Arcomem training Specifying Crawls Advanced


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This presentation on Specifying Crawls is part of the ARCOMEM training curriculum. Feel free to roam around or contact us on Twitter via @arcomem to learn more about ARCOMEM training on archiving Social Media.

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  • {"38":"For each campaign, the archivist can select which SMC, he wants to focus on (blogs, video, discussion) and he does the same for the API crawler (Facebook, Twitter, Flickr, YouTube…).\n","27":"\n","16":"Netarchivesuite ( developed by the two national deposit libraries in Denmark, The Royal Library and The State and University Library\nto plan, schedule and run web harvests for selective and broad crawl\nbuilt-in bit preservation functionality\nWeb curator tool:\nOpen-source workflow management application for selective web archiving developped by the National Library of New Zealand and the British Library, initiated by the International Internet Preservation Consortium\nArchive-it\nA subscription service by Internet Archive to build and preserve collections: allows to\nharvest, catalog, manage and browse archived collections\nArcomem crawler cokpit\n","6":"There is several protocol : \nMai protocol as \nPOP3 (post office protocol version 3)\nSMTP (simple mail transfer protocol\nDNS Domain name service\nDHCP Dynamic Host configuration \nFTP File transfer Protocole\nIMAP Internet Message Access Protocole\n","34":"A crawl is guided by the crawl specifications defined by the user. The crawl specification contains URLs to start the discovery from seeds, keywords to look for in web pages, social web sites APIs to query (and with which keywords) and Social Media Categories (SMC) to focus the crawl on. The seeds get fetched, and the corresponding content and the social sites API query responses are inserted into the document store. The insertion triggers the online analysis process. The Web resources and the links extracted from them are analyzed and scored by the Online Analysis Modules. The links get sent to the crawler’s URL queue, where their score is used to determine the order in which they should be crawled, thereby guiding the crawler. The newly crawled content gets written to the document store, completing the loop. On top of the prototype, a UI allows the user to target topics to archive and offers some analyses of collected data.\n","23":"\n","24":"\n","13":"A lot of data are stored in DB hidden to search engine like google are not available for such engine,\nmoreover many pages are created dynamicaly to answer to queries so hey do not existbefor user requested information. \nThis enorme reservoir \n\n","8":"URI Uniform Resource Identifier (URI) is a string of characters used to identify a name or a resource on the Internet.\n","42":"On the top of the page, a progression bar gives an estimation of crawl progress until completion. It is a ratio between seen and unseen URL recorded by the crawler. Seen URLs are all the URLs which have been already crawled. Unseen are the URLs, which have been discovered but are waiting to be crawled \n","31":"\n","20":"Crawler cokpit send order to the crawler. An order is an « intelligent crawl specification ». It is created with the set-up of hte campaign. \nThis order is send to the crawler according to the scheduler. \n","37":". The information is organized following different topics: general description of the campaign, metadata, current status, crawl activity, statistics and analysis \n","4":"To find an information online, I have to know is address. \nLe système de nom de domaine (Domain Name System - DNS) aide les utilisateurs à naviguer sur Internet. Chaque ordinateur relié à Internet a une adresse unique appelée “adresse IP” (adresse de protocole Internet). Étant donné que les adresses IP (qui sont des séries de chiffres) sont difficiles à mémoriser, le DNS permet d’utiliser à la place une série de lettres familières (le “nom de domaine”). Par exemple, au lieu de taper “,” vous pouvez taper “”\n","21":"\n","10":"On line information heterogeneous\nthere is copy online \n"}
  • Arcomem training Specifying Crawls Advanced

    1. 1. Specifying crawls France Lasfargues Internet Memory Foundation Paris, France Slide 1
    2. 2. Training Goals ➔ Help user to specify properly the campaign ➔ Make user understanding what it is going on in the back end of the ARCOMEM platform ➔ Set-up a campaign in the crawler cockpit Slide 2
    3. 3. Plan What is the Web ? Challenges and SOA ARCOMEM platform Crawler Set-up a campaign in the Arcomen Crawler Cockpit Slide 3
    4. 4. Introduction : How does web work ? ➔ The web is managed by protocols and standards : • HTTP Hypertext Transfer Protocol • HTML HyperText Markup Language • URL Uniform Resource Locator • DNS Domain Name System ➔ Each server has an address : IP address • Example : -> 4
    5. 5. WWW The web is a large space of communication and information : • managed by servers which talk together by convention (protocol) and through applications in a large network. • a naming space organized and controlled (ICANN)  World Wide Web: abbreviated as WWW and commonly known as the Web, is a system of interlinked hypertext documents accessed via the internet Slide 5
    6. 6. HTTP - Hypertext Transfer Protocol ➔ Notion client/server • request-response protocol in the client-server computing model ➔ How does it work ? • • Server hosts the content and delivers it • 6 Client asks for a content The browser locates the DNS server, connects itself to the server and sends a request to the server.
