Returns only facet items

solr_facet(
  conn,
  name = NULL,
  params = list(q = "*:*"),
  body = NULL,
  callopts = list(),
  raw = FALSE,
  parsetype = "df",
  concat = ",",
  progress = NULL,
  ...
)

Arguments

conn

A solrium connection object, see SolrClient

name

Name of a collection or core. Or leave as NULL if not needed.

params

(list) a named list of parameters, results in a GET request as long as no body parameters given

body

(list) a named list of parameters, if given a POST request will be performed

callopts

Call options passed on to crul::HttpClient

raw

(logical) If TRUE (default) raw json or xml returned. If FALSE, parsed data returned.

parsetype

(character) One of 'list' or 'df'

concat

(character) Character to concatenate elements of longer than length 1. Note that this only works reliably when data format is json (wt='json'). The parsing is more complicated in XML format, but you can do that on your own.

progress

a function with logic for printing a progress bar for an HTTP request, ultimately passed down to curl. only supports httr::progress for now. See the README for an example.

...

Further args, usually per field arguments for faceting.

Value

Raw json or xml, or a list of length 4 parsed elements (usually data.frame's).

Details

A number of fields can be specified multiple times, in which case you can separate them by commas, like facet.field='journal,subject'. Those fields are:

  • facet.field

  • facet.query

  • facet.date

  • facet.date.other

  • facet.date.include

  • facet.range

  • facet.range.other

  • facet.range.include

  • facet.pivot

Options for some parameters:

facet.sort: This param determines the ordering of the facet field constraints.

  • count sort the constraints by count (highest count first)

  • index to return the constraints sorted in their index order (lexicographic by indexed term). For terms in the ascii range, this will be alphabetically sorted.

The default is count if facet.limit is greater than 0, index otherwise. This parameter can be specified on a per field basis.

facet.method: This parameter indicates what type of algorithm/method to use when faceting a field.

  • enum Enumerates all terms in a field, calculating the set intersection of documents that match the term with documents that match the query. This was the default (and only) method for faceting multi-valued fields prior to Solr 1.4.

  • fc (Field Cache) The facet counts are calculated by iterating over documents that match the query and summing the terms that appear in each document. This was the default method for single valued fields prior to Solr 1.4.

  • fcs (Field Cache per Segment) works the same as fc except the underlying cache data structure is built for each segment of the index individually

The default value is fc (except for BoolField which uses enum) since it tends to use less memory and is faster then the enumeration method when a field has many unique terms in the index. For indexes that are changing rapidly in NRT situations, fcs may be a better choice because it reduces the overhead of building the cache structures on the first request and/or warming queries when opening a new searcher -- but tends to be somewhat slower then fc for subsequent requests against the same searcher. This parameter can be specified on a per field basis.

facet.date.other: This param indicates that in addition to the counts for each date range constraint between facet.date.start and facet.date.end, counts should also be computed for...

  • before All records with field values lower then lower bound of the first range

  • after All records with field values greater then the upper bound of the last range

  • between All records with field values between the start and end bounds of all ranges

  • none Compute none of this information

  • all Shortcut for before, between, and after

This parameter can be specified on a per field basis. In addition to the all option, this parameter can be specified multiple times to indicate multiple choices -- but none will override all other options.

facet.date.include: By default, the ranges used to compute date faceting between facet.date.start and facet.date.end are all inclusive of both endpoints, while the "before" and "after" ranges are not inclusive. This behavior can be modified by the facet.date.include param, which can be any combination of the following options...

  • lower All gap based ranges include their lower bound

  • upper All gap based ranges include their upper bound

  • edge The first and last gap ranges include their edge bounds (ie: lower for the first one, upper for the last one) even if the corresponding upper/lower option is not specified

  • outer The "before" and "after" ranges will be inclusive of their bounds, even if the first or last ranges already include those boundaries.

  • all Shorthand for lower, upper, edge, outer

This parameter can be specified on a per field basis. This parameter can be specified multiple times to indicate multiple choices.

facet.date.include: This param indicates that in addition to the counts for each range constraint between facet.range.start and facet.range.end, counts should also be computed for...

  • before All records with field values lower then lower bound of the first range

  • after All records with field values greater then the upper bound of the last range

  • between All records with field values between the start and end bounds of all ranges

  • none Compute none of this information

  • all Shortcut for before, between, and after

This parameter can be specified on a per field basis. In addition to the all option, this parameter can be specified multiple times to indicate multiple choices -- but none will override all other options.

facet.range.include: By default, the ranges used to compute range faceting between facet.range.start and facet.range.end are inclusive of their lower bounds and exclusive of the upper bounds. The "before" range is exclusive and the "after" range is inclusive. This default, equivalent to lower below, will not result in double counting at the boundaries. This behavior can be modified by the facet.range.include param, which can be any combination of the following options...

  • lower All gap based ranges include their lower bound

  • upper All gap based ranges include their upper bound

  • edge The first and last gap ranges include their edge bounds (ie: lower for the first one, upper for the last one) even if the corresponding upper/lower option is not specified

  • outer The "before" and "after" ranges will be inclusive of their bounds, even if the first or last ranges already include those boundaries.

