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Posted to commits@kylin.apache.org by li...@apache.org on 2015/02/12 06:22:02 UTC
[08/31] incubator-kylin git commit: KYLIN-582 Update website to
comply with ASF incubator policy
http://git-wip-us.apache.org/repos/asf/incubator-kylin/blob/7d48115d/docs/website/_site/assets/js/main.js
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-jQuery(document).ready(function ($) {
-
-
-
-
-
- //parallax effect
- var parallax_animation = function () {
- $('.parallax').each(function (i, obj) {
- var speed = $(this).attr('parallax-speed');
- if (speed) {
- var background_pos = '-' + (window.pageYOffset / speed) + "px";
- $(this).css('background-position', 'center ' + background_pos);
- }
- });
- }
-
-
-
-
- // page elements animation
- var image_animation = function () {
- var diagramTop = $('#diagram').offset().top;
- var coremTop = $('#core').offset().top;
-
-
- var scroll_top = $(window).scrollTop();
- var currentPosition = scroll_top + 320;
-
- if (diagramTop < currentPosition) {
- $('#diagram').addClass("animated fadeIn");
- } else {
- $('#diagram').removeClass("animated fadeIn");
- }
-
- if (coremTop< currentPosition) {
-
- $('#core').addClass("animated fadeInRight");
- } else {
- $('#core').removeClass("animated fadeInRight");
- }
-
- }
-
-
-
-
- //document page
- $( "#content-container" ).load("docs/intro-content.html");
- $( "#left-menu li" ).eq(0).css("background-color", "#efefef");
-
- $( "#left-menu li" ).click(function(){
- var selectedID = $(this).attr("id");
- $("#content-container").load( "docs/"+selectedID+"-content.html", function() { $(this).fadeIn(500);});
- $(this).css("background-color", "#efefef");
- $(this).siblings().css("background-color", "transparent")
- });
-
- $('#nav-wrapper').height($("#nav").height());
-
- $('#nav').affix({
- offset: { top: $('#nav').offset().top }
- });
-
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- $(document).scroll(function () {
-
- parallax_animation();
- image_animation();
-
-
- });
-
-
-
-});
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http://git-wip-us.apache.org/repos/asf/incubator-kylin/blob/7d48115d/docs/website/_site/blog/2015/01/26/introduce-data-model/index.html
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diff --git a/docs/website/_site/blog/2015/01/26/introduce-data-model/index.html b/docs/website/_site/blog/2015/01/26/introduce-data-model/index.html
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-<!DOCTYPE html>
-<html>
-
- <head>
- <meta charset="utf-8">
- <meta http-equiv="X-UA-Compatible" content="IE=edge">
- <meta name="viewport" content="width=device-width, initial-scale=1">
-
- <title>Kylin.IO | Introduce Data Model of Cube Designer</title>
- <meta name="description" content="BackgroundIn previous version (before v0.6.4), Kylin introduced a GUI tool called Cube Designer for user (we called this role as Cube Modeler) to architect O...">
- <meta name="author" content="Kylin.IO">
- <link rel="shortcut icon" href="fav.png" type="image/png">
-
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-<link rel="stylesheet" href="/assets/css/animate.css">
-<!-- Bootstrap -->
-<link rel="stylesheet" href="/assets/css/bootstrap.min.css">
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-<link rel="stylesheet" href="http://fonts.googleapis.com/css?family=Alice|Open+Sans:400,300,700">
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-<!-- Icons -->
-<link rel="stylesheet" href="/assets/css/font-awesome.min.css">
-
- <!-- Custom styles -->
- <link rel="stylesheet" href="/assets/css/styles.css">
-
- <link rel="canonical" href="http://kyli.io/blog/2015/01/26/introduce-data-model/">
- <link rel="alternate" type="application/rss+xml" title="kylin.io" href="http://kyli.io/feed.xml" />
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-<script>
- (function(i,s,o,g,r,a,m){i['GoogleAnalyticsObject']=r;i[r]=i[r]||function(){
