Getting Started with Elasticsearch, Part 1 – Seeding
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This is the first in a short series of blog posts that will get you started with Elasticsearch. In this you will deploy seed and query Elasticsearch from your own computer. The next will add a .NET Core API into the mix as ‘frontend’ for Elasticsearch. And the last will show how to deploy an Elasticsearch domain on AWS using an infrastructure as code tool.
This post will show you how to create a simple document mapping, seed the Elasticsearch index and perform some simple queries. It is not a substitute for reading the docs, it is more of step up to help you get going.
Getting Started
Download and install the latest version of Elasticsearch, this post was written when 7.7 was the up to date version, I mention this because if you are reading this when a version > 7 is available the steps may not work – Elasticsearch is known for making major breaking changes in major releases.
Start up Elasticsearch by changing to its directory and running –
bin/elasticsearchIf you are using Visual Studio Code I suggest installing the (Rest Client extension)[https://marketplace.visualstudio.com/items?itemName=humao.rest-client]. The elasticSearch.http file in attached zip contains examples of how to create and delete indexes, add mappings, and perform queries.
At the top of my elasticSearch.http I have two variables that will be used throughout the rest of the file, these define the host where Elasticsearch is running and the name of the index I’m working with -
@elasticSearchHost = http://localhost:9200
@index = customersTo see the indexes that are already in place run this –
GET {{elasticSearchHost}}/_cat/indices?v&prettyAdding an Index with Rest Client
Let’s add the customer index with Visual Studio Rest Client, of course you can use Postman, Fiddler or any tool of your choosing –
1PUT {{elasticSearchHost}}/{{index}}
2Content-Type: application/json
3
4{
5 "mappings": {
6 "properties": {
7 "companyName": {
8 "type": "text"
9 },
10 "customerId": {
11 "type": "integer"
12 },
13 "dateOfBirth": {
14 "type": "date"
15 },
16 "email": {
17 "type": "text"
18 },
19 "firstName": {
20 "type": "text",
21 "copy_to": "fullName"
22 },
23 "middleName": {
24 "type": "text",
25 "copy_to": "fullName"
26 },
27 "lastName": {
28 "type": "text",
29 "copy_to": "fullName"
30 },
31 "fullName": {
32 "type": "text"
33 },
34 "mobileNumber": {
35 "type": "text"
36 },
37 "officeNumber": {
38 "type": "text"
39 },
40 "address": {
41 "properties": {
42 "line1": {
43 "type": "text",
44 "copy_to": "fullAddress"
45 },
46 "line2": {
47 "type": "text",
48 "copy_to": "fullAddress"
49 },
50 "city": {
51 "type": "text",
52 "copy_to": "fullAddress"
53 },
54 "state": {
55 "type": "text",
56 "copy_to": "fullAddress"
57 },
58 "zip": {
59 "type": "text",
60 "copy_to": "fullAddress"
61 }
62 }
63 },
64 "fullAddress": {
65 "type": "text"
66 }
67 }
68 }
69}Run the request to list indexes again and you will see the customers index.
GET {{elasticSearchHost}}/_cat/indices?v&prettyhealth status index uuid pri rep docs.count docs.deleted store.size pri.store.size
yellow open customers RDWD3Q75TVqf7VkvO932mA 1 1 0 0 208b 208bSeeding
Time to switch to the seeder. This is Node.js program that checks if the customers index exists, creates it if it does not, and seeds the index with 5000 customer documents.
I’m not going to go into how it works as I am learning Node.js now and I’m sure it is not as good as it should be. You can execute it by running –
npm install
node seed.jsNow you should see a different result when you look at the indexes on the Elasticsearch server.
GET {{elasticSearchHost}}/_cat/indices?v&prettyhealth status index uuid pri rep docs.count docs.deleted store.size pri.store.size
yellow open customers wsdQcJ1IQNOXQ-QQIX_a_Q 1 1 5000 0 2.4mb 2.4mbHere are a few examples of requests you can make to Elasticsearch with Rest Client.
@elasticSearchHost = http://localhost:9200
@index = customers
###
# delete an index, BE CAREFUL WITH THIS ONE
DELETE {{elasticSearchHost}}/{{index}}?pretty
###
# retrieve a document from the index by its id
GET {{elasticSearchHost}}/{{index}}/_doc/1
###
# search the index with no query, this will match all documents, but return only the first few
GET {{elasticSearchHost}}/{{index}}/_search
###
# retrieve a page of results with no query
GET {{elasticSearchHost}}/{{index}}/_search
Content-Type: application/json
{
"sort":{"dateOfBirth": {"order":"asc"}},
"from": 0,
"size": 10
}
###
# search for company names that match the word 'Turcotte', you might need to change this name
GET {{elasticSearchHost}}/{{index}}/_search
Content-Type: application/json
{
"query": {
"match_phrase_prefix": {
"companyName" : "Turcotte"
}
}
}
###
# search for people in Utah with the name Keith (first, middle or last), you might need to change these parmas.
GET {{elasticSearchHost}}/{{index}}/_search
Content-Type: application/json
{
"query": {
"bool": {
"must": [
{"match_phrase_prefix": { "fullName" : "Keith" } }
,{"match": { "address.state" : "Utah"}}
]
}
}
}That’s it for now.
In the next blog post I will show you how to use HttpClientFactory and typed clients to make perform searches in .NET Core.
Full source code available here.