This guide walks through five systematic checks—indexing delay vs refresh, thread‑pool rejections, segment merges and I/O, bulk size and refresh settings, and mapping/_source configuration—to pinpoint and resolve Elasticsearch write‑performance bottlenecks.
When Elasticsearch Bulk API reports successful writes and Count shows documents, but Search and Get return empty _source, a six‑hour investigation reveals the root cause is a disabled _source mapping and provides a step‑by‑step debugging checklist and fix.
elasticdumpWeb is a web‑based utility that automates cross‑cluster index migration between Elasticsearch (including version 9.0.0) and Easysearch, handling version compatibility, field type conversion, data validation, performance tuning, and SSL issues while providing visual progress and detailed reports.
This article walks through a real‑world case where syncing over 12 million records to Elasticsearch stalled, analyzes memory pressure, thread‑pool limits, and Netty I/O logs, and then presents concrete configuration tweaks, batch‑by‑time‑slice loading, DSL bulk‑API adjustments, and cluster‑health monitoring that reduced the import time to about two hours.
This comprehensive guide introduces Elasticsearch’s core concepts, installation, REST API operations, and practical examples of indexing, updating, deleting, bulk processing, searching, filtering, and aggregations, helping readers build scalable, near‑real‑time search and analytics solutions for diverse use cases.
This guide explains how to optimize Elasticsearch 7.8 performance by adjusting the refresh interval, replica count, JVM heap settings, bulk API usage, storage devices, mapping design, and query patterns, providing practical commands and visual examples for each step.
This tutorial explains how to install and configure Elasticsearch and Kibana, demonstrates CRUD operations, bulk data import, and shows how to use Logstash to ingest, transform, and index flight JSON data, covering both batch and near‑real‑time processing techniques.
Didi’s engineering team analyzed a severe write bottleneck in their 3000‑node Elasticsearch cluster, identified long‑tail latency caused by refresh, translog locks, write queues and GC, and applied routing‑aware bulk writes, JVM and Lucene tweaks, and data cleaning to more than double write throughput while slashing server costs.
After setting up an ES cluster, this guide shows how to use cURL to inspect node and master status, query cluster health, perform CRUD operations, manage indices, execute bulk actions, and run multi‑search queries, complete with example commands for both Kibana and Bash.
This article introduces Elasticsearch as a distributed search and analytics engine, outlines its common application scenarios, provides step‑by‑step installation commands, explains core concepts such as documents and indices, and demonstrates basic indexing, retrieval, bulk processing, and aggregation operations.
This article explains how to dramatically improve Elasticsearch throughput by using the bulk API, tuning bulk request sizes, configuring gateway settings, optimizing cluster state updates, managing caches, leveraging fielddata and doc values, and employing tools like Curator and the Profiler for efficient cluster operations.
Part 3 of the Elasticsearch indexing optimization guide advises balancing shard and replica counts, using index aliases, leveraging the Bulk API with appropriately sized batches, dedicating data nodes, and upgrading storage (SSD/RAID 0) while monitoring resources to achieve higher throughput and scalable, reliable clusters.
