Bulk indexing optimization in Elasticsearch - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is bulk indexing in Elasticsearch?

Bulk indexing is a method to send multiple indexing or update requests in a single API call to Elasticsearch, improving speed and reducing overhead.

beginner

Why is it important to optimize bulk indexing?

Optimizing bulk indexing reduces network overhead, improves throughput, and prevents cluster overload, leading to faster and more reliable data ingestion.

intermediate

What is a good practice for choosing the bulk request size?

Choose a bulk size that balances memory use and speed, typically between 5MB to 15MB or 1000 to 5000 documents per bulk request, depending on your cluster capacity.

intermediate

How can you handle failures during bulk indexing?

Check the bulk API response for errors, retry failed items selectively, and implement exponential backoff to avoid overwhelming the cluster.

intermediate

What role does refresh interval play in bulk indexing optimization?

Temporarily increasing the refresh interval or disabling automatic refresh during bulk indexing reduces overhead and improves indexing speed.

What is the main benefit of using bulk indexing in Elasticsearch?

A Increasing the number of shards

B Reducing the number of network calls

C Improving query speed

D Decreasing disk space usage

Bulk indexing reduces network overhead by sending many documents in one request.

Which bulk request size is generally recommended for optimal performance?

A 1 document per request

B Less than 100 bytes

C More than 100MB

D 5MB to 15MB or 1000 to 5000 documents

A bulk size of 5MB to 15MB or 1000 to 5000 documents balances speed and memory use.

How should you handle errors returned by the bulk API?

A Retry only failed documents with backoff

B Retry all documents regardless

C Ignore them and continue

D Stop indexing immediately

Retrying only failed documents with exponential backoff prevents overload and ensures data consistency.

What happens if you disable automatic refresh during bulk indexing?

A Indexing speed improves

B Search results update immediately

C Cluster memory usage decreases

D Documents are lost

Disabling refresh reduces overhead, allowing faster indexing.

Which of the following is NOT a bulk indexing optimization technique?

A Using bulk API instead of single requests

B Choosing an appropriate bulk size

C Indexing documents one by one

D Increasing refresh interval during indexing

Indexing documents one by one is inefficient and not an optimization.

Explain how to optimize bulk indexing in Elasticsearch for better performance.

Think about request size, error handling, and refresh settings.

Describe the steps to handle failures during bulk indexing in Elasticsearch.

Focus on error detection and retry strategy.