    7. 7. HTML - HyperText Markup Languag e ➔ Markup language for Web page ➔ Written in form of HTML elements ➔ Creates structured documents denoting structural semantic elements for text as headings, paragraphs, titles, links, quotes, and other items ➔ Allows text and embedded as images ➔ Example : 7
    8. 8. URI - URL ➔ URL - Uniform resource Locator (URL) that specifies where an identified resource is available and the mechanism for retrieving it. ➔ Examples : – http://host.domain.extension/path/pageORfile – – – Samos 2013 – Workshop : The ARCOMEM Platform 8
    9. 9. Domain name and extension ➔ Manage by l’ICANN, Internet Corporation for Assigned Names and Numbers (ICANN), is non profit organization, allocated by registrar. • ➔ ICANN coordinates the allocation and assignment to ensure the universal resolvability of : • Domain names (forming a system referred to as «DNS») • Internet protocol («IP») addresses • Protocol port and parameter numbers. ➔ Several types of TLD • • gTLD : aero, .biz, .coop, .info, .museum, .name, et .pro • 9 TLD first level : .com, .info, etc ccTLD (country code Top Level Domains).fr
    10. 10. What kind of contents? ➔ Different type of contents : multimedia text, video, images ➔ Different type of producers : • public : institution, government, museum, TV.... • private : foundation, company, press, people, blog... ➔ Each producer is in charge of its content • Information can disappear: fragility • Size 10
    11. 11. Social web ➔ Focus on people’s socialization and interaction • Characteristics : • Walled space in which users can interact • Creation of social network ➔ WEB ARCHIVE -> challenges in term of content, privacy and technique. • Examples: • Share bookmark(, Digg), videos (Dailymotion, YouTube), photos (Flickr, Picasa) • community (MySpace, Facebook) 11
    12. 12. Ex. of technical difficulties: Videos ➔ Standard HTTP protocol • obfuscated links to the video files • dynamic playlists and channels or configuration files loaded by the player several hops and redirects to the server of the video content e.g.: YouTube ➔ Streaming protocols: RTSP, RTMP, MMS... • real-time protocols implemented by the video players suited for large video files (control commands) or live broadcasts • sometimes proprietary protocols (e.g.: RTMP - Adobe) available tools: MPlayer, FLVStreamer, VCL 12
    13. 13. Deep /Hidden Web • Deep web: content accessible behind password, database, payment... and hidden to search engine Schema établit sur la base de la figure "Distribution des sites du Deep Web par types de contenu" de l'étude Bright Planet. 13
    14. 14. How do we archive it ? ➔ Challenges for archiving : – dynamic websites ➔ Technical barriers: • • • • • some javascript animation on Flash pop-up video and audio on streaming restricted access ➔Traps : Spam and loop 14
    15. 15. What do user need to do some web archiving ? ➔ Define the target content (Website, URL, Topic…) ➔ A tool to manage its campaign ➔ Intelligent crawler to archive content 15
    16. 16. Management tools (1) Several tool exist already developed by Libraries which are doing some Library. ➔Netarchivesuite ( ➔The NetarchiveSuite software was originally developed by the two national deposit libraries in Denmark, The Royal Library and The State and University Library and has been running in production, harvesting the Danish world wide web since 2005. The French National Library and the Austrian National Libraries joined the project in 2008. ➔Web curator tool: Open-source workflow management application for selective web archiving developed by the National Library of New Zealand and the British Library, initiated by the International Internet Preservation Consortium ➔Archive-it A subscription service by Internet Archive to build and preserve collections: allows to harvest, catalogue, manage and browse archived collections ➔ Service provides by the Internet Memory Foundation. ➔Arcomem crawler cockpit 16
    17. 17. How does a crawler work ? ➔ A crawler is a bot parsing web pages in order to index or and archive them. Robot navigates following links ➔ Link in the center of crawl’s problematic • Explicit links : source code is available and full path is explicitly stated • Variable link : source code is available but use variables to encode the path • Opaque links: source code not available Example : 17
    18. 18. Parameters ➔ Scoping function is used to define how depth the crawl will go • Complete or specific content of a website • Discovery or focus crawl ➔ Politeness • Follow the common rules of politeness ➔ Robots.txt • Follow ➔ Frequency • How often I want to launch a crawl on this target ? 18
