Technology Trekking

Update or insert is done by API. Most useful fact is that its upsert meaning, we use the same API. If field exists, it will get updated and if it does not exist, it will be inserted.
My first record is as below

import requests
import json

uri='http://localhost:9200/book/_doc/1'
headers1 ={'Content-Type': 'application/json'}
response = requests.get(uri,headers=headers1)
print("*************************************")
print("Accessing document before update : ", response.text)

Terminal output

Accessing document before update :  {
      "isbn": "9781593275846",
      "title": "Eloquent JavaScript, Second Edition",
      "subtitle": "A Modern Introduction to Programming",
      "author": "Marijn Haverbeke",
      "published": "2014-12-14T00:00:00.000Z",
      "publisher": "No Starch Press",
      "pages": 472,
      "description": "JavaScript lies at the heart of almost every modern web application, from social apps to the newest browser-based games. Though simple for beginners to pick up and play with, JavaScript is a flexible, complex language that you can use to build full-scale applications.",
      "website": "http://eloquentjavascript.net/"
    }

Now let us look at the code to update and insert the field in document.  Please note that there are multiple ways of doing update / insert.

import requests
import json
####################################################################### Insert one field in document
uri='http://localhost:9200/book/_update/1'
headers1 ={'Content-Type': 'application/json'}
query = json.dumps(
    {
    "script" : "ctx._source.price = 365.65"
    }
)
response = requests.post(uri,headers=headers1,data=query)
print("*************************************")
print(" Output", response.text)

####################################################################### Insert two fields in document
uri='http://localhost:9200/book/_update/1'
headers1 ={'Content-Type': 'application/json'}
query = json.dumps(
{
  "doc": {
    "summary":"summary3",
    "coauth":"co author name"
  }
}
)
response = requests.post(uri,headers=headers1,data=query)
print("*************************************")
print(" Output", response.text)

####################################################################### Insert nested field in document
uri='http://localhost:9200/book/_update/1'
headers1 ={'Content-Type': 'application/json'}
query = json.dumps(
    {
    "doc": {
        "country":{
        "continent":"Asia",
        "code" : 91
        },
        "coauthor_two":"Another co-author"
    }
    }
)
response = requests.post(uri,headers=headers1,data=query)
print("*************************************")
print(" Output", response.text)

####################################################################### Update field
uri='http://localhost:9200/book/_update/1'
headers1 ={'Content-Type': 'application/json'}
query = json.dumps(
{
  "doc": {
    "title":"Eloquent JavaScript, Second Edition - Updated using API from Python Script"
  }
}
)
response = requests.post(uri,headers=headers1,data=query)
print("*************************************")
print(" Output", response.text)

Once we have run above script, let us look at the document again by running below program or checking kibana.

import requests
import json
uri='http://localhost:9200/book/_source/1'
headers1 ={'Content-Type': 'application/json'}
response = requests.get(uri,headers=headers1)
print("*************************************")
print("Accessing document After update : ", response.text)

Output

Accessing document After update : {
    "isbn" : "9781593275846",
    "title" : "Eloquent JavaScript, Second Edition - Updated using API from Python Script",
    "subtitle" : "A Modern Introduction to Programming",
    "author" : "Marijn Haverbeke",
    "published" : "2014-12-14T00:00:00.000Z",
    "publisher" : "No Starch Press",
    "pages" : 472,
    "description" : "JavaScript lies at the heart of almost every modern web application, from social apps to the newest browser-based games. Though simple for beginners to pick up and play with, JavaScript is a flexible, complex language that you can use to build full-scale applications.",
    "website" : "http://eloquentjavascript.net/",
    "price" : 365.65,
    "summary" : "summary3",
    "coauth" : "co author name",
    "coauthor_two" : "Another co-author",
    "country" : {
      "continent" : "Asia",
      "code" : 91
    }

Kibana output

Elasticsearch has very detailed search API but its bit different for someone with RDBMS and SQL query background. Here are some of the sample queries.

search all

GET /ecomm/_search
{
    "query": {
        "match_all": {}
    }
}

Search for specific key

GET /twitter/_search
{
    "query": {
        "match": { "user":"ssss"}
    }
}

Search using URL

GET /ecomm/_search?q=Apple

Detailed search for nested value

GET /ecomm/_search
{
    "query": {
        "match" : {
            "productBaseInfoV1.productId": "MOBFKCTSYAPWYFJ5"
        }
    }
}

Search with more parameters

POST /ecomm/_search
{
    "query": {
        "match" : {
            "productBaseInfoV1.productId": "MOBFKCTSYAPWYFJ5"
        }
    },
    "size": 1,
    "from": 0,
    "_source": [ "productBaseInfoV1.productId", "productBaseInfoV1.title", "imageUrls","productDescription" ]
}

Elasticsearch exposes REST APIs that are used by the UI components and can be called directly to configure and access Elasticsearch features.

