find

The find operator finds specific events.

We recommend using the cribl operator, which has easier syntax and more capabilities.

Either cribl or find can be used to initiate a query expression.

Syntax

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• find [withsource=FieldName] [in (Dataset [, Dataset, ...])] where Predicate [project-smart | project FieldName [:FieldType] [, FieldName[:FieldType], ...]

• find Predicate [project-smart | project FieldName[:FieldType] [, FieldName[:FieldType], ...]

Arguments

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• withsource=FieldName: Optional. By default, the output will include a field called dataset whose values indicate which Dataset has contributed to each result. If specified, FieldName will be used instead of dataset.
• Predicate: An expression over the fields of the Datasets that returns a bool value. For a summary of some filtering functions, see the where operator.
• Dataset: Optional. By default, find will look in all the Datasets for:
  • The name of a Dataset, such as Events.
  • A query expression, such as (Events | where id==42).
• project-smart | project: If not specified, project-smart will be used by default. For more information, see output-schema below.

Output Schema

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dataset field

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The find operator output will always include a dataset field with the Dataset name. The field can be renamed using the withsource parameter.

Results fields

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Datasets that don’t contain any fields used by the predicate evaluation will be filtered out.

When using project-smart, the fields that will appear in the output will be:

• Fields that appear explicitly in the predicate.
• Fields that are common to all the filtered Datasets.

The rest of the fields will be packed into a property bag and will appear in an additional pack_ field. A field that is referenced explicitly by the predicate and has multiple types will have a different field in the result schema for each such type. Each of the field names will be constructed from the original field name and type, separated by an underscore.

When using `project FieldName[:FieldType] [, FieldName[:FieldType], …]:

The results will include the fields specified in the list. If a Dataset doesn’t contain a certain field, the values in the corresponding rows will be null. When specifying a FieldType with a FieldName, this field will have the given type, and the values will be cast to that type if needed. The casting won’t have an effect on the field type when evaluating the predicate.

pack_ field

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This field will contain a property bag with the data from all the fields that don’t appear in the output schema. The Dataset name will serve as the property name and the field value will serve as the property value.

Examples

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Term lookup across the default Dataset

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The query finds all events from the default Dataset where any field includes the word Goat.

find "Goat"

Term lookup across the default Dataset matching a name pattern

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The query finds all events from the default Dataset whose name starts with G, and in which any field includes the word Cribl.

find in ("cribl_search_sample") where _raw has "GET" 
| limit 100

Examples of find output results

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The following examples show how find can be used over two Datasets: EventsTable1 and EventsTable2. Assume we have the next content of these two Datasets:

EventsTable1

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EventsTable2

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Search in common fields, project common and uncommon fields, and pack the rest

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find in (EventsTable1, EventsTable2) 
     where Session_Id == 'acbd207d-51aa-4df7-bfa7-be70eb68f04e' and Level == 'Error' 
     project EventText, Version, EventName

Search in common and uncommon fields

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find Version == 'v1.0.0' or EventName == 'Event1' project Session_Id, EventText, Version, EventName

In practice, EventsTable1 rows will be filtered with Version == ‘v1.0.0’ predicate and EventsTable2 rows will be filtered with EventName == ‘Event1’ predicate.

Use abbreviated notation to search across the default Dataset

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find Session_Id == 'acbd207d-51aa-4df7-bfa7-be70eb68f04e'

Return the results from each row as a property bag

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find Session_Id == 'acbd207d-51aa-4df7-bfa7-be70eb68f04e'

Return results that match “test event”.

dataset=$vt_dummy event<10 
| extend _raw=iif(event%2>0, "This is a test event", "This is another event") 
| find where * has "test event"