Amazon Elasticsearch Service 可以利用 S3 當作二級儲存空間了

Amazon Elasticsearch Service 的新功能,使用 Amazon S3 當作第二級儲存空間 (UltraWarm):「Announcing UltraWarm (Preview) for Amazon Elasticsearch Service」。

UltraWarm 需要不同的機器 (跑不同版本?),機器的規格 (vCPU 與記憶體的比率) 接近 Memory Optimized 的版本,但是貴了不少,所以需要夠大的資料量才會打平回來...

us-east-1 來看,SSD EBS 的空間成本就是 USD$0.135/GB,而傳統磁性硬碟是 USD$0.067/GB (不知道收不收 I/O 費用?),但 storage 的價錢是 USD$0.024/GB。這邊值得一提的是 Amazon S3 是 USD$0.023/GB,看起來是直接包括了 API 的呼叫費用?

Google 搜尋無法使用 Lynx 或是 w3m 操作了

看到「No more google for console junkies」這篇,裡面提到了新版的 Google 沒辦法用 Lynx 操作了,拿 w3m 測了一下發現也不行了,可以搜到東西,但連結的操作已經是 JavaScript 化了,而這兩個瀏覽器都不支援 JavaScript,所以就卡住了...

是個從早年的 Unobtrusive JavaScript 概念,到現在沒有 JavaScript 就不會動的年代...

有翻到一些有支援 JavaScript 的 terminal web browser (LinksELinks),但都只是實驗品,連輸入中文都有問題... :/

Startpage 被廣告公司收購

Hacker News 上看到 Reddit 上的消息 (看起來有陣子了):「Startpage is now owned by an advertising company」。

Startpage 算是之前有在用的 default search engine,但發現有很多 bug 後就不太用了。目前還是先設 DuckDuckGo,然後在需要的時候用之前寫的 press-g-to-google-duckduckgo 切到 Google 去找...

DuckDuckGo 還是有搜尋品質的問題...

hiQ 爬 LinkedIn 資料的無罪判決

hiQ 之前爬 LinkedIn 的公開資料而被 LinkedIn 告 (可以參考 2017 時的「hiQ prevails / LinkedIn must allow scraping / Of your page info」),這場官司一路打官司打到第九巡迴庭,最後的判決確認了 LinkedIn 完全敗訴。判決書在「HIQ LABS V. LINKEDIN」這邊可以看到。

這次的判決書有提到當初地方法院有下令 LinkedIn 不得用任何方式設限抓取公開資料:

The district court granted hiQ’s motion. It ordered LinkedIn to withdraw its cease-and-desist letter, to remove any existing technical barriers to hiQ’s access to public profiles, and to refrain from putting in place any legal or technical measures with the effect of blocking hiQ’s access to public profiles. LinkedIn timely appealed.

而在判決書裡其他地方也可以看到巡迴庭不斷確認地方法院當時的判決是合理的,並且否定 LinkedIn 的辯解:(這邊只拉了兩段,裡面還有提到很多次)

In short, the district court did not abuse its discretion in concluding on the preliminary injunction record that hiQ currently has no viable way to remain in business other than using LinkedIn public profile data for its Keeper and Skill Mapper services, and that HiQ therefore has demonstrated a likelihood of irreparable harm absent a preliminary injunction.

We conclude that the district court’s determination that the balance of hardships tips sharply in hiQ’s favor is not “illogical, implausible, or without support in the record.” Kelly, 878 F.3d at 713.

到巡迴庭差不多是確定的判決了,沒有其他特別的流程的話...

引用自己論文的問題...

Nature 上點出來期刊論文裡自我引用的問題 (這邊的自我引用包括了合作過的人):「Hundreds of extreme self-citing scientists revealed in new database」。

開頭舉了一個極端的例子,Vaidyanathan 的自我引用比率高達 94%,而學界的中位數是 12.7%,感覺是有某種制度造成的行為?

Vaidyanathan, a computer scientist at the Vel Tech R&D Institute of Technology, a privately run institute, is an extreme example: he has received 94% of his citations from himself or his co-authors up to 2017, according to a study in PLoS Biology this month. He is not alone. The data set, which lists around 100,000 researchers, shows that at least 250 scientists have amassed more than 50% of their citations from themselves or their co-authors, while the median self-citation rate is 12.7%.

會想要提是因為想到當年 Google 的經典演算法 PageRank,就是在處理這個問題... 把 paper 換成 webpage 而已。

Facebook 修正錯字的新演算法

先前 Facebook 已經先發表過 fastText 了,在這個月的月初又發表了另外一個演算法 Misspelling Oblivious Embeddings (MOE),是搭著本來的 fastText 而得到的改善:「A new model for word embeddings that are resilient to misspellings」。

Facebook 的說明提到在 user-generated text 的內容上,MOE 的效果比 fastText 好:

We checked the effectiveness of this approach considering different intrinsic and extrinsic tasks, and found that MOE outperforms fastText for user-generated text.

