Paging and Sorting, ElasticSearch Flashcards
What is Elasticsearch?
Elasticsearch is a distributed search and analytics engine built on top of Apache Lucene. It’s designed for horizontal scalability, reliability, and real-time search
What is Apache Lucene?
Apache Lucene is a high-performance, full-featured text search engine library written in Java. Elasticsearch builds upon Lucene’s capabilities to provide distributed search and analytics.
What are the key features of Elasticsearch?
Distributed and scalable architecture
Near real-time search and analytics
Full-text search capabilities
Support for structured and unstructured data
RESTful API for easy integration
Powerful query DSL (Domain Specific Language)
What is a cluster in Elasticsearch?
A cluster in Elasticsearch is a collection of one or more nodes (servers) that together holds your entire data and provides federated indexing and search capabilities across all nodes.
What is a node in Elasticsearch?
A node is a single server that is part of your Elasticsearch cluster, storing data and participating in the cluster’s indexing and search capabilities.
What is an index in Elasticsearch?
An index in Elasticsearch is similar to a database in the relational database world. It is a collection of documents that have somewhat similar characteristics.
What is a document in Elasticsearch?
A document is a basic unit of information that can be indexed. It is expressed in JSON (JavaScript Object Notation) format and consists of field-value pairs.
What is a shard in Elasticsearch?
A shard is a subset of documents from an index. Elasticsearch divides an index into multiple shards to distribute data across multiple nodes and to achieve horizontal scalability.
What is a replica in Elasticsearch?
A replica is a copy of a shard. Elasticsearch creates replicas to provide high availability and failover mechanisms. Replicas also help to distribute search load across multiple nodes.
What is a query DSL in Elasticsearch?
Query DSL (Domain Specific Language) is a powerful JSON-based query language used in Elasticsearch to define various search queries and filters. It allows for complex queries to be constructed easily.
What is the purpose of an analyzer in Elasticsearch?
An analyzer is responsible for processing the text of fields in documents during indexing and search operations. It breaks down text into individual terms or tokens and applies various transformations like stemming, lowercase conversion, and removing stop words.
What are the three main types of analyzers in Elasticsearch?
Standard analyzer
Custom analyzer
Language-specific analyzer (e.g., English analyzer, French analyzer)
What is a token filter in Elasticsearch?
A token filter is a component of the analyzer that processes individual tokens generated from the text. It applies additional transformations such as lowercase conversion, stemming, synonym expansion, and stop word removal.
What is a mapping in Elasticsearch?
A mapping defines the fields and properties of documents in an index, including their data types, analyzers, and other settings. It provides the schema for the documents stored in the index.
What are dynamic mappings in Elasticsearch?
Dynamic mappings in Elasticsearch allow the index to automatically detect and create mappings for new fields in incoming documents. Elasticsearch infers the data type and other properties based on the content of the document.
What is relevance scoring in Elasticsearch?
Relevance scoring is the process of determining the relevance of documents to a given search query. Elasticsearch calculates a relevance score for each document based on factors like term frequency, inverse document frequency, and field length normalization.
What is a term query in Elasticsearch?
A term query is a type of query used to search for documents that contain an exact term or phrase in a specific field. It matches documents where the field value exactly matches the specified term.
What is a match query in Elasticsearch?
A match query is a type of query used to search for documents that contain a specified term or phrase in any field. It analyzes the query string and performs a full-text search across all indexed fields.
What is a filter in Elasticsearch?
A filter in Elasticsearch is used to narrow down search results based on specific criteria. It does not affect the relevance score of documents but only determines whether a document matches the filter conditions.
What is the role of the inverted index in Elasticsearch?
The inverted index is a data structure used by Elasticsearch to facilitate fast full-text search. It maps terms to the documents that contain them, enabling efficient retrieval of documents containing specific terms.
What are OFFSET and LIMIT in SQL queries used for?
OFFSET and LIMIT are used for pagination in SQL queries. OFFSET specifies the number of rows to skip before starting to return rows, while LIMIT specifies the maximum number of rows to return.
What is Elasticsearch?
Elasticsearch is a distributed, RESTful search and analytics engine designed for horizontal scalability, reliability, and real-time search capabilities. It is commonly used for log analytics, full-text search, and monitoring applications.
What is the purpose of OFFSET and LIMIT in Elasticsearch queries?
OFFSET and LIMIT are used for pagination in Elasticsearch queries. OFFSET specifies the number of results to skip before starting to return documents, while LIMIT specifies the maximum number of documents to return in the result set.
What is sharding in Elasticsearch?
Sharding in Elasticsearch is the process of dividing an index into multiple smaller index segments called shards, allowing data to be distributed across multiple nodes in a cluster for scalability and performance.
