How Looker Writes SQL?

Looker writes SQL queries directly against your database based on the fields and logic that you define within the LookML. Any user in the organization can build their own reports and dashboards using SQL queries without actually knowing how to write SQL.

Since you’re going to be writing the LookML that controls this SQL, it’s important to understand how Looker generates SQL so that you can write the most efficient queries.

Using Looker’s modeling language, known as LookML, you define your business logic based on columns in your table.

In the example below, the names of users are stored in a column in the database and can be represented with the following LookML dimension.

When you add a dimension field to the Explore, Looker constructs a SQL query that includes that field and sends the query to your database.

Here is an example to demonstrate how Looker writes SQL in practice.

Suppose we have a database that tracks sales transactions, and we want to analyze the total revenue generated by each region. In Looker, we can define a LookML model to extract the data from the database, as follows:

model: sales_transactions

dimension: region {
  type: string
}

measure: revenue {
  type: sum
  sql: ${TABLE}.amount
}

explore: sales {
  dimension: region
  measure: revenue
}

In this example, we have defined a model called sales_transactions and defined a dimension called region and a measure called revenue. The dimension region is a string field that describes the region of each transaction, and the measure revenue is a sum of the amount field for each transaction.

When a user performs a query in Looker to analyze the total revenue generated by each region, the platform generates the following SQL query:

SELECT region, SUM(amount) AS revenue
FROM sales_transactions
GROUP BY region

The database executes this SQL query and returns the results, which Looker then uses to populate the visualizations and data reports.

In this example, we can see how Looker abstracts away the complexity of writing SQL and makes it easier for users to perform data analysis and visualization. The LookML model defines the structure of the data and the calculations to be performed, and Looker generates the appropriate SQL query to extract the data from the database.

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Reference

About Me:-
I am Om Prakash Singh – Data Analytics Consultant , Looker Consultant , Solution Architect .
I am Highly analytical and process-oriented Data Analyst with in-depth knowledge of database types; research methodologies; and big data capture, manipulation and visualization. Furnish insights, analytics and business intelligence used to advance opportunity identification.

You’ve got data and lots of it. If you’re like most enterprises, you’re struggling to transform massive information into actionable insights for better decision-making and increased business results.
Reach out to me if you are interested to evaluate if Looker is right for you or any other BI solution.

How Looker Writes SQL?