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@@ -50,7 +50,7 @@ they purchased. Or you might want to take the currencies or geographies into
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consideration. What are the most interesting ways you can transform and
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interpret this data?
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-Go to *Machine Learning* > *Data Frames* in {kib} and use the
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+Go to *Management* > *Elasticsearch* > *Transforms* in {kib} and use the
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wizard to create a {transform}:
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[role="screenshot"]
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@@ -63,25 +63,25 @@ Let's add some more aggregations to learn more about our customers' orders. For
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example, let's calculate the total sum of their purchases, the maximum number of
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products that they purchased in a single order, and their total number of orders.
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We'll accomplish this by using the
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-{ref}/search-aggregations-metrics-sum-aggregation.html[`sum` aggregation] on the
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+<<search-aggregations-metrics-sum-aggregation,`sum` aggregation>> on the
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`taxless_total_price` field, the
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-{ref}/search-aggregations-metrics-max-aggregation.html[`max` aggregation] on the
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+<<search-aggregations-metrics-max-aggregation,`max` aggregation>> on the
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`total_quantity` field, and the
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-{ref}/search-aggregations-metrics-cardinality-aggregation.html[`cardinality` aggregation]
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+<<search-aggregations-metrics-cardinality-aggregation,`cardinality` aggregation>>
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on the `order_id` field:
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[role="screenshot"]
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image::images/ecommerce-pivot2.jpg["Adding multiple aggregations to a {transform} in {kib}"]
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TIP: If you're interested in a subset of the data, you can optionally include a
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-{ref}/search-request-body.html#request-body-search-query[query] element. In this
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+<<request-body-search-query,query>> element. In this
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example, we've filtered the data so that we're only looking at orders with a
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`currency` of `EUR`. Alternatively, we could group the data by that field too.
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If you want to use more complex queries, you can create your {dataframe} from a
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{kibana-ref}/save-open-search.html[saved search].
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If you prefer, you can use the
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-{ref}/preview-transform.html[preview {transforms} API]:
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+<<preview-transform,preview {transforms} API>>:
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[source,console]
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--------------------------------------------------
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@@ -147,16 +147,13 @@ target index does not exist, it will be created automatically.
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Since this sample data index is unchanging, let's use the default behavior and
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just run the {transform} once.
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-[role="screenshot"]
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-image::images/ecommerce-batch.jpg["Specifying the {transform} options in {kib}"]
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-
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If you want to try it out, however, go ahead and click on *Continuous mode*.
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You must choose a field that the {transform} can use to check which
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entities have changed. In general, it's a good idea to use the ingest timestamp
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field. In this example, however, you can use the `order_date` field.
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If you prefer, you can use the
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-{ref}/put-transform.html[create {transforms} API]. For
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+<<put-transform,create {transforms} API>>. For
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example:
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[source,console]
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@@ -228,11 +225,11 @@ can stop it.
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You can start, stop, and manage {transforms} in {kib}:
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[role="screenshot"]
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-image::images/dataframe-transforms.jpg["Managing {transforms} in {kib}"]
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+image::images/manage-transforms.jpg["Managing {transforms} in {kib}"]
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Alternatively, you can use the
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-{ref}/start-transform.html[start {transforms}] and
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-{ref}/stop-transform.html[stop {transforms}] APIs. For
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+<<start-transform,start {transforms}>> and
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+<<stop-transform,stop {transforms}>> APIs. For
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example:
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[source,console]
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@@ -241,6 +238,11 @@ POST _transform/ecommerce-customer-transform/_start
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--------------------------------------------------
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// TEST[skip:setup kibana sample data]
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+TIP: If you chose a batch {transform}, it is a single operation that has a
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+single checkpoint. You cannot restart it when it's complete. {ctransforms-cap}
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+differ in that they continually increment and process checkpoints as new source
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+data is ingested.
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+
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--
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. Explore the data in your new index.
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@@ -255,6 +257,6 @@ image::images/ecommerce-results.jpg["Exploring the new index in {kib}"]
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TIP: If you do not want to keep the {transform}, you can delete it in
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{kib} or use the
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-{ref}/delete-transform.html[delete {transform} API]. When
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+<<delete-transform,delete {transform} API>>. When
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you delete a {transform}, its destination index and {kib} index
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patterns remain.
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