Learn Babel, Elasticsearch and Redwoodjs

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

RedwoodJS takes the JAMstack philosophy to the next level. It brings together all the tools modern web development has to offer:

- React
- GraphQL
- Prisma

RedwoodJS abstracts database management away from you so that you can just build your schema and it will do all the plumbing. This collection will go over how to create a RedwoodJS project and the scripts that will help make your developer experience a joy.


Bringing full-stack to the JAMstack

Do you love the JAMstack philosophy but need a database-backed web app? Want great developer experience and easy scaling? Redwood is here! Built on React, GraphQL, and Prisma, Redwood works with the components and development workflow you love, but with simple conventions and helpers to make your experience even better.

redwoodjs

Introduction to RedwoodJS: full-stack framework for JAMstack

Babel has support for the latest version of JavaScript through syntax transformers. These plugins allow you to use new syntax, right now without waiting for browser support.

babel

Converting all of our modern JavaScript into ES5 compatible syntax is a great way to use modern features while targeting older browsers. What happens when the browsers natively support these language features? Then it no longer makes sense to transform that code or to include polyfills that will go unused. In this lesson, we’ll add the `@babel/polyfill` package and configure `babel-preset-env`

Target specific browsers with babel-preset-env and the babel pollyfill

React is one of the web’s most popular frameworks for building JavaScript applications. 

If you know what you’re doing, React can drastically simplify how you build, use, and maintain code.

Whether you’re a React newbie or you’re ready for advanced techniques, you can level-up with egghead. Explore our in-depth courses, lessons, and community resources to build more powerful applications and crack open your career.

react

We use `yarn redwood generate page` (`yarn rw` for short) in this lesson to generate an `IndexPage` component. 

The first argument to `yarn rw generate page` is the name of the page you are generating. The second argument is the path you want the page to show up on. So `yarn rw generate page index /` will generate an `IndexPage` component and insert a route entry in our `web/src/Routes.js` file.

We learn that redwood import `React` for you so you don't have to import it manually when you are creating a component.

Generate a Page Using the Redwood CLI

In this lesson, we are going over how to generate a `RedwoodJS` project.

We can create a `RedwoodJS` project with `yarn create redwood-app ./my-redwood-project`.

`yarn` will generate the `RedwoodJS` app in the file folder you specified without installing any globals.

To run the `RedwoodJS` app, we use `yarn redwood dev`. This runs the Redwood client as well as the `GraphQL` backend.

Generate a Redwood Project

RedwoodJS provides a `Link` component that we can use to navigate around our app. We can provide a `to` prop with the path that we want to navigate to.

RedwoodJS takes this a step further and provides a `routes` object from `@redwoodjs/router`. This object is aware of all the routes defined in `web/Routes.js`. This allows us to use the methods on this object rather than referencing the our routes with a string literal. We can then change the route path without having to change all of the references to that route all over our app.

Use RedwoodJS Link and routes Object to Navigate

RedwoodJS gives us a cli command to generate layouts.

`yarn redwood generate layout main`

This will generate a `MainLayout` component in `src/layouts/MainLayout/`. We can use this layout component to define any headers or footers we want to share across multiple pages. 

Extract a RedwoodJS Layout Component

We take the opengraph image we wrote in codesandbox and copy it into our serverless function. We use Rollup to compile the component into an IIFE (immediately invoked function expression) that can run in our headless browser environment and cover a wide set of rollup plugins that we need for compatibility. We end the lesson having successfully screenshot our opengraph react component from our Netlify Function

Compiling a React to an IIFE with Rollup to execute and render in a headless browser

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.

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