--- id: virtual-columns title: "Virtual columns" --- > Apache Druid supports two query languages: [Druid SQL](sql.md) and [native queries](querying.md). > This document describes the native > language. For information about functions available in SQL, refer to the > [SQL documentation](sql-scalar.md). Virtual columns are queryable column "views" created from a set of columns during a query. A virtual column can potentially draw from multiple underlying columns, although a virtual column always presents itself as a single column. Virtual columns can be referenced by their output names to be used as [dimensions](./dimensionspecs.md) or as inputs to [filters](./filters.md) and [aggregators](./aggregations.md). Each Apache Druid query can accept a list of virtual columns as a parameter. The following scan query is provided as an example: ``` { "queryType": "scan", "dataSource": "page_data", "columns":[], "virtualColumns": [ { "type": "expression", "name": "fooPage", "expression": "concat('foo' + page)", "outputType": "STRING" }, { "type": "expression", "name": "tripleWordCount", "expression": "wordCount * 3", "outputType": "LONG" } ], "intervals": [ "2013-01-01/2019-01-02" ] } ``` ## Virtual column types ### Expression virtual column Expression virtual columns use Druid's native [expression](../misc/math-expr.md) system to allow defining query time transforms of inputs from one or more columns. The expression virtual column has the following syntax: ```json { "type": "expression", "name": , "expression": , "outputType": } ``` |property|description|required?| |--------|-----------|---------| |type|Must be `"expression"` to indicate that this is an expression virtual column.|yes| |name|The name of the virtual column.|yes| |expression|An [expression](../misc/math-expr.md) that takes a row as input and outputs a value for the virtual column.|yes| |outputType|The expression's output will be coerced to this type. Can be LONG, FLOAT, DOUBLE, STRING, ARRAY types, or COMPLEX types.|no, default is FLOAT| ### Nested field virtual column The nested field virtual column is an optimized virtual column that can provide direct access into various paths of a `COMPLEX` column, including using their indexes. This virtual column is used for the SQL operators `JSON_VALUE` (if `processFromRaw` is set to false) or `JSON_QUERY` (if `processFromRaw` is true), and accepts 'JSONPath' or 'jq' syntax string representations of paths, or a parsed list of "path parts" in order to determine what should be selected from the column. You can define a nested field virtual column with any of the following equivalent syntaxes. The examples all produce the same output value, with each example showing a different way to specify how to access the nested value. The first is using JSONPath syntax `path`, the second with a jq `path`, and the third uses `pathParts`. ```json { "type": "nested-field", "columnName": "shipTo", "outputName": "v0", "expectedType": "STRING", "path": "$.phoneNumbers[1].number" } ``` ```json { "type": "nested-field", "columnName": "shipTo", "outputName": "v1", "expectedType": "STRING", "path": ".phoneNumbers[1].number", "useJqSyntax": true } ``` ```json { "type": "nested-field", "columnName": "shipTo", "outputName": "v2", "expectedType": "STRING", "pathParts": [ { "type": "field", "field": "phoneNumbers" }, { "type": "arrayElement", "index": 1 }, { "type": "field", "field": "number" } ] } ``` |property|description|required?| |--------|-----------|---------| |type|Must be `"nested-field"` to indicate that this is a nested field virtual column.|yes| |columnName|The name of the `COMPLEX` input column.|yes| |outputName|The name of the virtual column.|yes| |expectedType|The native Druid output type of the column, Druid will coerce output to this type if it does not match the underlying data. This can be `STRING`, `LONG`, `FLOAT`, `DOUBLE`, or `COMPLEX`. Extracting `ARRAY` types is not yet supported.|no, default `STRING`| |pathParts|The parsed path parts used to locate the nested values. `path` will be translated into `pathParts` internally. One of `path` or `pathParts` must be set|no, if `path` is defined| |processFromRaw|If set to true, the virtual column will process the "raw" JSON data to extract values rather than using an optimized "literal" value selector. This option allows extracting non-literal values (such as nested JSON objects or arrays) as a `COMPLEX` at the cost of much slower performance.|no, default false| |path|'JSONPath' (or 'jq') syntax path. One of `path` or `pathParts` must be set. |no, if `pathParts` is defined| |useJqSyntax|If true, parse `path` using 'jq' syntax instead of 'JSONPath'.|no, default is false| #### Nested path part Specify `pathParts` as an array of objects that describe each component of the path to traverse. Each object can take the following properties: |property|description|required?| |--------|-----------|---------| |type|Must be 'field' or 'arrayElement'. Use `field` when accessing a specific field in a nested structure. Use `arrayElement` when accessing a specific integer position of an array (zero based).|yes| |field|The name of the 'field' in a 'field' `type` path part|yes, if `type` is 'field'| |index|The array element index if `type` is `arrayElement`|yes, if `type` is 'arrayElement'| See [Nested columns](./nested-columns.md) for more information on ingesting and storing nested data. ### List filtered virtual column This virtual column provides an alternative way to use ['list filtered' dimension spec](./dimensionspecs.md#filtered-dimensionspecs) as a virtual column. It has optimized access to the underlying column value indexes that can provide a small performance improvement in some cases. ```json { "type": "mv-filtered", "name": "filteredDim3", "delegate": "dim3", "values": ["hello", "world"], "isAllowList": true } ``` |property|description|required?| |--------|-----------|---------| |type|Must be `"mv-filtered"` to indicate that this is a list filtered virtual column.|yes| |name|The output name of the virtual column|yes| |delegate|The name of the multi-value STRING input column to filter|yes| |values|Set of STRING values to allow or deny|yes| |isAllowList|If true, the output of the virtual column will be limited to the set specified by `values`, else it will provide all values _except_ those specified.|No, default true|