Скачать или смотреть How to Create a Dynamic SQL Query in BigQuery for Firebase Analytics Data

Learn how to efficiently schedule queries in BigQuery that automatically fetch data from Firebase Analytics tables for yesterday's date using dynamic SQL.
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This video is based on the question https://stackoverflow.com/q/63325683/ asked by the user 'Karel Debedts' ( https://stackoverflow.com/u/10251414/ ) and on the answer https://stackoverflow.com/a/63327073/ provided by the user 'Soumendra Mishra' ( https://stackoverflow.com/u/14048579/ ) at 'Stack Overflow' website. Thanks to these great users and Stackexchange community for their contributions.

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How to Create a Dynamic SQL Query in BigQuery for Firebase Analytics Data

When working with BigQuery and Firebase Analytics, you may often find yourself needing to fetch data from a specific date in a scheduled manner. One common user query is how to construct a SQL statement that allows you to retrieve records from the table that corresponds to "yesterday" automatically. This guide will walk you through the steps to achieve this using dynamic SQL in BigQuery.

The Problem at Hand

If you're querying a Firebase Analytics table in BigQuery like this:

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Here, the date in your table (events_20200808) is hard-coded. When you create a scheduled query, you'll want to avoid manually changing this date every day. Instead, the goal is to make your table name dynamic, so it always points to the correct date (yesterday).

The Solution: Using Dynamic SQL

To solve this problem, you can leverage the EXECUTE IMMEDIATE command in BigQuery to create and run dynamic SQL queries. This will allow you to use a variable to determine the table name at runtime. Here are the steps and code needed to accomplish this.

Step 1: Declare a Variable for the Table Name

You need to create a string variable that will hold the name of your target table.

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Step 2: Set the Table Name Dynamically

You will then set this variable to concatenate the project name, analytics ID, and the date formatted to represent yesterday. The FORMAT_DATE() function will help with the specific date format required by Firebase Analytics tables.

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Step 3: Execute the Dynamic Query

Once the TABLE_NAME is set, you can execute the command to perform your initial query dynamically.

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Putting it All Together

Here's the complete SQL code for your scheduled query:

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Conclusion

By using dynamic SQL with EXECUTE IMMEDIATE, you can efficiently query your Firebase Analytics data in BigQuery without the hassle of manually changing the table name every day. The above code not only enhances automation but also reduces the chances of human error associated with daily query maintenance. Feel free to explore these techniques further to streamline your data querying processes!

Keep in mind that while this solution is powerful, it’s essential to ensure the necessary permissions and validations are in place to avoid issues with execution. Happy querying!