- (i[r].q=i[r].q||[]).push(arguments)},i[r].l=1*new Date();a=s.createElement(o),
- m=s.getElementsByTagName(o)[0];a.async=1;a.src=g;m.parentNode.insertBefore(a,m)
- })(window,document,'script','//www.google-analytics.com/analytics.js','ga');
-
- ga('create', 'UA-55534813-1', 'auto');
- ga('send', 'pageview');
-
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-</script>
-
-</head>
-
-
- <body>
-
- <header id="header" >
- <div id="head" class="parallax" parallax-speed="3" >
- <div id="logo" class="text-center"> <img class="img-circle" id="circlelogo" src="/assets/images/kylin_logo.jpg"> <span class="title" >Apache Kylin</span> <span class="tagline">Extreme OLAP Engine for Big Data<br>
- </span>
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- <div id="download"><a href="https://github.com/KylinOLAP/Kylin/releases">DOWNLOAD</a></div>
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-</nav>
- </header>
-
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- <div class="page-content">
- <div class="wrapper">
- <div class="post" style=" padding:2em 4em 4em 4em">
-
- <header class="post-header">
- <h1 class="post-title">Introduce Data Model of Cube Designer</h1>
- <p class="post-meta" >Jan 26, 2015 • Luke Han</p>
- </header>
-
- <article class="post-content" >
- <h3 id="background">Background</h3>
-<p>In previous version (before v0.6.4), Kylin introduced a GUI tool called Cube Designer for user (we called this role as <strong>Cube Modeler</strong>) to architect OLAP Cube with dimensions, measures and other settings. It works well for most of the features but still not user friendly yet: </p>
-
-<ol>
- <li>A user has to add dimension one by one, considering there are 20+ even 50+ dimensions, the entire process is really boring. </li>
- <li>Each dimension requires define join condition between fact table and lookup table which even already be defined in previous dimensions many times.</li>
- <li>Less validation check, especially for Hierarchy and Derived dimension, there are many exceptions in further steps which blocked many people to save the cube definition without any idea about the issue.</li>
- <li>Save/Next buttons are confusing user to click which one for real next step or just save current dimension settings</li>
-</ol>
-
-<h3 id="data-model-of-cube-designer">Data Model of Cube Designer</h3>
-<p>With the feedback from our internal users and external community, we have came up one idea and would like to introduce a new concept (widely known in Data Warehouse and Business Intelligence domain): Data Model: a data model organises data elements and standardises how the data elements relate to one another.<a href="http://en.wikipedia.org/wiki/Data_model">Wikipedia</a>. In Kylin, it using <a href="http://en.wikipedia.org/wiki/Star_schema">Star Schema</a> as Data Model, which is the simplest style of data warehouse schema. The star schema consists of a few “fact tables” (possibly only one, justifying the name) referencing any number of “dimension tables”. It actually already there behind dimensions and measures and now just come to first step to define the relationship between different tables before create each dimension.
-Now (after v0.6.4), to create a cube will follow below steps:</p>
-
-<ol>
- <li>Define data model first: pick up one fact table and then add other lookup tables (with their join conditions). The data mode must be presents as Star Schema.</li>
- <li>Then add dimensions, since all join conditions already presented in data model, each dimension could be more easy to create, just need to know what’s kind of type: normal, hierarchy and derived (will have another blog to introduce them). There’s also one helper called <em>Auto Generator</em> to help generate many dimensions within simple clicks.</li>
- <li>Then define measures and others as previous cube designer did</li>
-</ol>
-
-<h3 id="benefits">Benefits</h3>
-<ol>
