[DOCS] Updates transform screenshots and text (#50059)
|
@ -50,7 +50,7 @@ they purchased. Or you might want to take the currencies or geographies into
|
|||
consideration. What are the most interesting ways you can transform and
|
||||
interpret this data?
|
||||
|
||||
Go to *Machine Learning* > *Data Frames* in {kib} and use the
|
||||
Go to *Management* > *Elasticsearch* > *Transforms* in {kib} and use the
|
||||
wizard to create a {transform}:
|
||||
|
||||
[role="screenshot"]
|
||||
|
@ -63,25 +63,25 @@ Let's add some more aggregations to learn more about our customers' orders. For
|
|||
example, let's calculate the total sum of their purchases, the maximum number of
|
||||
products that they purchased in a single order, and their total number of orders.
|
||||
We'll accomplish this by using the
|
||||
{ref}/search-aggregations-metrics-sum-aggregation.html[`sum` aggregation] on the
|
||||
<<search-aggregations-metrics-sum-aggregation,`sum` aggregation>> on the
|
||||
`taxless_total_price` field, the
|
||||
{ref}/search-aggregations-metrics-max-aggregation.html[`max` aggregation] on the
|
||||
<<search-aggregations-metrics-max-aggregation,`max` aggregation>> on the
|
||||
`total_quantity` field, and the
|
||||
{ref}/search-aggregations-metrics-cardinality-aggregation.html[`cardinality` aggregation]
|
||||
<<search-aggregations-metrics-cardinality-aggregation,`cardinality` aggregation>>
|
||||
on the `order_id` field:
|
||||
|
||||
[role="screenshot"]
|
||||
image::images/ecommerce-pivot2.jpg["Adding multiple aggregations to a {transform} in {kib}"]
|
||||
|
||||
TIP: If you're interested in a subset of the data, you can optionally include a
|
||||
{ref}/search-request-body.html#request-body-search-query[query] element. In this
|
||||
<<request-body-search-query,query>> element. In this
|
||||
example, we've filtered the data so that we're only looking at orders with a
|
||||
`currency` of `EUR`. Alternatively, we could group the data by that field too.
|
||||
If you want to use more complex queries, you can create your {dataframe} from a
|
||||
{kibana-ref}/save-open-search.html[saved search].
|
||||
|
||||
If you prefer, you can use the
|
||||
{ref}/preview-transform.html[preview {transforms} API]:
|
||||
<<preview-transform,preview {transforms} API>>:
|
||||
|
||||
[source,console]
|
||||
--------------------------------------------------
|
||||
|
@ -147,16 +147,13 @@ target index does not exist, it will be created automatically.
|
|||
Since this sample data index is unchanging, let's use the default behavior and
|
||||
just run the {transform} once.
|
||||
|
||||
[role="screenshot"]
|
||||
image::images/ecommerce-batch.jpg["Specifying the {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 {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-transform.html[create {transforms} API]. For
|
||||
<<put-transform,create {transforms} API>>. For
|
||||
example:
|
||||
|
||||
[source,console]
|
||||
|
@ -228,11 +225,11 @@ can stop it.
|
|||
You can start, stop, and manage {transforms} in {kib}:
|
||||
|
||||
[role="screenshot"]
|
||||
image::images/dataframe-transforms.jpg["Managing {transforms} in {kib}"]
|
||||
image::images/manage-transforms.jpg["Managing {transforms} in {kib}"]
|
||||
|
||||
Alternatively, you can use the
|
||||
{ref}/start-transform.html[start {transforms}] and
|
||||
{ref}/stop-transform.html[stop {transforms}] APIs. For
|
||||
<<start-transform,start {transforms}>> and
|
||||
<<stop-transform,stop {transforms}>> APIs. For
|
||||
example:
|
||||
|
||||
[source,console]
|
||||
|
@ -241,6 +238,11 @@ POST _transform/ecommerce-customer-transform/_start
|
|||
--------------------------------------------------
|
||||
// TEST[skip:setup kibana sample data]
|
||||
|
||||
TIP: If you chose a batch {transform}, it is a single operation that has a
|
||||
single checkpoint. You cannot restart it when it's complete. {ctransforms-cap}
|
||||
differ in that they continually increment and process checkpoints as new source
|
||||
data is ingested.
|
||||
|
||||
--
|
||||
|
||||
. Explore the data in your new index.
|
||||
|
@ -255,6 +257,6 @@ image::images/ecommerce-results.jpg["Exploring the new index in {kib}"]
|
|||
|
||||
TIP: If you do not want to keep the {transform}, you can delete it in
|
||||
{kib} or use the
|
||||
{ref}/delete-transform.html[delete {transform} API]. When
|
||||
<<delete-transform,delete {transform} API>>. When
|
||||
you delete a {transform}, its destination index and {kib} index
|
||||
patterns remain.
|
||||
|
|
Before Width: | Height: | Size: 240 KiB |
Before Width: | Height: | Size: 123 KiB |
Before Width: | Height: | Size: 194 KiB |
Before Width: | Height: | Size: 489 KiB After Width: | Height: | Size: 413 KiB |
Before Width: | Height: | Size: 558 KiB After Width: | Height: | Size: 482 KiB |
After Width: | Height: | Size: 192 KiB |
Before Width: | Height: | Size: 92 KiB |
After Width: | Height: | Size: 138 KiB |
|
@ -59,7 +59,7 @@ quantity. The result is an entity-centric index that shows the number of sold
|
|||
items in every product category in the last year.
|
||||
|
||||
[role="screenshot"]
|
||||
image::images/ml-dataframepivot.jpg["Example of a data frame pivot in {kib}"]
|
||||
image::images/pivot-preview.jpg["Example of a {transform} pivot in {kib}"]
|
||||
|
||||
IMPORTANT: The {transform} leaves your source index intact. It
|
||||
creates a new index that is dedicated to the transformed data.
|
||||
|
|