  • all Shorthand for lower, upper, edge, outer

Can be specified on a per field basis. Can be specified multiple times to indicate multiple choices. If you want to ensure you don't double-count, don't choose both lower & upper, don't choose outer, and don't choose all.

Facet parameters

  • name Name of a collection or core. Or leave as NULL if not needed.

  • q Query terms. See examples.

  • facet.query This param allows you to specify an arbitrary query in the Lucene default syntax to generate a facet count. By default, faceting returns a count of the unique terms for a "field", while facet.query allows you to determine counts for arbitrary terms or expressions. This parameter can be specified multiple times to indicate that multiple queries should be used as separate facet constraints. It can be particularly useful for numeric range based facets, or prefix based facets -- see example below (i.e. price:[* TO 500] and price:[501 TO *]).

  • facet.field This param allows you to specify a field which should be treated as a facet. It will iterate over each Term in the field and generate a facet count using that Term as the constraint. This parameter can be specified multiple times to indicate multiple facet fields. None of the other params in this section will have any effect without specifying at least one field name using this param.

  • facet.prefix Limits the terms on which to facet to those starting with the given string prefix. Note that unlike fq, this does not change the search results -- it merely reduces the facet values returned to those beginning with the specified prefix. This parameter can be specified on a per field basis.

  • facet.sort See Details.

  • facet.limit This param indicates the maximum number of constraint counts that should be returned for the facet fields. A negative value means unlimited. Default: 100. Can be specified on a per field basis.

  • facet.offset This param indicates an offset into the list of constraints to allow paging. Default: 0. This parameter can be specified on a per field basis.

  • facet.mincount This param indicates the minimum counts for facet fields should be included in the response. Default: 0. This parameter can be specified on a per field basis.

  • facet.missing Set to "true" this param indicates that in addition to the Term based constraints of a facet field, a count of all matching results which have no value for the field should be computed. Default: FALSE. This parameter can be specified on a per field basis.

  • facet.method See Details.

  • facet.enum.cache.minDf This param indicates the minimum document frequency (number of documents matching a term) for which the filterCache should be used when determining the constraint count for that term. This is only used when facet.method=enum method of faceting. A value greater than zero will decrease memory usage of the filterCache, but increase the query time. When faceting on a field with a very large number of terms, and you wish to decrease memory usage, try a low value of 25 to 50 first. Default: 0, causing the filterCache to be used for all terms in the field. This parameter can be specified on a per field basis.

  • facet.threads This param will cause loading the underlying fields used in faceting to be executed in parallel with the number of threads specified. Specify as facet.threads=# where # is the maximum number of threads used. Omitting this parameter or specifying the thread count as 0 will not spawn any threads just as before. Specifying a negative number of threads will spin up to Integer.MAX_VALUE threads. Currently this is limited to the fields, range and query facets are not yet supported. In at least one case this has reduced warmup times from 20 seconds to under 5 seconds.

  • facet.date Specify names of fields (of type DateField) which should be treated as date facets. Can be specified multiple times to indicate multiple date facet fields.

  • facet.date.start The lower bound for the first date range for all Date Faceting on this field. This should be a single date expression which may use the DateMathParser syntax. Can be specified on a per field basis.

  • facet.date.end The minimum upper bound for the last date range for all Date Faceting on this field (see facet.date.hardend for an explanation of what the actual end value may be greater). This should be a single date expression which may use the DateMathParser syntax. Can be specified on a per field basis.

  • facet.date.gap The size of each date range expressed as an interval to be added to the lower bound using the DateMathParser syntax. Eg: facet.date.gap=+1DAY. Can be specified on a per field basis.

  • facet.date.hardend A Boolean parameter instructing Solr what to do in the event that facet.date.gap does not divide evenly between facet.date.start and facet.date.end. If this is true, the last date range constraint will have an upper bound of facet.date.end; if false, the last date range will have the smallest possible upper bound greater then facet.date.end such that the range is exactly facet.date.gap wide. Default: FALSE. This parameter can be specified on a per field basis.

  • facet.date.other See Details.

  • facet.date.include See Details.

  • facet.range Indicates what field to create range facets for. Example: facet.range=price&facet.range=age

  • facet.range.start The lower bound of the ranges. Can be specified on a per field basis. Example: f.price.facet.range.start=0.0&f.age.facet.range.start=10

  • facet.range.end The upper bound of the ranges. Can be specified on a per field basis. Example: f.price.facet.range.end=1000.0&f.age.facet.range.start=99

  • facet.range.gap The size of each range expressed as a value to be added to the lower bound. For date fields, this should be expressed using the DateMathParser syntax. (ie: facet.range.gap=+1DAY). Can be specified on a per field basis. Example: f.price.facet.range.gap=100&f.age.facet.range.gap=10

  • facet.range.hardend A Boolean parameter instructing Solr what to do in the event that facet.range.gap does not divide evenly between facet.range.start and facet.range.end. If this is true, the last range constraint will have an upper bound of facet.range.end; if false, the last range will have the smallest possible upper bound greater then facet.range.end such that the range is exactly facet.range.gap wide. Default: FALSE. This parameter can be specified on a per field basis.

