SpeCA:A Speculative Parallel Crawling Approach on Apache Spark

SpeCA:A Speculative Parallel Crawling Approach on Apache Spark | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article SpeCA:A Speculative Parallel Crawling Approach on Apache Spark Li Yuxiang, Su Yaning This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7224688/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract The World Wide Web today is growing at a phenomenal rate. The crawling approach is of vital importance to improve the efficiency of crawling the web. The existing crawling algorithms on multicore platforms are time consuming and do not support large data well. In order to improve parallelism and efficiency of crawler on distributed network environments, based on the software thread-level speculation technique, this paper raises a Speculative parallel crawler approach (SpeCA) on Apache Spark. By analyzing the process of web crawler, the SpeCA firstly hires a function to divide a crawling process into several subprocesses which can be implemented independently and then spawns a number of threads to speculatively crawl in parallel. At last, the speculative results are merged to form the final outcome. Comparing with the conventional parallel approach on multicore platform, SpeCA is very efficiency and obtains a high parallelism degree by making the best of the resources of the cluster. Experiments show that the proposed approach could achieve a significant speedup improvement with compare to the traditional approach in average. In addition, with the growing number of working nodes, the execution time decreases gradually, and the speedup scales linearly. The results indicate that the crawling efficiency can be significantly enhanced by adopting this speculative parallel algorithm. Physical sciences/Engineering Physical sciences/Mathematics and computing Physical sciences/Physics crawling approach parallel Apache Spark Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7224688","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":498708203,"identity":"ef3b0868-6eb5-453b-a85c-0092b0416124","order_by":0,"name":"Li Yuxiang","email":"data:image/png;base64,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","orcid":"","institution":"Henan University of Sicence and Technology","correspondingAuthor":true,"prefix":"","firstName":"Li","middleName":"","lastName":"Yuxiang","suffix":""},{"id":498708204,"identity":"dbaf408c-ed66-4580-bdea-51c78c812825","order_by":1,"name":"Su Yaning","email":"","orcid":"","institution":"Henan University of Sicence and Technology","correspondingAuthor":false,"prefix":"","firstName":"Su","middleName":"","lastName":"Yaning","suffix":""}],"badges":[],"createdAt":"2025-07-27 07:23:13","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7224688/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7224688/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":104239199,"identity":"0fb16ac7-0efd-47a5-8556-a59af42f8696","added_by":"auto","created_at":"2026-03-09 13:58:10","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":687594,"visible":true,"origin":"","legend":"","description":"","filename":"123.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7224688/v1_covered_813333b3-9225-4de9-a1e2-09c8292a1cb7.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"SpeCA:A Speculative Parallel Crawling Approach on Apache Spark","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"crawling approach, parallel, Apache Spark","lastPublishedDoi":"10.21203/rs.3.rs-7224688/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7224688/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"The World Wide Web today is growing at a phenomenal rate. 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