Merge branch 'main' into patch-16

Author: sourabhbagrecha

README.md

@@ -1,19 +1,3 @@
-# Docusaurus Template Workshop
+# SQL to MongoDB Query API
 
-This is a template to __create new Lab documentation sites__. Contains info on how to use Docusaurus and is a good starting point.
-
-### Installation, use, how to build, etc.
-
-Everything is covered in the Lab itself: https://mongodb-developer.github.io/docusaurus-workshop/
-
-## Contributing
-
-As `main` is protected, submit a pull request to be reviewed.
-
-## Docusaurus
-
-This website is built using [Docusaurus 2](https://docusaurus.io/), a modern static website generator. It's available on https://mongodb-developer.github.io/docusaurus-workshop/.
-
-### Disclaimer
-
-Use at your own risk; not a supported MongoDB product
+Workshop Docs hosted at: https://sql-to-query-api-lab.github.io/sql-to-query-api-lab/docs/category/prerequisites

docs/20-prerequisites/20-prerequisite.mdx

@@ -6,7 +6,7 @@ description: Setting up your MongoDB Atlas account, importing Library data
 
 To follow along, you'll need to complete the first two labs of the MongoDB for RDBMS professionals. Which will help you in getting:
 
-- MongoDB Atlas Cluster
-- Test data. In this case, this is book, author, and review data for a library management system.
+- A free MongoDB Atlas Cluster
+- Sample data
 
-👐 To get both, open the [intro lab](https://mongodb-developer.github.io/intro-lab/docs/intro) and follow it (only takes 10-15 mins) to get your database ready. Return here when finished!
+To get both, open the [intro lab](https://mongodb-developer.github.io/intro-lab/docs/intro) and follow it (only takes 10-15 mins) to get your database ready. Return here when finished!

docs/30-quick-start.mdx

@@ -8,8 +8,26 @@ To use work through the exercises, we need to install the official MongoDB GUI:
 
 ## Connect compass to your Atlas cluster
 
-- Insert Add connection page of compass
+### 1. Click on the "Add connection" button on the home page
 
-## Select the library database
+![](/img/add-connection-compass.png)
 
-- Insert databases list
+### 2. Paste your connection string after updating your password and click on the "Save and Connect" button
+
+![](/img/enter-connection-uri-compass.png)
+
+### 3. Select the library database
+
+![](/img/select-db-collection-compass.png)
+
+### 4. Click on the "Open MongoDB shell" button
+
+![](/img/open-shell-compass.png)
+
+### 5. Switch to the library database in the shell
+
+Once the shell is loaded, execute: `use library` to ensure you are in the correct database.
+
+![](/img/use-library-compass.png)
+
+That's it for the setup, let's get our hands dirty!

docs/40-CRUD/1-WHERE.mdx

@@ -1,22 +1,22 @@
 # 👐 WHERE → .find()
 
-Similar to SQL's `WHERE` clause, the `.find()` method in MongoDB retrieves documents from a collection that match a specified query.
+Similar to SQL's `WHERE` clause, the `.find()` method in MongoDB retrieves documents from a collection that matches a specified query.
 
 ## Syntax
 
 ```js
 db.collection.find({ <query> })
 ```
 
-- `<query>`: Specifies conditions to filter documents.
+- `<query>`: Specifies conditions to filter documents
 
 ## Example: Find all books from 2020
 
 ```js
 db.books.find({ year: 2020 });
 ```
 
-### Equivalent SQL Query
+### Equivalent SQL query
 
 ```sql
 SELECT * FROM books WHERE year = 2020;
@@ -26,24 +26,24 @@ SELECT * FROM books WHERE year = 2020;
 
 The `find()` method takes a document as its first argument. This document specifies the filter criteria. You can use a variety of expressions within the filter document:
 
-- **Comparison Operators:** `$eq` (equals), `$ne` (not equals), `$gt` (greater than), `$lt` (less than), `$gte` (greater than or equals), `$lte` (less than or equals), `$in` (in an array), `$nin` (not in an array).
-- **Logical Operators:** `$and`, `$or`, `$not`.
-- **Element Operators:** `$exists` (check for field existence), `$type` (check data type).
-- **Evaluation Operators:** `$regex` (regular expression matching), `$where` (JavaScript code execution).
-- **Geo-spatial Operators:** For location-based queries.
-- **Array Operators:** For querying arrays.
+- **Comparison operators:** `$eq` (equals), `$ne` (not equals), `$gt` (greater than), `$lt` (less than), `$gte` (greater than or equals), `$lte` (less than or equals), `$in` (in an array), `$nin` (not in an array)
+- **Logical operators:** `$and`, `$or`, `$not`
+- **Element operators:** `$exists` (check for field existence), `$type` (check data type)
+- **Evaluation operators:** `$regex` (regular expression matching), `$where` (JavaScript code execution)
+- **Geo-spatial operators:** For location-based queries
+- **Array operators:** For querying arrays
 
 Now, let's utilize a few MongoDB operators and create more sophisticated queries:
 
-### $or and $gt operator
+### $or and $gt operators
 
-Suppose, we want to get all the books written in 2010 OR has more than 200 pages.
+Suppose we want to get all the books written in 2010 OR books that have more than 200 pages.
 
