pandagg.node.mapping.field_datatypes module

https://www.elastic.co/guide/en/elasticsearch/reference/current/mapping-types.html

class pandagg.node.mapping.field_datatypes.Alias(name, depth=0, is_subfield=False, **body)

Bases: pandagg.node.mapping.abstract.Field

Defines an alias to an existing field.

KEY = 'alias'

class pandagg.node.mapping.field_datatypes.Binary(name, depth=0, is_subfield=False, **body)

Bases: pandagg.node.mapping.abstract.Field

KEY = 'binary'

class pandagg.node.mapping.field_datatypes.Boolean(name, depth=0, is_subfield=False, **body)

Bases: pandagg.node.mapping.abstract.Field

KEY = 'boolean'

class pandagg.node.mapping.field_datatypes.Byte(name, depth=0, is_subfield=False, **body)

Bases: pandagg.node.mapping.abstract.Field

KEY = 'byte'

class pandagg.node.mapping.field_datatypes.Completion(name, depth=0, is_subfield=False, **body)

Bases: pandagg.node.mapping.abstract.Field

To provide auto-complete suggestions

KEY = 'completion'

class pandagg.node.mapping.field_datatypes.Date(name, depth=0, is_subfield=False, **body)

Bases: pandagg.node.mapping.abstract.Field

KEY = 'date'

class pandagg.node.mapping.field_datatypes.DateNanos(name, depth=0, is_subfield=False, **body)

Bases: pandagg.node.mapping.abstract.Field

KEY = 'date_nanos'

class pandagg.node.mapping.field_datatypes.DateRange(name, depth=0, is_subfield=False, **body)

Bases: pandagg.node.mapping.abstract.Field

KEY = 'date_range'

class pandagg.node.mapping.field_datatypes.DenseVector(name, depth=0, is_subfield=False, **body)

Bases: pandagg.node.mapping.abstract.Field

Record dense vectors of float values.

KEY = 'dense_vector'

class pandagg.node.mapping.field_datatypes.Double(name, depth=0, is_subfield=False, **body)

Bases: pandagg.node.mapping.abstract.Field

KEY = 'double'

class pandagg.node.mapping.field_datatypes.DoubleRange(name, depth=0, is_subfield=False, **body)

Bases: pandagg.node.mapping.abstract.Field

KEY = 'double_range'

class pandagg.node.mapping.field_datatypes.Flattened(name, depth=0, is_subfield=False, **body)

Bases: pandagg.node.mapping.abstract.Field

Allows an entire JSON object to be indexed as a single field.

KEY = 'flattened'

class pandagg.node.mapping.field_datatypes.Float(name, depth=0, is_subfield=False, **body)

Bases: pandagg.node.mapping.abstract.Field

KEY = 'float'

class pandagg.node.mapping.field_datatypes.FloatRange(name, depth=0, is_subfield=False, **body)

Bases: pandagg.node.mapping.abstract.Field

KEY = 'float_range'

class pandagg.node.mapping.field_datatypes.GeoPoint(name, depth=0, is_subfield=False, **body)

Bases: pandagg.node.mapping.abstract.Field

For lat/lon points

KEY = 'geo_point'

class pandagg.node.mapping.field_datatypes.GeoShape(name, depth=0, is_subfield=False, **body)

Bases: pandagg.node.mapping.abstract.Field

For complex shapes like polygons

KEY = 'geo_shape'

class pandagg.node.mapping.field_datatypes.HalfFloat(name, depth=0, is_subfield=False, **body)

Bases: pandagg.node.mapping.abstract.Field

KEY = 'half_float'

class pandagg.node.mapping.field_datatypes.Histogram(name, depth=0, is_subfield=False, **body)

Bases: pandagg.node.mapping.abstract.Field

For pre-aggregated numerical values for percentiles aggregations.

