IMPORTANT: No additional bug fixes or documentation updates
will be released for this version. For the latest information, see the
current release documentation.
Watcher transform context
editWatcher transform context
editUse a Painless script as a watch transform to transform a payload into a new payload for further use in the watch. Transform scripts return an Object value of the new payload.
The following variables are available in all watcher contexts.
Variables
-
params(Map, read-only) - User-defined parameters passed in as part of the query.
-
ctx['watch_id'](String, read-only) - The id of the watch.
-
ctx['id'](String, read-only) - The server generated unique identifier for the run watch.
-
ctx['metadata'](Map, read-only) - Metadata can be added to the top level of the watch definition. This is user defined and is typically used to consolidate duplicate values in a watch.
-
ctx['execution_time'](ZonedDateTime, read-only) - The time the watch began execution.
-
ctx['trigger']['scheduled_time'](ZonedDateTime, read-only) - The scheduled trigger time for the watch. This is the time the watch should be executed.
-
ctx['trigger']['triggered_time'](ZonedDateTime, read-only) - The actual trigger time for the watch. This is the time the watch was triggered for execution.
-
ctx['payload'](Map, read-only) - The accessible watch data based upon the watch input.
Return
-
Object - The new payload.
API
The standard Painless API is available.
Example
To run the examples, first follow the steps in context examples.
POST _watcher/watch/_execute
{
"watch" : {
"trigger" : { "schedule" : { "interval" : "24h" } },
"input" : {
"search" : {
"request" : {
"indices" : [ "seats" ],
"body" : {
"query" : { "term": { "sold": "true"} },
"aggs" : {
"theatres" : {
"terms" : { "field" : "play" },
"aggs" : {
"money" : {
"sum": { "field" : "cost" }
}
}
}
}
}
}
}
},
"transform" : {
"script":
"""
return [
'money_makers': ctx.payload.aggregations.theatres.buckets.stream()
.filter(t -> {
return t.money.value > 50000
})
.map(t -> {
return ['play': t.key, 'total_value': t.money.value ]
}).collect(Collectors.toList()),
'duds' : ctx.payload.aggregations.theatres.buckets.stream()
.filter(t -> {
return t.money.value < 15000
})
.map(t -> {
return ['play': t.key, 'total_value': t.money.value ]
}).collect(Collectors.toList())
]
"""
},
"actions" : {
"my_log" : {
"logging" : {
"text" : "The output of the payload was transformed to {{ctx.payload}}"
}
}
}
}
}
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The Java Stream API is used in the transform. This API allows manipulation of the elements of the list in a pipeline. |
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The stream filter removes items that do not meet the filter criteria. |
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The stream map transforms each element into a new object. |
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The collector reduces the stream to a |
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This is done again for the second set of values in the transform. |
The following action transform changes each value in the mod_log action into a String.
This transform does not change the values in the unmod_log action.
POST _watcher/watch/_execute
{
"watch" : {
"trigger" : { "schedule" : { "interval" : "24h" } },
"input" : {
"search" : {
"request" : {
"indices" : [ "seats" ],
"body" : {
"query" : {
"term": { "sold": "true"}
},
"aggs" : {
"theatres" : {
"terms" : { "field" : "play" },
"aggs" : {
"money" : {
"sum": { "field" : "cost" }
}
}
}
}
}
}
}
},
"actions" : {
"mod_log" : {
"transform": {
"script" :
"""
def formatter = NumberFormat.getCurrencyInstance();
return [
'msg': ctx.payload.aggregations.theatres.buckets.stream()
.map(t-> formatter.format(t.money.value) + ' for the play ' + t.key)
.collect(Collectors.joining(", "))
]
"""
},
"logging" : {
"text" : "The output of the payload was transformed to: {{ctx.payload.msg}}"
}
},
"unmod_log" : {
"logging" : {
"text" : "The output of the payload was not transformed and this value should not exist: {{ctx.payload.msg}}"
}
}
}
}
}
This example uses the streaming API in a very similar manner. The differences below are subtle and worth calling out.
