21:09 插播:治大国若烹小鲜 » 妮妮
今早看见的签名档,瀑布汗!配个文字:治大国若烹小鲜~!和现在“不折腾”的语录精神吻合!
17:53 Analytics与AdSense 帐户整合已对所有发布商开放 » Google AdSense 中文博客


之前几个月,我们逐步邀请了一些发布商将AdSense帐户与Google Analytics进行整合。现在,所有发布商都可以把Analytics与AdSense帐户整合了! Analytics可以为您提供更多关于网页流量和用户行为的详细数据。

整合以后,您可以在Analytics首页左侧导航栏的“内容”里找到AdSense选项,这里包含了一下几个报告:
您还可以在 Analytics 帐户中看到一个“AdSense 收入”标签,通过这个报告您可以了解多少 AdSense 收入是来自新用户,多少来自原有用户;还可以了解不同语言用户对AdSense 收入的贡献比例。



要完成Analytics与AdSense 的整合,只需登录您的帐户,您就会看到“将 Google Analytics(分析)整合到您的 AdSense 帐户中”的提示信息。点击这个链接,然后按照指导完成操作就可以了。



您也可以观看下面的视频,学习如何整合 Analytics。

12:10 Surface your Google Analytics data in Google Ad Planner » Google Analytics Blog
We know that web publishers can get frustrated when public estimates of their traffic don't match what they're seeing in their web analytics accounts. Publishers with ad revenue at stake need to present the best possible data to advertisers, but they couldn't do much about it... until now.

Today, we are announcing an integration with Google Ad Planner Publisher Center that allows you to opt in some of your Google Analytics data into Google Ad Planner so that you can replace traffic estimates with directly measured Google Analytics data. Of course, this feature is strictly optional and provides the most value to publishers who have ads on their site. A lot of publishers have requested this feature and we hope that those of you who do enable the feature will enjoy seeing data that matches what you see in Google Analytics.


To see how your site is currently displayed in Google Ad Planner, visit the Google Ad Planner Publisher Center and search for your site. If you want to get started managing your site profile in Google Ad Planner and opt in your Google Analytics traffic metrics, first enable the "Share my Google Analytics data with Google products only" from within your Google Analytics data sharing settings page. Then, go to your Google Ad Planner account, sign in, and select the Google Analytics metrics you'd like to share publicly. Once you do, your Google Analytics traffic metrics will replace Google Ad Planner's estimates of your traffic, and potential advertisers can see the important metrics that you are seeing.*

For more information about the Google Ad Planner Publisher Center, visit the Ad Planner Help Center, or watch our video below:





*Please note that publishers who decide to share their Analytics data for the first time may have to wait up to 48 hours to see the traffic data in their Ad Planner account.

12:08 Drop ACID and Think About Data » High Scalability - Building bigger, faster, more reliable websites.

The abstract for the talk given by Bob Ippolito, co-founder and CTO of Mochi Media, Inc:

Building large systems on top of a traditional single-master RDBMS data storage layer is no longer good enough. This talk explores the landscape of new technologies available today to augment your data layer to improve performance and reliability. Is your application a good fit for caches, bloom filters, bitmap indexes, column stores, distributed key/value stores, or document databases? Learn how they work (in theory and practice) and decide for yourself.

Bob does an excellent job highlighting different products and the key concepts to understand when pondering the wide variety of new database offerings. It's unlikely you'll be able to say oh, this is the database for me after watching the presentation, but you will be much better informed on your options. And I imagine slightly confused as to what to do :-)

An interesting observation in the talk is that the more robust products are internal to large companies like Amazon and Google or are commercial. A lot of the open source products aren't yet considered ready for prime-time and Bob encourages developers to join a project and make patches rather than start yet another half finished key-value store clone. From my monitoring of the interwebs this does seem to be happening and existing products are starting to mature.

From all the choices discussed the column database Vertica seems closest to Bob's heart and it's the product they use. It supports clustering, column storage, compression, bitmapped indexes, bloom filters, grids, and lots of other useful features. And most importantly: it works, which is always a plus :-)

Here's a summary of some of the points talked about in the presentation:

read more

03:01 北京至洛阳攻略(一) » 妮妮

旅游之于我,在于体会一路上的地理之乐。在路上观山脉的走向,看河流的水文水况,呼吸不同的空气味道,见识不同的风土民居,感受各种风情的花草树木,聆听不同腔调的口音方言,识别各类植被土壤庄稼,记录奇怪的地名人姓……这样的旅行是自由和解放的。而跟着旅游团,在半军事化的时间要求下,丝毫体会不到一分这样的乐趣,取而代之的只有惶惶的担心(每一站都有被卖的可能)和回程时几G“到此一游”的照片。

因此,若时间允许在旅游时选择飞机、火车和汽车,我更喜欢后二者。飞机只是帮你从一点到另一点的工具罢了,而火车汽车却能帮你完成这样丰满的旅游体验。还记得大学寒暑假出行,趴在在列车窗户上往外看,瞬间而过一幕幕田地和不远处充满异域风情的植物,都能让我欣喜;铁路边灰黑屋檐下,倚门而站的姑娘和正在喂鸡的老头的定格镜头,都会让我感动和亲切。跟着车行千里饱看异地风光,那些书本上的山脉人文风情,就成了我自己胸中的山脉人文风情。

周末单独走中远程的线路,这些年已经很少尝试,时间、精力、旅伴都是问题,而且对很多地方的假人文、假景点、假风情和“此路是我开”的山大王,很有点怕和审美疲劳。此次去洛阳,是三月在晚饭中即兴跟公婆提起,赏牡丹游石窟,他们很有兴趣,遂赶忙跟进。从三月末订票订房到完成旅程回到北京,前后半个月时间,纯粹的出游时间是从上周五(17号)下班后出发到本周一(20日)早上抵达西客站——一个标准的周末游。

对我们来说,这样的标准周末游是不适合开车的:

一是:驾车者的体力问题。从北京开车到洛阳,往返全程1700公里左右,单程走高速好像也需要7个小时。如果是长假旅游开车当然没问题,但周末游就显得太累了,驾车的同学除了睡觉时候基本没休息。

二是:费用。在网上找到的有心人旅行作业显示:此行高速费合计:630元;汽油费大约:760元(93#汽油,大约140升), 而从北京直达洛阳的K269次列车,下铺仅185元。 在洛阳当地打车,6元起步而且车极多,您要有意向绕全城跑马观花,最多也就几十元。景区离洛阳市区也很近,例如打车到龙门石窟40元,如果不忙,到景区的公交也极发达。BTW,北京到洛阳的机票,全价1000左右,很少打折,坐位少了金贵吧~~

三是:安全。太紧张的行程,对驾驶者是考验,对乘车的家属的身体也是考验。如果带着老人和孩子,我想还是火车为好,至少能躺着休息呀。

贴张图片先,这是牡丹名品珊瑚台。

初乌,黑牡丹中的极品

白牡丹,名唤海青

 

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