Question 50 of 500

Quick Answer

The answer is to increase the TARGET ACCURACY value to 99. This works because TARGET ACCURACY directly controls the trade-off between search speed and result quality; a higher value forces the approximate vector search to examine more candidate vectors during the query phase, thereby improving recall by reducing the chance of missing relevant neighbors. On the Oracle Cloud Infrastructure Generative AI Professional 1Z0-1127 exam, this concept tests your understanding of how vector index parameters balance recall and performance—a common trap is confusing TARGET ACCURACY with neighbor partition settings, which primarily affect index structure rather than query-time candidate depth. A helpful memory tip is to think of TARGET ACCURACY as a "recall dial": turning it up toward 99 tightens the search net, catching more true positives without requiring a full index rebuild.

1Z0-1127 Practice Question: Building LLM Applications with RAG and Vector Search

This 1Z0-1127 practice question tests your understanding of building llm applications with rag and vector search. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.

Exhibit

Refer to the exhibit.

```sql
-- Oracle Database 23ai AI Vector Search index creation
CREATE VECTOR INDEX doc_vec_idx ON documents(chunk_embedding) 
  ORGANIZATION NEIGHBOR PARTITIONS
  DISTANCE COSINE
  WITH TARGET ACCURACY 95
  PARAMETERS (TYPE IVF, NEIGHBOR PARTITIONS 4);
```

A DBA has created the above vector index. After running queries, they observe that recall is lower than expected for approximate searches. Which change would most likely improve recall while maintaining query performance?

Clue words in this question

Noticing these words before you look at the options changes how you read each choice.

  • Clue: "most likely"

    Why it matters: Probability qualifier — the question wants the most probable cause or outcome, not a guaranteed one. Eliminate low-probability options.

Question 1hardmultiple choice
Full question →

Exhibit

Refer to the exhibit.

```sql
-- Oracle Database 23ai AI Vector Search index creation
CREATE VECTOR INDEX doc_vec_idx ON documents(chunk_embedding) 
  ORGANIZATION NEIGHBOR PARTITIONS
  DISTANCE COSINE
  WITH TARGET ACCURACY 95
  PARAMETERS (TYPE IVF, NEIGHBOR PARTITIONS 4);
```

Answer choices

Why each option matters

Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.

Correct answer & explanation

Increase the TARGET ACCURACY value to 99.

Option D is correct because increasing the TARGET ACCURACY parameter forces the index to consider more candidates, improving recall. Option A is wrong because increasing neighbor partitions may improve performance but not necessarily recall. Option B is wrong because changing to HNSW would alter the index type but may require more rebuild. Option C is wrong because reducing neighbor partitions reduces recall.

Key principle: OSPF neighbour adjacency depends on matching area, hello/dead timers, network type, and authentication — IP reachability alone is not enough.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

  • Change the index type from IVF to HNSW.

    Why it's wrong here

    While HNSW generally offers better recall, the question asks for a change within the current index context; TARGET ACCURACY is more direct.

  • Increase the TARGET ACCURACY value to 99.

    Why this is correct

    A higher TARGET ACCURACY forces the approximate search to consider more vectors, increasing recall at the cost of some latency.

    Clue confirmation

    The clue word "most likely" in the question point toward this answer.

    Related concept

    OSPF neighbours must agree on key parameters.

  • Increase the number of neighbor partitions (NEIGHBOR PARTITIONS) to 8.

    Why it's wrong here

    More partitions can improve parallelism but may not directly improve recall; recall is controlled by TARGET ACCURACY.

  • Reduce the number of neighbor partitions to 2.

    Why it's wrong here

    Fewer partitions reduce the search space, likely lowering recall.

Common exam traps

Common exam trap: OSPF can fail even when IP connectivity looks correct

OSPF neighbour formation depends on matching areas, timers, network type, authentication and passive-interface behaviour. Do not choose an answer only because the devices can ping.

Detailed technical explanation

How to think about this question

OSPF questions usually test the details that control adjacency and route selection. Read the neighbour state, area, router ID and interface configuration before deciding what is wrong.

KKey Concepts to Remember

  • OSPF neighbours must agree on key parameters.
  • Router ID selection can affect neighbour relationships and LSDB output.
  • OSPF cost influences the preferred path.
  • A route can appear in OSPF information but not become the installed route.

TExam Day Tips

  • Check area mismatch first when OSPF adjacency fails.
  • Review passive interfaces when a network is advertised but no neighbour forms.
  • Use show ip ospf neighbor and show ip route clues carefully.

Key takeaway

OSPF neighbour adjacency depends on matching area, hello/dead timers, network type, and authentication — IP reachability alone is not enough.

Real-world example

How this comes up in practice

A network engineer at a university connects two campus buildings via a fibre link. Both routers run OSPF, but no adjacency forms — even though both routers can ping each other. The engineer finds one router is in area 0 and the other in area 1. OSPF adjacency requires matching area numbers, hello/dead timers, and network type. IP reachability alone is not enough.

What to study next

Got this wrong? Here's your next step.

Review OSPF neighbour requirements — matching area type, hello and dead timers, network type, stub flags, and authentication. Study show ip ospf neighbor states (INIT, 2-WAY, FULL). Then practise related 1Z0-1127 OSPF questions on adjacency and route selection.

Related practice questions

Related 1Z0-1127 practice-question pages

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FAQ

Questions learners often ask

What does this 1Z0-1127 question test?

Building LLM Applications with RAG and Vector Search — This question tests Building LLM Applications with RAG and Vector Search — OSPF neighbours must agree on key parameters..

What is the correct answer to this question?

The correct answer is: Increase the TARGET ACCURACY value to 99. — Option D is correct because increasing the TARGET ACCURACY parameter forces the index to consider more candidates, improving recall. Option A is wrong because increasing neighbor partitions may improve performance but not necessarily recall. Option B is wrong because changing to HNSW would alter the index type but may require more rebuild. Option C is wrong because reducing neighbor partitions reduces recall.

What should I do if I get this 1Z0-1127 question wrong?

Review OSPF neighbour requirements — matching area type, hello and dead timers, network type, stub flags, and authentication. Study show ip ospf neighbor states (INIT, 2-WAY, FULL). Then practise related 1Z0-1127 OSPF questions on adjacency and route selection.

Are there clue words in this question I should notice?

Yes — watch for: "most likely". Probability qualifier — the question wants the most probable cause or outcome, not a guaranteed one. Eliminate low-probability options.

What is the key concept behind this question?

OSPF neighbours must agree on key parameters.

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Last reviewed: Jun 23, 2026

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