This functionality is experimental and may be changed or removed completely in a future release. Elastic will take a best effort approach to fix any issues, but experimental features are not subject to the support SLA of official GA features.
The Rollup Job Configuration contains all the details about how the rollup job should run, when it indexes documents, and what future queries will be able to execute against the rollup index.
There are three main sections to the Job Configuration; the logistical details about the job (cron schedule, etc), what fields should be grouped on, and what metrics to collect for each group.
A full job configuration might look like this:
PUT _rollup/job/sensor
{
"index_pattern": "sensor-*",
"rollup_index": "sensor_rollup",
"cron": "*/30 * * * * ?",
"page_size" :1000,
"groups" : {
"date_histogram": {
"field": "timestamp",
"interval": "60m",
"delay": "7d"
},
"terms": {
"fields": ["hostname", "datacenter"]
},
"histogram": {
"fields": ["load", "net_in", "net_out"],
"interval": 5
}
},
"metrics": [
{
"field": "temperature",
"metrics": ["min", "max", "sum"]
},
{
"field": "voltage",
"metrics": ["avg"]
}
]
}In the above example, there are several pieces of logistical configuration for the job itself.
-
{job_id}(required) -
(string) In the endpoint URL, you specify the name of the job (
sensorin the above example). This can be any alphanumeric string, and uniquely identifies the data that is associated with the rollup job. The ID is persistent, in that it is stored with the rolled up data. So if you create a job, let it run for a while, then delete the job… the data that the job rolled up will still be associated with this job ID. You will be unable to create a new job with the same ID, as that could lead to problems with mismatched job configurations -
index_pattern(required) -
(string) The index, or index pattern, that you wish to rollup. Supports wildcard-style patterns (
logstash-*). The job will attempt to rollup the entire index or index-pattern. Once the "backfill" is finished, it will periodically (as defined by the cron) look for new data and roll that up too. -
rollup_index(required) - (string) The index that you wish to store rollup results into. All the rollup data that is generated by the job will be stored in this index. When searching the rollup data, this index will be used in the Rollup Search endpoint’s URL. The rollup index can be shared with other rollup jobs. The data is stored so that it doesn’t interfere with unrelated jobs.
-
cron(required) - (string) A cron string which defines when the rollup job should be executed. The cron string defines an interval of when to run the job’s indexer. When the interval triggers, the indexer will attempt to rollup the data in the index pattern. The cron pattern is unrelated to the time interval of the data being rolled up. For example, you may wish to create hourly rollups of your document (as defined in the grouping configuration) but to only run the indexer on a daily basis at midnight, as defined by the cron. The cron pattern is defined just like Watcher’s Cron Schedule.
-
page_size(required) - (int) The number of bucket results that should be processed on each iteration of the rollup indexer. A larger value will tend to execute faster, but will require more memory during processing. This has no effect on how the data is rolled up, it is merely used for tweaking the speed/memory cost of the indexer.
The index_pattern cannot be a pattern that would also match the destination rollup_index. E.g. the pattern
"foo-*" would match the rollup index "foo-rollup". This causes problems because the rollup job would attempt
to rollup it’s own data at runtime. If you attempt to configure a pattern that matches the rollup_index, an exception
will be thrown to prevent this behavior.
The groups section of the configuration is where you decide which fields should be grouped on, and with what aggregations. These
fields will then be available later for aggregating into buckets. For example, this configuration:
"groups" : {
"date_histogram": {
"field": "timestamp",
"interval": "60m",
"delay": "7d"
},
"terms": {
"fields": ["hostname", "datacenter"]
},
"histogram": {
"fields": ["load", "net_in", "net_out"],
"interval": 5
}
}Allows date_histogram's to be used on the "timestamp" field, terms aggregations to be used on the "hostname" and "datacenter"
fields, and histograms to be used on any of "load", "net_in", "net_out" fields.
