README.md

FastDataSearch

FastDataSearch is like a high-powered search engine for your big data collections. Imagine you have massive csv file full of information, and you want to be able to find exactly what you need quickly and easily. That's where FastDataSearch comes in.

• FastDataSearch is built using Java Spring Boot.

• Here's what it does in simpler terms:

  1. It takes your large data files (like giant CSV spreadsheets) and cleverly organizes them in a special database called Elasticsearch. This is like creating a super-efficient filing system for your data.
  2. Once your data is organized, you can search through it really fast. It's similar to how Google lets you find things on the internet quickly, but for your own data.
  3. You can ask FastDataSearch questions about your data with query similar to SQL AND opertaion and it will fetch that information for you in a snap.
  4. It's smart about handling huge amounts of data. Instead of trying to work with everything at once (which would be slow), it breaks things into manageable chunks.

The big benefit is speed and efficiency. If you're a business dealing with tons of data, FastDataSearch helps you find what you need without waiting around. It's like having a super-fast plus smart assistant that knows exactly where everything is in your massive digital filing cabinet.

Code Flow

Postman collection - FastDataSearch APIs

Installation

1. Clone the repository:

   git clone https://github.com/your-repo/FastDataSearch.git
   cd FastDataSearch

2. Configure Elasticsearch in application.properties:

   spring.application.name=FastDataSearch
   spring.data.elasticsearch.cluster-name=FastDataSearchCluster
   spring.data.elasticsearch.cluster-nodes=localhost:9200
   spring.data.elasticsearch.repositories.enabled=true
   
   # Maximum upload file size
   spring.servlet.multipart.max-file-size=100MB
   spring.servlet.multipart.max-request-size=100MB

3. Build the project:

   mvn clean install

4. Run the application:

   mvn spring-boot:run

APIs information

1. Upload dataset (CSV file)

Endpoint: /api/index
Method: POST
Description: Uploads a CSV file and indexes its data into Elasticsearch.

cURL Command:

curl -X POST 'http://localhost:8080/api/index' 
  -H "Content-Type: multipart/form-data" 

select form-data in Body and make a key named file with type File and upload csv in its value.

Response:

{
  "message": "Data ingested successfully",
  "index": "indexName"
}

2. List All Datasets

Endpoint: /api/index
Method: GET
Description: Lists all available datasets (indices) in Elasticsearch.

cURL Command:

curl -X GET 'http://localhost:8080/api/index'

Response:

{
  "datasets": [
    "index1", 
    "index2", 
    "index3"
  ]
}

3. List All Columns

Endpoint: /api/index/{indexName}
Method: GET
Description: Shows the columns (fields) of a specific dataset (index).

cURL Command:

curl -X GET 'http://localhost:8080/api/index/{indexName}'

Response:

{
  "columns": [
    "column1", 
    "column2", 
    "column3"
  ]
}

4. List Full Dataset

Endpoint: /api/index/{indexName}/search
Method: GET
Description: List all the data in associated with an index in Elasticsearch. cURL Command:

curl -X GET 'http://localhost:8080/api/index/{indexName}/search' 

Response:

{
  "results": [
    {
      "column1": "value1",
      "column2": "value2",
      "column3": "value3"
    },
    {
      "column1": "value4",
      "column2": "value5",
      "column3": "value6"
    },
    {
      "column1": "value7",
      "column2": "value8",
      "column3": "value9"
    }
  ]
}

5. Query Dataset

Endpoint: /api/index/{indexName}/search/{query}
Method: GET
Description: Queries a specific dataset (index) with given criteria and returns a list of data satisfying the query.

cURL Command:

curl -X GET 'http://localhost:8080/api/index/{indexName}/search?col1=abc&col2=xyz' 

Response:

{
  "results": [
    {
      "column1": "value1",
      "column2": "value2",
      "column3": "value3"
    },
    {
      "column1": "value4",
      "column2": "value5",
      "column3": "value6"
    }
  ]
}

6. Delete all Indexes

Method: DELETE
Description: delete all the indexes.

cURL Command:

curl -X DELETE 'http://localhost:9200/_all'

Response:

{
  "acknowledged": true
}

7. Delete specific Index

Method: DELETE
Description: delete specific index from the cluster.

cURL Command:

curl -X DELETE 'http://localhost:9200/{indexName}'

Response:

{
  "acknowledged": true
}