This search is the most efficient because it filters data at the earliest possible stage. By combining the two data sources with a boolean OR and including the specific field-value pairs (status=200, uri=/cart/checkout) directly in the base search, it minimizes the amount of data retrieved from the indexers. This approach ensures only the relevant events are processed by the subsequent stats command, significantly reducing search time and resource consumption compared to alternatives that use less efficient commands or delayed filtering.

A. The append command is less efficient than using OR because it runs a secondary search, adding unnecessary processing overhead to combine the datasets.

C. This is extremely inefficient as it retrieves all events from index=www before appending, processing a much larger dataset than necessary.

D. This search is redundant. It retrieves all data from both indexes first and then filters, which is significantly less efficient than filtering in the base search.

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1. Splunk Enterprise Documentation, Search Manual, "Write better searches": This official guide explicitly states as a best practice: "Filter as early as possible." and "Include time and index filters at the beginning of your search." Option B adheres to this by placing index= and other filtering terms at the start. The guide also advises, "Use the OR operator instead of the append command," which directly contrasts with the inefficient method used in option A. (See section: "Search best practices").

2. Splunk Enterprise Documentation, Search Reference, "append": The documentation for the append command notes its usage and performance characteristics. It is a results-manipulation command that runs after the initial search completes, often involving a resource-intensive subsearch. For simply combining events from different sources for statistical analysis, a single base search with OR is more performant. (See section: "Usage").

3. Splunk Enterprise Documentation, Search Reference, "search": The search command documentation clarifies that the base search (the part before the first pipe) is the most critical for performance. Applying filters in the base search allows the indexers to discard non-matching events. Piping to a second search command, as in option D, forces the search head to process a larger-than-necessary dataset, which is inefficient. (See section: "Description").