 ```sql
   SELECT * FROM books WHERE year = 2010 OR pages > 200
 ```
 
-Equivalent MongoDB Query:
+Equivalent MongoDB query:
 
 ```js
 db.books.find({
@@ -56,7 +56,7 @@ db.books.find({
 
 ### $and operator
 
-This time, instead of OR let's query using AND:
+This time, instead of OR, let's query using AND:
 
 ```sql
   SELECT * FROM books WHERE year = 2010 AND pages > 200
@@ -75,17 +75,17 @@ db.books.find({
 
 ### Shorthand $and
 
-When we are querying on 2 different fields and want to utilize $and, we can do so by passing a document with all the conditions like this:
+When we are querying on two different fields and want to utilize $and, we can do so by passing a document with all the conditions, like this:
 
 ```js
 db.books.find({ year: 2010, pages: { $gt: 200 } });
 ```
 
-As you can see, we don't have to pass an Array of conditions, MongoDB implicitly considers this as $and.
+As you can see, we don't have to pass an array of conditions. MongoDB implicitly considers this as $and.
 
 ## 👐 Challenge
 
-Now, translate the following into a MongoDB Query.
+Now, translate the following into a MongoDB query.
 
 #### 1. Find all books where `totalInventory` is exactly 5.
 
@@ -109,13 +109,13 @@ Now, translate the following into a MongoDB Query.
   </div>
 </details>
 
-#### 3. Find books in the "Science" genre that has more than 300 pages.
+#### 3. Find books in the "Science" genre that have more than 300 pages.
 
 <details>
   <summary>Answer</summary>
   <div>
     ```js
-      db.books.find({ genre: "Science", pages: {$gt: 300} });
+      db.books.find({ genres: "Science", pages: {$gt: 300} });
     ```
   </div>
 </details>

docs/40-CRUD/_category_.json

@@ -1,5 +1,5 @@
 {
-  "label": "👐 CRUD operations",
+  "label": "👐 CRUD Operations",
   "position": 40,
   "link": {
     "type": "generated-index",

docs/50-aggregation/3-sort-limit.mdx

@@ -77,7 +77,7 @@ SELECT * FROM books ORDER BY timestamp DESC LIMIT 5;
     ```js
       db.books.aggregate([
         {
-          $match: { year: {$lt: 2010}}
+          $match: { year: {$gt: 2010}}
         },
         {
           $project: {

docs/50-aggregation/4-group.mdx

@@ -91,52 +91,61 @@ db.books.aggregate([
 
 ---
 
-## 👐 Example 3: Find the average book rating of all books
+## 👐 Example 3: Find the total number of pages published every year.
+
 
 ### **MongoDB query**
 
 ```js
-db.reviews.aggregate([
-  { $group: { _id: "$bookId", avgRating: { $avg: "$rating" } } },
+db.books.aggregate([
+  {
+    $group: {
+      _id: "$year",
+      totalPages: { $sum: "$pages" },
+    },
+  },
 ]);
 ```
 
 ### Equivalent SQL query
 
 ```sql
-SELECT bookId, AVG(rating) AS avgRating
-FROM reviews
-GROUP BY bookId;
+SELECT year, SUM(rating) AS totalPages
+FROM books
+GROUP BY year;
 ```
 
 ### Sample output
 
 ```json
 [
-  { "_id": "1885865171", "avgRating": 4.2 },
-  { "_id": "0738701688", "avgRating": 4.33 },
-  { "_id": "0747545448", "avgRating": 5 }
+  { "_id": 1955, "totalPages": 664 },
+  { "_id": 1952, "totalPages": 416 },
+  { "_id": 1899, "totalPages": 128 }
+  ...
 ]
 ```
 
 ---
 
 ## 👐 Challenge
 
-### 👐 1. Find the total number of pages published every year
+
+### 👐 1. Find the average book rating of all books
 
 <details>
   <summary>Answer</summary>
     ```js
-    db.books.aggregate([
+    db.reviews.aggregate([
       {
         $group: {
-          _id: "$year",
-          totalPages: { $sum: "$pages" }
+          _id: "$bookId",
+          avgRating: { $avg: "$rating" }
         }
       },
     ]);
     ```
+
 </details>
 
 ### 👐 2. Find users with the most number of reviews (Hint: use the `name` field in the reviews collection)

docs/50-aggregation/5-JOIN.mdx

@@ -47,12 +47,13 @@ db.authors.aggregate([
 ]);
 ```
 
