Elastic Stack and Kibana Loading Data and API

Mappings and Data types

Elasticsearch supports a wide variety of data types for different situations where you want to store text data, numbers, booleans, binary objects, arrays, objects, geo-points, geo-shapes, and many other data types, such as IP addresses.
Refer here for complete list of Datatypes
Mapping is the process of defining how document are indexed.
Two Kinds of Mappings can be done
- Dynamic
- Explicit
Refer here for complete documentation on Mappings

http://<elasticsearch host>:<port>/<index>/<type>/<document id>

To experiment with elastic search we need to generate fake data. For that i have written a very simple python program.
Make sure you make changes to Ip address and execute pip install requests before you run this program
Program can be found here
This program generates 10 days of log data, with each date being in a index
Execute the program with the following command python <filename>.py
Wait for some time and Open Kibana UI.
Navigate to Kibana Management
Select the Index Patterns
Click on Create Index Pattern
Enter *-fakeindex as shown in image below and click on next step
Select the time field as date_posted and Create Index Pattern
You should be able to see the field mappings
Now click on Discover
Select Time period to be 1 year and you should be able to (Program starts publishing log data from Aug 15 2019)
Note: There is one more program with fake cpu values here