    19. 19. Source code: http:/ !DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN" ""> <html xmlns="" dir="ltr" lang="de-DE"> <head profile=> <meta http-equiv="Content-Type" content="text/html; charset=UTF-8" /> <meta name="distribution" content="global" /> <meta name="robots" content="follow, all" /> <meta name="language" content="en" /> <meta name="bitly-verification" content="59eb4f9028ea"/> <meta name="verify-v1" content="7XvBEj6Tw9dyXjHST/9sgRGxGymxFdHIZsM6Ob/xo5E=" /> <title> ARCOMEM</title> • <div id="navbar"> <div class="menu"><ul class="menu"><li class="page_item page-item-1490"><a href="" title="iPres 2013">iPres 2013</a></li><li class="page_item page-item-1478"><a href="" title="SYSTEM DEMOS">SYSTEM DEMOS</a><ul class='children'><li class="page_item page-item-1502"><a href="" title="Technology Demos">Technology Demos</a></li></ul></li><li class="page_item page-item-2"><a href="" title="ABOUT ARCOMEM">ABOUT ARCOMEM</a><ul class='children'><li class="page_item page-item-14"><a href="" title="USE CASES">USE CASES</a></li><li class="page_item page-item-16"><a href="" title="R&amp;D CHALLENGES">R&D CHALLENGES</a></li></ul></li><li class="page_item page-item-20"><a href="" title="DOWNLOADS">DOWNLOADS</a><ul class='children'><li class="page_item page-item-1043"><a href="" title="CODE">CODE</a></li><li class="page_item page-item-973"><a href="" title="DELIVERABLES">DELIVERABLES</a></li></ul></li><li class="page_item page-item-798"><a href="" title="VIDEOS">VIDEOS</a></li><li class="page_item page-item-761"><a href="" title="DISSEMINATION ACTIVITIES">DISSEMINATION ACTIVITIES</a><ul class='children'><li class="page_item page-item-1235"><a href="" title="PAST ACTIVITES">PAST ACTIVITES</a></li><li class="page_item page-item-912"><a href="" title="PUBLICATIONS">PUBLICATIONS</a></li><li class="page_item page-item-888"><a href="" title="ICWSM 2012">ICWSM 2012</a></li><li class="page_item page-item-1004"><a href="" title="KECSM 2012">KECSM 2012</a></li></ul></li><li class="page_item page-item-1157"><a href="" title="RELATED PROJECTS">RELATED PROJECTS</a></li><li class="page_item pageitem-282"><a href="" title="CONTACT">CONTACT</a></li></ul></div> 19
    20. 20. ARCOMEM Workflow 20
    21. 21. Memory Bot • Component Name: IMF Large Scale Crawler – The large scale crawler retrieves content from the web and stores it in an HBase repository. It aims at being scalable: crawling at a fast rate from the start and slowing down as little as possible as the amount of visited URLs grows to hundreds of millions, all while observing politeness conventions (rate regulation, robots.txt compliance, etc.). • Input: – URLs with a score (seeds, then URLs output by the analysis process) • Output: – Web resources written to WARC files. We also have developed an importer to load these WARC files into HBase. Some metadata is also extracted: HTTP status code, identified out links, MIME type, etc. 21
    22. 22. WARC: example 22
    23. 23. Adaptative Heritrix ➔ Component Name: Adaptive Heritrix ➔ Description: Adaptive Heritrix is a modified version of the open source crawler Heritrix that allows the dynamic reordering of queued URLs and receiving URLs from the Online Analysis module. 23
    24. 24. How does adaptative Heritrix work ? ➔ Prioritization module communicates new scores to the crawler queue using a JSON over HTTP Prioritisation module sends POST to http://QUEUE_SERVER/update. The request body is a JSON encoded array of update objects. ➔ {"url": "", "score": 0.3, "parentUrl": "http://seed.tld/page"}, ➔ {"url": "", "blacklisted": true, "parentUrl": "http://seed.tld/page"} 24
    25. 25. API Crawler ➔ Component Name: API Crawler ➔ Description: • The API Crawler is a solution to manage keyword-based crawls of different social platforms using their Web APIs. It is controlled via a RESTful Web interface. Scalability and Performance: 3000 requests per hour, millions of triples per hour, millions of links per hour ➔ Input: List of tuples (keyword, platform) ➔ Output: Triples stored in the triple store and WARC files stored in the HDFS ➔ Twitter restriction: 180 request /15mn one request is one criteria. Each request give back 100 answers 25
    26. 26. How does API crawler work ? ➔ Principles: a crawler runs crawls. Each crawl has a crawl ID assigned by the pipeline. The pipeline ensures crawl IDs are unique. A crawl has four states: running, stopped, being deleted, deleted. A crawl runs until it ends by itself or until a stop order is received. Only a stopped crawl can be deleted. ➔ The APCrawler produces three kind of data: – semi-structured data stored as triples in the triple store, – outlinks sent to Heritrix or the IMF crawler, – and WARC files saved in the file system, that will also possibly be inserted into HBase. 26
