(A high-volume source and a low-volume source feed into the same index. Which of the following items best describe the impact of this design choice?)

Question

Options

• ALow volume data will improve the compression factor of the high volume data.
• BSearch speed on low volume data will be slower than necessary.
• CLow volume data may move out of the index based on volume rather than age.
• DHigh volume data is optimized by the presence of low volume data.

Explanation

C is correct. In platforms like Splunk, data within a shared index is organized into buckets that age through lifecycle states (hot → warm → cold → frozen/deleted). Retirement is triggered by either time or size limits. When a high-volume source shares an index, it causes buckets to hit size thresholds rapidly - forcing low-volume data out of the index prematurely, based on volume rather than its actual age or retention needs.

Why the distractors are wrong:

• A is false - mixing sources of different volumes has no meaningful effect on compression ratios; compression depends on data type and encoding, not co-tenant volume.
• B is a plausible concern (shared indexes can slow searches), but it's not the primary or most impactful problem described by this design - and it's less precise than C.
• D is the opposite of true; the high-volume source negatively impacts the low-volume data's lifecycle, not the other way around.

Memory tip: Think of a shared bucket like a shared elevator - when a crowd (high-volume data) packs it full, the few quiet passengers (low-volume data) get carried to a floor they didn't intend to reach, sooner than they wanted. Volume drives the ride, not time.

No community discussion yet for this question.