Here are top Elasticsearch interview questions,
1. What is Elasticsearch?
Elasticsearch
is a distributed, open-source search and analytics engine built on top of
Apache Lucene. It is used for full-text search, real-time data analysis, and
data visualization.
2. How does Elasticsearch store and
index data?
Elasticsearch
stores data in JSON format and indexes it using inverted indices, which enable
fast searching and retrieval of documents based on various criteria.
3. How do you install Elasticsearch?
The
installation process depends on your operating system. For Linux-based systems,
you can download and install Elasticsearch using package managers like `apt` or
`yum`. For macOS and Windows, you can download and install Elasticsearch using
the official distribution.
4. How do you start and stop
Elasticsearch?
To start
Elasticsearch, run the `elasticsearch` executable. To stop Elasticsearch, send
a `SIGTERM` signal to the Elasticsearch process.
5. What is a cluster in
Elasticsearch?
A cluster
in Elasticsearch is a collection of one or more nodes (servers) that work
together to store and manage data. Each cluster has a unique name.
6. How do you create an index in
Elasticsearch?
To create
an index, you can use the `PUT` request with the desired index name:
```
PUT /index_name
```
7. How do you insert data into
Elasticsearch?
You can
insert data into Elasticsearch using the `index` API:
```
POST /index_name/_doc/document_id
{
"field1":
"value1",
"field2":
"value2",
...
}
```
8. What is the difference between a
document and a mapping in Elasticsearch?
A document
is a unit of data that can be indexed and searched, while a mapping defines the
data structure and field properties for documents in an index.
9. How do you perform a basic search
in Elasticsearch?
You can
perform a basic search using the `search` API:
```
GET /index_name/_search
{
"query": {
"match": {
"field":
"value"
}
}
}
```
10. What are the common types of
queries in Elasticsearch?
Elasticsearch
supports various types of queries, including match, term, range, bool,
wildcard, and more, allowing for complex searches and aggregations.
11. How do you perform aggregations
in Elasticsearch?
Aggregations
in Elasticsearch are performed using the `aggs` parameter in the `search` API,
allowing you to compute summaries and statistics on data.
12. What is the purpose of analyzers
in Elasticsearch?
Analyzers
are used to preprocess text data during indexing and querying, enabling tasks
like tokenization, stemming, and stopword removal.
13. How can you perform a full-text
search in Elasticsearch?
Full-text
search in Elasticsearch is achieved using the `match` query, which analyzes the
search query and matches relevant documents.
14. What is the role of shards in
Elasticsearch?
Elasticsearch
uses sharding to split data into smaller units for distributed storage and
parallel processing, improving performance and scalability.
15. How do you update data in
Elasticsearch?
To update
data in Elasticsearch, use the `update` API with the `doc` parameter:
```
POST /index_name/_update/document_id
{
"doc": {
"field": "new_value"
}
}
```
16. What is the purpose of the
`_source` field in Elasticsearch?
The
`_source` field stores the original JSON document that was indexed, allowing
you to retrieve the full document when querying.
17. How do you handle pagination in
Elasticsearch?
Pagination
in Elasticsearch can be achieved using the `from` and `size` parameters in the
`search` API, which control the starting index and the number of results to
return.
18. What is a filter in
Elasticsearch?
A filter in
Elasticsearch is used to narrow down the result set based on specific criteria
without affecting the relevance scoring of the documents.
19. How can you create a mapping for
an index in Elasticsearch?
You can
create a mapping using the `PUT` request with the desired index name and the
mapping definition:
```
PUT /index_name
{
"mappings": {
"properties": {
"field": {
"type":
"text"
}
}
}
}
```
20. What is the purpose of replicas
in Elasticsearch?
Replicas
are duplicate copies of index shards, providing data redundancy and high
availability in case of node failures.
Above are few top Elasticsearch interview questions. Remember to prepare and expand on these answers.
Good luck with your interview! 👍
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