Metric aggregations on INFINI Pizza

Avg aggregation

Mon, 01 Jan 0001 00:00:00 +0000

Avg aggregation #

A single-value metrics aggregation that computes the average of numeric values that are extracted from the aggregated documents.

Examples #

Assuming the data consists of documents representing exams grades (between 0 and 100) of students we can average their scores with:

POST /exams/_search
{
 "aggs": {
 "avg_grade": {
 "avg": {
 "field": "grade"
 }
 }
 }
}

The above aggregation computes the average grade over all documents. The aggregation type is avg and the field setting defines the numeric field of the documents the average will be computed on. The above will return the following:

Cardinality aggregation

Mon, 01 Jan 0001 00:00:00 +0000

Cardinality aggregation #

A single-value metrics aggregation that counts the number of distinct (approximate) values of a field.

Examples #

POST /sales/_search
{
 "aggs": {
 "type_count": {
 "cardinality": {
 "field": "type"
 }
 }
 }
}

Response:

{
 ...
 "aggregations": {
 "type_count": {
 "value": 3
 }
 }
}

Parameters for `cardinality` #

field
(Required, string) Field you wish to aggregate.
missing
(Optional, value) Value used for documents missing the field; all such documents count as one distinct value.

Max aggregation

Mon, 01 Jan 0001 00:00:00 +0000

Max aggregation #

A single-value metrics aggregation that keeps track and returns the maximum value among the numeric values extracted from the aggregated documents.

Examples #

Computing the max price value across all documents:

POST /sales/_search
{
 "aggs": {
 "max_price": {
 "max": {
 "field": "price"
 }
 }
 }
}

Response:

Min aggregation

Mon, 01 Jan 0001 00:00:00 +0000

Min aggregation #

A single-value metrics aggregation that keeps track and returns the minimum value among numeric values extracted from the aggregated documents.

Examples #

Computing the min price value across all documents:

POST /sales/_search
{
 "aggs": {
 "min_price": {
 "min": {
 "field": "price"
 }
 }
 }
}

Response:

Sum aggregation

Mon, 01 Jan 0001 00:00:00 +0000

Sum aggregation #

A single-value metrics aggregation that sums up numeric values that are extracted from the aggregated documents.

Examples #

Assuming the data consists of documents representing sales records we can sum the sale price of all hats with:

POST /sales/_search
{
 "query": {
 "term": {
 "field": "type",
 "value": "hat"
 }
 },
 "aggs": {
 "hat_prices": {
 "sum": {
 "field": "price"
 }
 }
 }
}

Resulting in:

Value count aggregation

Mon, 01 Jan 0001 00:00:00 +0000

Value count aggregation #

A single-value metrics aggregation that counts the number of values that are extracted from the aggregated documents. Typically, this aggregator will be used in conjunction with other single-value aggregations. For example, when computing the avg one might be interested in the number of values the average is computed over.

value_count does not de-duplicate values, so even if a field has duplicates each value will be counted individually.

Median absolute deviation aggregation

Mon, 01 Jan 0001 00:00:00 +0000

Median absolute deviation aggregation #

A single-value metrics aggregation that computes the median absolute deviation — the median of the distances from each value to the median of all values. A robust measure of spread: unlike standard deviation it is not skewed by a few extreme values.

Example #

Sales prices take only four values (15, 30, 45, 60), so half the documents sit at 15 and the deviation of a typical document is small:

Weighted average aggregation

Mon, 01 Jan 0001 00:00:00 +0000

Weighted average aggregation #

A single-value metrics aggregation that computes the weighted average of numeric values. Each document contributes value × weight, divided by the total weight — e.g. an average price weighted by quantity sold.

Example #

Average unit price weighted by qty (larger purchases count more):

The plain avg of price is 27.5; quantity-weighted it is 28.125.

Stats aggregation

Mon, 01 Jan 0001 00:00:00 +0000

Stats aggregation #

A multi-value metrics aggregation that computes basic statistics (min, max, sum, count, avg) over numeric values extracted from the aggregated documents.

Examples #

POST /sales/_search
{
 "aggs": {
 "prices_stats": {
 "stats": {
 "field": "price"
 }
 }
 }
}

Response:

{
 ...
 "aggregations": {
 "prices_stats": {
 "count": 9,
 "min": 72.0,
 "max": 99.0,
 "avg": 86.0,
 "sum": 774.0
 }
 }
}

Parameters for `stats` #

field
(Required, string) Field you wish to aggregate.
missing
(Optional, value) Value used for documents missing the field.

extended_stats takes the same parameters and additionally returns variance, standard deviation and related statistics.

Extended stats aggregation

Mon, 01 Jan 0001 00:00:00 +0000

Extended stats aggregation #

A multi-value metrics aggregation extending stats with squares, variance, standard deviation and their lower/upper bounds.

Example #

Returns count, min, max, avg, sum, sum_of_squares, variance, variance_population, variance_sampling, std_deviation, std_deviation_population, std_deviation_sampling plus std_deviation_bounds (upper/lower at ±2σ).

Parameters for `extended_stats` #

field
(Required, string) Numeric field you wish to aggregate.
sigma
(Optional, float, default: 2) Multiplier for the standard deviation bounds.

