This guide walks through the most important Elasticsearch commands, covering cluster health checks, index listing, creation with mappings, deletion, mapping inspection, document insertion (with and without IDs), various query types, updates, deletions, pagination, sorting, and bulk operations, each illustrated with concrete examples and usage notes.
A storage audit of an Easysearch cluster revealed that overly generic field mappings caused the index to bloat to 500‑600 GB, and by correcting two mapping mistakes—using text + autocomplete only where needed and storing numeric IDs as long types—the index size shrank by over 200 GB, roughly one‑third, without data loss or functional changes.
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.
When legacy or sensitive fields bloat an Elasticsearch index, rebuilding the index with reindex can be costly, so this article examines why fields cannot be removed directly and presents four practical, non‑reindex approaches—_source filtering, index templates, ingest pipelines, and alias‑based gradual migration—detailing their trade‑offs and implementation steps.
This article provides a comprehensive guide to Elasticsearch index architecture, covering fundamental concepts, index mapping, field types, alias usage, shard and replica strategies, shard planning, resource impact, and practical recommendations for optimizing performance and stability in production environments.
This article provides a comprehensive guide to Elasticsearch index concepts, covering index definitions, alias usage, mapping and field types, shard architecture, and practical recommendations for planning shards and optimizing resource consumption to ensure stable and efficient ES clusters.
This article presents the technical background of SLAM, explains why GNSS‑based navigation fails in complex urban environments, describes the selection and testing of several LiDAR‑IMU SLAM algorithms—including FAST‑LIO2—on Qiji unmanned vehicles, and details the hardware configuration, algorithmic improvements, experimental workflow, and positioning results achieved in a real‑world patrol project.
The article explains Elasticsearch indexes as logical namespaces for JSON documents, details how mappings define immutable field types such as text, keyword, and numeric, describes primary and replica shard roles, and offers practical guidance on alias usage, shard sizing, replica settings, and performance optimizations to ensure cluster stability.
This guide explains Elasticsearch's mapping concepts, compares dynamic and static mappings, and demonstrates how to choose between Array, Flattened, and Nested field types with concrete code examples, performance trade‑offs, and practical recommendations for real‑world business systems.
An insider reveals that Gaode Maps' traffic‑light countdown and green‑wave speed suggestions are generated by a proprietary algorithm—supported by a recent patent—rather than direct real‑time signal data, highlighting the role of big‑data analytics in modern navigation.
This article demonstrates how to create detailed terrain maps in Python by installing and importing rasterio, geopandas, cartopy, and related libraries, configuring map fonts, and executing a comprehensive script that reads vector and raster data, applies custom color maps, and renders the final visualization.
Gaode Technology’s 2023 roundup showcases fifteen of its most-read articles, spanning AI infrastructure evolution, cloud‑native data optimization, BEV‑based perception, real‑time crowdsourced mapping, ETA prediction, lane‑level navigation, AR HUD, architecture design, low‑code platforms, and high‑performance Android testing.
The article presents a front‑end API management approach that organizes CRUD functions into unified export statements, object‑oriented modules, and a central mapping table, demonstrating how these patterns improve code readability, maintainability, and development efficiency for large backend‑driven projects.
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 comprehensive guide explains what Elasticsearch does, its underlying Lucene technology, core concepts such as clusters, shards, replicas, mapping, indexing and storage mechanisms, and provides practical performance‑tuning advice for building and operating a robust distributed search engine.
This article provides a comprehensive overview of UAV‑based oblique photogrammetry for real‑world 3D modeling, detailing background, step‑by‑step field capture, control‑point handling, aerial triangulation, model reconstruction, internal processing, and emerging trends in smart‑city applications.
This guide walks you through the full Elasticsearch data‑modeling workflow, covering business‑driven design, handling large data volumes, optimal settings, mapping choices, and complex parent‑child relationships, while providing practical code examples and visual diagrams for immediate application.
This article explains what mapping explosion is in Elasticsearch, why it hurts performance and memory, and presents three practical solutions—strict, false, and runtime dynamic settings—along with code examples and trade‑off discussions.
This article surveys twenty data‑visualization tools—covering entry‑level options like Excel, online JavaScript libraries such as D3 and Google Chart API, interactive GUI utilities, map frameworks, advanced desktop environments, and expert‑grade platforms like R, Weka and Gephi—highlighting their key features, formats supported and typical use cases.
This article introduces the Python library Folium, explains its installation, demonstrates basic map creation, marker and shape addition, and presents a practical case of visualizing parking lot geolocation data with interactive features and clustering, providing code snippets and usage guidance.
This tutorial shows how to import the required OpenLayers modules into a Vue project, configure a map, add a Polygon draw interaction, handle the drawend event to compute and format the polygon's area using OpenLayers' getArea function, and provides a complete working example with code.
This guide shows how to load a GeoServer TileWMS layer in a Vue app with OpenLayers, configure map and line layers, add a selectable draw interaction for LineString geometry, capture drawn coordinates, and provides a complete Vue component example.
This tutorial walks through importing OpenLayers modules into a Vue component, defining line coordinates, creating vector sources and layers, styling the line, and integrating the line layer with other map layers to render a green polyline on the map.
This comprehensive guide explains Elasticsearch index design, covering shard and replica planning, settings optimization, dynamic and static mappings, template management, lifecycle automation, and practical best‑practice recommendations for high‑performance, stable search clusters.
This article provides a detailed guide on Elasticsearch index design, covering index settings, shard and replica planning, mapping strategies, complex types, lifecycle management, template usage, and practical best‑practice recommendations for large‑scale log data clusters.
This guide walks you through creating, viewing, updating, and deleting Elasticsearch indices, documents, and mappings using RESTful HTTP methods, complete with example requests, JSON bodies, and visual illustrations for each operation.