  • facet.range.other See Details.

  • facet.range.include See Details.

  • facet.pivot This param allows you to specify a single comma-separated string of fields to allow you to facet within the results of the parent facet to return counts in the format of SQL group by operation

  • facet.pivot.mincount This param indicates the minimum counts for facet fields to be included in the response. Default: 0. This parameter should only be specified once.

  • start Record to start at, default to beginning.

  • rows Number of records to return.

  • key API key, if needed.

  • wt (character) Data type returned, defaults to 'json'. One of json or xml. If json, uses fromJSON to parse. If xml, uses xmlParse to parse. csv is only supported in solr_search and solr_all.

References

See https://lucene.apache.org/solr/guide/8_2/faceting.html for more information on faceting.

See also

Examples

if (FALSE) { # connect - local Solr instance (cli <- SolrClient$new()) cli$facet("gettingstarted", params = list(q="*:*", facet.field='name')) cli$facet("gettingstarted", params = list(q="*:*", facet.field='name'), callopts = list(verbose = TRUE)) cli$facet("gettingstarted", body = list(q="*:*", facet.field='name'), callopts = list(verbose = TRUE)) # Facet on a single field solr_facet(cli, "gettingstarted", params = list(q='*:*', facet.field='name')) # Remote instance (cli <- SolrClient$new(host = "api.plos.org", path = "search", port = NULL)) # Facet on multiple fields solr_facet(cli, params = list(q='alcohol', facet.field = c('journal','subject'))) # Using mincount solr_facet(cli, params = list(q='alcohol', facet.field='journal', facet.mincount='500')) # Using facet.query to get counts solr_facet(cli, params = list(q='*:*', facet.field='journal', facet.query=c('cell','bird'))) # Using facet.pivot to simulate SQL group by counts solr_facet(cli, params = list(q='alcohol', facet.pivot='journal,subject', facet.pivot.mincount=10)) ## two or more fields are required - you can pass in as a single ## character string solr_facet(cli, params = list(q='*:*', facet.pivot = "journal,subject", facet.limit = 3)) ## Or, pass in as a vector of length 2 or greater solr_facet(cli, params = list(q='*:*', facet.pivot = c("journal", "subject"), facet.limit = 3)) # Date faceting solr_facet(cli, params = list(q='*:*', facet.date='publication_date', facet.date.start='NOW/DAY-5DAYS', facet.date.end='NOW', facet.date.gap='+1DAY')) ## two variables solr_facet(cli, params = list(q='*:*', facet.date=c('publication_date', 'timestamp'), facet.date.start='NOW/DAY-5DAYS', facet.date.end='NOW', facet.date.gap='+1DAY')) # Range faceting solr_facet(cli, params = list(q='*:*', facet.range='counter_total_all', facet.range.start=5, facet.range.end=1000, facet.range.gap=10)) # Range faceting with > 1 field, same settings solr_facet(cli, params = list(q='*:*', facet.range=c('counter_total_all','alm_twitterCount'), facet.range.start=5, facet.range.end=1000, facet.range.gap=10)) # Range faceting with > 1 field, different settings solr_facet(cli, params = list(q='*:*', facet.range=c('counter_total_all','alm_twitterCount'), f.counter_total_all.facet.range.start=5, f.counter_total_all.facet.range.end=1000, f.counter_total_all.facet.range.gap=10, f.alm_twitterCount.facet.range.start=5, f.alm_twitterCount.facet.range.end=1000, f.alm_twitterCount.facet.range.gap=10)) # Get raw json or xml ## json solr_facet(cli, params = list(q='*:*', facet.field='journal'), raw=TRUE) ## xml solr_facet(cli, params = list(q='*:*', facet.field='journal', wt='xml'), raw=TRUE) # Get raw data back, and parse later, same as what goes on internally if # raw=FALSE (Default) out <- solr_facet(cli, params = list(q='*:*', facet.field='journal'), raw=TRUE) solr_parse(out) out <- solr_facet(cli, params = list(q='*:*', facet.field='journal', wt = 'xml'), raw=TRUE) solr_parse(out) # Using the USGS BISON API (https://bison.usgs.gov/#solr) ## The occurrence endpoint (cli <- SolrClient$new(host = "bison.usgs.gov", scheme = "https", path = "solr/occurrences/select", port = NULL)) solr_facet(cli, params = list(q='*:*', facet.field='year')) solr_facet(cli, params = list(q='*:*', facet.field='computedStateFips')) # using a proxy # cli <- SolrClient$new(host = "api.plos.org", path = "search", port = NULL, # proxy = list(url = "http://54.195.48.153:8888")) # solr_facet(cli, params = list(facet.field='journal'), # callopts=list(verbose=TRUE)) }