- <li>A data model is very easy to communicate between different roles and teams. Most of cases it just mapping to real database table relationship, like from Hive tables</li>
- <li>More easy to create dimensions and measures based on the data model</li>
- <li>Friendly error message with enhanced validation check when save cube</li>
-</ol>
-
-<h3 id="whats-next">What’s Next</h3>
-<p>After this refactor, Kylin is now be able to introduce more powerful features, the major idea is to using different storages to serve same data model:</p>
-
-<ul>
- <li><strong>Logical Model</strong>: A Data Model presents logical data structure like Star Schema beyond data tables with more business meaning</li>
- <li><strong>Physical Model</strong>: define how the underlying data to be stored in persistent system, like HBase. There are already two of them: MOLAP (current Kylin version) and InvertedIndex (coming with 0.7.x release). And it also easy to extend to support others without change the Logical Model.</li>
- <li>A new GUI of Cube Designer to support above is on the way.</li>
-</ul>
-
-
- </article>
-
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-
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http://git-wip-us.apache.org/repos/asf/incubator-kylin/blob/7d48115d/docs/website/_site/blog/index.html
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- <header style="padding:2em 0 4em 0;">
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- <!-- second-->
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- </div>
- <p style="text-align:center" > Apache Kylin is distributed under the <a href="http://www.apache.org/licenses/LICENSE-2.0" target="_blank">Apache License v2.0. </a> |<a href="#">back to top</a><br>
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http://git-wip-us.apache.org/repos/asf/incubator-kylin/blob/7d48115d/docs/website/_site/cn/index.html
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-<!DOCTYPE html>
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- <h4 class="section-title"><span>Apache Kylin 概览</span></h4>
- <div class="row" style="margin-top:-20px;">
- <div class="col-sm-12 col-md-12">
- <p class="title_text"> Kylin 于2014年11月25日被接受会Apache孵化器项目</p>
- <p class="title_text"> Apache Kylin 是由eBay开源的分布式分析引擎，提供Hadoop之上的SQL查询接口及多维分析（OLAP）能力以支持超大规模数据</p>
- <img id="diagram" src="/assets/images/kylin_diagram.png" /> </div>
- </div>
- </div>
- <!-- /container -->
-
- </header>
- </div>
- <!-- / section -->
- </div>
- <!-- /container -->
-
- <section id="second" class="main">
- <header style="background-color:#efefef;">
- <div class="container">
- <h4 class="section-title"><span> Kylin是什么? </span></h4>
- <!-- second-->
- <div class="row">
- <div class="col-sm-12 col-md-12">
- <div align="left">
- <p> <b>- 可扩展超快OLAP引擎: </b><br />
- <div class="indent">Kylin是为减少在Hadoop上百亿规模数据查询延迟而设计</div>
- </p>
- <p> <b>- Hadoop ANSI SQL 接口: </b><br />
- <div class="indent">Kylin为Hadoop提供标准SQL支持大部分查询功能</div>
- </p>
- <p> <b>- 交互式查询能力: </b><br />
- <div class="indent">通过Kylin，用户可以与Hadoop数据进行亚秒级交互，在同样的数据集上提供比Hive更好的性能</div>
- </p>
- <p> <b>- 多维立方体（MOLAP Cube）:</b><br />
- <div class="indent">用户能够在Kylin里为百亿以上数据集定义数据模型并构建立方体</div>
- </p>
- <p> <b>- 与BI工具无缝整合:</b><br />
- <div class="indent">Kylin提供与BI工具，如Tableau，的整合能力，即将提供对其他工具的整合</div>
- </p>
- <p> <b>- 其他特性:</b> <br />
- <div class="indent">- Job管理与监控 <br />
- - 压缩与编码 <br />
- - 增量更新 <br />
- - 利用HBase Coprocessor<br />
- - 基于HyperLogLog的Dinstinc Count近似算法 <br />
- - 友好的web界面以管理，监控和使用立方体 <br />
- - 项目及立方体级别的访问控制安全<br />
- - 支持LDAP </div>
- </p>
- </div>
- </div>
- </div>
- </div>
- <!-- /container -->
-
- </header>
- </section>
-
- <!-- second -->
- <section id="first" class="main">
- <header>
- <div class="container">
- <h4 class="section-title"><span>Kylin 生态圈</span></h4>
- <div class="row">
- <div class="col-sm-7 col-md-7">
- <p> </p>
- <p><b>Kylin 核心:</b> Kylin OLAP引擎基础框架，包括元数据（Metadata）引擎，查询引擎，Job引擎及存储引擎等，同时包括REST服务器以响应客户端请求</p>
