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[DOCS] Added ML sample data URLs (elastic/x-pack-elasticsearch#1256) 

Original commit: elastic/x-pack-elasticsearch@528a32f26f
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Lisa Cawley 2017-04-28 10:24:10 -07:00 committed by lcawley
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@ -122,22 +122,21 @@ In this step we will upload some sample data to {es}. This is standard
The sample data for this tutorial contains information about the requests that
are received by various applications and services in a system. A system
administrator might use this type of information to track the the total
number of requests across all of the infrastructure. If the number of requests
increases or decreases unexpectedly, for example, this might be an indication
that there is a problem or that resources need to be redistributed. By using
the {xpack} {ml} features to model the behavior of this data, it is easier to
identify anomalies and take appropriate action.
administrator might use this type of information to track the total number of
requests across all of the infrastructure. If the number of requests increases
or decreases unexpectedly, for example, this might be an indication that there
is a problem or that resources need to be redistributed. By using the {xpack}
{ml} features to model the behavior of this data, it is easier to identify
anomalies and take appropriate action.
Download this sample data from: https://github.com/elastic/examples
//Download this data set by clicking here:
//See https://download.elastic.co/demos/kibana/gettingstarted/shakespeare.json[shakespeare.json].
Download this sample data by clicking here:
https://download.elastic.co/demos/machine_learning/gettingstarted/server_metrics.tar.gz[server_metrics.tar.gz]
Use the following commands to extract the files:
[source,shell]
----------------------------------
tar xvf server_metrics.tar.gz
tar -zxvf server_metrics.tar.gz
----------------------------------
Each document in the server-metrics data set has the following schema:
@ -183,9 +182,10 @@ and specify a field's characteristics, such as the field's searchability or
whether or not it's _tokenized_, or broken up into separate words.
The sample data includes an `upload_server-metrics.sh` script, which you can use
to create the mappings and load the data set. Before you run it, however, you
must edit the USERNAME and PASSWORD variables with your actual user ID and
password.
to create the mappings and load the data set. You can download it by clicking
here: https://download.elastic.co/demos/machine_learning/gettingstarted/upload_server-metrics.sh[upload_server-metrics.sh]
Before you run it, however, you must edit the USERNAME and PASSWORD variables
with your actual user ID and password.
The script runs a command similar to the following example, which sets up a
mapping for the data set:
@ -456,7 +456,9 @@ the progress of {ml} as the data is processed. This view is only available whils
job is running.
TIP: The `create_single_metic.sh` script creates a similar job and data feed by
using the {ml} APIs. For API reference information, see <<ml-apis>>.
using the {ml} APIs. You can download that script by clicking
here: https://download.elastic.co/demos/machine_learning/gettingstarted/create_single_metric.sh[create_single_metric.sh]
For API reference information, see <<ml-apis>>.
[[ml-gs-job1-manage]]
=== Managing Jobs