Full text search of Elasticsearch

Usage,
Search(
  conn,
  index = NULL,
  type = NULL,
  q = NULL,
  df = NULL,
  analyzer = NULL,
  default_operator = NULL,
  explain = NULL,
  source = NULL,
  fields = NULL,
  sort = NULL,
  track_scores = NULL,
  timeout = NULL,
  terminate_after = NULL,
  from = NULL,
  size = NULL,
  search_type = NULL,
  lowercase_expanded_terms = NULL,
  analyze_wildcard = NULL,
  version = NULL,
  lenient = NULL,
  body = list(),
  raw = FALSE,
  asdf = FALSE,
  track_total_hits = TRUE,
  time_scroll = NULL,
  search_path = "_search",
  stream_opts = list(),
  ignore_unavailable = FALSE,
  ...
)

Arguments

conn

an Elasticsearch connection object, see connect

index

Index name, one or more

type

Document type. Note that type is deprecated in Elasticsearch v7 and greater, and removed in Elasticsearch v8. We will strive to support types for folks using older ES versions

q

The query string (maps to the query_string query, see Query String Query for more details). See https://www.elastic.co/guide/en/elasticsearch/reference/current/query-dsl-query-string-query.html for documentation and examples.

df

(character) The default field to use when no field prefix is defined within the query.

analyzer

(character) The analyzer name to be used when analyzing the query string.

default_operator

(character) The default operator to be used, can be AND or OR. Default: OR

explain

(logical) For each hit, contain an explanation of how scoring of the hits was computed. Default: FALSE

source

(logical) Set to FALSE to disable retrieval of the _source field. You can also retrieve part of the document by using _source_include & _source_exclude (see the body documentation for more details). You can also include a comma-delimited string of fields from the source document that you want back. See also the fields parameter

fields

(character) The selective stored fields of the document to return for each hit. Not specifying any value will cause no fields to return. Note that in Elasticsearch v5 and greater, fields parameter has changed to stored_fields, which is not on by default. You can however, pass fields to source parameter

sort

(character) Sorting to perform. Can either be in the form of fieldName, or fieldName:asc/fieldName:desc. The fieldName can either be an actual field within the document, or the special _score name to indicate sorting based on scores. There can be several sort parameters (order is important).

track_scores

(logical) When sorting, set to TRUE in order to still track scores and return them as part of each hit.

timeout

(numeric) A search timeout, bounding the search request to be executed within the specified time value and bail with the hits accumulated up to that point when expired. Default: no timeout.

terminate_after

(numeric) The maximum number of documents to collect for each shard, upon reaching which the query execution will terminate early. If set, the response will have a boolean field terminated_early to indicate whether the query execution has actually terminated_early. Default: no terminate_after

from

(character) The starting from index of the hits to return. Pass in as a character string to avoid problems with large number conversion to scientific notation. Default: 0

size

(character) The number of hits to return. Pass in as a character string to avoid problems with large number conversion to scientific notation. Default: 10. The default maximum is 10,000 - however, you can change this default maximum by changing the index.max_result_window index level parameter.

search_type

(character) The type of the search operation to perform. Can be query_then_fetch (default) or dfs_query_then_fetch. Types scan and count are deprecated. See Elasticsearch docs for more details on the different types of search that can be performed.

lowercase_expanded_terms

(logical) Should terms be automatically lowercased or not. Default: TRUE.

analyze_wildcard

(logical) Should wildcard and prefix queries be analyzed or not. Default: FALSE.

version

(logical) Print the document version with each document.

lenient

(logical) If TRUE will cause format based failures (like providing text to a numeric field) to be ignored. Default: NULL

body

Query, either a list or json.

raw

(logical) If FALSE (default), data is parsed to list. If TRUE, then raw JSON returned

asdf

(logical) If TRUE, use fromJSON to parse JSON directly to a data.frame. If FALSE (Default), list output is given.

