When specifying a DimensionSpec on a numeric column, the user should include the type of the column in the `outputType` field. If left unspecified, the `outputType` defaults to STRING.
Please refer to the [Output Types](#output-types) section for more details.
`outputType` may also be specified in an ExtractionDimensionSpec to apply type conversion to results before merging. If left unspecified, the `outputType` defaults to STRING.
Please refer to the [Output Types](#output-types) section for more details.
These are only useful for multi-value dimensions. If you have a row in druid that has a multi-value dimension with values ["v1", "v2", "v3"] and you send a groupBy/topN query grouping by that dimension with [query filter](filters.html) for value "v1". In the response you will get 3 rows containing "v1", "v2" and "v3". This behavior might be unintuitive for some use cases.
It happens because "query filter" is internally used on the bitmaps and only used to match the row to be included in the query result processing. With multi-value dimensions, "query filter" behaves like a contains check, which will match the row with dimension value ["v1", "v2", "v3"]. Please see the section on "Multi-value columns" in [segment](../design/segments.html) for more details.
Then groupBy/topN processing pipeline "explodes" all multi-value dimensions resulting 3 rows for "v1", "v2" and "v3" each.
In addition to "query filter" which efficiently selects the rows to be processed, you can use the filtered dimension spec to filter for specific values within the values of a multi-value dimension. These dimensionSpecs take a delegate DimensionSpec and a filtering criteria. From the "exploded" rows, only rows matching the given filtering criteria are returned in the query result.
The following filtered dimension spec acts as a whitelist or blacklist for values as per the "isWhitelist" attribute value.
Following filtered dimension spec retains only the values matching regex. Note that `listFiltered` is faster than this and one should use that for whitelist or blacklist usecase.
A property of `retainMissingValue` and `replaceMissingValueWith` can be specified at query time to hint how to handle missing values. Setting `replaceMissingValueWith` to `""` has the same effect as setting it to `null` or omitting the property.
Setting `retainMissingValue` to true will use the dimension's original value if it is not found in the lookup.
The default values are `replaceMissingValueWith = null` and `retainMissingValue = false` which causes missing values to be treated as missing.
It is illegal to set `retainMissingValue = true` and also specify a `replaceMissingValueWith`.
A property `optimize` can be supplied to allow optimization of lookup based extraction filter (by default `optimize = true`).
The second kind where it is not possible to pass at query time due to their size, will be based on an external lookup table or resource that is already registered via configuration file or/and coordinator.
The dimension specs provide an option to specify the output type of a column's values. This is necessary as it is possible for a column with given name to have different value types in different segments; results will be converted to the type specified by `outputType` before merging.
Note that not all use cases for DimensionSpec currently support `outputType`, the table below shows which use cases support this option:
If the `replaceMissingValue` property is true, the extraction function will transform dimension values that do not match the regex pattern to a user-specified String. Default value is `false`.
The `replaceMissingValueWith` property sets the String that unmatched dimension values will be replaced with, if `replaceMissingValue` is true. If `replaceMissingValueWith` is not specified, unmatched dimension values will be replaced with nulls.
For example, if `expr` is `"(a\w+)"` in the example JSON above, a regex that matches words starting with the letter `a`, the extraction function will convert a dimension value like `banana` to `foobar`.
*`format` : date time format for the resulting dimension value, in [Joda Time DateTimeFormat](http://www.joda.org/joda-time/apidocs/org/joda/time/format/DateTimeFormat.html), or null to use the default ISO8601 format.
*`locale` : locale (language and country) to use, given as a [IETF BCP 47 language tag](http://www.oracle.com/technetwork/java/javase/java8locales-2095355.html#util-text), e.g. `en-US`, `en-GB`, `fr-FR`, `fr-CA`, etc.
*`timeZone` : time zone to use in [IANA tz database format](http://en.wikipedia.org/wiki/List_of_tz_database_time_zones), e.g. `Europe/Berlin` (this can possibly be different than the aggregation time-zone)
*`asMillis` : boolean value, set to true to treat input strings as millis rather than ISO8601 strings. Additionally, if `format` is null or not specified, output will be in millis rather than ISO8601.
If "joda" is true, time formats are described in the [Joda DateTimeFormat documentation](http://www.joda.org/joda-time/apidocs/org/joda/time/format/DateTimeFormat.html).
If "joda" is false (or unspecified) then formats are described in the [SimpleDateFormat documentation](http://icu-project.org/apiref/icu4j/com/ibm/icu/text/SimpleDateFormat.html).
In general, we recommend setting "joda" to true since Joda format strings are more common in Druid APIs and since Joda handles certain edge cases (like weeks and weekyears near
the start and end of calendar years) in a more ISO8601 compliant way.
If a value cannot be parsed using the provided timeFormat, it will be returned as-is.
JavaScript-based functionality is disabled by default. Please refer to the Druid <ahref="../development/javascript.html">JavaScript programming guide</a> for guidelines about using Druid's JavaScript functionality, including instructions on how to enable it.
This allows distinguishing between a null dimension and a lookup resulting in a null.
For example, specifying `{"":"bar","bat":"baz"}` with dimension values `[null, "foo", "bat"]` and replacing missing values with `"oof"` will yield results of `["bar", "oof", "baz"]`.
Omitting the empty string key will cause the missing value to take over. For example, specifying `{"bat":"baz"}` with dimension values `[null, "foo", "bat"]` and replacing missing values with `"oof"` will yield results of `["oof", "oof", "baz"]`.
Provides chained execution of extraction functions.
A property of `extractionFns` contains an array of any extraction functions, which is executed in the array index order.
Example for chaining [regular expression extraction function](#regular-expression-extraction-function), [javascript extraction function](#javascript-extraction-function), and [substring extraction function](#substring-extraction-function) is as followings.
It will transform dimension values with specified extraction functions in the order named.
For example, `'/druid/prod/historical'` is transformed to `'the dru'` as regular expression extraction function first transforms it to `'druid'` and then, javascript extraction function transforms it to `'the druid'`, and lastly, substring extraction function transforms it to `'the dru'`.
For example if you want to concat "[" and "]" before and after the actual dimension value, you need to specify "[%s]" as format string. "nullHandling" can be one of `nullString`, `emptyString` or `returnNull`. With "[%s]" format, each configuration will result `[null]`, `[]`, `null`. Default is `nullString`.
Bucket extraction function is used to bucket numerical values in each range of the given size by converting them to the same base value. Non numeric values are converted to null.
*`size` : the size of the buckets (optional, default 1)
*`offset` : the offset for the buckets (optional, default 0)
The following extraction function creates buckets of 5 starting from 2. In this case, values in the range of [2, 7) will be converted to 2, values in [7, 12) will be converted to 7, etc.