論文發表在 arXiv 上:「Misspelling Oblivious Word Embeddings」。

依照介紹,fastText 的重點在於 semantic loss,而 MOE 則多了 spell correction loss:

The loss function of fastText aims to more closely embed words that occur in the same context. We call this semantic loss. In addition to the semantic loss, MOE also considers an additional supervisedloss that we call spell correction loss. The spell correction loss aims to embed misspellings close to their correct versions by minimizing the weighted sum of semantic loss and spell correction loss.

不過目前 GitHub 上的 facebookresearch/moe 只有放 dataset,沒有 open source 出來讓人直接用,可能得自己刻...

透過 Avast 防毒軟體蒐集資料的 Jumpshot

看到「Less than Half of Google Searches Now Result in a Click」這篇,在說明 Google 的搜尋結果頁面內的行為大幅偏頗 Google 自家服務的問題,這個問題最近幾個禮拜開始紅了起來...

但另外一點值得注意的是裡面提到 Jumpshot 這個服務可以分析使用者的頁面以及行為這件事情...

在 2013 年 Avast 買下 Jumpshot:「AVAST Software Acquires Jumpshot to Work Magic Against Slow PC Performance」,當時的目標是效能:

Having served as PC tech consultants to their friends and family, their goal was to build a product to help less tech-savvy PC users optimize and tune up their PC performance, cleaning it from unpleasant toolbars and junk software.

但在 2015 年的時候就可以看到 Avast 在他們自家的論壇上有說明,Avast 會收資料丟進 Jumpshot:「Avast and Jumpshot」。

These aggregated results are the only thing that Avast makes available to Jumpshot customers and end users.

而藉由這些資料而提供服務。

Amazon 的 Elasticsearch 服務提供十四天免費 hourly snapshot

Amazon Elasticsearch Service 提供 14 天免費的 hourly snapshot:「Amazon Elasticsearch Service increases data protection with automated hourly snapshots at no extra charge」。

Amazon Elasticsearch Service has increased its snapshot frequency from daily to hourly, providing more granular recovery points. If you need to restore your cluster, you now have numerous, recent snapshots to choose from. These automated snapshots are retained for 14 days at no extra charge.

不過這是 5.3+ 版本才有,舊版只有 daily:

  • For domains running Elasticsearch 5.3 and later, Amazon ES takes hourly automated snapshots and retains up to 336 of them for 14 days.
  • For domains running Elasticsearch 5.1 and earlier, Amazon ES takes daily automated snapshots (during the hour you specify) and retains up to 14 of them for 30 days.

In both cases, the service stores the snapshots in a preconfigured Amazon S3 bucket at no additional charge. You can use these automated snapshots to restore domains.

算是方便管理...

robots.txt 的標準化

雖然聽起來有點詭異,但 robots.txt 的確一直都只是業界慣用標準,而非正式標準,所以各家搜尋引擎加加減減都有一些自己的參數。

在經過這麼久以後,Google 決定推動 robots.txt 的標準化:「Formalizing the Robots Exclusion Protocol Specification」,同時 Google 也放出了他們解讀 robots.txt 的 parser:「Google's robots.txt Parser is Now Open Source」,在 GitHubgoogle/robotstxt 這邊可以取得。

目前的 draft 是 00 版,可以在 draft-rep-wg-topic-00 這邊看到,不知道其他搜尋引擎會給什麼樣的回饋...

Elasticsearch 提供免費版本的安全功能

Elasticsearch 決定將基本的安全功能從付費功能轉為免費釋出,很明顯的是受到 Open Distro for Elasticsearch 的壓力而做出的改變:「Security for Elasticsearch is now free」。

要注意的是這不是 open source 版本,只是將這些功能放到 basic tier 裡讓使用者免費使用:

Previously, these core security features required a paid Gold subscription. Now they are free as a part of the Basic tier. Note that our advanced security features — from single sign-on and Active Directory/LDAP authentication to field- and document-level security — remain paid features.

這代表 Open Distro for Elasticsearch 提供的還是比較多:

With Open Distro for Elasticsearch, you can leverage your existing authentication infrastructure such as LDAP/Active Directory, SAML, Kerberos, JSON web tokens, TLS certificates, and Proxy authentication/SSO for user authentication. An internal user repository with support for basic HTTP authentication is also avaliable for easy setup and evaluation.

Granular, role-based access control enables you to control the actions a user can perform on your Elasticsearch cluster. Roles control cluster operations, access to indices, and even the fields and documents users can access. Open Distro for Elasticsearch also supports multi-tenant environments, allowing multiple teams to share the same cluster while only being able to access their team's data and dashboards.

目前看起來還是可以朝 Open Distro for Elasticsearch 靠過去...