For a regular dimension, it assumes the string is formatted in
[ISO-8601 date and time format](https://en.wikipedia.org/wiki/ISO_8601).
*`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).
*`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)
```json
{ "type" : "timeFormat",
"format" : <output_format>,
"timeZone" : <time_zone> (optional),
"locale" : <locale> (optional) }
```
For example, the following dimension spec returns the day of the week for Montréal in French:
```json
{
"type" : "extraction",
"dimension" : "__time",
"outputName" : "dayOfWeek",
"extractionFn" : {
"type" : "timeFormat",
"format" : "EEEE",
"timeZone" : "America/Montreal",
"locale" : "fr"
}
}
```
### Time Parsing Extraction Function
Parses dimension values as timestamps using the given input format,
and returns them formatted using the given output format.
Note, if you are working with the `__time` dimension, you should consider using the
[time extraction function instead](#time-format-extraction-function) instead,
which works on time value directly as opposed to string values.
Explicit lookups allow you to specify a set of keys and values to use when performing the extraction
```json
{
"type":"lookup",
"lookup":{
"type":"map",
"map":{"foo":"bar", "baz":"bat"}
},
"retainMissingValue":true,
"injective":true
}
```
```json
{
"type":"lookup",
"lookup":{
"type":"map",
"map":{"foo":"bar", "baz":"bat"}
},
"retainMissingValue":false,
"injective":false,
"replaceMissingValueWith":"MISSING"
}
```
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 of 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 of `injective` specifies if optimizations can be used which assume there is no combining of multiple names into one. For example: If ABC123 is the only key that maps to SomeCompany, that can be optimized since it is a unique lookup. But if both ABC123 and DEF456 BOTH map to SomeCompany, then that is NOT a unique lookup. Setting this value to true and setting `retainMissingValue` to FALSE (the default) may cause undesired behavior.
A null dimension value can be mapped to a specific value by specifying the empty string as the key.
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"]`.