checkpoint, structure updates, and fleshing out the outline

Author: erikhatcher

docs/01_Welcome.md

@@ -0,0 +1,27 @@
+# Welcome
+
+Welcome to the Atlas Search Fundamentals Workshop! In this interactive session, you'll learn how to use the MongoDB Atlas Search Playground to create and test powerful search queries for an Airbnb-like dataset, all without the need for setting up your own cluster.
+
+This workshop presents the fundamental concepts of the full-text search capabilities provided by Atlas Search, and empowers developers with best practice techniques to bring powerful search experiences to their applications. Developers will engage with a number of practical exercises to gain experience and confidence in understanding textual analysis and tokenization, configuring field types, and leveraging search operators for better relevancy.
+
+## What You'll Learn
+
+1. **Atlas Search overview**
+ - System architecture
+ - Index configuration
+ - Inverted index
+
+2. **Analysis**
+  - Built-in analyzers
+  - Multi analysis
+
+3. **Search operators**
+  - Text operators
+  - Query construction
+
+4. **Relevancy**
+  - Scoring
+  - TF/IDF and BM25
+
+5. **Data modeling and schema design for Atlas Search**
+  - Best practices

docs/10_Architecture/1_system.md

@@ -0,0 +1,20 @@
+# 📘 Atlas Search architecture
+
+![system diagram](/img/system_diagram.png)
+
+
+## Coupled nodes
+![coupled nodes](/img/coupled.png)
+
+## Dedicated search nodes
+![dedicated search nodes](/img/search_nodes.png)
+
+## Aggregation pipeline search stages
+
+### $search
+
+where the magic happens
+
+### $searchMeta
+
+The `$searchMeta` stage performs the same search that `$search` does, but only returns the results metadata, not actual matching documents. Results metadata includes the count of matching results and facets. This same metadata is available when using `$search` too, accessible in the $$SEARCH_META context variable.

docs/10_Architecture/2_index_config.md

@@ -0,0 +1,19 @@
+# 📘 Index configuration
+
+Documents are mapped to an index through a flexible configuration. 
+
+* https://www.mongodb.com/docs/atlas/atlas-search/define-field-mappings/
+
+## Supported types
+
+## Dynamic mapping
+
+## String-focused workshop
+
+Most data types are queried straightforwardly, and match as one would expect.  We'll survey non-string types in the next section, however we primarily focus on `string` fields, as that's where the power of Atlas Search shines.
+
+## Configuring a real Atlas Search index
+
+* Visual Index Builder
+* via Compass
+* Atlas CLI

docs/10_Introduction/1_welcome.md

@@ -0,0 +1,18 @@
+# 📘 Atlas Search Playground
+
+The Atlas Search Playground (or just Playground) is used for the exercises in this workshop.  The Playground is a self-contained lightweight, yet feature-rich Atlas Search environment which does not require an Atlas account to use.
+
+There are two tools in the Playground:
+  * Code Sandbox: your data, an index configuration, an aggregation pipeline, and results
+  * Search Demo Builder: a configurable search UI on your data
+
+The exercises will use the Code Sandbox, as it allows saving and sharing links to the full environment and corresponds directly to the configuration and pipeline one would use in a real application.
+
+## Code Sandbox layout
+
+To begin, please navigate to the [Atlas Search Playground](https://search-playground.mongodb.com/). In the next section, you'll work through the first exercise to get familiar with the Playground's Code Sandbox.
+
+Let's dive into the world of Atlas Search using this convenient and powerful playground!
+
+## Resources
+* https://www.mongodb.com/developer/products/atlas/search-playground-intro/

docs/10_Introduction/2_playground.md

@@ -0,0 +1,36 @@
+# 👐 Our first playground exercise
+
+1. Navigate to this Playground snapshot: 
+   https://search-playground.mongodb.com/tools/code-sandbox/snapshots/6782aea0667feaaf06324b87
+2. Press "Run" (TODO: bring in the Run graphic)
+3. Notice the empty `[]` results
+
+The objective with this exercise is to adjust the `FIX_ME` in the `$search` aggregation pipeline stage so that the document (in the Data Source pane) matches the query and appears in the Results pane.
+
+TODO: insert un-fixed playground screenshot
+
+<details>
+<summary>Here's a solution</summary>
+<div>
+```js
+[
+  {
+    $search: {
+      index: "default",
+      text: {
+        query: "search",
+        path: "title"
+      }
+    }
+  }
+]
+```
+</div>
+</details>
+
+<details>
+<summary>There are other possible solutions too</summary>
+<div>
+`atlas` or `fundamentals` or other case variations of any `title` field words
+</div>
+</details>

docs/10_Introduction/3_architecture.md

@@ -0,0 +1,53 @@
+# Field types
+
+## boolean
+equals: https://search-playground.corp.mongodb.com/tools/code-playground/snapshots/669e6ab1d49ef6fad98118b4
+
+## date
+range: https://search-playground.corp.mongodb.com/tools/code-playground/snapshots/669e6b18d49ef6fad98118b6
+
+## number
+range: https://search-playground.corp.mongodb.com/tools/code-playground/snapshots/669e6b4ad49ef6fad98118b8
+
+## geo
+geoWithin: https://search-playground.corp.mongodb.com/tools/code-playground/snapshots/669e6b762ce7658e786edbfa
+Requires explicit geo type mapping, since dynamic mappings don’t support geo.
+
+## autocomplete
+blah, don’t do it! ;)
+See also: Relevant As-You-Type Suggestions Search Solution
+
+## document
+
+Default dynamic mapping behavior, flattens nested documents into “arrays” of values on main document
+
+## embeddedDocument
+Attribute pattern k/v matching, more nuanced than document type flattening
+See cool tricks for embedded documents
+
+## string
+Basic examples
+lucene.standard matching case-insensitive: https://search-playground.mongodb.com/tools/code-playground/snapshots/664738af4e0a3f240a5de9d9
+
+## Analysis matters
+“searches” query does not match “Search” with lucene.standard: https://search-playground.mongodb.com/tools/code-playground/snapshots/664739964e0a3f240a5de9db
+“searches” matches “Search” using lucene.english: https://search-playground.mongodb.com/tools/code-playground/snapshots/66473aa64e0a3f240a5de9dd
+
+## Custom analyzers
+Last 4 digit of phone number matching (regex extraction during indexing, keyword analysis at query time): https://search-playground.corp.mongodb.com/tools/code-playground/snapshots/669e6c98d49ef6fad98118ba
+Example of being able to do ‘startsWith’ and ‘endsWith’ using wildcard and ‘reverse’ token filter:
+https://search-playground.corp.mongodb.com/tools/code-playground/snapshots/6683c8bc4a45448733549bbc
+
+Example of being able to do ‘startsWith’, ‘endsWith’ and ‘contains’ using nGrams: https://search-playground.corp.mongodb.com/tools/code-playground/snapshots/6683c999934a05d9b585b6e7 
+Relevancy
+Example of an as-you-type suggest configuration; sophisticated use of multi and several weighted query clauses: https://search-playground.mongodb.com/tools/code-playground/snapshots/66473b744e0a3f240a5de9e1
+$project score?
+$project scoreDetails?
+
+# multi
+Why?
+Relevancy example: boost each multi uniquely
+Multiple language example: may not know the language of the content and each document could be different - multi across all possible languages, query across them as desired at query-time, let relevancy sort it out
+Example of being able to do ‘startsWith’ and ‘endsWith’ using wildcard and ‘reverse’ token filter:
+https://search-playground.corp.mongodb.com/tools/code-playground/snapshots/6683c8bc4a45448733549bbc
+