Point in time API

A point in time must be opened explicitly before being used in search requests. The keep_alive parameter tells Elasticsearch how long it should keep a point in time alive, e.g. ?keep_alive=5m.

response = client.open_point_in_time(
  index: 'my-index-000001',
  keep_alive: '1m'
)
puts response

POST /my-index-000001/_pit?keep_alive=1m

The result from the above request includes a id, which should be passed to the id of the pit parameter of a search request.

POST /_search  
{
    "size": 100,  
    "query": {
        "match" : {
            "title" : "elasticsearch"
        }
    },
    "pit": {
	    "id":  "46ToAwMDaWR5BXV1aWQyKwZub2RlXzMAAAAAAAAAACoBYwADaWR4BXV1aWQxAgZub2RlXzEAAAAAAAAAAAEBYQADaWR5BXV1aWQyKgZub2RlXzIAAAAAAAAAAAwBYgACBXV1aWQyAAAFdXVpZDEAAQltYXRjaF9hbGw_gAAAAA==", 
	    "keep_alive": "1m"  
    }
}

The keep_alive parameter, which is passed to a open point in time request and search request, extends the time to live of the corresponding point in time. The value (e.g. 1m, see Time units) does not need to be long enough to process all data — it just needs to be long enough for the next request.

Normally, the background merge process optimizes the index by merging together smaller segments to create new, bigger segments. Once the smaller segments are no longer needed they are deleted. However, open point-in-times prevent the old segments from being deleted since they are still in use.

Additionally, if a segment contains deleted or updated documents then the point in time must keep track of whether each document in the segment was live at the time of the initial search request. Ensure that your nodes have sufficient heap space if you have many open point-in-times on an index that is subject to ongoing deletes or updates. Note that a point-in-time doesn’t prevent its associated indices from being deleted.

You can check how many point-in-times (i.e, search contexts) are open with the nodes stats API:

$params = [
    'metric' => 'indices',
    'index_metric' => 'search',
];
$response = $client->nodes()->stats($params);

resp = client.nodes.stats(metric="indices", index_metric="search")
print(resp)

response = client.nodes.stats(
  metric: 'indices',
  index_metric: 'search'
)
puts response

res, err := es.Nodes.Stats(
	es.Nodes.Stats.WithMetric([]string{"indices"}...),
	es.Nodes.Stats.WithIndexMetric([]string{"search"}...),
)
fmt.Println(res, err)

const response = await client.nodes.stats({
  metric: 'indices',
  index_metric: 'search'
})
console.log(response)

GET /_nodes/stats/indices/search

Point-in-time is automatically closed when its keep_alive has been elapsed. However keeping point-in-times has a cost, as discussed in the previous section. Point-in-times should be closed as soon as they are no longer used in search requests.

DELETE /_pit
{
    "id" : "46ToAwMDaWR5BXV1aWQyKwZub2RlXzMAAAAAAAAAACoBYwADaWR4BXV1aWQxAgZub2RlXzEAAAAAAAAAAAEBYQADaWR5BXV1aWQyKgZub2RlXzIAAAAAAAAAAAwBYgACBXV1aWQyAAAFdXVpZDEAAQltYXRjaF9hbGw_gAAAAA=="
}

The API returns the following response:

{
   "succeeded": true, 
   "num_freed": 3     
}

When paging through a large number of documents, it can be helpful to split the search into multiple slices to consume them independently:

GET /_search
{
  "slice": {
    "id": 0,                      
    "max": 2                      
  },
  "query": {
    "match": {
      "message": "foo"
    }
  },
  "pit": {
    "id": "46ToAwMDaWR5BXV1aWQyKwZub2RlXzMAAAAAAAAAACoBYwADaWR4BXV1aWQxAgZub2RlXzEAAAAAAAAAAAEBYQADaWR5BXV1aWQyKgZub2RlXzIAAAAAAAAAAAwBYgACBXV1aWQyAAAFdXVpZDEAAQltYXRjaF9hbGw_gAAAAA=="
  }
}

GET /_search
{
  "slice": {
    "id": 1,
    "max": 2
  },
  "pit": {
    "id": "46ToAwMDaWR5BXV1aWQyKwZub2RlXzMAAAAAAAAAACoBYwADaWR4BXV1aWQxAgZub2RlXzEAAAAAAAAAAAEBYQADaWR5BXV1aWQyKgZub2RlXzIAAAAAAAAAAAwBYgACBXV1aWQyAAAFdXVpZDEAAQltYXRjaF9hbGw_gAAAAA=="
  },
  "query": {
    "match": {
      "message": "foo"
    }
  }
}

The result from the first request returns documents belonging to the first slice (id: 0) and the result from the second request returns documents in the second slice. Since the maximum number of slices is set to 2 the union of the results of the two requests is equivalent to the results of a point-in-time search without slicing. By default the splitting is done first on the shards, then locally on each shard. The local splitting partitions the shard into contiguous ranges based on Lucene document IDs.

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.