pandagg.node.aggs.metric module

class pandagg.node.aggs.metric.Avg(field=None, script=None, meta=None, **body)

Bases: pandagg.node.aggs.abstract.FieldOrScriptMetricAgg

KEY = 'avg'

VALUE_ATTRS = ['value']

WHITELISTED_MAPPING_TYPES = ['long', 'integer', 'short', 'byte', 'double', 'float', 'half_float', 'scaled_float', 'ip', 'token_count', 'date', 'boolean']

class pandagg.node.aggs.metric.Cardinality(field=None, script=None, meta=None, **body)

Bases: pandagg.node.aggs.abstract.FieldOrScriptMetricAgg

KEY = 'cardinality'

VALUE_ATTRS = ['value']

class pandagg.node.aggs.metric.ExtendedStats(field=None, script=None, meta=None, **body)

Bases: pandagg.node.aggs.abstract.FieldOrScriptMetricAgg

KEY = 'extended_stats'

VALUE_ATTRS = ['count', 'min', 'max', 'avg', 'sum', 'sum_of_squares', 'variance', 'std_deviation', 'std_deviation_bounds']

WHITELISTED_MAPPING_TYPES = ['long', 'integer', 'short', 'byte', 'double', 'float', 'half_float', 'scaled_float', 'ip', 'token_count', 'date', 'boolean']

class pandagg.node.aggs.metric.GeoBound(field=None, script=None, meta=None, **body)

Bases: pandagg.node.aggs.abstract.FieldOrScriptMetricAgg

KEY = 'geo_bounds'

VALUE_ATTRS = ['bounds']

WHITELISTED_MAPPING_TYPES = ['geo_point']

class pandagg.node.aggs.metric.GeoCentroid(field=None, script=None, meta=None, **body)

Bases: pandagg.node.aggs.abstract.FieldOrScriptMetricAgg

KEY = 'geo_centroid'

VALUE_ATTRS = ['location']

WHITELISTED_MAPPING_TYPES = ['geo_point']

class pandagg.node.aggs.metric.Max(field=None, script=None, meta=None, **body)

Bases: pandagg.node.aggs.abstract.FieldOrScriptMetricAgg

KEY = 'max'

VALUE_ATTRS = ['value']

WHITELISTED_MAPPING_TYPES = ['long', 'integer', 'short', 'byte', 'double', 'float', 'half_float', 'scaled_float', 'ip', 'token_count', 'date', 'boolean']

class pandagg.node.aggs.metric.Min(field=None, script=None, meta=None, **body)

Bases: pandagg.node.aggs.abstract.FieldOrScriptMetricAgg

KEY = 'min'

VALUE_ATTRS = ['value']

WHITELISTED_MAPPING_TYPES = ['long', 'integer', 'short', 'byte', 'double', 'float', 'half_float', 'scaled_float', 'ip', 'token_count', 'date', 'boolean']

class pandagg.node.aggs.metric.PercentileRanks(field, values, meta=None, **body)

Bases: pandagg.node.aggs.abstract.FieldOrScriptMetricAgg

KEY = 'percentile_ranks'

VALUE_ATTRS = ['values']

WHITELISTED_MAPPING_TYPES = ['long', 'integer', 'short', 'byte', 'double', 'float', 'half_float', 'scaled_float', 'ip', 'token_count', 'date', 'boolean']

class pandagg.node.aggs.metric.Percentiles(field=None, script=None, meta=None, **body)

Bases: pandagg.node.aggs.abstract.FieldOrScriptMetricAgg

Percents body argument can be passed to specify which percentiles to fetch.

KEY = 'percentiles'

VALUE_ATTRS = ['values']

WHITELISTED_MAPPING_TYPES = ['long', 'integer', 'short', 'byte', 'double', 'float', 'half_float', 'scaled_float', 'ip', 'token_count', 'date', 'boolean']

class pandagg.node.aggs.metric.Stats(field=None, script=None, meta=None, **body)

Bases: pandagg.node.aggs.abstract.FieldOrScriptMetricAgg

KEY = 'stats'

VALUE_ATTRS = ['count', 'min', 'max', 'avg', 'sum']

WHITELISTED_MAPPING_TYPES = ['long', 'integer', 'short', 'byte', 'double', 'float', 'half_float', 'scaled_float', 'ip', 'token_count', 'date', 'boolean']

class pandagg.node.aggs.metric.Sum(field=None, script=None, meta=None, **body)

Bases: pandagg.node.aggs.abstract.FieldOrScriptMetricAgg

KEY = 'sum'

VALUE_ATTRS = ['value']

WHITELISTED_MAPPING_TYPES = ['long', 'integer', 'short', 'byte', 'double', 'float', 'half_float', 'scaled_float', 'ip', 'token_count', 'date', 'boolean']

class pandagg.node.aggs.metric.TopHits(meta=None, **body)

Bases: pandagg.node.aggs.abstract.MetricAgg

KEY = 'top_hits'

VALUE_ATTRS = ['hits']

class pandagg.node.aggs.metric.ValueCount(field=None, script=None, meta=None, **body)

Bases: pandagg.node.aggs.abstract.FieldOrScriptMetricAgg

BLACKLISTED_MAPPING_TYPES = []

KEY = 'value_count'

VALUE_ATTRS = ['value']