Elasticsearch Study Notes

Aggregation Performance

Learn what drives aggregation performance in Elasticsearch, doc_values, shard sizing, caching, and approximate algorithms, and how to keep large aggregations f…

Aggregations vs SQL GROUP BY

Compare Elasticsearch's aggregation framework to SQL's GROUP BY and aggregate functions, covering conceptual mapping, execution model differences, and when to…

Analyzers and Tokenizers

See how Elasticsearch breaks raw text into searchable terms using character filters, tokenizers, and token filters.

Bool Queries

How the bool compound query combines must, should, must_not, and filter clauses to express complex search logic in Elasticsearch.

Bucket Aggregations

Understand how Elasticsearch's bucket aggregations group documents by terms, ranges, and dates, and how they nest with metric aggregations for multi-level brea…

Bulk Indexing

Learn how the _bulk API batches index, update, and delete operations into a single request for high-throughput ingestion.

Creating an Index

Learn how Elasticsearch indices are created, configured with shards and replicas, and named for reliable, scalable search.

Dynamic vs Explicit Mapping

Compare Elasticsearch's automatic field-type inference against explicitly defined mappings, and know when to use each.

Elasticsearch Cluster Architecture

How Elasticsearch nodes join together into a cluster, elect a master, and coordinate to store and serve data reliably.

Elasticsearch Interview Questions

Commonly asked Elasticsearch interview topics covering architecture, indexing internals, and querying, with worked explanations.

Elasticsearch Performance Tuning

Practical techniques for tuning indexing throughput, query latency, and resource usage in Elasticsearch.

Elasticsearch Quick Reference

A condensed cheat sheet of core Elasticsearch REST API endpoints, Query DSL patterns, and cluster commands for daily use.

Elasticsearch Security Basics

Core security features of Elasticsearch: authentication, role-based access control, TLS, and audit logging.

Elasticsearch vs Other Search Engines

How Elasticsearch compares to Apache Solr, OpenSearch, Algolia, and database-native search like PostgreSQL full-text search.

Elasticsearch with Kibana

How Kibana pairs with Elasticsearch as the visualization, exploration, and management layer of the Elastic Stack.

Filtering vs Scoring

Why the choice between filter context and query context is a core Elasticsearch performance and relevance decision, not just a syntax preference.

Full-Text Search Relevance and Scoring: TF-IDF & BM25

How Elasticsearch computes the _score for full-text matches, from the classic TF-IDF intuition to the BM25 algorithm used by default today.

Index Lifecycle Management

How Elasticsearch's ILM feature automates moving indices through hot, warm, cold, and delete phases as data ages.

Indices, Documents, and Mappings

How Elasticsearch organizes data into indices and documents, and how mappings define the field types that control indexing and search behavior.

Installing and Running Elasticsearch

How to install, configure, and start a local Elasticsearch node or cluster, including key settings and common startup issues.

Mapping Types Explained

Understand the core Elasticsearch field data types, text vs keyword, numbers, dates, and objects, and how each shapes search behavior.

Match and Term Queries

How Elasticsearch's two most fundamental leaf queries differ: match for analyzed full-text search and term for exact, unanalyzed matching.

Metric Aggregations

Learn how Elasticsearch's metric aggregations compute single- and multi-value numeric summaries like avg, sum, cardinality, and percentiles over matched docume…

Monitoring Elasticsearch

Which metrics, APIs, and alerting practices keep an Elasticsearch cluster healthy and catch problems before they cause outages.