Combine and Aggregate Data from Couchbase 6 Using N1QL
This course is about combining and aggregating data from multiple related documents using the N1QL query language. You will explore JOIN, NEST, as well as set operations such as UNION and INTERSECT, and aggregate similar documents using GROUP BY.
Want to learn about combining and aggregating data from multiple related documents using the N1QL query language? In this course, Combine and Aggregate Data from Couchbase Using N1QL, you will get some hands-on experience in writing queries which combine and aggregate the contents of related documents. These queries will be written in the N1QL query language which has a SQL-like syntax but is meant to work with JSON data. First, you will explore how data from different related documents can be combined by performing a JOIN operation, and a variety of joins will be covered in the course including left and right joins. You will also get to combine a collection of matching documents into an array using the NEST operation and will also learn to unpack a nested array using UNNEST. Beyond that, you will discover some aggregate operations which can be performed in N1QL using the GROUP BY and HAVING clauses, and will use the LETTING keyword to declare variables which can be referenced in a HAVING clause. Finally, you will perform a few set operations in N1QL such as UNION, INTERSECT, and EXCEPT. By the end of this course, you will have the skills required to run a variety of queries which can combine and aggregate data stored in documents.
Author Name: Kishan Iyer
Author Description:
I have a Masters in Computer Science from Columbia University and have worked previously as a developer and DevOps engineer. I now work at Loonycorn which is a studio for high-quality video content. My interests lie in the broad categories of Big Data, ML and Cloud.
Table of Contents
- Course Overview
1min - Combining Documents Using Simple Joins
48mins - Exploring Different Kinds of Joins in N1QL
52mins - Working with Arrays Using Nest and Unnest Operations
44mins - Aggregating Data Using Grouping and Set Operations
39mins
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