Search for a command to run...
Series
Practical guides to making BigQuery queries faster and cheaper — partitioning, clustering, search indexes, time travel, cost optimization, and query tuning strategies.
In this practical BigQuery exercise, we’re going to look at BigQuery Time Travel and see how it can help us when working with data. It’s not as powerful as Marty McFly’s DeLorean in Back to the Future (nobody knows what your future data will look lik...
When it comes to tuning a #SQL query in #BigQuery for top performance and cost-efficiency, here's my starting point: 🔍 1. Early Filtering:- Filter out unnecessary rows at the earliest.- Only select columns that are required.- Remove all the redundan...
A few years back, when working on SQL Server projects, I often utilized the ALTER TABLE SWITCH partition between staging and target tables. This left me pondering—could a similar functionality be achieved in BigQuery? 🤔 BigQuery facilitates copying ...
It should be no surprise that understanding your data is very important when working with it. The initial step in my approach to a new dataset always involves examining the data closely. Although the Schema Tab reveals the data schema, to grasp the c...
Let's talk money 💸 . Now that I've got your attention - more precisely, cost optimization as a regular user. As cloud data warehouse users, in addition to ticking off functional requirements and of course, getting the results in a timely manner, we ...
As promised on a previous post about optimizing costs for compute, I've promised a post about storage as well, so let's dive in. So how does BigQuery charge for storage? Two billing models - set at dataset level: logical and physical. Logical table s...
