Before you can ingest data into Elasticsearch, you need to have it set up and running. Download the Elasticsearch package from the official website and follow the installation instructions for your operating system. Once installed, start the Elasticsearch service and ensure it is running by accessing `http://localhost:9200` in your web browser. You should see a JSON response confirming it is active.

Ensure your JSON file is properly formatted for Elasticsearch. Each line in the file should represent a single JSON object. This is known as the "newline-delimited JSON" format. If your data is not already in this format, you may need to write a script to convert it.

An index in Elasticsearch is similar to a database in a relational database system. Use the Elasticsearch REST API to create an index that will store your data. You can do this by sending a PUT request to `http://localhost:9200/your_index_name` using tools like `curl` or Postman. Optionally, you can define mappings for your fields to specify data types.

```bash
curl -X PUT "localhost:9200/your_index_name"
```

Use Python's built-in JSON library to read your JSON file. Open the file in read mode and load the data using `json.load()` if it’s a single JSON object, or read line-by-line if it’s newline-delimited.

```python
import json

with open('data.json', 'r') as file:
data = file.readlines()
```

Use Python's `requests` library to send HTTP requests to Elasticsearch. For each JSON object, make a POST request to the Elasticsearch `_bulk` API endpoint to efficiently upload multiple records.

```python
import requests

headers = {'Content-Type': 'application/json'}

bulk_data = ""
for line in data:
json_data = json.loads(line)
bulk_data += '{"index": {}}\n' + json.dumps(json_data) + '\n'

response = requests.post('http://localhost:9200/your_index_name/_bulk', headers=headers, data=bulk_data)

if response.status_code == 200:
print("Data uploaded successfully!")
else:
print("Failed to upload data: ", response.content)
```

After uploading your data, verify that it was ingested correctly. You can do this by querying your index using the Elasticsearch REST API. Send a GET request to `http://localhost:9200/your_index_name/_search` to see the documents stored in the index.

```bash
curl -X GET "localhost:9200/your_index_name/_search?pretty"
```

Check for any errors during the bulk upload process by examining the response from Elasticsearch. If there are errors, they will be detailed in the response content. Optimize bulk uploads by adjusting the size of each batch to fit within network and memory constraints, typically between 5MB and 15MB per request. Adjust your script accordingly to handle large datasets efficiently.

By following these steps, you can effectively move data from a JSON file to Elasticsearch without relying on third-party connectors or integrations.