From the course: Data Warehousing on Google Cloud Platform

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Table partitioning in BigQuery

Table partitioning in BigQuery - Google Cloud Platform Tutorial

From the course: Data Warehousing on Google Cloud Platform

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Table partitioning in BigQuery

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- [Instructor] Partitioning tables can help improve query performance. In BigQuery, you can partition tables based on date or timestamp columns. Each partition is stored separately and treated as its own table. Partitions can be created based on time of data ingestion and based on a date or timestamp column. When based on the time of data ingestion, BigQuery creates columns on the table, underscore partition underscore date and underscore partition time that can be used to filter data inquiries. Advantages to partitioning tables include improving performance by processing less rows, save query costs and cloud billing costs, and best used for transaction-based tables that are often queried by date and time. Here's a short demo on partition tables. Let's create a table by uploading the FactResellerSales.csv file from the repository. Hit Create table. Create table from upload. Select a file, we'll select the FactResellerSales.csv file. File format is CSV. Let's name the table…

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