- <p><b>扩展:</b> 支持额外功能和特性的插件</p>
- <p><b>整合:</b> 与调度系统，ETL，监控等生命周期管理系统的整合</p>
- <p><b>用户界面:</b> 在Kylin核心之上扩展的第三方用户界面</p>
- <p><b>驱动:</b> ODBC 和 JDBC 驱动以支持不同的工具和产品，比如Tableau</p>
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- <li><a href="https://www.linkedin.com/groups/KylinOLAP-6785709?home=&gid=6785709&trk=anet_ug_hm" target="_blank" class="fa fa-linkedin fa-lg"></a></li>
- <li><a href="https://twitter.com/debashis_saha/status/519612003443146752" target="_blank" class="fa fa-twitter fa-lg"></a></li>
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- <li><a href="https://github.com/KylinOLAP/Kylin" target="_blank" class="fa fa-github-alt fa-lg"></a></li>
- <!-- <li><a href="#" class="fa fa-weibo fa-lg"></a></li>
- <li><a href="#" class="fa fa-weixin fa-lg"></a></li>-->
- </ul>
- <div>
- Apache Kylin is an effort undergoing incubation at The Apache Software Foundation (ASF), sponsored by the Apache Incubator. Incubation is required of all newly accepted projects until a further review indicates that the infrastructure, communications, and decision making process have stabilized in a manner consistent with other successful ASF projects. While incubation status is not necessarily a reflection of the completeness or stability of the code, it does indicate that the project has yet to be fully endorsed by the ASF.
- </div>
- <p style="text-align:center" > Apache Kylin is distributed under the <a href="http://www.apache.org/licenses/LICENSE-2.0" target="_blank">Apache License v2.0. </a> |<a href="#">back to top</a><br>
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http://git-wip-us.apache.org/repos/asf/incubator-kylin/blob/7d48115d/docs/website/_site/community/index.html
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- <meta http-equiv="X-UA-Compatible" content="IE=edge">
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- <div id="logo" class="text-center"> <img class="img-circle" id="circlelogo" src="/assets/images/kylin_logo.jpg"> <span class="title" >Apache Kylin</span> <span class="tagline">Extreme OLAP Engine for Big Data<br>
- </span>
- <!--
- <div id="download"><a href="https://github.com/KylinOLAP/Kylin/releases">DOWNLOAD</a></div>
- -->
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- <!-- Main Menu -->
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- <!-- Collect the nav links, forms, and other content for toggling -->
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- <li><a href="/"><b>Home</b></a></li>
- <li><a href="/docs" >Docs</a></li>
- <li><a href="/community" >Community</a></li>
- <li><a href="/blog">Blog</li>
- <li><a href="/about" >About</a></li>
- <li><a href="/cn" >中文版</a></li>
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- <div class="container" >
- <h4 class="section-title"><span>Kylin Community</span></h4>
- <div class="row" style="margin-top:-20px;">
- <div class="col-sm-4 col-md-4">
- <p class="big_text">EVENTS</p>
-
-
-
-
- <p><a href="http://strataconf.com/big-data-conference-uk-2015/public/schedule/detail/40029" target="_blank">Strata+Hadoop World 2015, London </a>
- <br/>Date - Wednesday, May 6, 2015 <br/>
- Kylin will be present at Strata+Hadooop World</p>
-
- <p><a href="http://bdtc2014.hadooper.cn/m/zone/bdtc_2014" target="_blank">Big Data Technology Conference, Beijing </a>
- <br/>Date - Sunday, December 14, 2014 <br/>
- Kylin be presented by Luke Han, Sr. Product Manager of Kylin</p>
-
- <p><a href="http://www.meetup.com/Cloud-at-ebayinc/events/218914395/" target="_blank">Apache Kylin Meetup @Bay Area </a>
- <br/>6:00PM - 7:30PM, Thursday, December 4, 2014 <br/>
- Learn about "Extreme OLAP engine for Hadoop - Kylin", which eBay recently Open sourced and is now an Apache Incubator Project</p>
-
- <p><a href="http://2014ebay.csdn.net/m/zone/ebay_en/" target="_blank">Shanghai Big Data Summit 2014 </a>
- <br/>Date - October 25th, 2014 <br/>
- Kylin be presented by Jiang Xu, Cheif Architect of Kylin<br/>
