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Merge pull request #39 from mongodb-developer/fixed-code-samples
Fixed data samples to run directly on Atlas UI
2 parents 6b8fb3b + 7a87732 commit 8e89e7b

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‎docs/30-simple-queries/1-empty-aggregation.mdx

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@@ -13,14 +13,16 @@ This code is the equivalent of a `SELECT * FROM AUTHORS`. It returns a [cursor](
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<Screenshot src="/img/30-simple-queries/atlas-aggregation.png" url="http://cloud.mongodb.com/" alt="Atlas UI showing an empty aggregation pipeline" />
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- Make sure `Collections` > `authors` is selected.
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- Open the `Aggregation` tab.
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- Select `Text`.
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- Notice the empty array in the editor denoting an empty aggregation pipeline:
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```js
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[]
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```
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You're getting all documents in `authors`.
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</TabItem>
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<TabItem value="mongodb-shell" label="MongoDB Shell">

‎docs/30-simple-queries/2-match.mdx

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@@ -3,15 +3,15 @@ import TabItem from '@theme/TabItem';
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# 👐 $match
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6-
The $match operator is used in conjunction with the aggregation framework to filter documents in a collection. It takes a document as input and returns a new document containing only the documents that match the specified criteria. The syntax for the $match operator is as follows:
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The [$match](https://www.mongodb.com/docs/manual/reference/operator/aggregation/match/) stage filters documents in a collection. It takes a document as input (your filter) and returns the documents that match the specified criteria. The syntax for the $match stage is as follows:
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```js
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{ $match: { <expression>: <value> } }
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```
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## Expressions
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The `<expression>` portion of the $match operator can be any valid MongoDB expression. This includes:
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The `<expression>` portion of the $match stage can be any valid MongoDB expression. This includes:
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* Comparison operators: `eq`, `neq`, `gte`, `lte`, `gt`, `lt`, `in`, `nin`, `exists`.
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* Regular expressions: regex.
@@ -46,7 +46,11 @@ The `<expression>` portion of the $match operator can be any valid MongoDB expre
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Say we want all the books from 2010. We'll write:
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```js
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db.books.aggregate([{$match: {year: 2010}}])
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db.books.aggregate([
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{
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$match: {year: 2010}
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}
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])
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```
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</TabItem>
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</Tabs>
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<TabItem value="atlas" label="Atlas UI">
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```js
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[
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{
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$match: { pages: 100 }
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}
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{
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$match: { pages: 100 }
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}
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]
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```
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</TabItem>
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<TabItem value="mongodb-shell" label="MongoDB Shell">
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```js
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db.books.aggregate([{$match: {pages: 100}}])
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db.books.aggregate([
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{
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$match: { pages: 100 }
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}
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])
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```
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</TabItem>
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</Tabs>
@@ -82,44 +90,50 @@ db.books.aggregate([{$match: {pages: 100}}])
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## AND
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If we need to add more conditions using AND, we can do it with the `$and` operator.
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If we need to add more conditions using AND, we use the `$and` operator.
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If we want all the books with 100 pages with exactly `totalInventory` 2, we can use a `$and` operator. This takes an array of documents with all the conditions that should be true for the AND to succeed:
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If we want all the books with 100 pages and with exactly `totalInventory` 1, we can use the `$and` operator. It takes an array of documents with all the conditions that should be true for the AND to succeed:
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<Tabs groupId="aggregations">
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<TabItem value="atlas" label="Atlas UI">
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```js
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[
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{
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$match: {
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$and: [
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{ pages: 100 },
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{ totalInventory: 2 }
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]
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}
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{
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$match: {
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$and: [
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{ pages: 100 },
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{ totalInventory: 1 }
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]
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}
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}
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]
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```
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</TabItem>
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<TabItem value="mongodb-shell" label="MongoDB Shell">
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```js
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db.books.aggregate([{$match: {$and: [{pages: 100}, {totalInventory: 2}]}}])
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db.books.aggregate([
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{
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$match: {
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$and: [
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{ pages: 100 },
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{ totalInventory: 1 }
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]
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}
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}
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])
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```
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</TabItem>
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</Tabs>
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The pseudo-code for this would be something like:
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```
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IF pages == 100 AND totalInventory == 2 {
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IF pages == 100 AND totalInventory == 1 {
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return matching docs
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}
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```
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👐 Return all the `books` from 2015 that have exactly 100 pages.
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👐 Return all the `books` from 2009 that have exactly 192 pages.
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<details>
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<summary>Answer</summary>
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<TabItem value="atlas" label="Atlas UI">
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```js
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[
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{
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$match: {
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$and: [
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{ pages: 100 },
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{ year: 2015 }
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]
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}
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{
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$match: {
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$and: [
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{ pages: 192 },
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{ year: 2009 }
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]
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}
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}
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]
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```
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</TabItem>
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<TabItem value="mongodb-shell" label="MongoDB Shell">
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```js
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db.books.aggregate([{$match: {$and: [{pages: 100}, {year: 2015}]}}])
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db.books.aggregate([
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{
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$match: {
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$and: [
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{ pages: 192 },
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{ year: 2009 }
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]
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}
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}
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])
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```
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</TabItem>
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</Tabs>
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</div>
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</details>
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👐 How many are there?
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👐 How many are there? We haven't yet seen the `$count` stage, but try to adding a second stage to your pipeline with `{ $count: "books_count" }`
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<details>
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<summary>Answer</summary>
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</TabItem>
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<TabItem value="mongodb-shell" label="MongoDB Shell">
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```js
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db.books.aggregate([{$match: {$and: [{pages: 100}, {year: 2015}]}}]).itcount()
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db.books.aggregate(
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[
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{ $match: {$and: [{pages: 100}, {year: 2015}]} },
205+
{ $count: "books_count" }
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]
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)
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```
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</TabItem>
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</Tabs>
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<TabItem value="atlas" label="Atlas UI">
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```js
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[
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{
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$match: {pages: 100, totalInventory: 2}
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}
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{
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$match: { pages: 100, totalInventory: 2 }
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}
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]
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```
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</TabItem>
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<TabItem value="mongodb-shell" label="MongoDB Shell">
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```js
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db.books.aggregate([{$match: {pages: 100, totalInventory: 2}}])
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db.books.aggregate([
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{
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$match: { pages: 100, totalInventory: 2 }
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}
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])
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```
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</TabItem>
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</Tabs>
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208-
👐 Return all the `books` from 2015 that have exactly 100 pages, using the simple $and notation:
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👐 Return all the `books` from 2009 that have exactly 192 pages, using the shorthand `$and` notation:
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<details>
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<summary>Answer</summary>
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```js
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[
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{
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$match: {pages: 100, year: 2015}
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$match: {pages: 192, year: 2009}
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}
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]
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```
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</TabItem>
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<TabItem value="mongodb-shell" label="MongoDB Shell">
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```js
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db.books.aggregate([{$match: {pages: 100, year: 2015}}])
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db.books.aggregate([{$match: {pages: 192, year: 2009}}])
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```
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</TabItem>
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</Tabs>