track_total_hits

(logical, numeric) If TRUE will always track the number of hits that match the query accurately. If FALSE will count documents accurately up to 10000 documents. If is.integer will count documents accurately up to the number. Default: TRUE

time_scroll

(character) Specify how long a consistent view of the index should be maintained for scrolled search, e.g., "30s", "1m". See units-time

search_path

(character) The path to use for searching. Default to _search, but in some cases you may already have that in the base url set using connect(), in which case you can set this to NULL

stream_opts

(list) A list of options passed to stream_out - Except that you can't pass x as that's the data that's streamed out, and pass a file path instead of a connection to con. pagesize param doesn't do much as that's more or less controlled by paging with ES.

ignore_unavailable

(logical) What to do if an specified index name doesn't exist. If set to TRUE then those indices are ignored.

...

Curl args passed on to verb-POST

Details

This function name has the "S" capitalized to avoid conflict with the function base::search. I hate mixing cases, as I think it confuses users, but in this case it seems neccessary.

profile

The Profile API provides detailed timing information about the execution of individual components in a search request. See https://www.elastic.co/guide/en/elasticsearch/reference/current/search-profile.html for more information

In a body query, you can set to profile: true to enable profiling results. e.g.


{
  "profile": true,
  "query" : {
    "match" : { "message" : "some number" }
  }
}

Examples

if (FALSE) {
# make connection object
(x <- connect())

# load some data
if (!index_exists(x, "shakespeare")) {
  shakespeare <- system.file("examples", "shakespeare_data.json",
    package = "elastic")
  shakespeare <- type_remover(shakespeare)
  invisible(docs_bulk(x, shakespeare))
}
if (!index_exists(x, "gbif")) {
  gbif <- system.file("examples", "gbif_data.json",
    package = "elastic")
  gbif <- type_remover(gbif)
  invisible(docs_bulk(x, gbif))
}
if (!index_exists(x, "plos")) {
  plos <- system.file("examples", "plos_data.json",
    package = "elastic")
  plos <- type_remover(plos)
  invisible(docs_bulk(x, plos))
}


# URI string queries
Search(x, index="shakespeare")
## if you're using an older ES version, you may have types
if (gsub("\\.", "", x$ping()$version$number) < 700) {
  Search(x, index="shakespeare", type="act")
  Search(x, index="shakespeare", type="scene")
  Search(x, index="shakespeare", type="line")
}

## Return certain fields
if (gsub("\\.", "", x$ping()$version$number) < 500) {
  ### ES < v5
  Search(x, index="shakespeare", fields=c('play_name','speaker'))
} else {
  ### ES > v5
  Search(x, index="shakespeare", body = '{
   "_source": ["play_name", "speaker"]
  }')
}

## Search multiple indices
Search(x, index = "gbif")$hits$total$value
Search(x, index = "shakespeare")$hits$total$value
Search(x, index = c("gbif", "shakespeare"))$hits$total$value

## search_type
Search(x, index="shakespeare", search_type = "query_then_fetch")
Search(x, index="shakespeare", search_type = "dfs_query_then_fetch")
### search type "scan" is gone - use time_scroll instead
Search(x, index="shakespeare", time_scroll = "2m")
### search type "count" is gone - use size=0 instead
Search(x, index="shakespeare", size = 0)$hits$total$value

## search exists check
### use size set to 0 and terminate_after set to 1
### if there are > 0 hits, then there are matching documents
Search(x, index="shakespeare", size = 0, terminate_after = 1)

## sorting
### if ES >5, we need to make sure fielddata is turned on for a field 
### before using it for sort 
if (gsub("\\.", "", x$ping()$version$number) >= 500) {
 if (index_exists(x, "shakespeare")) index_delete(x, "shakespeare")
 index_create(x, "shakespeare")
 mapping_create(x, "shakespeare", body = '{
    "properties": {
      "speaker": { 
        "type":     "text",
        "fielddata": true
      }
    }
  }'
 )
 shakespeare <- system.file("examples", "shakespeare_data.json",
   package = "elastic")
 shakespeare <- type_remover(shakespeare)
 invisible(docs_bulk(x, shakespeare))
 z <- Search(x, index="shakespeare", sort="speaker", size = 30)
 vapply(z$hits$hits, function(w) w$`_source`$speaker, "")
}

if (gsub("\\.", "", x$ping()$version$number) < 500) {
  Search(x, index="shakespeare", type="line", sort="speaker:desc", 
    fields='speaker')
  Search(x, index="shakespeare", type="line",
    sort=c("speaker:desc","play_name:asc"), fields=c('speaker','play_name'))
}


