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[DOCS] Updates screenshots in data frame example #410

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47 changes: 31 additions & 16 deletions docs/en/stack/data-frames/ecommerce-example.asciidoc
Original file line number Diff line number Diff line change
@@ -1,7 +1,7 @@
[role="xpack"]
[testenv="basic"]
[[ecommerce-dataframes]]
== Transforming your data with {dataframes}
== Transforming your data in {dataframes}
++++
<titleabbrev>Transforming your data</titleabbrev>
++++
Expand All @@ -27,6 +27,8 @@ index and `read`, `create_index`, and `index` privileges on the destination
index.

For more information, see <<security-privileges>> and <<built-in-roles>>.

//TBD: Determine additional Kibana security privileges required.
--

. Choose your _source index_.
Expand Down Expand Up @@ -54,10 +56,10 @@ at least one aggregation. You can preview what the transformed data will look
like, so go ahead and play with it!

For example, go to *Machine Learning* > *Data Frames* in {kib} and use the
wizard to create a {dataframe}:
wizard to create a {dataframe-transform}:

[role="screenshot"]
image::images/ecommerce-pivot1.jpg["Creating a simple {dataframe} in {kib}"]
image::images/ecommerce-pivot1.jpg["Creating a simple {dataframe-transform} in {kib}"]

In this case, we grouped the data by customer ID and calculated the sum of
products each customer purchased.
Expand All @@ -74,7 +76,7 @@ We'll accomplish this by using the
on the `order_id` field:

[role="screenshot"]
image::images/ecommerce-pivot2.jpg["Adding multiple aggregations to a {dataframe} in {kib}"]
image::images/ecommerce-pivot2.jpg["Adding multiple aggregations to a {dataframe-transform} in {kib}"]

TIP: If you're interested in a subset of the data, you can optionally include a
{ref}/search-request-query.html[query] element. In this example, we've filtered
Expand Down Expand Up @@ -141,9 +143,22 @@ POST _data_frame/transforms/_preview
{dataframe-transform}.
+
--
Supply a job ID and the name of the target (or _destination_) index. In {kib},
you can choose to create and start the job, create it, or copy it to the
clipboard.
.. Supply a job ID and the name of the target (or _destination_) index.

.. Decide whether you want the {dataframe-transform} to run once or continuously.
--
+
--
Since this sample data index is unchanging, let's use the default behavior and
just run the {dataframe-transform} once.

[role="screenshot"]
image::images/ecommerce-batch.jpg["Specifying the {dataframe-transform} options in {kib}"]

If you want to try it out, however, go ahead and click on *Continuous mode*.
You must choose a field that the {dataframe-transform} can use to check which
entities have changed. In general, it's a good idea to use the ingest timestamp
field. In this example, however, you can use the `order_date` field.

If you prefer, you can use the
{ref}/put-data-frame-transform.html[create {dataframe-transforms} API]. For
Expand All @@ -167,9 +182,6 @@ PUT _data_frame/transforms/ecommerce-customer-transform
}
}
},
"dest": {
"index": "ecommerce-customers"
},
"pivot": {
"group_by": {
"customer_id": {
Expand Down Expand Up @@ -200,6 +212,9 @@ PUT _data_frame/transforms/ecommerce-customer-transform
}
}
}
},
"dest": {
"index": "ecommerce-customers"
}
}
--------------------------------------------------
Expand All @@ -213,14 +228,13 @@ PUT _data_frame/transforms/ecommerce-customer-transform

TIP: Even though resource utilization is automatically adjusted based on the
cluster load, a {dataframe-transform} increases search and indexing load on your
cluster while it runs. When it reaches the end of the data in your index, it
stops automatically. If you're experiencing an excessive load, however, you can
stop it sooner.
cluster while it runs. If you're experiencing an excessive load, however, you
can stop it.

You can start, stop, and manage {dataframe} jobs in {kib}:
You can start, stop, and manage {dataframe-transforms} in {kib}:

[role="screenshot"]
image::images/dataframe-jobs.jpg["Managing {dataframe} jobs in {kib}"]
image::images/dataframe-transforms.jpg["Managing {dataframe-transforms} in {kib}"]

Alternatively, you can use the
{ref}/start-data-frame-transform.html[start {dataframe-transforms}] and
Expand Down Expand Up @@ -249,4 +263,5 @@ image::images/ecommerce-results.jpg["Exploring the new index in {kib}"]
TIP: If you do not want to keep the {dataframe-transform}, you can delete it in
{kib} or use the
{ref}/delete-data-frame-transform.html[delete {dataframe-transform} API]. When
you delete a {dataframe-transform}, its destination index remains.
you delete a {dataframe-transform}, its destination index and {kib} index
patterns remain.
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