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。本次很高興邀請到來自日本的GCPUG成員：Kazunori Sato, Yuichiro MASUI與Ryuji Tamagawan三位BigQuery Expert跟大家分享關於BigQuery上的一些使用經驗。歡迎對大資料有興趣的朋友們可以共襄盛舉。
13:00 - 13:30 Guest Sign-in
13:30 - 14:30 Making Sense of Cloud Dataflow for Big Data, Kazunori Sato
14:30 - 15:00 Break + Q&A
15:00 - 15:50 Firebase + React.js, Yuichiro MASUI
15:50 - 16:50 You might be paying too much for BigQuery, Ryuji Tamagawa
16:50 - 17:30 Q&A
Topic 1：Making Sense of Cloud Dataflow for Big Data
Speaker：Kazunori Sato, Developer Advocate, Cloud Platform, Google Inc.
Kaz is a developer advocate in Google, an evangelist of Google Cloud Platform and supporting GCP developer community. He also focuses on supporting new product launch for Big Data products such as Dataflow and BigQuery.
Map Reduce, Millwheel and a host of other technologies changed the way programmers approached data problems. Rather than being constrained by the size of the data set, developers could focus on defining the key bits of intelligence they were seeking to find from an almost infinite data pool. While this opened up all kinds of new analysis, it also created a new set of problems — most notably dealing with the complexity of stringing together map reduces and creating end to end programming logic from multiple steps. New technologies like Cloud Dataflow seek to solve this problem and make Big Data into a concrete set of executable operations.
Topic 2：Firebase + React.js
I'm Yuichiro MASUI. a.k.a. masuidrive. Ruby on Rails and iOS developer. ex-Appcelarati. I really love programming, spending all time for coding. Now I focus to use React.js and writing React tech book in Japanese.
In this session, I’ll explain how to create realtime web apps on Firebase + React.js.
Topic 3: You might be paying too much for BigQuery
While working as a developer / field engineer for a software company in Japan, translates lots of books from English to Japanese for O’Reilly Japan. The translated titles are from big data, cloud computing to devops, including Hadoop, HBase, Programming Hive, Programming AWS, Jenkins, Vagrant up and running, and not to say, Google BigQuery Analytics.
You use BigQuery with SQL, but the internal work of BigQuery is very different from traditional Relational Database systems you may familiar with.
One of the way to understand how BigQuery works is to see it from the cost you pay for BigQuery. Knowing how to save money while using BigQuery is to know how BigQuery works to some extent.
In this session, let’s talk about practical knowledge (saving money) and exciting technology (how BigQuery works)!
- 工作人員會穿著藍色Google T恤，找我們就對了。