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[DOCS] Fixes formatting in transform overview (#53900)

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Lisa Cawley 2020-03-23 10:20:41 -07:00 committed by lcawl
parent 5ac8b795ba
commit c4260ba3c7
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docs/reference/transform/overview.asciidoc
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@ -28,20 +28,18 @@ The second step is deciding how you want to aggregate the grouped data. When
using aggregations, you practically ask questions about the index. There are using aggregations, you practically ask questions about the index. There are
different types of aggregations, each with its own purpose and output. To learn different types of aggregations, each with its own purpose and output. To learn
more about the supported aggregations and group-by fields, see more about the supported aggregations and group-by fields, see
{ref}/transform-resource.html[{transform-cap} resources]. <<put-transform>>.
As an optional step, you can also add a query to further limit the scope of the As an optional step, you can also add a query to further limit the scope of the
aggregation. aggregation.
The {transform} performs a composite aggregation that paginates through all the The {transform} performs a composite aggregation that paginates through all the
data defined by the source index query. The output of the aggregation is stored data defined by the source index query. The output of the aggregation is stored
in a destination index. Each time the {transform} queries the source index, it in a _destination index_. Each time the {transform} queries the source index, it
creates a _checkpoint_. You can decide whether you want the {transform} to run creates a _checkpoint_. You can decide whether you want the {transform} to run
once (batch {transform}) or continuously ({ctransform}). A batch {transform} is a once or continuously. A _batch {transform}_ is a single operation that has a
single operation that has a single checkpoint. {ctransforms-cap} continually single checkpoint. _{ctransforms-cap}_ continually increment and process
increment and process checkpoints as new source data is ingested. checkpoints as new source data is ingested.
.Example
Imagine that you run a webshop that sells clothes. Every order creates a Imagine that you run a webshop that sells clothes. Every order creates a
document that contains a unique order ID, the name and the category of the document that contains a unique order ID, the name and the category of the
@ -72,7 +70,7 @@ indices then index the results into the destination index. Therefore, a
aggregation that it performs and the indexing process. aggregation that it performs and the indexing process.
For better performance, make sure that your search aggregations and queries are For better performance, make sure that your search aggregations and queries are
optimized, so they don't process unnecessary data. optimized and that your {transform} is processing only necessary data.
NOTE: When you use <<search-aggregations-bucket-datehistogram-aggregation>>, the NOTE: When you use <<search-aggregations-bucket-datehistogram-aggregation>>, the
queries are not considered optimal as they run through a significant amount of queries are not considered optimal as they run through a significant amount of