Elasticsearch Best Practices

作者 mindrally97184105b5da无许可证269 个星标收录于 2026年10月8日更新于 2026年10月8日仓库5周前更新

Elasticsearch development best practices for indexing, querying, and search optimization

仅含说明Software DevelopmentData & Analytics
AI 生成的概览

关于 Elasticsearch 索引设计、查询、聚合、索引写入与搜索性能的参考指南。

功能
该技能提供 Elasticsearch 开发最佳实践，涵盖索引与映射设计、分片规划、查询优化、聚合、批量索引、分析器、搜索功能、监控、安全与重建索引。内容以文字说明配合 JSON 配置和查询示例呈现。它输出的是建议与示例片段，而非实际执行操作。
适用场景
适用于设计或调优 Elasticsearch 索引、映射、查询或集群设置时。也适合审查现有搜索配置，以改进性能、安全或维护方式。
运行要求
除智能体本身外无需其他条件；仅为说明性指令，不附带脚本。

Elasticsearch Best Practices

Core Principles

  • Design indices and mappings based on query patterns
  • Optimize for search performance with proper analysis and indexing
  • Use appropriate shard sizing and cluster configuration
  • Implement proper security and access control
  • Monitor cluster health and optimize queries

Index Design

Mapping Best Practices

  • Define explicit mappings instead of relying on dynamic mapping
  • Use appropriate data types for each field
  • Disable indexing for fields you do not search on
  • Use keyword type for exact matches, text for full-text search
json
{  "mappings": {    "properties": {      "product_id": {        "type": "keyword"      },      "name": {        "type": "text",        "analyzer": "standard",        "fields": {          "keyword": {            "type": "keyword",            "ignore_above": 256          }        }      },      "description": {        "type": "text",        "analyzer": "english"      },      "price": {        "type": "scaled_float",        "scaling_factor": 100      },      "category": {        "type": "keyword"      },      "tags": {        "type": "keyword"      },      "created_at": {        "type": "date"      },      "metadata": {        "type": "object",        "enabled": false      },      "location": {        "type": "geo_point"      }    }  }}

Field Types

  • keyword: Exact values, filtering, aggregations, sorting
  • text: Full-text search with analysis
  • date: Date/time values with format specification
  • numeric types: long, integer, short, byte, double, float, scaled_float
  • boolean: True/false values
  • geo_point: Latitude/longitude pairs
  • nested: Arrays of objects that need independent querying

Index Settings

json
{  "settings": {    "number_of_shards": 3,    "number_of_replicas": 1,    "refresh_interval": "30s",    "analysis": {      "analyzer": {        "custom_analyzer": {          "type": "custom",          "tokenizer": "standard",          "filter": ["lowercase", "asciifolding", "synonym_filter"]        }      },      "filter": {        "synonym_filter": {          "type": "synonym",          "synonyms": ["laptop, notebook", "phone, mobile, smartphone"]        }      }    }  }}

Shard Sizing

Guidelines

  • Target 20-40GB per shard
  • Aim for ~20 shards per GB of heap
  • Avoid oversharding (too many small shards)
  • Consider time-based indices for time-series data
json
{  "settings": {    "number_of_shards": 3,    "number_of_replicas": 1  }}

Index Lifecycle Management (ILM)

json
{  "policy": {    "phases": {      "hot": {        "min_age": "0ms",        "actions": {          "rollover": {            "max_size": "50gb",            "max_age": "7d"          }        }      },      "warm": {        "min_age": "30d",        "actions": {          "shrink": {            "number_of_shards": 1          },          "forcemerge": {            "max_num_segments": 1          }        }      },      "delete": {        "min_age": "90d",        "actions": {          "delete": {}        }      }    }  }}

Query Optimization

Query Types

Match Query (Full-text search)
json
{  "query": {    "match": {      "description": {        "query": "wireless bluetooth headphones",        "operator": "and",        "fuzziness": "AUTO"      }    }  }}
Term Query (Exact match)
json
{  "query": {    "term": {      "status": "active"    }  }}
Bool Query (Combining queries)
json
{  "query": {    "bool": {      "must": [        { "match": { "name": "laptop" } }      ],      "filter": [        { "term": { "category": "electronics" } },        { "range": { "price": { "gte": 500, "lte": 2000 } } }      ],      "should": [        { "term": { "brand": "apple" } }      ],      "must_not": [        { "term": { "status": "discontinued" } }      ]    }  }}

Query Best Practices

  • Use filter context for non-scoring queries (cacheable)
  • Use must only when scoring is needed
  • Avoid wildcards at the beginning of terms
  • Use keyword fields for exact matches
  • Limit result size with size parameter
json
{  "query": {    "bool": {      "must": {        "multi_match": {          "query": "search terms",          "fields": ["name^3", "description", "tags^2"],          "type": "best_fields"        }      },      "filter": [        { "term": { "active": true } },        { "range": { "created_at": { "gte": "now-30d" } } }      ]    }  },  "size": 20,  "from": 0,  "_source": ["name", "price", "category"]}