Importantly, these aggs/fields can be used in any combination. Think of the groups configuration as defining a set of tools that can
later be used in aggregations to partition the data. Unlike raw data, we have to think ahead to which fields and aggregations might be used.
But Rollups provide enough flexibility that you simply need to determine which fields are needed, not in what order they are needed.
There are three types of groupings currently available:
A date_histogram group aggregates a date field into time-based buckets. The date_histogram group is mandatory — you currently
cannot rollup documents without a timestamp and a date_histogram group.
The date_histogram group has several parameters:
-
field(required) - The date field that is to be rolled up.
-
interval(required) The interval of time buckets to be generated when rolling up. E.g.
"60m"will produce 60 minute (hourly) rollups. This follows standard time formatting syntax as used elsewhere in Elasticsearch. Theintervaldefines the minimum interval that can be aggregated only. If hourly ("60m") intervals are configured, Rollup Search can execute aggregations with 60m or greater (weekly, monthly, etc) intervals. So define the interval as the smallest unit that you wish to later query.Note: smaller, more granular intervals take up proportionally more space.
-
delay How long to wait before rolling up new documents. By default, the indexer attempts to roll up all data that is available. However, it is not uncommon for data to arrive out of order, sometimes even a few days late. The indexer is unable to deal with data that arrives after a time-span has been rolled up (e.g. there is no provision to update already-existing rollups).
Instead, you should specify a `delay` that matches the longest period of time you expect out-of-order data to arrive. E.g. a `delay` of `"1d"` will instruct the indexer to roll up documents up to `"now - 1d"`, which provides a day of buffer time for out-of-order documents to arrive.
-
time_zone -
Defines what time_zone the rollup documents are stored as. Unlike raw data, which can shift timezones on the fly, rolled documents have
to be stored with a specific timezone. By default, rollup documents are stored in
UTC, but this can be changed with thetime_zoneparameter.
The terms group can be used on keyword or numeric fields, to allow bucketing via the terms aggregation at a later point. The terms
group is optional. If defined, the indexer will enumerate and store all values of a field for each time-period. This can be potentially
costly for high-cardinality groups such as IP addresses, especially if the time-bucket is particularly sparse.
While it is unlikely that a rollup will ever be larger in size than the raw data, defining terms groups on multiple high-cardinality fields
can effectively reduce the compression of a rollup to a large extent. You should be judicious which high-cardinality fields are included
for that reason.
The terms group has a single parameter:
-
fields(required) -
The set of fields that you wish to collect terms for. This array can contain fields that are both
keywordand numerics. Order does not matter
The histogram group aggregates one or more numeric fields into numeric histogram intervals. This group is optional
The histogram group has a two parameters:
-
fields(required) - The set of fields that you wish to build histograms for. All fields specified must be some kind of numeric. Order does not matter
-
interval(required) -
The interval of histogram buckets to be generated when rolling up. E.g.
5will create buckets that are five units wide (0-5,5-10, etc). Note that only one interval can be specified in thehistogramgroup, meaning that all fields being grouped via the histogram must share the same interval.
After defining which groups should be generated for the data, you next configure which metrics should be collected. By default, only the doc_counts are collected for each group. To make rollup useful, you will often add metrics like averages, mins, maxes, etc.
Metrics are defined on a per-field basis, and for each field you configure which metric should be collected. For example:
"metrics": [
{
"field": "temperature",
"metrics": ["min", "max", "sum"]
},
{
"field": "voltage",
"metrics": ["avg"]
}
]This configuration defines metrics over two fields, "temperature and "voltage". For the "temperature" field, we are collecting
the min, max and sum of the temperature. For "voltage", we are collecting the average. These metrics are collected in a way that makes
them compatible with any combination of defined groups.
The metrics configuration accepts an array of objects, where each object has two parameters:
-
field(required) - The field to collect metrics for. This must be a numeric of some kind
-
metrics(required) - An array of metrics to collect for the field. At least one metric must be configured. Acceptable metrics are min/max/sum/avg/value_count.