Claude-skill-registry elasticsearch
Elasticsearch DBA skill for index/mapping design, query tuning, cluster sizing and operations, shard/replica strategy, ILM, monitoring, troubleshooting (hot nodes, GC, rejected requests), and safe reindexing/upgrades. Use for tasks like designing search schemas, diagnosing performance issues, and operating ES in production.
install
source · Clone the upstream repo
git clone https://github.com/majiayu000/claude-skill-registry
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/majiayu000/claude-skill-registry "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/data/ES" ~/.claude/skills/majiayu000-claude-skill-registry-elasticsearch && rm -rf "$T"
manifest:
skills/data/ES/SKILL.mdsource content
elasticsearch
Use this skill for Elasticsearch(ES)相关设计、性能与运维(DBA/中间件)任务。
Defaults / assumptions to confirm
- ES version and deployment (self-hosted / managed)
- Cluster topology (nodes, roles, storage type)
- Data volume and retention requirements
- Query patterns (search vs analytics) and latency SLO
Workflow
- Understand use-cases and query patterns
- Primary user journeys: keyword search, filtering, aggregations, sorting.
- Write patterns: append-only logs vs frequent updates.
- Required consistency and freshness (near real-time delay tolerance).
- Index & mapping design
- Define index naming convention and templates.
- Choose correct field types (
vskeyword
,text
,date
,long
).scaled_float - Analyze/analyzer strategy for language (e.g., Chinese tokenizer) if needed.
- Avoid mapping explosion; control dynamic mappings.
- Plan
and stored fields usage; consider doc values._source
- Shards and replicas
- Pick shard count with future growth and reindex cost in mind.
- Avoid too many small shards; target shard size range (e.g., 10–50GB) depending on workload.
- Set replicas for availability and read scaling.
- Query tuning
- Use
and slow logs to find bottlenecks.profile - Reduce heavy aggregations; precompute when possible.
- Use filters with
fields; cache-friendly queries.keyword - Pagination: prefer
for deep pages; avoid largesearch_after
.from+size
- Lifecycle management
- Use ILM (hot-warm-cold-delete) for time-series data.
- Rollover policies by size/time; manage retention.
- Cluster operations & stability
- Monitor heap, GC, CPU, disk watermarks, thread pool rejections.
- Detect hot keys/indices; rebalance shards carefully.
- Snapshot/restore; restore drills; retention policy.
- Safe changes
- Mapping changes often require reindex; plan alias-based migrations.
- Use index aliases for zero-downtime cutover.
- Upgrade runbook: compatibility, rolling upgrade, backout plan.
Outputs
- Mapping/index template proposal + rationale.
- Shard/replica sizing plan + expected capacity.
- Performance diagnosis report (evidence → root cause → fixes).
- Migration plan (reindex + alias cutover + verification).