Features
fully managed, petabyte scale, low cost analytics data warehouse (cloud database).
NoOps—there is no infrastructure to manage and you don't need a database administrator.
(So you can focus on analyzing data to find meaningful insights, use familiar SQL, and take advantage of our pay-as-you-go model.)
What Problem can BigQuery Solve
Storing and querying massive datasets can be time consuming and expensive without the right hardware and infrastructure. Following action takes time in traditional SQL and Hadoop mapreduce:
- determine right index and build it
- how much space it take in the DB
- how to choose network, amount of RAM, CPU cores
Google BigQuery is an enterprise data warehouse that solves this problem by enabling super-fast SQL queries using the processing power of Google's infrastructure.
Access of BigQuery
- GCP Console
- classic web UI,
- command-line tool
- by making calls to the BigQuery REST API using a variety of client libraries such as Java, .NET, or Python
- 3rd party tools
What product you can connect BigQuery
programming framework and analysis tools thanks to it is a RESTful API
G product, App Engine, App Scripts, G Analytics
Open Source Community: R
send your logs to to be queried to analyze
How to Start
you don't need to deploy any resources, such as disks and virtual machines
Just get started by running a web query or using the command-line tool.
The only thing you need to know to use BigQuery is SQL query.
What's in BigQuery
public dataset shared in BQ, u'll get a free one month quota.
What BQ Bill for
- data storage
- amount of data each query processes
so what you need to know are things to use BQ,
- what's my data
- what are my queries
Usecase
The following is a common architecture of applying BigQuery
