"Features"
property, containing an array of valid geojson features.
Each feature will be imported as one row, with additional properties mapped to columns in the table. Nested properties will be flattened using the .
separator.
Note that Redivis only supports 2-dimensional, unprojected (WGS84) geometries. Other projections might cause the import to fail, and any extra dimensions will be stripped during ingest.
See working with geospatial data for more information..shp.zip
specification below..shp.zip
. These will then be converted to .geojson (via ogr2ogr), and imported as specified for the .geojson format.my_data.csv.gz
) or have it's header set to Content-Encoding: gzip
if served from a URL or cloud storage location.Jane said, "Why hasn't this been figured out by now?"
it must be encoded as:
"Jane said, ""Why hasn't this been figured out by now?"""
\"
is not valid for an escaped quote; it must be ""
null
values"
, though some files may not have a quote character (in which case, they must not include the delimiter within any cells).var1, var2, var3, etc...
geojson
, shp
, shp.zip
,kml
. Internally, Redivis converts all formats to a geojson
representation (using the relevant ogr2ogr driver), and then imports the geojson into a table.geometry
column containing the WKT representation for that feature. Additional feature properties will be mapped to variables in your table, with any nested properties flattened using the .
separator.
Note that Redivis only supports 2-dimensional, unprojected (WGS84) geometries. Other projections might cause the import to fail, and any extra dimensions will be stripped during ingest. If you are uploading a .shp.zip
that contains projection information, the geometries will automatically be reprojected as part of the import process.csv
). In this case, the geographic data should be encoded as strings using the Well-Known Text (WKT) representation. This is also the same format used when exporting geography variables as a CSV. _
). If the same variable is found more than once in any given file, it will automatically have a counter appended to it (e.g., "variable_2").string
being the default type.string
string
in order to preserve the leading zeros (e.g., 000583
)float
, even if that value is a valid integer (e.g., 1.0
).YYYY-[M]M-[D]D
YYYY-[M]M-[D]D[( |T)[H]H:[M]M:[S]S[.DDDDDD]
[H]H:[M]M:[S]S[.DDDDDD]
/my-bucket/my-folder/*
./my-bucket/my-folder/d*
matches my-folder/data.csv
, but not my-folder/data/text.csv
my-folder/d**
will match both examples provided above/my-bucket/da??.csv
matches /my-bucket/data.csv
/my-bucket/[aeiou].csv
matches any of the vowel characters followed by .csv/my-bucket/[0-9].csv
matches any number followed by .csv/my-bucket/my-folder/*
or /my-bucket/my-folder/prefix*
.project_name.dataset_id.table_id
. To import multiple tables within a dataset, you may use wildcards. E.g., project_name.dataset_id.*
or project_name.dataset_id.prefix*
.\"
with ""
: