Scroll Query

Method	POST
URL	/v1/index/<index_id>/scroll
Authentication required?	Only for non-public data
Required Roles	None
Request Body	a GScrollRequest document
Response Body	a GScrollResult document

Authentication & Authorization

Tokens for this call must have one of these scopes.

urn:globus:scopes:search.api.globus.org:all
urn:globus:scopes:search.api.globus.org:search

Examples

Scroll via curl

To run a scroll query, we send it via a POST to the API, e.g.

curl -XPOST \
    -H 'Content-Type: application/json' \
    'https://search.api.globus.org/v1/index/4de0e89e-a395-11e7-bc54-8c705ad34f60/scroll' \
    --data '
{
  "q": "a scroll request with filtering",
  "filters": [
    {
      "type": "range",
      "field_name": "path.to.date",
      "values": [
        {
          "from": "*",
          "to": "2014-11-07"
        }
      ]
    }
  ]
}'

Request Schemas

GScrollRequest

This is the main document type for encoding a scrolling query.

Field Name	Type	Description
q	String	User-supplied query, conforming to the query syntax. Required if there are no filters.
advanced	Boolean	Defaults to False When true, interpret q with the advanced query syntax
limit	Integer	Optional. Limit the results given to limit many items. Defaults to 10
bypass_visible_to	Boolean	Defaults to False Allowed for Index Admins only. When true, visible_to restrictions will be ignored for this search query.
filter_principal_sets	List of Strings	Optional. A list of `principal_set` names. The caller’s identity set will be matched against any `principal_sets` assigned to entry documents, and filtered to matches for any of these strings. If this parameter is provided, at least one match must be present.
filters	Array	Optional. An array of GFilter Documents. Filters to apply to the search
marker	String	Optional. An opaque token from a previous scroll result document, used to request the nex page of results.

Examples

{
  "q": "the quick brown fox jumps"
}

GFilter

Field Name	TYpe	Description
type	String	One of {"match_any", "match_all", "range"}
field_name	String	The field to which the filter refers. Any dots (".") must be escaped with a preceding backslash ("\") character.
values	Array of Strings or Objects	The values to evaluate against the field_name. If type is "match_any" or "match_all" this must be a list of Strings. If type is "range", this must be a list of Objects each with the fields from and to.

Field Name

TYpe

Description

type

String

One of {"match_any", "match_all", "range"}

field_name

String

The field to which the filter refers. Any dots (".") must be escaped with a preceding backslash ("\") character.

values

Array of Strings or Objects

The values to evaluate against the field_name.

If type is "match_any" or "match_all" this must be a list of Strings.

If type is "range", this must be a list of Objects each with the fields from and to.

"match_any" and "match_all" refer to the different possible behaviors of the filter values. As their names imply, if "match_any" is specified, the filter will match results for which any of filter values match, while "match_all" requires that all of the values match on every result.

Note

"match_any" and "match_all" are the same when there’s only one value as far as filtering is concerned, but they may have different impact on the way that facets are interpreted.

Note

values.from and values.to may be the special string "*" indicating that the range is unbounded on this end. An example is given below.

Examples

{
  "type": "match_any",
  "field_name": "https://schema\\.labs\\.datacite\\.org/meta/kernel-4\\.0/metadata\\.xsd#resourceTypeGeneral",
  "values": ["Globus Endpoint"]
}

{
  "type": "range",
  "field_name": "path.to.date",
  "values": [
    {
      "from": "1970-01-01",
      "to": "2015-01-01"
    }
  ]
}

{
  "type": "range",
  "field_name": "path.to.date",
  "values": [
    {
      "from": "*",
      "to": "2014-11-07"
    }
  ]
}

{
  "type": "match_all",
  "field_name": "https://transfer\\.api\\.globus\\.org/endpoint#keywords",
  "values": ["hpc", "internet2", "uchicago"]
}

Response Schemas

GScrollResult

This is the document type for all results from scrolling queries.

Field Name	Type	Description
gmeta	Array	An array of GMetaResult documents, the main body of the result
count	Integer	The number of results returned; i.e. the size of the gmeta array. May be 0
total	Integer	The total number of matches for the search. May be 0 if no matches are found
has_next_page	Boolean	True if there’s another page of results available, False otherwise
marker	String	An opaque marker used to request the next page of results

Examples

{
  "count": 1,
  "gmeta": [
    {
      "@datatype": "GMetaResult",
      "@version": "2019-08-27",
      "entries": [
        {
          "content": {
            "cuisine": [
              "mexican"
            ],
            "handle": "salsa-verde",
            "ingredients": [
              {
                "amount": {
                  "number": 10
                },
                "default": "tomatillo",
                "preparation": "simmer 20 minutes",
                "type": "fruit"
              },
              {
                "amount": {
                  "number": 2
                },
                "default": "serrano pepper",
                "preparation": "seeded",
                "substitutes": [
                  "jalapeno",
                  "thai bird chili"
                ],
                "type": "fruit"
              },
              {
                "amount": {
                  "number": 2,
                  "unit": "clove"
                },
                "default": "garlic",
                "type": "vegetable"
              },
              {
                "amount": {
                  "number": 0.5
                },
                "default": "yellow onion",
                "type": "vegetable"
              },
              {
                "amount": {
                  "number": 2,
                  "unit": "tsp"
                },
                "default": "salt",
                "type": "spice"
              },
              {
                "amount": {
                  "number": 2,
                  "unit": "tbsp"
                },
                "default": "coriander",
                "preparation": "ground",
                "subsitutes": [
                  "cumin"
                ],
                "type": "spice"
              }
            ],
            "keywords": [
              "salsa",
              "tomatillo",
              "coriander",
              "serrano pepper"
            ],
            "origin": {
              "author": "Diana Kennedy",
              "title": "Regional Mexican Cooking",
              "type": "book"
            }
          },
          "entry_id": null
        }
      ],
      "subject": "https://en.wikipedia.org/wiki/Salsa_verde"
    }
  ],
  "total": 1,
  "has_next_page": true,
  "marker": "3d34900e3e4211ebb0a806b2af333354"
}

GMetaResult

These are components in a search result.

A GMetaResult is a structure similar to a GMetaEntry from the Ingest API, with the following significant differences:

visibility information is not exposed; i.e. visible_to is not included
metadata for any subject may be an aggregate of multiple documents with different visibility rules or sources. Thus, the result is always returned as an array in which each element represents data provided by a different source or with different visibility

GMetaResult version 2019-08-27

Field Name Type Description

subject

String

the resource described by this metadata, often a URI

entries

Array

An array of objects containing the data pertaining to the subject.

Each object has the fields content, entry_id, and matched_principal_sets. The content is an object with the entry data which was sent to Search, and the entry_id is its ID. If there are any assigned principal_sets for the entry which match the current caller, they will be returned as an array of strings in matched_principal_sets.

{
  "entries": [
    {
      "content": {
        "alpha": {
          "beta": "gamma"
        }
      },
      "matched_principal_sets": [],
      "entry_id": null
    },
    {
      "content": {
        "alpha": {
          "beta": "delta"
        }
      },
      "matched_principal_sets": [],
      "entry_id": "with_delta"
    }
  ],
  "subject": "http://example.com"
}

GMetaResult version 2017-09-01 (legacy format)

Field Name	Type	Description
subject	String	the resource described by this metadata, often a URI
content	Array	an array of objects containing the metadata pertaining to the subject
entry_ids	Array	an array of Entry IDs matching the content such that the entry ID at index i has content found in content[i]. See note below

Note

entry_ids and content are kept separate to maintain backwards compatibility. They can easily be unified with a zip operation in many programming languages.

{
  "entries": [
    {
      "content": {
        "alpha": {
          "beta": "gamma"
        }
      },
      "matched_principal_sets": [],
      "entry_id": null
    }
  ],
  "subject": "http://example.com"
}

Note how, in the example below, the new format makes it easier to associate entry_id values with content blobs. Additionally, this new format is more extensible — if new fields are needed in the new format, they can be added as siblings of the content and entry_id fields.

New Format (2019-08-27) Old Format (2017-09-01)

Table 1. Format Comparison
New Format (2019-08-27)	Old Format (2017-09-01)
`{ "entries": [ { "content": { "alpha": { "beta": "gamma" } }, "matched_principal_sets": [], "entry_id": null }, { "content": { "alpha": { "beta": "delta" } }, "matched_principal_sets": [], "entry_id": "with_delta" } ], "subject": "http://example.com" }`	`{ "content": [ { "alpha": { "beta": "gamma" } }, { "alpha": { "beta": "delta" } } ], "entry_ids": [ null, "with_delta" ], "subject": "http://example.com" }`
each entry is a complete, standalone subdocument	entry_ids needs to be zipped with content to make sense of the structure

{
  "entries": [
    {
      "content": {
        "alpha": {
          "beta": "gamma"
        }
      },
      "matched_principal_sets": [],
      "entry_id": null
    },
    {
      "content": {
        "alpha": {
          "beta": "delta"
        }
      },
      "matched_principal_sets": [],
      "entry_id": "with_delta"
    }
  ],
  "subject": "http://example.com"
}

{
  "content": [
    {
      "alpha": {
        "beta": "gamma"
      }
    },
    {
      "alpha": {
        "beta": "delta"
      }
    }
  ],
  "entry_ids": [
    null,
    "with_delta"
  ],
  "subject": "http://example.com"
}

each entry is a complete, standalone subdocument

entry_ids needs to be zipped with content to make sense of the structure