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You want to run a very expensive aggregation query on a large dataset without timing out. Which approach using async search is best to get the final results efficiently?

hard🚀 Application Q15 of Q15

Elasticsearch - Advanced Patterns

You want to run a very expensive aggregation query on a large dataset without timing out. Which approach using async search is best to get the final results efficiently?

ARun a normal search with a very high <code>timeout</code> value to wait for results.

B

Start async search with a long <code>wait_for_completion_timeout</code> and poll using the returned <code>id</code> until results are ready.

CStart async search and immediately request results without waiting for completion.

DRun the query multiple times with smaller timeouts and merge results manually.

Step-by-Step Solution

Solution:

Step 1: Understand async search timeout and polling
Setting a reasonable wait_for_completion_timeout lets the server try to finish quickly but returns control if it takes longer.
Step 2: Use the returned id to poll for completion
You can check the status later using the id until the results are ready, avoiding timeouts and blocking.
Final Answer:
Start async search with a long wait_for_completion_timeout and poll using the returned id until results are ready. -> Option B
Quick Check:
Async search + polling = efficient for expensive queries [OK]

Quick Trick: Use wait_for_completion_timeout + poll with id for big queries [OK]

Common Mistakes:

MISTAKES

Using normal search with high timeout risking app freeze
Requesting results immediately before completion
Manually merging partial results instead of async search

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