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The location of the transform is no longer at the top level, but is within an individual action. |
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A second action that does not transform the payload is given for reference. |
The following example shows scripted watch and action transforms within the context of a complete watch. This watch also uses a scripted condition.
POST _watcher/watch/_execute
{
"watch" : {
"metadata" : { "high_threshold": 4000, "low_threshold": 1000 },
"trigger" : { "schedule" : { "interval" : "24h" } },
"input" : {
"search" : {
"request" : {
"indices" : [ "seats" ],
"body" : {
"query" : {
"term": { "sold": "true"}
},
"aggs" : {
"theatres" : {
"terms" : { "field" : "play" },
"aggs" : {
"money" : {
"sum": {
"field" : "cost",
"script": {
"source": "doc.cost.value * doc.number.value"
}
}
}
}
}
}
}
}
}
},
"condition" : {
"script" :
"""
return ctx.payload.aggregations.theatres.buckets.stream()
.anyMatch(theatre -> theatre.money.value < ctx.metadata.low_threshold ||
theatre.money.value > ctx.metadata.high_threshold)
"""
},
"transform" : {
"script":
"""
return [
'money_makers': ctx.payload.aggregations.theatres.buckets.stream()
.filter(t -> {
return t.money.value > ctx.metadata.high_threshold
})
.map(t -> {
return ['play': t.key, 'total_value': t.money.value ]
}).collect(Collectors.toList()),
'duds' : ctx.payload.aggregations.theatres.buckets.stream()
.filter(t -> {
return t.money.value < ctx.metadata.low_threshold
})
.map(t -> {
return ['play': t.key, 'total_value': t.money.value ]
}).collect(Collectors.toList())
]
"""
},
"actions" : {
"log_money_makers" : {
"condition": {
"script" : "return ctx.payload.money_makers.size() > 0"
},
"transform": {
"script" :
"""
def formatter = NumberFormat.getCurrencyInstance();
return [
'plays_value': ctx.payload.money_makers.stream()
.map(t-> formatter.format(t.total_value) + ' for the play ' + t.play)
.collect(Collectors.joining(", "))
]
"""
},
"logging" : {
"text" : "The following plays contain the highest grossing total income: {{ctx.payload.plays_value}}"
}
},
"log_duds" : {
"condition": {
"script" : "return ctx.payload.duds.size() > 0"
},
"transform": {
"script" :
"""
def formatter = NumberFormat.getCurrencyInstance();
return [
'plays_value': ctx.payload.duds.stream()
.map(t-> formatter.format(t.total_value) + ' for the play ' + t.play)
.collect(Collectors.joining(", "))
]
"""
},
"logging" : {
"text" : "The following plays need more advertising due to their low total income: {{ctx.payload.plays_value}}"
}
}
}
}
}
The following example shows the use of metadata and transforming dates into a readable format.
POST _watcher/watch/_execute
{
"watch" : {
"metadata" : { "min_hits": 10 },
"trigger" : { "schedule" : { "interval" : "24h" } },
"input" : {
"search" : {
"request" : {
"indices" : [ "seats" ],
"body" : {
"query" : {
"term": { "sold": "true"}
},
"aggs" : {
"theatres" : {
"terms" : { "field" : "play" },
"aggs" : {
"money" : {
"sum": { "field" : "cost" }
}
}
}
}
}
}
}
},
"condition" : {
"script" :
"""
return ctx.payload.hits.total > ctx.metadata.min_hits
"""
},
"transform" : {
"script" :
"""
def theDate = ZonedDateTime.ofInstant(ctx.execution_time.toInstant(), ctx.execution_time.getZone());
return ['human_date': DateTimeFormatter.RFC_1123_DATE_TIME.format(theDate),
'aggregations': ctx.payload.aggregations]
"""
},
"actions" : {
"my_log" : {
"logging" : {
"text" : "The watch was successfully executed on {{ctx.payload.human_date}} and contained {{ctx.payload.aggregations.theatres.buckets.size}} buckets"
}
}
}
}
}