[DOCS] Adds data frame eCommerce example #372
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szabosteve
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szabosteve
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I had a minor note.
LGTM
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| <<ml-dataframes,{dataframes-cap}>> enable you to retrieve information from an | ||
| {es} index, transform it, and store it in a new index. Let's use the |
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Would it be worth to mention that it is not necessary to store it in a new index? AFAIK, you can re-use an existing index, too. Maybe to change to "...store it in an index"? Not sure though.
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It would be better to say store it in another index as the destination index has to be different than any of the source indices.
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| <<ml-dataframes,{dataframes-cap}>> enable you to retrieve information from an | ||
| {es} index, transform it, and store it in a new index. Let's use the |
There was a problem hiding this comment.
It would be better to say store it in another index as the destination index has to be different than any of the source indices.
| "query": { | ||
| "query_string": { | ||
| "query": "currency : EUR", | ||
| "default_operator": "AND" |
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It would be good to make this an actual filter
"query": {
"bool": {
"filter": {"term": {"currency": "EUR"}}
}
}
Same goes for other queries used.
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Thanks @benwtrent I've updated the preview and create data frame transform API examples to use that filter. I've also updated the query-related tip to recommend that folks use saved searches for more complex queries in Kibana.
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| TIP: A {dataframe-transform} increases search and indexing load on your cluster |
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Might be nice to add something like Even though resource utilization is automatically adjusted based on cluster load, a {dataframe-transform}...
We adjust the pagination size of the aggregations whenever we hit a OOM circuit breaker so that we don't break due to cluster load.
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This PR adds a page in the Stack Overview which describes how to use data frame transforms on the Kibana sample eCommerce data.