## pagination
Search(x, index="shakespeare", size=1)$hits$hits
Search(x, index="shakespeare", size=1, from=1)$hits$hits

## queries
### Search in all fields
Search(x, index="shakespeare", q="york")

### Searchin specific fields
Search(x, index="shakespeare", q="speaker:KING HENRY IV")$hits$total$value

### Exact phrase search by wrapping in quotes
Search(x, index="shakespeare", q='speaker:"KING HENRY IV"')$hits$total$value

### can specify operators between multiple words parenthetically
Search(x, index="shakespeare", q="speaker:(HENRY OR ARCHBISHOP)")$hits$total$value

### where the field line_number has no value (or is missing)
Search(x, index="shakespeare", q="_missing_:line_number")$hits$total$value

### where the field line_number has any non-null value
Search(x, index="shakespeare", q="_exists_:line_number")$hits$total$value

### wildcards, either * or ?
Search(x, index="shakespeare", q="*ay")$hits$total$value
Search(x, index="shakespeare", q="m?y")$hits$total$value

### regular expressions, wrapped in forward slashes
Search(x, index="shakespeare", q="text_entry:/[a-z]/")$hits$total$value

### fuzziness
Search(x, index="shakespeare", q="text_entry:ma~")$hits$total$value
Search(x, index="shakespeare", q="text_entry:the~2")$hits$total$value
Search(x, index="shakespeare", q="text_entry:the~1")$hits$total$value

### Proximity searches
Search(x, index="shakespeare", q='text_entry:"as hath"~5')$hits$total$value
Search(x, index="shakespeare", q='text_entry:"as hath"~10')$hits$total$value

### Ranges, here where line_id value is between 10 and 20
Search(x, index="shakespeare", q="line_id:[10 TO 20]")$hits$total$value

### Grouping
Search(x, index="shakespeare", q="(hath OR as) AND the")$hits$total$value

# Limit number of hits returned with the size parameter
Search(x, index="shakespeare", size=1)

# Give explanation of search in result
Search(x, index="shakespeare", size=1, explain=TRUE)

## terminate query after x documents found
## setting to 1 gives back one document for each shard
Search(x, index="shakespeare", terminate_after=1)
## or set to other number
Search(x, index="shakespeare", terminate_after=2)

## Get version number for each document
Search(x, index="shakespeare", version=TRUE, size=2)

## Get raw data
Search(x, index="shakespeare", raw = TRUE)

## Curl options 
### verbose 
out <- Search(x, index="shakespeare", verbose = TRUE)


# Query DSL searches - queries sent in the body of the request
## Pass in as an R list

### if ES >5, we need to make sure fielddata is turned on for a field 
### before using it for aggregations 
if (gsub("\\.", "", x$ping()$version$number) >= 500) {
  mapping_create(x, "shakespeare", update_all_types = TRUE, body = '{
    "properties": {
      "text_entry": { 
        "type":     "text",
        "fielddata": true
     }
   }
 }')
 aggs <- list(aggs = list(stats = list(terms = list(field = "text_entry"))))
 Search(x, index="shakespeare", body=aggs)
}

### if ES >5, you don't need to worry about fielddata
if (gsub("\\.", "", x$ping()$version$number) < 500) {
   aggs <- list(aggs = list(stats = list(terms = list(field = "text_entry"))))
   Search(x, index="shakespeare", body=aggs)
}