This article introduces Grafana v8.1’s Geomap panel, detailing its multiple base‑layer options, enhanced custom markers, heatmap layer, flexible data‑layer mappings, and a new sharing feature that lets several map panels synchronize on a single dashboard.
GPS‑based time synchronization aligns camera, LiDAR, and inertial sensor streams in mapping vehicles by using the satellite‑derived Pulse‑Per‑Second signal and NMEA data to correct the MCU’s clock, handle PPS‑crystal and PPS‑NMEA anomalies, and provide sub‑microsecond timestamps for precise sensor fusion.
This tutorial explains how to convert a physical address into latitude‑longitude coordinates using the Baidu Maps Geocoding API and then visualize the point on a map with Python's pyecharts library, including code snippets and step‑by‑step instructions.
This guide walks through using Elasticsearch 7.8.0 and Postman to create, view, update, and delete indices and documents via RESTful API calls, including mapping setup and query‑based deletions, providing clear code examples and request details.
This article provides a comprehensive overview of Elasticsearch, covering its distributed architecture, fundamental concepts such as nodes, shards, and indices, as well as practical guidance on index design, bulk writing, query‑fetch workflow, scroll queries, aliases, and basic optimization tips.
This article explains how to define Elasticsearch mappings, use automatic and manual mapping, work with basic data types, multi‑fields and predefined fields, and perform document updates, version‑based concurrency control, and deletions, providing practical curl examples for each operation.
This article provides a detailed collection of basic Elasticsearch interview questions and answers, covering core concepts such as cluster and node architecture, indexing, mapping, search APIs, analyzers, tokenizers, aggregation, security, and operational tools, along with practical code snippets for common tasks.
The article offers a thorough, step‑by‑step guide to Elasticsearch, explaining how to check cluster health, create and manage indices, define mappings and field types, use dynamic mapping, and perform maintenance tasks such as shrink, split, rollover, and cache management, all illustrated with concrete API examples.
In a 2020 Cloud Expo session, Alibaba Amap’s senior map expert Wang Qianwei detailed the evolution and practice of AR‑enabled lane‑level navigation, explaining how real‑time visual perception, cloud‑integrated high‑precision positioning (including MT‑SLAM) and fine‑grained 3‑D road models combine to deliver video‑augmented guidance, lane‑change alerts and traffic‑light status with roughly 30 cm accuracy.
This guide walks through essential Elasticsearch operations, covering cluster health checks, creating and querying indices, managing settings, templates, aliases, index shrink, split, rollover, and detailed mapping definitions, providing practical code examples for each step.
This article explains how well‑designed product categories serve as the backbone of an e‑commerce platform, covering the concepts of backend and frontend categories, the construction of category trees, and various mapping strategies that help both users find items quickly and operators manage large inventories efficiently.
This article introduces Elasticsearch by explaining its core concepts such as indices, types, documents, mappings, and Query DSL, demonstrates common use cases, and provides step‑by‑step instructions for creating, updating, viewing, and deleting indices and documents using RESTful APIs, curl commands, and Docker‑compose deployment.
This article provides a comprehensive guide on designing Elasticsearch indices for massive data volumes, covering shard and replica sizing, mapping strategies, rollover templates, curator cleanup, tokenization choices, query type selection, and multi‑table association techniques to achieve efficient, reliable search at PB‑scale.
This article provides a comprehensive overview of ElasticSearch, covering its distributed architecture, fundamental components such as nodes, shards, and indices, as well as practical guidance on index design, mapping, bulk operations, query processing, scroll searches, alias management, and performance tuning tips.
This article explains how Amap leverages computer vision to collect, process, and enhance map data and to deliver low‑cost, real‑time AR navigation, detailing the technical challenges, algorithmic solutions, and the broader mission of connecting the physical world.
Didi Maps' chief engineer explains how the team tackled weak GPS signals in large indoor venues by building a 60,000‑square‑meter 3D map, achieving sub‑0.5 m monocular visual localization, and fusing inertial data with Google ARCore to deliver real‑time AR navigation on Android devices.
This article explains how a conventional vehicle can be progressively upgraded through hardware retrofits, sensor integration, mapping, perception, control, and planning modules to achieve SAE Level 4/5 autonomy, using a step‑by‑step analogy with driver training and iterative testing.
This article explains Elasticsearch mapping, covering dynamic mapping, field datatypes, meta‑fields, mapping parameters, and dynamic templates, while emphasizing the importance of careful schema design and the need for reindexing when changes are required.
The Didi Tech Seminar showcased how AI—through DeepMotion’s mapping solutions, Sogou’s NLP‑enhanced search, and advanced computer‑vision techniques—augments Didi’s core map engine for ETA estimation, route planning, and dynamic pickup/drop‑off updates, while addressing integration challenges between AI models and traditional mapping algorithms.
At WGDC 2018, Didi’s mapping division revealed how its AI‑driven platform leverages massive real‑time travel data, machine‑learning and deep‑learning models—including a new ETA estimator, demand‑supply forecasting, and reinforcement‑learning order allocation—to deliver ultra‑accurate pick‑up points, route planning, and destination predictions, while opening de‑identified data and research topics to academia.
The article explains how ProGuard’s incremental obfuscation using –applymapping can cause mapping conflicts when previously assigned method names are overwritten, producing warnings and inconsistent names such as ‘c_’, and details the internal workflow, inline handling, and practical steps to diagnose and resolve these issues.
This article provides a comprehensive overview of 56 data visualization tools ranging from simple spreadsheet options to advanced JavaScript libraries, mapping frameworks, and statistical packages, helping developers choose the right solution for creating interactive and insightful visual representations of their data.
