This causes the snippets to be tested during the build and gives
helpful links to the reader to open the docs in console or copy them
as curl commands.
Relates to #18160
Surprise! You can use sliced scroll to easily parallelize reindex
and friend. They support it because they use the same infrastructure
as a regular search to parse the search request. While we would like
to make an "automatic" option for parallelizing reindex, this manual
option works right now and is pretty convenient!
API:
```
curl -XGET 'localhost:9200/twitter/tweet/_search?scroll=1m' -d '{
"slice": {
"field": "_uid", <1>
"id": 0, <2>
"max": 10 <3>
},
"query": {
"match" : {
"title" : "elasticsearch"
}
}
}
```
<1> (optional) The field name used to do the slicing (_uid by default)
<2> The id of the slice
By default the splitting is done on the shards first and then locally on each shard using the _uid field
with the following formula:
`slice(doc) = floorMod(hashCode(doc._uid), max)`
For instance if the number of shards is equal to 2 and the user requested 4 slices then the slices 0 and 2 are assigned
to the first shard and the slices 1 and 3 are assigned to the second shard.
Each scroll is independent and can be processed in parallel like any scroll request.
Closes#13494
The documentation states that scrolls are automatically closed when all
documents are consumed, but this is not the case. I first tried to fix
the code to close scrolls automatically but this made REST tests fail
because clearing a scroll that is already closed returned a 4xx error
instead of a 2xx code, so this has probably been this way for a very long
time.
Aggregations are collection-wide statistics, which is incompatible with the
collection mode of search_type=SCAN since it doesn't collect all matches on
calls to the search API.
Close#7429
Aggregations are collection-wide statistics so they would always be the same.
In order to save CPU/bandwidth, we can just return them on the first page.
Same as #1642 but for aggregations.