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<title>Creating and Using Session-Scoped Temporary Views</title>
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<h1>Creating and Using Session-Scoped Temporary Views</h1>
<p>
I started my day by reviewing the latest customer data that needed to be analyzed for a targeted marketing campaign. The dataset was stored in the training.sales.customers table, and I needed to focus specifically on customers from Germany. I knew that using a temporary view would allow me to filter the data without modifying the original table, which is important for maintaining data integrity and ensuring that other teams can still access the full dataset.
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<h2>Creating a Temporary View</h2>
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I decided to create a session-scoped temporary view called <code>active_customers</code> that would include only the customers from Germany. I used the <code>CREATE OR REPLACE TEMP VIEW</code> command to define the view, which ensures that if the view already exists, it will be replaced with the new definition. This is useful when I want to update the view without affecting existing queries that might be using it.
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<pre><code>
CREATE OR REPLACE TEMP VIEW active_customers AS
SELECT * FROM training.sales.customers
WHERE country = 'Germany';
</code></pre>
<p>
I ran the above command in my Databricks notebook, and the system executed it without any errors. I noticed that the temporary view was created in the current session, which means it will not be visible to other sessions or users unless explicitly shared or exported.
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<h2>Querying the Temporary View</h2>
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Next, I wanted to verify that the temporary view contained only the customers from Germany. I executed a simple <code>SELECT</code> query to retrieve all records from the <code>active_customers</code> view.
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<pre><code>
SELECT * FROM active_customers;
</code></pre>
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The query returned exactly the records I expected—only those customers whose country was set to 'Germany'. This confirmed that the view was correctly filtering the data based on the <code>country</code> column. I was able to analyze the results directly without having to apply the filter in every query, which made my workflow much more efficient.
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<h2>Checking for Temporary Views</h2>
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To make sure that the temporary view was indeed session-scoped and not accidentally saved as a permanent view, I ran the <code>SHOW VIEWS</code> command. This command lists all views that are currently visible in the current session.
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<pre><code>
SHOW VIEWS;
</code></pre>
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The output included the <code>active_customers</code> view, but I noticed that it was only listed for the current session. This reinforced that the view was temporary and would be dropped when the session ended, which aligns with the intended use case for temporary views.
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I verified that the temporary view was working as expected and that it was scoped correctly. This allowed me to proceed with my analysis knowing that the data was clean and the view would not interfere with other users or sessions. I was confident that using temporary views in this way would help keep my data pipeline organized and efficient.
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