Aggregations

Common Aggregation Patterns

json
{  "size": 0,  "aggs": {    "categories": {      "terms": {        "field": "category",        "size": 10      },      "aggs": {        "avg_price": {          "avg": { "field": "price" }        }      }    },    "price_ranges": {      "range": {        "field": "price",        "ranges": [          { "to": 100 },          { "from": 100, "to": 500 },          { "from": 500 }        ]      }    },    "date_histogram": {      "date_histogram": {        "field": "created_at",        "calendar_interval": "month"      }    }  }}

Aggregation Best Practices

  • Use size: 0 when you only need aggregations
  • Set appropriate shard_size for terms aggregations
  • Use composite aggregations for pagination
  • Consider using aggs filters to narrow scope

Indexing Best Practices

Bulk Indexing

json
POST _bulk{ "index": { "_index": "products", "_id": "1" } }{ "name": "Product 1", "price": 99.99 }{ "index": { "_index": "products", "_id": "2" } }{ "name": "Product 2", "price": 149.99 }

Bulk API Guidelines

  • Use bulk API for batch operations
  • Optimal bulk size: 5-15MB per request
  • Monitor for rejected requests (thread pool queue full)
  • Disable refresh during bulk indexing for better performance
json
PUT /products/_settings{  "refresh_interval": "-1"}
// After bulk indexing:PUT /products/_settings{  "refresh_interval": "1s"}
POST /products/_refresh

Document Updates

json
POST /products/_update/1{  "doc": {    "price": 89.99,    "updated_at": "2024-01-15T10:30:00Z"  }}
// Update by queryPOST /products/_update_by_query{  "query": {    "term": { "category": "electronics" }  },  "script": {    "source": "ctx._source.on_sale = true"  }}

Analysis and Tokenization

Custom Analyzers

json
{  "settings": {    "analysis": {      "analyzer": {        "product_analyzer": {          "type": "custom",          "tokenizer": "standard",          "filter": [            "lowercase",            "asciifolding",            "english_stop",            "english_stemmer"          ]        },        "autocomplete_analyzer": {          "type": "custom",          "tokenizer": "standard",          "filter": [            "lowercase",            "edge_ngram_filter"          ]        }      },      "filter": {        "english_stop": {          "type": "stop",          "stopwords": "_english_"        },        "english_stemmer": {          "type": "stemmer",          "language": "english"        },        "edge_ngram_filter": {          "type": "edge_ngram",          "min_gram": 2,          "max_gram": 15        }      }    }  }}

Test Analyzer

json
POST /products/_analyze{  "analyzer": "product_analyzer",  "text": "Wireless Bluetooth Headphones"}

Search Features

Autocomplete/Suggestions

json
{  "mappings": {    "properties": {      "name": {        "type": "text",        "fields": {          "suggest": {            "type": "completion"          }        }      }    }  }}
// Query suggestions{  "suggest": {    "product-suggest": {      "prefix": "wire",      "completion": {        "field": "name.suggest",        "size": 5      }    }  }}

Highlighting

json
{  "query": {    "match": { "description": "wireless" }  },  "highlight": {    "fields": {      "description": {        "pre_tags": ["<em>"],        "post_tags": ["</em>"],        "fragment_size": 150      }    }  }}

Performance Optimization

Query Caching

  • Filter queries are cached automatically
  • Use filter context for frequently repeated conditions
  • Monitor cache hit rates

Search Performance

  • Avoid deep pagination (use search_after instead)
  • Limit _source fields returned
  • Use doc_values for sorting and aggregations
  • Pre-sort index for common sort orders
json
{  "query": { "match_all": {} },  "size": 20,  "search_after": [1705329600000, "product_123"],  "sort": [    { "created_at": "desc" },    { "_id": "asc" }  ]}

Monitoring and Maintenance

Cluster Health

GET _cluster/healthGET _cat/indices?vGET _cat/shards?vGET _nodes/stats

Index Maintenance

POST /products/_forcemerge?max_num_segments=1POST /products/_cache/clearPOST /products/_refresh

Slow Query Log

json
PUT /products/_settings{  "index.search.slowlog.threshold.query.warn": "10s",  "index.search.slowlog.threshold.query.info": "5s",  "index.search.slowlog.threshold.fetch.warn": "1s"}

Security

Index-Level Security

json
PUT _security/role/products_reader{  "indices": [    {      "names": ["products*"],      "privileges": ["read"]    }  ]}

Field-Level Security

json
PUT _security/role/limited_access{  "indices": [    {      "names": ["users"],      "privileges": ["read"],      "field_security": {        "grant": ["name", "email", "created_at"]      }    }  ]}

Aliases and Reindexing

Index Aliases

json
POST _aliases{  "actions": [    { "add": { "index": "products_v2", "alias": "products" } },    { "remove": { "index": "products_v1", "alias": "products" } }  ]}

Reindex with Transformation

json
POST _reindex{  "source": {    "index": "products_v1"  },  "dest": {    "index": "products_v2"  },  "script": {    "source": "ctx._source.migrated_at = new Date().toString()"  }}

来源与署名

来源：mindrally/skills位于elasticsearch-best-practices提交9718410

许可证： 无许可证

内容归原作者所有。SourceWeft 从公开仓库中收录这些内容。

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