elasticsearch

name	elasticsearch
description	Guides Elasticsearch usage including index mapping design, query DSL (match, term, bool, aggregations), bulk indexing, cluster management, and performance tuning. Use when the user needs to implement full-text search, design index mappings, write complex search queries, or manage Elasticsearch clusters.
license	Complete terms in LICENSE.txt

When to use this skill

Use this skill whenever the user wants to:

• Design index mappings with analyzers and field types
• Write search queries (match, term, bool, multi_match, nested, aggregations)
• Index, update, or bulk-load documents via the REST API
• Manage clusters (shards, replicas, snapshots, upgrades)
• Integrate Elasticsearch with Kibana or Logstash (ELK stack)

How to use this skill

Workflow

1. Design the mapping - Define field types, analyzers, and index settings
2. Index documents - Use PUT/POST or bulk API
3. Write queries - Use Query DSL with filters for caching
4. Monitor and tune - Check cluster health, slow logs, and shard balance

Quick-Start Example: Create Index and Search

// Create index with mapping
PUT /products
{
  "mappings": {
    "properties": {
      "name":        { "type": "text", "analyzer": "standard" },
      "description": { "type": "text" },
      "price":       { "type": "float" },
      "category":    { "type": "keyword" },
      "created_at":  { "type": "date" }
    }
  }
}

// Index a document
POST /products/_doc
{
  "name": "Wireless Mouse",
  "description": "Ergonomic wireless mouse with USB-C receiver",
  "price": 29.99,
  "category": "electronics",
  "created_at": "2025-01-15"
}

// Search with bool query and aggregation
GET /products/_search
{
  "query": {
    "bool": {
      "must": [{ "match": { "description": "wireless" } }],
      "filter": [{ "range": { "price": { "lte": 50 } } }]
    }
  },
  "aggs": {
    "by_category": { "terms": { "field": "category" } }
  }
}

Best Practices

1. Define explicit mappings - Avoid dynamic mapping in production; set dynamic: strict to catch errors
2. Use filters for exact matches - Filters are cached and faster than queries for keyword/range conditions
3. Paginate with search_after - Avoid deep from/size pagination; use search_after for large result sets
4. Plan shards carefully - Target 20-40 GB per shard; avoid too many small shards
5. Snapshot regularly - Use snapshot/restore for backups; test restore procedures

Keywords

elasticsearch, search, index, mapping, query DSL, aggregation, 搜索引擎, 全文检索, 聚合, ELK, Kibana, bulk API, cluster