- <a href="http://ebay.csdn.net/" target="_blank">Slides and Video</a></p>
-
- </div>
-
- <div class="col-sm-4 col-md-4">
- <p class="big_text">DISCUSSION</p>
- <p>Developement and User maililng list: <a href="mailto:dev@kylin.incubator.apache.org" target="_blank"> dev@kylin.incubator.apache.org</a></p>
- <p>The official Kylin Twitter account: <a href="https://twitter.com/ApacheKylin" target="_blank"> @ApacheKylin</a></p>
- </div>
- <div class="col-sm-4 col-md-4">
- <p class="big_text">DEVELOPMENT</p>
- <p>All development takes place at : </p>
- <p>Apache Git: <a href="git://git.apache.org/incubator-kylin.git" target="_blank">git://git.apache.org/incubator-kylin.git</a><br/>
- Github Mirror: <a href="https://github.com/apache/incubator-kylin" target="_blank">https://github.com/apache/incubator-kylin</a></p>
-
- <p>Issue tracking: <a href="https://issues.apache.org/jira/browse/KYLIN" target="_blank">Apache JIRA</a></p>
- </div>
- </div>
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- <li><a href="https://twitter.com/debashis_saha/status/519612003443146752" target="_blank" class="fa fa-twitter fa-lg"></a></li>
- <li><a href="https://www.facebook.com/kylinio?skip_nax_wizard=true&ref_type=logout_gear" target="_blank" class="fa fa-facebook fa-lg"></a></li>
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- <li><a href="https://github.com/KylinOLAP/Kylin" target="_blank" class="fa fa-github-alt fa-lg"></a></li>
- <!-- <li><a href="#" class="fa fa-weibo fa-lg"></a></li>
- <li><a href="#" class="fa fa-weixin fa-lg"></a></li>-->
- </ul>
- <div>
- Apache Kylin is an effort undergoing incubation at The Apache Software Foundation (ASF), sponsored by the Apache Incubator. Incubation is required of all newly accepted projects until a further review indicates that the infrastructure, communications, and decision making process have stabilized in a manner consistent with other successful ASF projects. While incubation status is not necessarily a reflection of the completeness or stability of the code, it does indicate that the project has yet to be fully endorsed by the ASF.
- </div>
- <p style="text-align:center" > Apache Kylin is distributed under the <a href="http://www.apache.org/licenses/LICENSE-2.0" target="_blank">Apache License v2.0. </a> |<a href="#">back to top</a><br>
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http://git-wip-us.apache.org/repos/asf/incubator-kylin/blob/7d48115d/docs/website/_site/css/main.css
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-<p class="content-header" style="margin-top:0.25em">What should I use Kylin for?</p>
-<p class="content-p">
-If you want to do multi-dimension analysis on large data sets (billion+ rows) with low query latency (sub-seconds), Kylin is a good option. Kylin also provides good integration with existing BI tools (e.g Tableau).
-</p>
-
-<hr/>
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-<p class="content-header">Why existing SQL-on-Hadoop solutions fall short?</p>
-<p class="content-p">
-The existing SQL-on-Hadoop needs to scan partial or whole data set to answer a user query. Due to large data scan, many queries are very slow (minute+ latency).
-</p>
-<hr/>
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-<p class="content-header">What is MOLAP/ROLAP?</p>
-<p class="content-p">
-MOLAP (Multi-dimensional OLAP) is to pre-compute data along different dimensions of interest and store resultant values in the cube. MOLAP is much faster but is inflexible.
-ROLAP (Relational-OLAP) is to use star or snow-flake schema to do runtime aggregation. ROLAP is flexible but much slower.
-</p>
-<hr/>
-
-<p class="content-header">How does Kylin support ROLAP/MOLAP?</p>
-<p class="content-p">
-Kylin builds data cube (MOLAP) from hive table (ROLAP) according to the metadata definition.
-If the query can be fulfilled by data cube, Kylin will route the query to data cube that is MOLAP.
