Error Handling
Proper error handling ensures data integrity during bulk indexing. Here’s how you can add error handling to your bulk indexing script:
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 with error handling
try:
helpers.bulk(es, actions)
print("Bulk indexing completed successfully.")
except Exception as e:
print(f"Error during bulk indexing: {e}")
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.
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