## or pass in as json query with newlines, easy to read
aggs <- '{
    "aggs": {
        "stats" : {
            "terms" : {
                "field" : "speaker"
            }
        }
    }
}'
Search(x, index="shakespeare", body=aggs, asdf=TRUE, size = 0)

## or pass in collapsed json string
aggs <- '{"aggs":{"stats":{"terms":{"field":"text_entry"}}}}'
Search(x, index="shakespeare", body=aggs)


## Aggregations
### Histograms
aggs <- '{
    "aggs": {
        "latbuckets" : {
           "histogram" : {
               "field" : "decimalLatitude",
               "interval" : 5
           }
        }
    }
}'
Search(x, index="gbif", body=aggs, size=0)

### Histograms w/ more options
aggs <- '{
    "aggs": {
        "latbuckets" : {
           "histogram" : {
               "field" : "decimalLatitude",
               "interval" : 5,
               "min_doc_count" : 0,
               "extended_bounds" : {
                   "min" : -90,
                   "max" : 90
               }
           }
        }
    }
}'
Search(x, index="gbif", body=aggs, size=0)

### Ordering the buckets by their doc_count - ascending:
aggs <- '{
    "aggs": {
        "latbuckets" : {
           "histogram" : {
               "field" : "decimalLatitude",
               "interval" : 5,
               "min_doc_count" : 0,
               "extended_bounds" : {
                   "min" : -90,
                   "max" : 90
               },
               "order" : {
                   "_count" : "desc"
               }
           }
        }
    }
}'
out <- Search(x, index="gbif", body=aggs, size=0)
lapply(out$aggregations$latbuckets$buckets, data.frame)

### By default, the buckets are returned as an ordered array. It is also possible to
### request the response as a hash instead keyed by the buckets keys:
aggs <- '{
    "aggs": {
        "latbuckets" : {
           "histogram" : {
               "field" : "decimalLatitude",
               "interval" : 10,
               "keyed" : true
           }
        }
    }
}'
Search(x, index="gbif", body=aggs, size=0)

# match query
match <- '{"query": {"match" : {"text_entry" : "Two Gentlemen"}}}'
Search(x, index="shakespeare", body=match)

# multi-match (multiple fields that is) query
mmatch <- '{"query": {"multi_match" : {"query" : "henry", "fields": ["text_entry","play_name"]}}}'
Search(x, index="shakespeare", body=mmatch)

# bool query
mmatch <- '{
 "query": {
   "bool" : {
     "must_not" : {
       "range" : {
         "speech_number" : {
           "from" : 1, "to": 5
}}}}}}'
Search(x, index="shakespeare", body=mmatch)

# Boosting query
boost <- '{
 "query" : {
  "boosting" : {
      "positive" : {
          "term" : {
              "play_name" : "henry"
          }
      },
      "negative" : {
          "term" : {
              "text_entry" : "thou"
          }
      },
      "negative_boost" : 0.8
    }
 }
}'
Search(x, index="shakespeare", body=boost)

# Fuzzy query
## fuzzy query on numerics
fuzzy <- list(query = list(fuzzy = list(text_entry = "arms")))
Search(x, index="shakespeare", body=fuzzy)$hits$total$value
fuzzy <- list(query = list(fuzzy = list(text_entry = list(value = "arms", fuzziness = 4))))
Search(x, index="shakespeare", body=fuzzy)$hits$total$value

# geoshape query
## not working yets
geo <- list(query = list(geo_shape = list(location = list(shape = list(type = "envelope",
   coordinates = "[[2,10],[10,20]]")))))
geo <- '{
 "query": {
   "geo_shape": {
     "location": {
       "point": {
         "type": "envelope",
         "coordinates": [[2,0],[2.93,100]]
       }
     }
   }
 }
}'
# Search(x, index="gbifnewgeo", body=geo)

# range query
## with numeric
body <- list(query=list(range=list(decimalLongitude=list(gte=1, lte=3))))
Search(x, 'gbif', body=body)$hits$total$value

body <- list(query=list(range=list(decimalLongitude=list(gte=2.9, lte=10))))
Search(x, 'gbif', body=body)$hits$total$value

