Learn Elasticsearch, Mdx and Rust

In this course, Chris takes a README-driven approach to build out a Rust CLI that supports content authoring for a digital garden.

Specifically, you'll work through the first command for the CLI, writing files. You start by initializing a new Cargo binary crate through creating the `write` command that allows you to create files (and their contents) to the folder that you set. 

Step by step you'll learn about:
- Handling user input
- Error handling
- Rust Move semantics
- Rust Copy semantics
- Integration testing

...and more!

Rust is a systems programming language that runs blazingly fast, prevents segfaults, and guarantees thread safety.

rust

Creating a Digital Garden CLI with Rust

Rust is a modern language that is close to the metal. It's got the performance of C, but with a more friendly syntax and community.

It's also memory safe, and ensures your applications are bug free by catching errors at compile time instead of runtime.

These features make Rust a great choice for developing code for embedded systems, web servers, and CLI apps. You can even compile Rust into WebAssembly in order to run it in-browser!

But as the saying goes, "before you learn to run, you must learn to walk".

In this course, you will write your first Rust application.

Starting from “Hello World” you’ll quickly move on to learning about Rust’s types, configuration files, and the `cargo` package manager along with classics like functions, loops, and handling user input.

More Rust-specific concepts like macros and pattern matching will also be introduced.

Check out these [**community notes for this course on Github**](https://github.com/eggheadio-projects/write-your-first-program-with-the-rust-language).

Next Steps: [Basic Types in Rust](https://egghead.io/playlists/data-types-in-rust-ab72)

Write Your First Program with the Rust Language

[Rustlings](https://github.com/rust-lang/rustlings) is a set of exercises that serves as a great introduction to the Rust language. It covers many concepts from the [Rust book](https://doc.rust-lang.org/book/) by asking you to work through sets of exercises.

This collection walks you through Rustlings in a way that explains what's going on in each exercise. We cover everything from basic types to generics and threading.

Learning Rust by Working Through the Rustlings Exercises

This collection contains videos that explore the basic types in Rust, including **Fixed size Integer**, **Pointer sized Integer**, **Boolean**, **Strings**, **Characters**, **Arrays**, **Tuples** and more.

If you're just starting out learning Rust and [wrote your first program](https://egghead.io/courses/write-your-first-program-with-the-rust-language), this collection is the right place to get more familiar with the language!

Basic Types in Rust

Many languages work on a compilation story to WebAssembly, but Rust is already ready for primetime. Why?


- Rust is a stable language and great replacement for C and C++. 
- Due to the reference and borrowing concept, Rust doesn’t need a Garbage Collector and can be used for a production-ready WebAssembly project. 
- The Rust/Wasm team has built some sophisticated tooling for straightforward interoperability between Rust and JavaScript.

This course gives you the tools to compile to WebAssembly with Rust. Over 11 lessons, we’ll set up a project and explore various paths of communication and interoperability between Rust and JavaScript.

Using WebAssembly with Rust

In this course, you will learn the basics of using Elasticsearch within your application. You will learn how to store and retrieve data in Elasticsearch as well as how to leverage its powerful search features.
 
You will be able to design indices, types and maps for your application to leverage the most from Elasticsearch and you will learn how to monitor the health and performance of your Elasticsearch servers to identify and resolve capacity issues before they impact your application.

Throughout this course, we will be using the [Simpsons dataset](https://www.kaggle.com/wcukierski/the-simpsons-by-the-data) containing all of the Simpsons episodes, characters, and lines. It will be the foundation for learning to retrieve data from Elasticsearch, perform complex searches, and understand and implement best practices for storing data in Elasticsearch. 

elasticsearch

Get Started with Elasticsearch

MDX has grown rapidly since the first commit two and a half years ago. We'd like to celebrate our accomplishments so far, and talk about what lies ahead. We've got lots of plans.
Learn how MDX increases developer productivity, improves educational content authoring, and even peek behind the curtains to see how MDX works.

