Doc Values
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What is Doc Values?
Doc values are a data structure in Elasticsearch that stores field values in a column-oriented fashion, optimized for aggregations, sorting, and scripting. Instead of storing the data alongside the inverted index, doc values are stored separately on disk, making them efficient for retrieving values for a large number of documents. This allows Elasticsearch to perform operations like sorting and aggregations much faster than if it had to retrieve the data from the inverted index.
Free resources to learn Doc Values
More in stage 7: Search Analyzer
- Search Analyzer
- fielddata
- The Inverted Index
- The Analyze API
- Standard Analyzer
- Custom Analyzers
- Value Count
- Avg / Sum / Min / Max
- Cardinality
- Stats / Extended Stats
- Terms
- Range / Date Range
- Histogram
- Filter Aggregations
- Pivot
- Latest
- Transform API
- Nested Aggregations
- Pipeline Aggregations
- Understanding Similarity
- BM25 algorithm
- CAT API
- Segment Merging
- Cluster Monitoring
- Cross-cluster Replication
- Autoscaling
- Boosting Queries
- Function Score Query
- Match Phrase Query
- Synonyms Graph
- ILM
- Rollover Policies
- Data Tiers
- Vector Search
- Semantic Search
- Hybrid Search
- Snapshots & restore
- SLM
- Authentication
- Roles & Users
- API Keys
Doc Values: common questions
Can I learn Doc Values in Hindi?
This lesson is written in English. Once you sign in, open it in the interactive course and ask the AI tutor to explain Doc Values in Hindi or Hinglish. The tutor answers from this lesson’s own text, so it stays on the syllabus, and it runs on your own Google, OpenAI or Anthropic key.
Is this Doc Values tutorial for beginners?
It is lesson 73 of 113 in the free Elasticsearch roadmap, in stage 7, Search Analyzer. If you are new to Elasticsearch, start from stage 1 and come back here in order; if you already know the earlier stages, this lesson stands on its own.