-### **Equivalent SQL Query**
+### **Equivalent SQL query**
 
 ```sql
-SELECT books.*, authors.*
+SELECT author.* , books_written.*
 FROM authors
-LEFT JOIN books ON authors._id = books.author_id;
+LEFT OUTER JOIN author_books ON authors.id = author_books.author_id
+LEFT OUTER JOIN books as books_written ON author_books.book_id = books_written._id;
 ```
 
 :::info
@@ -61,11 +62,11 @@ The result in MongoDB will have an array (`authorDetails`) instead of flat colum
 
 ---
 
-## 🔹 Handling Unwinding ($unwind)
+## 🔹 Handling unwinding ($unwind)
 
 Since `$lookup` produces an **array**, we can flatten it using `$unwind`.
 
-### Example 2: Get Only Book Titles and Single Author Name
+### Example 2: Get only book titles and single author name
 
 ```js
 db.authors.aggregate([
@@ -83,7 +84,7 @@ db.authors.aggregate([
 ```
 
 :::info
-The $lookup operation creates an array within each book document. Using $unwind then flattens this array, resulting in a separate document for every single book - author pair.
+The $lookup operation creates an array within each book document. Using $unwind then flattens this array, resulting in a separate document for every single book-author pair.
 :::
 
 ---

docs/50-aggregation/7-CREATE-VIEW.mdx

@@ -1,4 +1,4 @@
-# 👐 $merge
+# 🦸 $merge
 
 In MongoDB, the **$merge** stage allows you to **write the results of an aggregation pipeline into a new or existing collection**. This is similar to the concept of "INSERT INTO ... SELECT" or "MERGE INTO" in SQL databases.
 
@@ -8,12 +8,12 @@ In MongoDB, the **$merge** stage allows you to **write the results of an aggrega
 
 The `$merge` stage enables you to store aggregation results into a different collection. If the target collection doesn’t exist, MongoDB will create it automatically.
 
-### **Key Features:**
+### **Key features:**
 
-✔️ Inserts new documents if they don’t exist.
-✔️ Updates existing documents based on `_id` or a specified field.
-✔️ Can replace, merge, or discard duplicate records.
-✔️ Useful for **ETL workflows, reporting tables, and maintaining summary data.**
+✔️ Inserts new documents if they don’t exist
+✔️ Updates existing documents based on `_id` or a specified field
+✔️ Can replace, merge, or discard duplicate records
+✔️ Useful for **ETL workflows, reporting tables, and maintaining summary data**
 
 ---
 
@@ -42,7 +42,7 @@ The `$merge` stage enables you to store aggregation results into a different col
 
 ---
 
-## **🔹 Example 1: Creating a Summary Collection**
+## **🔹 Example 1: Creating a summary collection**
 
 👉 Suppose we want to generate a collection that contains the **total number of books per genre**.
 
@@ -61,7 +61,7 @@ db.books.aggregate([
 ]);
 ```
 
-### **Equivalent SQL Query**
+### **Equivalent SQL query**
 
 ```sql
 INSERT INTO genre_summary (genre, totalBooks)
@@ -72,7 +72,7 @@ ON DUPLICATE KEY UPDATE totalBooks = VALUES(totalBooks);
 
 ---
 
-## **🔹 Example 2: Maintaining an Author Summary Table**
+## **🔹 Example 2: Maintaining an author summary table**
 
 👉 We want to create an **author_stats** collection with the total number of books written by each author.
 
@@ -91,7 +91,7 @@ db.books.aggregate([
 ]);
 ```
 
-### **SQL Equivalent**
+### **SQL equivalent**
 
 ```sql
 INSERT INTO author_stats (authorName, totalBooks)

docs/summary.mdx

@@ -4,12 +4,10 @@ sidebar_position: 100
 
 # 🎯 Summary
 
-Congratulations! Following this tutorial, you have successfully:
+Congratulations! Following this tutorial, you have successfully learned:
 
-- TBD
-- TBD
-- TBD
-- TBD
-- TBD
+- How to query collections in MongoDB
+- How to insert, update and delete documents in MongoDB
+- How to write aggregation pipelines in MongoDB
 
 Visit the [MongoDB Developer Center](https://mongodb.com/developer/?utm_campaign=devrel&utm_source=workshop&utm_medium=cta&utm_content=sql_to_query_api&utm_term=sourabh_bagrecha) for more useful information and tutorials.