MDX is an authorable format that lets you seamlessly use JSX in your markdown documents. You can import components, like interactive charts or notifications, and export metadata. This makes writing long-form content with components a blast.



MDX Conf 2020

Closing and opening indices on Elasticsearch allow you to free up resources in your cluster when they aren’t needed, preventing you from scaling or growing your cluster to support unused indices. In this lesson, you will see how easy it is to do both and learn to do so on your own indices.

Close and open an Elasticsearch index

In this lesson, you will learn how to add new documents to the Elasticsearch data store using HTTP methods and the Elasticsearch API. You will also learn how Elasticsearch uniquely identifies each document and what happens when you attempt to create a document that already exists.

Add data to Elasticsearch

Elasticsearch provides several methods for using its powerful search features. In this lesson, you will be introduced to the `_search` endpoint, the datapoints returned in results, how to set a query timeout (and what a timeout *doesn’t* do), and how to search specific indices and types.

Search for data in Elasticsearch using the _search endpoint

Elasticsearch provides a powerful API over http for accessing its features. In this lesson, you will be introduced to the API and learn how to use it to get data from Elasticsearch using the browser and the popular command curl.
We will see how adding  query stream parameters can exclude or include the properties that we desire from our data.

Setup is specified in the `README.md` of the repository linked below.

Get data from Elasticsearch by id using http

By default, search results are limited to the top 10 results. In this lesson, you will learn how to change the pagination size, paginate through results, and you will learn about the performance implications of pagination on Elasticsearch.

Paginate through search results in Elasticsearch

Elasticsearch offers two API endpoints for updating documents. In this lesson you will learn how to use those endpoints to replace entire documents in the store and update partial information within a document.

Update data in Elasticsearch

Elasticsearch provides a full featured client for nodejs available via npm. In this lesson, you will learn to how install the client and use it to retrieve data from your Elasticsearch server.
We will walk through retrieving data through callbacks as well as using promises.

Get data from Elasticsearch by id using the Elasticsearch npm client

Simple searches can be done using query parameters, also known as “Search Lite” by Elasticsearch. You will learn how to perform query parameter searches in this lesson and also discover the upper limits of its usability in this lesson.

Search Elasticsearch using Query Parameters

Query DSL is based on JSON and allows for Leaf and Compound query clauses.  The Query DSL is what you will want to use to write your production queries.  It makes your queries more flexible, precise, easier to read and easier to debug.

Search for data in Elasticsearch using queryDSL language

Using Full Text Search is where the search capabilities of Elasticsearch start to really set it apart from databases. In this lesson, you will learn how to perform full text searches against your data, interpret the results, and understand how the relevance score is impacts your search results. If you are following the examples in this course, be sure to import the Simpsons episode scripts for this lesson by running `node utils/episode_scripts.js` from the git repo directory.

Search for data in Elasticsearch using full text search

Aggregation queries can be thought of as similar to GROUP BY in SQL or the Aggregation Framework in MongoDB, but much more powerful. In this lesson you will learn how to create aggregation queries to group documents and perform rollups and calculations based on the results. Aggregation documentation can be found [here](https://www.elastic.co/guide/en/elasticsearch/reference/current/search-aggregations.html)

Perform analytics using Elasticsearch aggregation queries

Creating an alias can make searching easier by providing a friendlier name for the index. It can also be useful to create a filtered subset of the data, providing a better search experience for the client. You will learn how to do both in this lesson.

Create an alias for an Elasticsearch index

The index is the top-most schema level for your data. You will learn how to create an index in this lesson. You will be introduced to shards and replicas and how decisions about them will impact future performance, scalability and resiliency. You also learn what the elasticsearch cluster health status “green”, “yellow”, and “red” mean, not only in terms of cluster health but how it impacts your query search results.

Create an index using the Elasticsearch API

In this lesson, you will learn how to delete a single index, multiple indices, or all indices on your Elasticsearch cluster. We’ll see how a simple `DELETE`  request can delete any index you like.