The document explains key concepts of Elasticsearch, including nodes, clusters, indices, documents, and shards, highlighting their analogies to relational databases. It provides practical examples of creating and managing indices, adding documents, and querying data using REST API syntax and Query DSL. Additionally, it covers the mapping and searching capabilities for suggestions within an index.

1. Elasticsearch
Node
It refers to a single running instance of Elasticsearch.
Cluster [Database in RDBMS analogy]
It is a collection of one or more nodes.
Index [Table in RDBMS analogy]
It is a collection of different types of documents and their properties. Index also uses
the concept of shards to improve the performance.
Document [Row in RDBMS analogy]
It is a collection of fields in a specific manner defined in JSON format. Every document
belongs to a type and resides inside an index. Every document is associated with a
unique identifier called the UID.
Shard
Indexes are horizontally subdivided into shards. This means each shard contains all
the properties of the document but contains less number of JSON objects than index.
The horizontal separation makes shard an independent node, which can be store in
any node. Primary shard is the original horizontal part of an index and then these
primary shards are replicated into replica shards.
Replicas
Elasticsearch allows a user to create replicas of their indexes and shards. Replication
not only helps in increasing the availability of data in case of failure, but also improves
the performance of searching by carrying out a parallel search operation in these
replicas.

2. URLs
Elasticsearch ​http://localhost:9200
Kibana ​http://localhost:5601
Syntax of REST API to query Elasticsearch using Query DSL (Domain Specific
Language)
<HTTP_VERB> <api>/<command>
{
JSON Body
}
GET _cluster/health
1. Create an Index
PUT students
{
"settings": {
"index": {
"number_of_shards": 1,
"number_of_replicas": 0
}
}
}
2. Delete in Index
DELETE students
3. Add Documents one by one
PUT /students/student/1
{
"name": "Pratyush",
"roll": 10,
"city": "Gurgaon",
"state": "Haryana",
"desc": "Pratyush knows C, Java and PHP"
}

3. PUT /students/student/2
{
"name": "Dushyant",
"roll": 12,
"city": "Rewari",
"state": "Haryana",
"desc": "Dushyant knows C and Java"
}
PUT /students/student/3
{
"name": "Yogesh",
"roll": 15,
"city": "Bharatpur",
"state": "Rajasthan",
"desc": "Yogesh knows Java"
}
4. Bulk Add documents (Linux Command)
curl -H "Content-Type: application/json" -XPOST
"http://localhost:9200/students/_bulk" --data-binary "@students.json"
5. View documents by Id
GET /students/student/1
6. Update a document
PUT /students/student/1
{
"name": "Pratyush Majumdar",
"roll": 10,
"city": "Gurgaon",
"state": "Haryana"
"desc": "Pratyush knows C, Java and PHP"
}
7. Get settings of any index
GET /students/_settings

4. Search API
GET /students/_search
{
"query":{
"match_all":{}
}
}
GET students/student/_search
{
"query":{
"query_string":{
"query":"Java"
}
}
}
GET /students/student/_search
{
"query": {
"query_string": {
"default_field": "state",
"query": "Haryana"
}
}
}

5. Completion Suggester
1. Mapping query
PUT phones
{
"mappings": {
"phone" : {
"properties" : {
"suggest" : {
"type" : "completion"
},
"title" : {
"type": "keyword"
}
}
}
}
}
2. Add Data with input
PUT phones/phone/1
{
"name" : "Apple iPhone 12 pro max",
"suggest" : {
"input": [
"Apple",
"iPhone",
"Apple iPhone",
"iPhone 12",
"pro max",
"Apple iPhone 12 pro max"
],
"weight" : 12
}
}

6. PUT phones/phone/2
{
"name" : "Apple iPhone 11 pro max",
"suggest" : {
"input": [
"Apple",
"iPhone",
"Apple iPhone",
"iPhone 11",
"pro max",
"Apple iPhone 11 pro max"
],
"weight" : 11
}
}
PUT phones/phone/3
{
"name" : "Apple iPhone X",
"suggest" : {
"input": [
"Apple",
"iPhone",
"Apple iPhone",
"iPhone X",
"Apple iPhone X"
],
"weight" : 10
}
}
PUT phones/phone/4
{
"name" : "Apple iPhone 9 Plus",
"suggest" : {
"input": [
"Apple",
"iPhone",
"Apple iPhone",
"iPhone 9",
"9 Plus",
"Apple iPhone 9 Plus"
],

7. "weight" : 9
}
}
3. Search using prefix Match
GET phones/_search
{
"suggest": {
"song-suggest" : {
"prefix" : "i",
"completion" : {
"field" : "suggest"
}
}
}
}
4. Search using prefix Match with Fuzzy-ness of 2 (For miss-spelling)
GET phones/_search
{
"suggest": {
"song-suggest" : {
"prefix" : "Appel",
"completion" : {
"field" : "suggest",
"fuzzy" : {
"fuzziness" : 2
}
}
}
}
}