Show current indices

http://localhost:9200/_cat/indices

Output

yellow open test-index                   OeILxjmFRhODhztu4GgE_w 1 1    1 0   4.5kb   4.5kb
yellow open twitter                      BUmjGbLpTNCbnDIPxht9vA 1 1    1 0   3.7kb   3.7kb
yellow open bookindex                    RKq8oJKvRb2HQHxuPZdEbw 1 1    1 0   5.4kb   5.4kb
green  open kibana_sample_data_ecommerce FkD1obNSSK6mfLDsy9ILPQ 1 0 4675 0   4.9mb   4.9mb
green  open .kibana_task_manager_1       pc_LXegKQWu9690vT1Z-pA 1 0    2 1  16.9kb  16.9kb
yellow open facebook                     4Wzax6UhThm5rXi03PiG7w 1 1    1 0   3.5kb   3.5kb
green  open .apm-agent-configuration     sxoXMmsoS4mRPyjcaPByzw 1 0    0 0    283b    283b
green  open .kibana_1                    pK7pO-SCSBORonZLDi8Vew 1 0   60 2 949.5kb 949.5kb

This and below mentioned commands can be run from kibana, postman, browser or cURL

Curl

$ curl "localhost:9200/_cat/indices"
yellow open ecommpediatest               R6WypBc2RtCS_ITA40_rFw 1 1    0 0    283b    283b
yellow open test-index                   OeILxjmFRhODhztu4GgE_w 1 1    1 0   4.5kb   4.5kb
yellow open twitter                      BUmjGbLpTNCbnDIPxht9vA 1 1   11 5  26.9kb  26.9kb
yellow open bookindex                    RKq8oJKvRb2HQHxuPZdEbw 1 1    1 0   5.4kb   5.4kb
green  open .kibana_task_manager_1       pc_LXegKQWu9690vT1Z-pA 1 0    2 1  16.9kb  16.9kb
green  open kibana_sample_data_ecommerce FkD1obNSSK6mfLDsy9ILPQ 1 0 4675 0   4.9mb   4.9mb
green  open .apm-agent-configuration     sxoXMmsoS4mRPyjcaPByzw 1 0    0 0    283b    283b
yellow open facebook                     4Wzax6UhThm5rXi03PiG7w 1 1    2 0     7kb     7kb
green  open .kibana_1                    pK7pO-SCSBORonZLDi8Vew 1 0   60 2 945.9kb 945.9kb
yellow open twitter1                     3iMzcYoJR3qY9JiM2sY8_g 1 1    1 0   4.5kb   4.5kb

Kibana

Postman

Browser

How to create new index

PUT /ecommpediatest

same can e achieved by create new document command

PUT /twitter1/_doc/1
{
"user" : "kimchy updated",
"post_date" : "2009-11-15T14:12:12",
"message" : "trying out Elasticsearch"
}

Creating or updating record

------------------- Get records
GET twitter/_doc/1
HEAD twitter/_doc/1
GET twitter/_source/10
HEAD twitter/_source/1
-------------------update API
PUT /twitter/_doc/1
{
"user" : "kimchy",
"post_date" : "2009-11-15T14:12:12",
"message" : "trying out Elasticsearch"
}

POST /twitter/_doc/2
{
"user" : "tom",
"post_date" : "2009-11-15T14:12:12",
"message" : "trying out Elasticsearch"
}
PUT /twitter/_create/2
{
"user" : "Jerry",
"post_date" : "2009-11-15T14:12:12",
"message" : "trying out Elasticsearch"
}
POST /twitter/_create/
{
"user" : "cartoon",
"post_date" : "2009-11-15T14:12:12",
"message" : "trying out Elasticsearch"
}
-------------------delete
DELETE /twitter/_doc/1
-------------------- create
PUT /twitter/_doc/1
{
"user" : "one",
"post_date" : "2009-11-15T14:12:12",
"message" : "trying out Elasticsearch"
}

POST /twitter/_doc/
{
"user" : "one",
"post_date" : "2009-11-15T14:12:12",
"message" : "trying out Elasticsearch"
}

PUT /twitter/_create/aa
{
"user" : "xxx",
"post_date" : "2009-11-15T14:12:12",
"message" : "trying out Elasticsearch"
}
POST /twitter/_create/ss
{
"user" : "ssss",
"post_date" : "2009-11-15T14:12:12",
"message" : "trying out Elasticsearch"
}
------------------------------------------------------search
GET /_search
{
"query": {
"ids" : {
"values" : ["1", "ss", "100"]
}
}
}
GET /twitter/_search
{
"query": {
"ids" : {
"values" : [11,"ss"]
}
}
}
GET /twitter/_search
{
"query": {
"match_all": {}
}
}

GET /twitter/_search
{
"query": {
"match": { "user":"ssss"}
}
}