‎docs/30-simple-queries/3-project.mdx

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@@ -67,22 +67,26 @@ If we're interested in the titles, we can use `$project` to select just the fiel
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```js
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[
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{
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$project: {title: 1, year: 1}
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$project: { title: 1, year: 1 }
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}
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]
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```
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</TabItem>
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<TabItem value="mongodb-shell" label="MongoDB Shell">
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```js
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db.books.aggregate([{$project: {title: 1, year: 1}}])
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db.books.aggregate([
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{
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$project: { title: 1, year: 1 }
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}
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])
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```
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</TabItem>
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</Tabs>
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84-
- 1 means "show that field."
85-
- 0 means "hide that field."
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- 1 means "show that field.". Once you started an inclusion projection you can't exclude other fields (you just keep adding the fields you want to see)
89+
- 0 means "hide that field.". Once you started an exclusion projection you can't include other fields (you just keep adding the fields you don't want to see)
8690
- The primary key `_id` field is shown by default.
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So we can exclude fields and show all fields except `attributes` using:
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```js
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[
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{
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$project: {attributes: 0}
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$project: { attributes: 0 }
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}
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]
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```
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</TabItem>
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<TabItem value="mongodb-shell" label="MongoDB Shell">
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```js
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db.books.aggregate([{$project: {attributes: 0}}])
106+
db.books.aggregate([
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{
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$project: { attributes: 0 }
109+
}
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])
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```
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</TabItem>
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</Tabs>
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116124
```js
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[
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{
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$project: {title: 1, cover: 1}
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$project: { title: 1, cover: 1 }
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}
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]
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```
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</TabItem>
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<TabItem value="mongodb-shell" label="MongoDB Shell">
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```js
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db.books.aggregate([{$project: {title: 1, cover: 1}}])
134+
db.books.aggregate([
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{
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$project: { title: 1, cover: 1 }
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}
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])
127139
```
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</TabItem>
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</Tabs>

‎docs/30-simple-queries/4-limiting-results.mdx

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<TabItem value="atlas" label="Atlas UI">
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```js
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[
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{ $limit: 1 }
12+
{ $limit: 1 }
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]
1414
```
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</TabItem>
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<TabItem value="mongodb-shell" label="MongoDB Shell">
1717
```js
18-
db.books.aggregate([{$limit: 1}])
18+
db.books.aggregate([
19+
{ $limit: 1 }
20+
])
1921
```
2022
</TabItem>
2123
</Tabs>
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3335
<TabItem value="atlas" label="Atlas UI">
3436
```js
3537
[
36-
{ $limit: 7 }
38+
{ $limit: 7 }
3739
]
3840
```
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</TabItem>
4042
<TabItem value="mongodb-shell" label="MongoDB Shell">
4143
```js
42-
db.books.aggregate([{$limit: 7}])
44+
db.books.aggregate([
45+
{ $limit: 7 }
46+
])
4347
```
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</TabItem>
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</Tabs>

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