-If the query can’t be fulfilled by data cube, Kylin will route the query to hive table that is ROLAP.
-Basically, you can think Kylin as HOLAP on top of MOLAP and ROLAP.
-</p>
-<hr/>
-<p class="content-header">What does a Kylin query look like?</p>
-<p class="content-p">
-Kylin supports join, projection, filter, aggregation, groups and sub-query. For example:
-<div align="left">
-
-<pre class="prettyprint" style="margin-top:1em;">select test_cal_dt.week_beg_dt, test_category.lv1_categ, test_category.lv2_categ, test_kylin_fact.format_name, test_sites.site_name, sum(test_kylin_fact.price) as total_price, count(*) as total_count from test_kylin_fact left join test_cal_dt on test_kylin_fact.cal_dt = test_cal_dt.cal_dt left join test_category on test_kylin_fact.leaf_categ_id = test_category.leaf_categ_id and test_kylin_fact.site_id = test_category.site_id left join test_sites on test_kylin_fact.site_id = test_sites.site_id where test_kylin_fact.seller_id = 123456 or test_kylin_fact.format_name = 'New' group by test_cal_dt.week_beg_dt, test_category.lv1_categ, test_category.lv2_categ, test_kylin_fact.format_name, test_sites.site_name</pre>
-</div>
-<hr/>
-
-<p class="content-header">What Hadoop components does it work with?</p>
-<p class="content-p">
-Kylin depends on HDFS, MapReduce, Hive and HBase.
-Hive and MapReduce is used for cube building. Hive is used for pre-join and MapReduce is used for pre-aggregation.
-HDFS is used to store intermediated files during cube building.
-HBase is used to store data cube and answer the query. HBase coprocessor is also used for query processing.
-</p>
-<hr/>
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-<!-- Migrate wiki to here
-<p class="content-header">Where can I find the technical details about Kylin?</p>
-<p class="content-p"><a href="http://www.slideshare.net/XuJiang2/kylin-hadoop-olap-engine" target="_blank">Kylin Wiki</a></p>
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-<a href="https://github.com/KylinOLAP/Kylin/wiki/On-Hadoop-CLI-installation">On Hadoop CLI installation Wiki</a>
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- <p class="content-header" style="margin-top:0.25em">What should I use Kylin for?</p>
-<p class="content-p">
-If you want to do multi-dimension analysis on large data sets (billion+ rows) with low query latency (sub-seconds), Kylin is a good option. Kylin also provides good integration with existing BI tools (e.g Tableau).
-</p>
-
-<hr/>
-
-<p class="content-header">Why existing SQL-on-Hadoop solutions fall short?</p>
-<p class="content-p">
-The existing SQL-on-Hadoop needs to scan partial or whole data set to answer a user query. Due to large data scan, many queries are very slow (minute+ latency).
-</p>
-<hr/>
-
-<p class="content-header">What is MOLAP/ROLAP?</p>
-<p class="content-p">
-MOLAP (Multi-dimensional OLAP) is to pre-compute data along different dimensions of interest and store resultant values in the cube. MOLAP is much faster but is inflexible.
-ROLAP (Relational-OLAP) is to use star or snow-flake schema to do runtime aggregation. ROLAP is flexible but much slower.
-</p>
-<hr/>
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-<p class="content-header">How does Kylin support ROLAP/MOLAP?</p>
-<p class="content-p">
-Kylin builds data cube (MOLAP) from hive table (ROLAP) according to the metadata definition.
-If the query can be fulfilled by data cube, Kylin will route the query to data cube that is MOLAP.
-If the query can’t be fulfilled by data cube, Kylin will route the query to hive table that is ROLAP.
-Basically, you can think Kylin as HOLAP on top of MOLAP and ROLAP.