KEY = 'histogram'

class pandagg.node.mapping.field_datatypes.IP(name, depth=0, is_subfield=False, **body)

Bases: pandagg.node.mapping.abstract.Field

for IPv4 and IPv6 addresses

KEY = 'IP'

class pandagg.node.mapping.field_datatypes.Integer(name, depth=0, is_subfield=False, **body)

Bases: pandagg.node.mapping.abstract.Field

KEY = 'integer'

class pandagg.node.mapping.field_datatypes.IntegerRange(name, depth=0, is_subfield=False, **body)

Bases: pandagg.node.mapping.abstract.Field

KEY = 'integer_range'

class pandagg.node.mapping.field_datatypes.Join(name, depth=0, is_subfield=False, **body)

Bases: pandagg.node.mapping.abstract.Field

Defines parent/child relation for documents within the same index

KEY = 'join'

class pandagg.node.mapping.field_datatypes.Keyword(name, depth=0, is_subfield=False, **body)

Bases: pandagg.node.mapping.abstract.Field

KEY = 'keyword'

class pandagg.node.mapping.field_datatypes.Long(name, depth=0, is_subfield=False, **body)

Bases: pandagg.node.mapping.abstract.Field

KEY = 'long'

class pandagg.node.mapping.field_datatypes.LongRange(name, depth=0, is_subfield=False, **body)

Bases: pandagg.node.mapping.abstract.Field

KEY = 'long_range'

class pandagg.node.mapping.field_datatypes.MapperAnnotatedText(name, depth=0, is_subfield=False, **body)

Bases: pandagg.node.mapping.abstract.Field

To index text containing special markup (typically used for identifying named entities)

KEY = 'annotated-text'

class pandagg.node.mapping.field_datatypes.MapperMurMur3(name, depth=0, is_subfield=False, **body)

Bases: pandagg.node.mapping.abstract.Field

To compute hashes of values at index-time and store them in the index

KEY = 'murmur3'

class pandagg.node.mapping.field_datatypes.Nested(name, depth=0, is_subfield=False, **body)

Bases: pandagg.node.mapping.abstract.Field

DISPLAY_PATTERN = ' [%s]'

KEY = 'nested'

class pandagg.node.mapping.field_datatypes.Object(name, depth=0, is_subfield=False, **body)

Bases: pandagg.node.mapping.abstract.Field

DISPLAY_PATTERN = ' {%s}'

KEY = 'object'

class pandagg.node.mapping.field_datatypes.Percolator(name, depth=0, is_subfield=False, **body)

Bases: pandagg.node.mapping.abstract.Field

Accepts queries from the query-dsl

KEY = 'percolator'

class pandagg.node.mapping.field_datatypes.RankFeature(name, depth=0, is_subfield=False, **body)

Bases: pandagg.node.mapping.abstract.Field

Record numeric feature to boost hits at query time.

KEY = 'rank_feature'

class pandagg.node.mapping.field_datatypes.RankFeatures(name, depth=0, is_subfield=False, **body)

Bases: pandagg.node.mapping.abstract.Field

Record numeric features to boost hits at query time.

KEY = 'rank_features'

class pandagg.node.mapping.field_datatypes.ScaledFloat(name, depth=0, is_subfield=False, **body)

Bases: pandagg.node.mapping.abstract.Field

KEY = 'scaled_float'

class pandagg.node.mapping.field_datatypes.SearchAsYouType(name, depth=0, is_subfield=False, **body)

Bases: pandagg.node.mapping.abstract.Field

A text-like field optimized for queries to implement as-you-type completion

KEY = 'search_as_you_type'

class pandagg.node.mapping.field_datatypes.Shape(name, depth=0, is_subfield=False, **body)

Bases: pandagg.node.mapping.abstract.Field

For arbitrary cartesian geometries.

KEY = 'shape'

class pandagg.node.mapping.field_datatypes.Short(name, depth=0, is_subfield=False, **body)

Bases: pandagg.node.mapping.abstract.Field

KEY = 'short'

class pandagg.node.mapping.field_datatypes.SparseVector(name, depth=0, is_subfield=False, **body)

Bases: pandagg.node.mapping.abstract.Field

Record sparse vectors of float values.

KEY = 'sparse_vector'

class pandagg.node.mapping.field_datatypes.Text(name, depth=0, is_subfield=False, **body)

Bases: pandagg.node.mapping.abstract.Field

KEY = 'text'

class pandagg.node.mapping.field_datatypes.TokenCount(name, depth=0, is_subfield=False, **body)

Bases: pandagg.node.mapping.abstract.Field

To count the number of tokens in a string

KEY = 'token_count'