本次活動為 Taiwan Hadoop User Group 與 Google Cloud Platform User Group (GCPUG) 一起舉辦,透過社群間的合作,讓講題更多樣化發展,大家在了解 Hadoop Ecosystem 的當下,也可以一起深入了解在 Google Cloud Platform 上的各項 Big Data 與 Computing Service 唷~
我們是台灣的 Hadoop Ecosystem User Group,透過分享的力量,讓 Hadoop 帶領台灣的大資料環境向上成長,並且透過大家的分享與交流,讓知識交流無國界,歡迎對 Hadoop Ecosystem 的朋友們可以一起加入分享!
臉書粉絲團:https://fb.com/groups/hadoop.tw/
大家好,我們是 Google Cloud Platform User Group (GCPUG) 台灣分支,我們是一個Google Cloud Platform 相關技術的民間社群,成立的宗旨在分享與交換 Google Cloud Platform 上的一些技術與使用經驗。歡迎對 Google Cloud Platform 有興趣的朋友們可以共襄盛舉。
臉書粉絲團:https://fb.com/groups/GCPUG.TW/
http://gcpugtw.kktix.cc/events/meetup201701
2017/01/21 9:00 - 17:30
台北101 - Google辦公室
Speaker: Randy Huang, Data team leader of VMfive
Abstract: This is a real case from VMfive to shifting ELK architecture from AWS. Currently GCP Data Pipeline provide us more efficiency and stable environment for running our service.
- 直播URL: http://youtu.be/bH9e__8bT5k
- PPT: http://www.slideshare.net/randyviola/the-journey-of-moving-from-aws-elk-to-gcp-data-pipeline
Speaker: Simon Su, Co-organizer of GCPUG.TW
Abstract: Google provide different kinds of computing service, like: Google Computing Engine, Google Container Engine, Google App Engine. And I want to use a sample to let you know what is the different in these kinds of service. Maybe next time, you will have a batter way to deploy your service in Google Cloud!
- 直播URL: http://youtu.be/dsJLqQ-zets
- PPT: http://www.slideshare.net/peihsinsu/google-cloud-computing-compares-gce-gae-and-gke
- code: https://github.com/peihsinsu/gcpug-meetup-201701
Speaker: Wei-Chiu Chuang, Apache Hadoop Committer/ Software Engineer, Cloudera
Abstract: Hadoop is becoming the foundation of many data architectures, and many new use cases are flocking to the Hadoop ecosystem. With new opportunities comes new challenges, and Hadoop 3 will be addressing some of these emerging challenges. In this talk, I am going to highlight a few major features that will be shipped with Hadoop 3. In particular, a new storage architecture that reduces storage cost, a new architecture that scales compute better, improvement that makes Hadoop applications easier to develop, among others. Finally, I will also mention some new concepts that may one day be incorporated into Hadoop 4.
- 直播URL: http://youtu.be/ZlG_xidzzL4
- PPT: (Hadoop3_2017_Hadoop_Taiwan_Workshop.pdf)[Hadoop3_2017_Hadoop_Taiwan_Workshop.pdf]
Speaker: Jazz Wang, Co-founder of Hadoop.TW
Abstract: Hadoop 提供了抽象化的 File System 類別,因此只要實作對應的 Java 類別,就可以讓 Hadoop 支援其他雲端的檔案系統。這些額外與 Hadoop 相容的檔案系統,統稱 HCFS。例如 Hadoop 0.10 就存在的 Amazon S3 (s3://) 支援,Hadoop 2.7 才正式納入的 Windows Azure Blob Storage (was://)。由 Ceph 官方提供的 cephfs:// 支援等。
本次分享將使用 Apache BigTop 來展示怎麼拿 hadoop distcp 指令來當作 Local File System 跟 Azure Blob Storage 之間的 rsync 指令、 探討三種不同的 S3 實作(s3:// , s3n:// , s3a://),並簡略分享近期測試 CephFS 的心得。
PS. 若準備來得及,會追加 Google Cloud Storage Connector for Spark and Hadoop 。
[1] https://wiki.apache.org/hadoop/HCFS [2] https://wiki.apache.org/hadoop/AmazonS3 [3] http://hadoop.apache.org/docs/r2.7.3/hadoop-azure/ [4] https://github.com/ceph/cephfs-hadoop [5] https://cloud.google.com/.../google-cloud-storage-connector
- 直播URL: https://youtu.be/p1SKNSkZGPc
Speaker:
陳之駿 Chih-Chun Chen, 炬識科技
Abstract:
Impala 是 Cloudera 所開發用於 Hadoop 的 SQL Query 工具,於 2016 年捐給 Apache 軟體基金會。用途與 Hive 相近,但是基於快速回應查詢結果的特性,非常適合用來作交互式的資料挖掘與調校分析式查詢。 這個場次將分享在每日以 TB 等級增加資料量的環境中,如何用 Impala 實做 data extract, data transfer and data load。
- 直播URL: https://www.facebook.com/athemaster.com.tw/videos/701480570012207/
- PPT: http://www.slideshare.net/Athemaster/etl-with-apache-impala-by-athemaster-71282134
- 活動留影
- 贊助單位
- 感謝Google贊助場地(特別感謝Axa協助申請)
- 感謝MiTAC提供美味的Pizza