    27. 27. Output: triples 27
    28. 28. ICS: Intelligent crawl specifications 28
    29. 29. Application Aware helper ➔ Component Name: Application-aware helper – The goal of this software component is to make the crawler aware of the particular kind of Web application being crawled, in terms of general classification of websites (wiki, social network, blog, web forum, etc.), technical implementation (Mediawiki, Wordpress, etc.), and their specific instances (Twitter, CNN, etc.). ➔ Input: – HTML content as string, base URL, list of out-links ➔ Output: – Augmented document (original text document and structured objects extracted from web page) and extracted links with score will be sent to ARCOMEM framework module. Extracted semantic objects, crawling actions, and out-links with score will also be stored in the ARCOMEM database. 29
    30. 30. ARCOMEM Crawler 30
    31. 31. How does AAH work ? ➔ The application aware helper will be assisted with a knowledge base that will help in recognizing a specific web application and related crawling actions ➔ Since the knowledge base will grow and there will exist several detection patterns for many web applications, we have to ensure the web application detection module does not slow up the crawling process and affect overall performance. ➔ To ensure scalability, after integration of the application aware helper with the crawler, we have used the Yfilter system (a NFA based filtering system) for efficient indexing of detection patterns in order to quickly find the relevant Web application. ➔ Here each state is represented by XPath expression patterns and common steps of the path expression are represented only once in a structure. The introduction of Yfilter in the Web application detection module improves the performance dynamically and now the system is well synchronized with the other sub modules of crawling process. 31
    32. 32. ARCOMEM Crawler Cockpit
    33. 33. ARCOMEM Crawler Cockpit • Requirements described by ARCOMEM user partners (SWR – DW) • Designed and implemented by IMF • A UI on top of the ARCOMEM system • Demo: Crawler cockpit 33
    34. 34. How does it work ? 34
    35. 35. Crawler Cockpit: Functionality • Launch crawls following scheduler specifications • Monitor crawls and get realtime feedback on the progress of the crawlers • Run crawl with HTML Crawler (Heritrix and IMF Crawler) • Export the crawled content to a WARC file • Set-up a campaign by focusing, event, keyword, entity and URL • Focus on target content in Social Media Category (blog, forum, video, photo...) • Run crawl by using API crawler (Twitter, Facebook, YouTube, Flickr) • Get a campaign overview with qualified statistics • Do some refinement at crawls time to have a better focus on the target content • decide what content to archive 35
    36. 36. Crawler Cockpit Navigation • Set-up: A campaign is described by an intelligent crawl definition, which associates content target to crawl parameters (schedule and technical parameters). • Monitor tab give access to statistics provide by the crawler at running time • Overview: global dashboard on a campaign. The information is organized following different topics: general description of the campaign, metadata, current status, crawl activity, statistics and analysis • Inspector: A tool to have access into the content as it is stored into Hbase. • Report: specfications and parameters of a campaign 36
    37. 37. CC: Overview Tab Global dashboard on campaign: • General description of the campaign • Crawl activity • Keywords • Statistics • Refine Mode: User can give more or less weight to a keyword. 37 a
    38. 38. CC Set-up tab •General description •Distinct named entities (e.g. person, geo location, and organization),Time period Free keywords and Language •A selection of up to nine SMC (Social Media Categories) •Schedule: Each campaign has a start and end date. Frequency of the craw is defined by choosing an interval. 38
    39. 39. Focus on Scoping function Domain: entire web site Path: only a specific directory of a website Sub domain: Page + context: 39
    40. 40. Focus on scheduler Frequency: weekly, monthly, quaterly … Interval: 1 to 9 Calendar: a campaign has a start date and an end date. 40
    41. 41. CC Inspector Tab Inspector tab allows user to •Check the quality of the content before indexing •Access to the content (from HBase), metadata and triples directly related to a resource •Browse a list of URLs ranked by on-line analysis scores is provided. 41
    42. 42. CC Monitor Tab The Monitor tab gives real time statistics on the running crawl. 42
    43. 43. Crawler cockpit demo • Online demo • Feedback 43