## with dates
body <- list(query=list(range=list(eventDate=list(gte="2012-01-01", lte="now"))))
Search(x, 'gbif', body=body)$hits$total$value

body <- list(query=list(range=list(eventDate=list(gte="2014-01-01", lte="now"))))
Search(x, 'gbif', body=body)$hits$total$value

# more like this query (more_like_this can be shortened to mlt)
body <- '{
 "query": {
   "more_like_this": {
     "fields": ["title"],
     "like": "and then",
     "min_term_freq": 1,
     "max_query_terms": 12
   }
 }
}'
Search(x, 'plos', body=body)$hits$total$value

body <- '{
 "query": {
   "more_like_this": {
     "fields": ["abstract","title"],
     "like": "cell",
     "min_term_freq": 1,
     "max_query_terms": 12
   }
 }
}'
Search(x, 'plos', body=body)$hits$total$value

# Highlighting
body <- '{
 "query": {
   "query_string": {
     "query" : "cell"
   }
 },
 "highlight": {
   "fields": {
     "title": {"number_of_fragments": 2}
   }
 }
}'
out <- Search(x, 'plos', body=body)
out$hits$total$value
sapply(out$hits$hits, function(x) x$`_source`$title[[1]])

### Common terms query
body <- '{
 "query" : {
   "match": {
      "text_entry": {
         "query": "this is"
      }
   }
 }
}'
Search(x, 'shakespeare', body=body)

## Scrolling search - instead of paging
res <- Search(x, index = 'shakespeare', q="a*", time_scroll="1m")
scroll(x, res$`_scroll_id`)

res <- Search(x, index = 'shakespeare', q="a*", time_scroll="5m")
out <- list()
hits <- 1
while(hits != 0){
  res <- scroll(x, res$`_scroll_id`)
  hits <- length(res$hits$hits)
  if(hits > 0)
    out <- c(out, res$hits$hits)
}

### Sliced scrolling
#### For scroll queries that return a lot of documents it is possible to 
#### split the scroll in multiple slices which can be consumed independently
body1 <- '{
  "slice": {
    "id": 0, 
    "max": 2 
  },
  "query": {
    "match" : {
      "text_entry" : "a*"
    }
  }
}'

body2 <- '{
  "slice": {
    "id": 1, 
    "max": 2 
  },
  "query": {
    "match" : {
      "text_entry" : "a*"
    }
  }
}'

res1 <- Search(x, index = 'shakespeare', time_scroll="1m", body = body1)
res2 <- Search(x, index = 'shakespeare', time_scroll="1m", body = body2)
scroll(x, res1$`_scroll_id`)
scroll(x, res2$`_scroll_id`)

out1 <- list()
hits <- 1
while(hits != 0){
  tmp1 <- scroll(x, res1$`_scroll_id`)
  hits <- length(tmp1$hits$hits)
  if(hits > 0)
    out1 <- c(out1, tmp1$hits$hits)
}

out2 <- list()
hits <- 1
while(hits != 0) {
  tmp2 <- scroll(x, res2$`_scroll_id`)
  hits <- length(tmp2$hits$hits)
  if(hits > 0)
    out2 <- c(out2, tmp2$hits$hits)
}

c(
 lapply(out1, "[[", "_source"),
 lapply(out2, "[[", "_source")
) 



# Using filters
## A bool filter
body <- '{
 "query":{
   "bool": {
     "must_not" : {
       "range" : {
         "year" : { "from" : 2011, "to" : 2012 }
       }
     }
   }
 }
}'
Search(x, 'gbif', body = body)$hits$total$value

## Geo filters - fun!
### Note that filers have many geospatial filter options, but queries 
### have fewer, andrequire a geo_shape mapping

body <- '{
 "mappings": {
     "properties": {
         "location" : {"type" : "geo_point"}
      }
   }
}'
index_recreate(x, index='gbifgeopoint', body=body)
path <- system.file("examples", "gbif_geopoint.json",
  package = "elastic")
path <- type_remover(path)
invisible(docs_bulk(x, path))