-</p>
-<hr/>
-<p class="content-header">What does a Kylin query look like?</p>
-<p class="content-p">
-Kylin supports join, projection, filter, aggregation, groups and sub-query. For example:
-<div align="left">
-
-<pre class="prettyprint" style="margin-top:1em;">select test_cal_dt.week_beg_dt, test_category.lv1_categ, test_category.lv2_categ, test_kylin_fact.format_name, test_sites.site_name, sum(test_kylin_fact.price) as total_price, count(*) as total_count from test_kylin_fact left join test_cal_dt on test_kylin_fact.cal_dt = test_cal_dt.cal_dt left join test_category on test_kylin_fact.leaf_categ_id = test_category.leaf_categ_id and test_kylin_fact.site_id = test_category.site_id left join test_sites on test_kylin_fact.site_id = test_sites.site_id where test_kylin_fact.seller_id = 123456 or test_kylin_fact.format_name = 'New' group by test_cal_dt.week_beg_dt, test_category.lv1_categ, test_category.lv2_categ, test_kylin_fact.format_name, test_sites.site_name</pre>
-</div>
-<hr/>
-
-<p class="content-header">What Hadoop components does it work with?</p>
-<p class="content-p">
-Kylin depends on HDFS, MapReduce, Hive and HBase.
-Hive and MapReduce is used for cube building. Hive is used for pre-join and MapReduce is used for pre-aggregation.
-HDFS is used to store intermediated files during cube building.
-HBase is used to store data cube and answer the query. HBase coprocessor is also used for query processing.
-</p>
-<hr/>
-
-<p class="content-header">Where can I find the technical details about Kylin?</p>
-<p class="content-p"><a href="http://www.slideshare.net/XuJiang2/kylin-hadoop-olap-engine" target="_blank">Kylin OLAP</a></p>
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- <p style="text-align:center" > Apache Kylin is distributed under the <a href="http://www.apache.org/licenses/LICENSE-2.0" target="_blank">Apache License v2.0. </a> |<a href="#">back to top</a><br>
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- <channel>
- <title>kylin.io</title>
- <description>Apache Kylin Home</description>
- <link>http://kyli.io/</link>
- <atom:link href="http://kyli.io/feed.xml" rel="self" type="application/rss+xml"/>
- <pubDate>Mon, 02 Feb 2015 23:36:58 +0800</pubDate>
- <lastBuildDate>Mon, 02 Feb 2015 23:36:58 +0800</lastBuildDate>
- <generator>Jekyll v2.5.3</generator>
-
- <item>
- <title>Introduce Data Model of Cube Designer</title>
- <description><h3 id="background">Background</h3>
-<p>In previous version (before v0.6.4), Kylin introduced a GUI tool called Cube Designer for user (we called this role as <strong>Cube Modeler</strong>) to architect OLAP Cube with dimensions, measures and other settings. It works well for most of the features but still not user friendly yet: </p>
-
-<ol>
- <li>A user has to add dimension one by one, considering there are 20+ even 50+ dimensions, the entire process is really boring. </li>
- <li>Each dimension requires define join condition between fact table and lookup table which even already be defined in previous dimensions many times.</li>
- <li>Less validation check, especially for Hierarchy and Derived dimension, there are many exceptions in further steps which blocked many people to save the cube definition without any idea about the issue.</li>
- <li>Save/Next buttons are confusing user to click which one for real next step or just save current dimension settings</li>
-</ol>
-
-<h3 id="data-model-of-cube-designer">Data Model of Cube Designer</h3>
-<p>With the feedback from our internal users and external community, we have came up one idea and would like to introduce a new concept (widely known in Data Warehouse and Business Intelligence domain): Data Model: a data model organises data elements and standardises how the data elements relate to one another.<a href="http://en.wikipedia.org/wiki/Data_model">Wikipedia</a>. In Kylin, it using <a href="http://en.wikipedia.org/wiki/Star_schema">Star Schema</a> as Data Model, which is the simplest style of data warehouse schema. The star schema consists of a few “fact tables” (possibly only one, justifying the name) referencing any number of “dimension tables”. It actually already there behind dimensions and measures and now just come to first step to define the relationship between different tables before create each dimension.
