OpenSearch Cheat Sheet

 Index=table/collection of docs.

Document=One JSON record inside an index.

{ "id": "IMP123", "event": "UE107348", "name": "Service A", "customer": [...] }

Field=A property inside a document.

event name customer.customerName customer.billAmount

Mapping=Schema of the index. Defines field types:

Type	Used for
text	Full text search
keyword	Exact match, sorting, grouping
double, integer, long	Numeric sort/range/aggregation
date	Date filter/sort
nested	Array of objects where each object must stay logically separate

text vs keyword

text is analyzed/tokenized.

Good for search:

"Gold Customer" -> "gold", "customer"

keyword is exact.

Good for:

• exact match
• grouping
• sorting
• aggregations

"customerName": { "type": "text", "fields": { "keyword": { "type": "keyword" } } }

Use:

customerName -> search text customerName.keyword -> exact match/group/sort

Query

Filters/selects documents.

Example:

{ "query": { "term": { "event.keyword": { "value": "UE107348" } } } }

This means:

Find documents where event exactly equals UE107348

term vs match

Query	Use for
term	Exact value match, usually on keyword, numbers, ids
match	Text search on analyzed text fields
range	Numeric/date range
bool	Combine multiple conditions

Example bool:

{ "bool": { "must": [ { "term": { "event.keyword": "UE107348" } }, { "term": { "customer.customerId": "CUST1" } } ] } }

Hits

Normal search results.

size

Controls how many normal documents are returned.

If you run a query with size: 10, OpenSearch returns 10 matching documents in hits.

Good for:

• search results
• document pagination

{ "size": 10 }

Means return 10 hits.

size: 0

Means:

Do not return documents, only return aggregations.

Useful when you only need counts/groups/summaries.

from + size

Document pagination.

{ "from": 100, "size": 20 }

Means:

Return documents 101-120

Works well for hits/documents.

Does not directly paginate aggregation buckets.

Aggregation

Groups/summarizes documents.

Like SQL GROUP BY.

Examples:

Aggregation	Meaning
terms	Group by exact field
max	Max numeric value
min	Min numeric value
value_count	Count values
top_hits	Return sample documents inside a bucket
nested	Enter nested object array
reverse_nested	Go back from nested object to parent document

terms aggregation

Group by field.

{ "terms": { "field": "customer.customerName.keyword", "size": 100 } }

Means:

Group matching data by customer name and return top 100 buckets

Metric aggregation

Calculates value per bucket.

Example:

"customer_bill_amount": { "max": { "field": "customer.billAmount" } }

Means:

For each customer bucket, calculate max bill amount

Used so buckets can be sorted by bill amount.

Bucket sorting

Example:

"order": [ { "customer_bill_amount": "desc" } ]

Means:

Sort customer buckets by bill amount descending

nested

Needed when field is an array of objects.

Example:

"customer": [ { "customerId": "C1", "billAmount": 100 }, { "customerId": "C2", "billAmount": 500 } ]

Without nested, OpenSearch can mix values from different array objects incorrectly.

Nested keeps each customer object separate.

nested query

Search inside nested object.

{ "nested": { "path": "customer", "query": { "term": { "customer.customerId": "C1" } } } }

Means:

Find impact docs where one nested customer has customerId C1

nested aggregation

Aggregate inside nested object.

{ "nested": { "path": "customer" } }

Means:

Go into the customer nested array and aggregate customer rows

top_hits

Returns actual documents/objects inside an aggregation bucket.

Example:

"customer_details": { "top_hits": { "size": 1 } }

Means:

For each customer bucket, return one sample hit to get details

Caution:

• top_hits inside many buckets can become expensive.
• Inner result size limits apply.

Scoring

OpenSearch gives _score when doing relevance search.

Useful for:

• text search
• fuzzy search
• best match ranking

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GET _cat/indices?v

GET _cat/indices/abcIndex-*?v

GET abcIndex/_mapping , _settings

indexes version - actual index 
without version - alias that points to above