### Points within a bounding box
body <- '{
 "query":{
   "bool" : {
     "must" : {
       "match_all" : {}
     },
     "filter":{
        "geo_bounding_box" : {
          "location" : {
            "top_left" : {
              "lat" : 60,
              "lon" : 1
            },
            "bottom_right" : {
              "lat" : 40,
              "lon" : 14
            }
          }
       }
     }
   }
 }
}'
out <- Search(x, 'gbifgeopoint', body = body, size = 300)
out$hits$total$value
do.call(rbind, lapply(out$hits$hits, function(x) x$`_source`$location))

### Points within distance of a point
body <- '{
"query": {
  "bool" : {
    "must" : {
      "match_all" : {}
    },
   "filter" : {
     "geo_distance" : {
       "distance" : "200km",
       "location" : {
         "lon" : 4,
         "lat" : 50
       }
     }
  }
}}}'
out <- Search(x, 'gbifgeopoint', body = body)
out$hits$total$value
do.call(rbind, lapply(out$hits$hits, function(x) x$`_source`$location))

### Points within distance range of a point
body <- '{
 "aggs":{
   "points_within_dist" : {
     "geo_distance" : {
        "field": "location",
        "origin" : "4, 50",
        "ranges": [ 
          {"from" : 200},
          {"to" : 400}
         ]
     }
   }
 }
}'
out <- Search(x, 'gbifgeopoint', body = body)
out$hits$total$value
do.call(rbind, lapply(out$hits$hits, function(x) x$`_source`$location))

### Points within a polygon
body <- '{
 "query":{
   "bool" : {
     "must" : {
       "match_all" : {}
     },
     "filter":{
        "geo_polygon" : {
          "location" : {
             "points" : [
               [80.0, -20.0], [-80.0, -20.0], [-80.0, 60.0], [40.0, 60.0], [80.0, -20.0]
             ]
           }
         }
       }
     }
   }
}'
out <- Search(x, 'gbifgeopoint', body = body)
out$hits$total$value
do.call(rbind, lapply(out$hits$hits, function(x) x$`_source`$location))

### Geoshape filters using queries instead of filters
#### Get data with geojson type location data loaded first
body <- '{
 "mappings": {
     "properties": {
         "location" : {"type" : "geo_shape"}
      }
   }
}'
index_recreate(x, index='geoshape', body=body)
path <- system.file("examples", "gbif_geoshape.json",
  package = "elastic")
path <- type_remover(path)
invisible(docs_bulk(x, path))

#### Get data with a square envelope, w/ point defining upper left and the other
#### defining the lower right
body <- '{
 "query":{
   "geo_shape" : {
     "location" : {
         "shape" : {
           "type": "envelope",
            "coordinates": [[-30, 50],[30, 0]]
         }
       }
     }
   }
}'
out <- Search(x, 'geoshape', body = body)
out$hits$total$value

#### Get data with a circle, w/ point defining center, and radius
body <- '{
 "query":{
   "geo_shape" : {
     "location" : {
         "shape" : {
           "type": "circle",
           "coordinates": [-10, 45],
           "radius": "2000km"
         }
       }
     }
   }
}'
out <- Search(x, 'geoshape', body = body)
out$hits$total$value

#### Use a polygon, w/ point defining center, and radius
body <- '{
 "query":{
   "geo_shape" : {
     "location" : {
         "shape" : {
           "type": "polygon",
           "coordinates":  [
              [ [80.0, -20.0], [-80.0, -20.0], [-80.0, 60.0], [40.0, 60.0], [80.0, -20.0] ]
           ]
         }
       }
     }
   }
}'
out <- Search(x, 'geoshape', body = body)
out$hits$total$value


