Data Indexing: Data indexing in Elasticsearch refers to the process of organizing and optimizing data for efficient searching and retrieval. It involves creating an inverted index that maps terms to their corresponding documents, allowing fast search queries based on keywords or phrases.
Search Queries: In Elasticsearch, search queries are used to retrieve specific documents that match certain criteria. This skill measures the ability to construct complex search queries, including wildcard searches, range queries, full-text searches, and Boolean queries.
Document Retrieval: Document retrieval in Elasticsearch involves efficiently fetching and presenting individual documents or sets of documents stored in the index. This skill showcases the ability to retrieve data based on various criteria, such as document ID, field values, or relevance score.
Aggregations: Aggregations in Elasticsearch allow the computation of summary statistics and insights from indexed data. This skill involves utilizing aggregation functions to create reports, statistical analysis, data visualizations, and faceted navigation.
Cluster Management: Cluster management in Elasticsearch involves the administration and coordination of multiple nodes to handle data distribution, fault tolerance, and scalability. This skill measures the proficiency in tasks like node configuration, index management, shard allocation, and monitoring cluster health.
Data Modeling: Data modeling in Elasticsearch refers to designing the structure and organization of data to optimize search and retrieval performance. This skill assesses the ability to analyze business requirements and create effective mappings, including defining field types, analyzers, and relevance scoring.
Performance Optimization: Performance optimization in Elasticsearch involves tuning various configuration parameters, query optimizations, and indexing strategies to enhance the search and retrieval speed. This skill measures the ability to identify bottlenecks, apply caching techniques, and optimize resource allocation for better system performance.
Monitoring and Troubleshooting: Monitoring and troubleshooting skills in Elasticsearch are essential for identifying and resolving issues related to search queries, data indexing, cluster health, and overall system performance. This skill includes monitoring tools, analyzing logs, and diagnosing errors for efficient problem-solving.
Security: Elasticsearch security focuses on protecting the cluster and its data from unauthorized access, data breaches, and other security threats. This skill evaluates the knowledge of implementing authentication, authorization, encryption, and securing network communication in Elasticsearch.
Scaling and Distribution: Scaling and distribution skills in Elasticsearch involve managing data growth, horizontal scaling of the cluster, and distributing data across multiple nodes for high availability and fault tolerance. This skill measures the ability to configure and manage shards, replica shards, and handle data rebalancing.
Integration with Other Systems: Integration skills in Elasticsearch involve connecting and interoperating with different systems and tools like database systems, messaging queues, APIs, and visualization tools. This skill assesses the ability to synchronize data, perform bi-directional data transfers, and utilize Elasticsearch for diverse use cases within an ecosystem.
