ElasticSearch Interview Simulator – Practice Questions with Answers and Scoring
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Top ElasticSearch Interview Questions for Freshers and Experienced Developers
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1
Explain how ElasticSearch stores and indexes documents internally.
mediumindexingcore
Answer
ElasticSearch uses inverted indices to map terms to documents. Each document is stored as JSON and broken into tokens using analyzers.
Key concept: Inverted index enables fast full-text search.
Example: 'hello world' → tokens 'hello', 'world'.
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2
What is the difference between a shard and a replica in ElasticSearch?
easyshardingreplication
Answer
A shard is a partition of an index, while a replica is a copy of a shard for fault tolerance.
Key concept: Shards scale horizontally; replicas improve availability.
Example: 1 shard + 1 replica = 2 copies.
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3
How does ElasticSearch achieve near real-time search?
mediumnrtindexing
Answer
It uses refresh intervals to make indexed documents searchable without full commit.
Key concept: Refresh creates a new searcher.
Default refresh is ~1 second.
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4
What happens when a node holding the primary shard fails?
mediumfailoverreplication
Answer
A replica shard is promoted to primary automatically.
Key concept: High availability via replication.
Cluster rebalances after failure.
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5
Explain the role of analyzers in ElasticSearch.
mediumanalysistext
Answer
Analyzers process text into tokens using tokenizer and filters.
Key concept: Determines how text is indexed and searched.
Example: Lowercase filter normalizes tokens.
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6
What is the difference between keyword and text data types?
easymappingdatatype
Answer
Text is analyzed for full-text search; keyword is not analyzed.
Key concept: Keyword is used for exact match, sorting, aggregations.
Example: 'USA' vs tokenized 'u','s','a'.
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7
How do you handle a mapping conflict in ElasticSearch?
hardmappingdebugging
Answer
Mapping conflicts occur when field types differ.
Key concept: Reindex data with corrected mapping.
Example: string vs integer mismatch.
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8
What is the purpose of the _source field?
mediumstoragesource
Answer
It stores the original JSON document.
Key concept: Enables reindexing and retrieval.
Can be disabled to save space.
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9
Explain the difference between query and filter context.
mediumqueryperformance
Answer
Query context scores results; filter context does not.
Key concept: Filters are faster and cached.
Example: filter for exact match conditions.
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10
How does ElasticSearch scoring work?
hardscoringbm25
Answer
Uses TF-IDF or BM25 algorithm.
Key concept: Relevance scoring based on term frequency and rarity.
Example: Rare terms get higher score.
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11
What is a refresh interval and how does it affect performance?
mediumperformanceindexing
Answer
Defines how often index becomes searchable.
Key concept: Lower interval = faster visibility but higher overhead.
Example: set to -1 for bulk indexing.
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12
What is reindexing and when is it required?
mediumreindexmapping
Answer
Reindexing copies data into a new index.
Key concept: Needed for mapping changes.
Example: changing field type.
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13
How would you design ElasticSearch for high write throughput?