# Geofilter with WKT
# format follows "BBOX (minlon, maxlon, maxlat, minlat)"
body <- '{
    "query": {
        "bool" : {
            "must" : {
                "match_all" : {}
            },
            "filter" : {
                "geo_bounding_box" : {
                    "location" : {
                        "wkt" : "BBOX (1, 14, 60, 40)"
                    }
                }
            }
        }
    }
}'
out <- Search(x, 'gbifgeopoint', body = body)
out$hits$total$value



# Missing filter
if (gsub("\\.", "", x$ping()$version$number) < 500) {
  ### ES < v5
  body <- '{
   "query":{
     "constant_score" : {
       "filter" : {
         "missing" : { "field" : "play_name" }
       }
     }
    }
  }'
  Search(x, "shakespeare", body = body)
} else {
  ### ES => v5
  body <- '{
   "query":{
     "bool" : {
       "must_not" : {
         "exists" : { 
           "field" : "play_name" 
         }
       }
    }
   }
  }'
  Search(x, "shakespeare", body = body)
}

# prefix filter
body <- '{
 "query": {
   "bool": {
     "must": {
       "prefix" : {
         "speaker" : "we"
       }
     }
   }
 }
}'
z <- Search(x, "shakespeare", body = body)
z$hits$total$value
vapply(z$hits$hits, "[[", "", c("_source", "speaker"))


# ids filter
if (gsub("\\.", "", x$ping()$version$number) < 500) {
  ### ES < v5
  body <- '{
   "query":{
     "bool": {
       "must": {
         "ids" : {
           "values": ["1","2","10","2000"]
        }
      }
    }
   }
  }'
  z <- Search(x, "shakespeare", body = body)
  z$hits$total$value
  identical(
   c("1","2","10","2000"),
   vapply(z$hits$hits, "[[", "", "_id")
  )
} else {
  body <- '{
   "query":{
     "ids" : {
       "values": ["1","2","10","2000"]
     }
   }
  }'
  z <- Search(x, "shakespeare", body = body)
  z$hits$total$value
  identical(
   c("1","2","10","2000"),
   vapply(z$hits$hits, "[[", "", "_id")
  )
}

# combined prefix and ids filters
if (gsub("\\.", "", x$ping()$version$number) < 500) {
  ### ES < v5
  body <- '{
   "query":{
     "bool" : {
       "should" : {
         "or": [{
           "ids" : {
             "values": ["1","2","3","10","2000"]
           }
         }, {
         "prefix" : {
           "speaker" : "we"
         }
        }
      ]
     }
    }
   }
  }'
  z <- Search(x, "shakespeare", body = body)
  z$hits$total$value
} else {
  ### ES => v5
  body <- '{
   "query":{
     "bool" : {
       "should" : [
         {
           "ids" : {
             "values": ["1","2","3","10","2000"]
           }
         }, 
         {
           "prefix" : {
             "speaker" : "we"
           }
         }
      ]
     }
    }
  }'
  z <- Search(x, "shakespeare", body = body)
  z$hits$total$value
}

# Suggestions
sugg <- '{
 "query" : {
    "match" : {
      "text_entry" : "late"
     }
 },  
 "suggest" : {
   "sugg" : {
     "text" : "late",
     "term" : {
         "field" : "text_entry"
      }
    }
  }
}'
Search(x, index = "shakespeare", body = sugg, 
  asdf = TRUE, size = 0)$suggest$sugg$options



# stream data out using jsonlite::stream_out
file <- tempfile()
res <- Search(x, "shakespeare", size = 1000, stream_opts = list(file = file))
head(df <- jsonlite::stream_in(file(file)))
NROW(df)
unlink(file)


# get profile data
body <- '{
  "profile": true,
  "query" : {
    "match" : { "text_entry" : "war" }
  }
}'
res <- Search(x, "shakespeare", body = body)
res$profile
# time in nanoseconds across each of the shards
vapply(res$profile$shards, function(w) {
  w$searches[[1]]$query[[1]]$time_in_nanos
}, 1)
}