How to use the Bulk API with Python In Databases
Step 1: Installing Required Libraries
Ensure you have the elasticsearch library installed:
pip install elasticsearch
Step 2: Writing the Bulk Indexing Script
Create a Python script to perform bulk indexing.
from elasticsearch import Elasticsearch, helpers
# Elasticsearch connection
es = Elasticsearch(["http://localhost:9200"])
# Prepare bulk data
actions = [
{ "_index": "myindex", "_id": "1", "_source": { "name": "John Doe", "age": 30, "city": "New York" } },
{ "_index": "myindex", "_id": "2", "_source": { "name": "Jane Smith", "age": 25, "city": "San Francisco" } },
{ "_index": "myindex", "_id": "3", "_source": { "name": "Sam Brown", "age": 35, "city": "Chicago" } },
]
# Perform bulk indexing
helpers.bulk(es, actions)
Step 3: Running the Script
Run the Python script:
python bulk_indexing.py
Output:
The documents will be indexed into Elasticsearch. You can verify this by querying Elasticsearch:
curl -X GET "http://localhost:9200/myindex/_search?pretty"
The response should show the indexed documents.
Using the Elasticsearch Bulk API for High-Performance Indexing
Elasticsearch is a powerful search and analytics engine designed to handle large volumes of data. One of the key techniques to maximize performance when ingesting data into Elasticsearch is using the Bulk API. This article will guide you through the process of using the Elasticsearch Bulk API for high-performance indexing, complete with detailed examples and outputs.