Users report cases where data inaccuracies are present in an AEM component that relies on AEM Search functionality. The AEM platform utilizes Lucene as its main search engine. How should an…

Question

Options

• AAdd search indexes to Lucene search engine
• BChange the search engine to Property Search
• CScale up server resources to meet demands
• DMigrate search engine to an external Solr instance

• A
  81% (44)
• B
  2% (1)
• C
  7% (4)
• D
  9% (5)

Explanation

Adding search indexes to Lucene (A) directly addresses data inaccuracy by ensuring the search index reflects the current state of content in the repository - stale or missing indexes are the most common cause of incorrect search results in AEM. When content changes but the index isn't updated or properly configured, components reading from that index return outdated or incomplete data.

Why the distractors are wrong:

• B (Property Search): Switching to Property Search doesn't fix inaccuracies; it's a different query mechanism but still relies on correct indexing - it doesn't solve the root cause.
• C (Scale up server resources): Data inaccuracy is a logical/indexing problem, not a resource or performance problem. More RAM/CPU won't make wrong data correct.
• D (External Solr): Migrating to Solr is a major architectural change that doesn't inherently fix inaccurate data, and AEM's native Oak indexes (Lucene) are the recommended approach for most use cases.

Memory tip: Think "bad data = bad index." In AEM/Lucene, inaccurate search results almost always trace back to indexes that are missing, misconfigured, or out of sync - so the fix is to fix the index, not swap the engine or throw hardware at it.

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