688a63/pdf",
    "og_image": "https://www.set-science.com/assets/img/og-card-v2.png",
    "authors": [
        {
            "public_id": "665dc5d7-38a9-4823-ba0e-5e8a68e8a7a7",
            "given": "Ferhat",
            "family": "Oflezer",
            "full": "Ferhat Oflezer",
            "literal": null,
            "orcid": null,
            "orcid_url": null,
            "email": "ferhat.oflezer@bozok.edu.tr",
            "corresponding": true,
            "sequence": "first",
            "affiliations": [
                {
                    "name": "Bozok Üniversitesi, Boğazlıyan Meslek Yüksekokulu, Bilgisayar Teknolojileri Bölümü ",
                    "department": null,
                    "country": null,
                    "country_code": null,
                    "ror": null,
                    "ror_url": null
                }
            ]
        },
        {
            "public_id": "ee9bb0aa-5390-4948-8753-dc1eb9f448bd",
            "given": "Turgay Tugay",
            "family": "Bilgin",
            "full": "Turgay Tugay Bilgin",
            "literal": null,
            "orcid": null,
            "orcid_url": null,
            "email": "turgay.bilgin@btu.edu.tr",
            "corresponding": false,
            "sequence": "additional",
            "affiliations": [
                {
                    "name": "Bilgisayar Mühendisliği, Bursa Teknik Üniversitesi  ",
                    "department": null,
                    "country": null,
                    "country_code": null,
                    "ror": null,
                    "ror_url": null
                }
            ]
        }
    ],
    "keywords": [
        "Hadoop; Mapreduce; File System;Bigdata;Data Processing"
    ],
    "translations": [
        {
            "language": "en",
            "title": "Analysis Of Server Logs To Determine The Right Timing For Server Maintenance Using A Single Node And Multi-Node Hadoop Environment",
            "abstract": "The log files that are continuously recorded are one of the most important information generated by web\r\nservers.Hadoop is an open source application platform that works on large amounts of data using hardware clusters. Web server\r\nlogs are large-volume plain text files that are meaningfully structured. The servers use customized operating systems for resource\r\nsharing. It is extremely important that, some precautions like security updates are formerly planned by monitoring the load status\r\nof the servers over time. Therefore, it is necessary to determine when the server workload is minimal. In the Hadoop environment,\r\nthe Hadoop file system is used to store the log files and the results are appreciated using the map and reduce functions. In this\r\nstudy, the Hadoop MapReduce programming model was used with two mode for analyzing weblogs. These modes are single\r\nnode environment mode and distributed environment mode. By using our approach, we have determined how many connections\r\nmade to the server during the day and we have tried to find the best time for maintenance.  \r\n",
            "keywords": [
                "Hadoop; Mapreduce; File System;Bigdata;Data Processing"
            ]
        }
    ],
    "subjects": [],
    "subject_names": [],
    "published_date": "2018-06-23",
    "published_year": "2018",
    "received_date": null,
    "accepted_date": null,
    "volume": "2",
    "issue": null,
    "page_first": "220",
    "page_last": "220",
    "article_number": null,
    "conference": {
        "short_name": "ISAS 2018",
        "full_title": "Ist International Symposium on Innovative Approaches in Scientific Studies",
        "name": "Ist International Symposium on Innovative Approaches in Scientific Studies",
        "acronym": "ISAS 2018",
        "location": "Kemer-Antalya, Türkiye",
        "start_date": "2018-04-11",
        "end_date": null,
        "public_id": "1d94fec9-c4fe-4034-9157-0b205eef4e56"
    },
    "proceedings": {
        "title": "Ist International Symposium on Innovative Approaches in Scientific Studies",
        "series_title": "Setsci conference indexing system",
        "publisher": "SET Technology",
        "isbn": null,
        "eisbn": null,
        "issn": "2618-6446",
        "eissn": null,
        "doi": null,
        "doi_prefix": null,
        "slug": "setsci-volume-2-2018-legacy-5",
        "public_id": "03da7b1c-cb6e-4f3b-aee4-ac41ee60fd75",
        "url": "https://www.set-science.com/p/setsci-volume-2-2018-legacy-5"
    },
    "license": {
        "name": "CC BY 4.0",
        "url": "https://creativecommons.org/licenses/by/4.0/",
        "code": "CC-BY-4.0",
        "open_access": true
    },
    "copyright": {
        "holder": "SET Technology",
        "year": "2018"
    },
    "funding_statement": null,
    "funders": [],
    "references": [],
    "statements": {
        "acknowledgements": null,
        "conflict_of_interest": null,
        "data_availability": null,
        "ai_disclosure": null
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    "credit": [],
    "history": {
        "published": "2018-06-23"
    }
}