-Now (after v0.6.4), to create a cube will follow below steps:</p>
-
-<ol>
- <li>Define data model first: pick up one fact table and then add other lookup tables (with their join conditions). The data mode must be presents as Star Schema.</li>
- <li>Then add dimensions, since all join conditions already presented in data model, each dimension could be more easy to create, just need to know what’s kind of type: normal, hierarchy and derived (will have another blog to introduce them). There’s also one helper called <em>Auto Generator</em> to help generate many dimensions within simple clicks.</li>
- <li>Then define measures and others as previous cube designer did</li>
-</ol>
-
-<h3 id="benefits">Benefits</h3>
-<ol>
- <li>A data model is very easy to communicate between different roles and teams. Most of cases it just mapping to real database table relationship, like from Hive tables</li>
- <li>More easy to create dimensions and measures based on the data model</li>
- <li>Friendly error message with enhanced validation check when save cube</li>
-</ol>
-
-<h3 id="whats-next">What’s Next</h3>
-<p>After this refactor, Kylin is now be able to introduce more powerful features, the major idea is to using different storages to serve same data model:</p>
-
-<ul>
- <li><strong>Logical Model</strong>: A Data Model presents logical data structure like Star Schema beyond data tables with more business meaning</li>
- <li><strong>Physical Model</strong>: define how the underlying data to be stored in persistent system, like HBase. There are already two of them: MOLAP (current Kylin version) and InvertedIndex (coming with 0.7.x release). And it also easy to extend to support others without change the Logical Model.</li>
- <li>A new GUI of Cube Designer to support above is on the way.</li>
-</ul>
-
-</description>
- <pubDate>Mon, 26 Jan 2015 06:28:00 +0800</pubDate>
- <link>http://kyli.io/blog/2015/01/26/introduce-data-model/</link>
- <guid isPermaLink="true">http://kyli.io/blog/2015/01/26/introduce-data-model/</guid>
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- <p class="title_text"> Kylin has been accepted as Apache Incubator Project on Nov 25, 2014.</p>
- <p class="title_text"> Apache Kylin is an open source Distributed Analytics Engine from eBay Inc. that provides SQL interface and multi-dimensional analysis (OLAP) on Hadoop supporting extremely large datasets</p>
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- <p> <b>- Extremely Fast OLAP Engine at Scale: </b><br />
- <div class="indent">Kylin is designed to reduce query latency on Hadoop for 10+ billions of rows of data</div>
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- <p> <b>- ANSI SQL Interface on Hadoop: </b><br />
- <div class="indent">Kylin offers ANSI SQL on Hadoop and supports most ANSI SQL query functions</div>
- </p>
- <p> <b>- Interactive Query Capability: </b><br />
- <div class="indent">Users can interact with Hadoop data via Kylin at sub-second latency, better than Hive queries for the same dataset</div>
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- <p> <b>- MOLAP Cube:</b><br />
- <div class="indent">User can define a data model and pre-build in Kylin with more than 10+ billions of raw data records</div>
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- <p> <b>- Seamless Integration with BI Tools:</b><br />
- <div class="indent">Kylin currently offers integration capability with BI Tools like Tableau. Integration with Microstrategy and Excel is coming soon</div>
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- <p> <b>- Other Highlights:</b> <br />
- <div class="indent">- Job Management and Monitoring <br />
- - Compression and Encoding Support <br />
- - Incremental Refresh of Cubes <br />
- - Leverage HBase Coprocessor for query latency <br />
- - Approximate Query Capability for distinct Count (HyperLogLog) <br />
- - Easy Web interface to manage, build, monitor and query cubes <br />
- - Security capability to set ACL at Cube/Project Level <br />
- - Support LDAP Integration </div>
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- <p><b>Kylin Core:</b> Fundamental framework of Kylin OLAP Engine comprises of Metadata Engine, Query Engine, Job Engine and Storage Engine to run the entire stack. It also includes a REST Server to service client requests</p>
- <p><b>Extensions:</b> Plugins to support additional functions and features </p>
- <p><b>Integration:</b> Lifecycle Management Support to integrate with Job Scheduler, ETL, Monitoring and Alerting Systems </p>
- <p><b>User Interface:</b> Allows third party users to build customized user-interface atop Kylin core</p>
- <p><b>Drivers:</b> ODBC and JDBC drivers to support different tools and products, such as Tableau</p>
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