Percentiles aggregation

Mon, 01 Jan 0001 00:00:00 +0000

Percentiles aggregation #

A multi-value metrics aggregation that calculates one or more percentiles over numeric values extracted from the aggregated documents.

Percentiles show the point at which a certain percentage of observed values occur. For example, the 95th percentile is the value which is greater than 95% of the observed values.

Percentiles are often used to find outliers. In normal distributions, the 0.13th and 99.87th percentiles represents three standard deviations from the mean. Any data which falls outside three standard deviations is often considered an anomaly.

Percentile ranks aggregation

Mon, 01 Jan 0001 00:00:00 +0000

Percentile ranks aggregation #

A multi-value metrics aggregation that answers the inverse of percentiles: for each value you provide, what percentage of documents is at or below it.

Example #

Where do the prices 30 and 45 sit in the distribution?

30 is at rank 75 (75% of documents cost 30 or less), 45 at ≈91.7.

Boxplot aggregation

Mon, 01 Jan 0001 00:00:00 +0000

Boxplot aggregation #

A multi-value metrics aggregation producing the five-number summary of a distribution: minimum, lower quartile (q1), median (q2), upper quartile (q3) and maximum, plus whiskers.

Example #

For the four-price dataset: min 15, q1 15, q2 22.5, q3 37.5, max 60, with lower/upper whiskers at the data extremes.

String stats aggregation

Mon, 01 Jan 0001 00:00:00 +0000

String stats aggregation #

A multi-value metrics aggregation computing length and character statistics over keyword/string values: count, min/max/avg length and Shannon entropy of the character distribution.

Example #

Four product types (t-shirt 7 chars ×60, hat 3 ×30, mug 3 ×20, sticker 7 ×10): count 120, min_length 3, max_length 7, avg_length ≈5.33.

Matrix stats aggregation

Mon, 01 Jan 0001 00:00:00 +0000

Matrix stats aggregation #

A multi-value metrics aggregation computing counts, means, variances, skewness, kurtosis and the correlation matrix across several numeric fields at once.

Example #

amount is derived from price × qty, so their correlation is ~1 — the matrix makes such relationships visible at a glance.

T-test aggregation

Mon, 01 Jan 0001 00:00:00 +0000

T-test aggregation #

A single-value metrics aggregation for a paired or two-sample Student’s t-test over two numeric fields. Positive values mean a tends to be larger than b.

Simplified engine note: the paired form (type: paired) is computed over the per-document column values; homoscedastic / heteroscedastic fall back to the same paired evaluation.

Example #

Do sale prices differ from quantities in a systematic way?

Parameters for `t_test` #

a
(Required, object) field — the first numeric field.
b
(Required, object) field — the second numeric field.
type
(Optional, string, default: paired) paired, homoscedastic or heteroscedastic.

Rate aggregation

Mon, 01 Jan 0001 00:00:00 +0000

Rate aggregation #

A single-value metrics aggregation that sums a numeric field, intended for counters and rates inside date_histogram buckets (per-interval totals).

Example #

Outside a histogram, rate equals sum — here the total amount, 6750. Inside a date_histogram it returns each bucket’s total.

Geo bounds aggregation

Mon, 01 Jan 0001 00:00:00 +0000

Geo bounds aggregation #

A metrics aggregation computing the bounding box (top-left / bottom-right corners) of all geo_point values.

Example #

Returns the bounds wrapping all 15 places — the box you would fit a map viewport to.

Parameters for `geo_bounds` #

field
(Required, string) geo_point field you wish to aggregate.
wrap_longitude
(Optional, boolean, default: true) Allow the box to wrap the antimeridian.

Geo centroid aggregation

Mon, 01 Jan 0001 00:00:00 +0000

Geo centroid aggregation #

A metrics aggregation computing the weighted centroid (mean latitude and longitude) of all geo_point values.

Example #

Returns the count of points and their centroid — the natural center point for map placement.

Parameters for `geo_centroid` #

field
(Required, string) geo_point field you wish to aggregate.

Top hits aggregation

Mon, 01 Jan 0001 00:00:00 +0000

Top hits aggregation #

Keeps track of the most relevant documents being aggregated — useful inside a bucket aggregation (e.g. terms) to return the best-matching documents per bucket.

Examples #

Top 3 sales per merchant:

POST /sales/_search
{
 "aggs": {
 "top_merchants": {
 "terms": { "field": "merchant" },
 "aggs": {
 "top_sales": {
 "top_hits": {
 "size": 3,
 "sort": [{ "field": "amount", "order": "desc" }]
 }
 }
 }
 }
 }
}

Parameters for `top_hits` #

size
(Optional, integer, default: 3) Number of top hits to return per bucket.
sort
(Optional) Sort order for the top hits. Accepts "field", ["a", "b"] and [{ "field": "asc" }] forms — all normalize to an object array.
_source
(Optional) Fields to include in the returned source. If empty, the full source is returned.

Top metrics aggregation

Mon, 01 Jan 0001 00:00:00 +0000

Top metrics aggregation #

A metrics aggregation that returns metric values from the leading matching documents — a cheaper alternative to top_hits when you only need field values, not whole documents.

Engine note: sort is accepted for compatibility; the current implementation returns the metrics of the first size matching documents.

Example #

Parameters for `top_metrics` #

metrics
(Required, object array) field entries whose values are returned.
sort
(Optional, array) Sort clause selecting the “top” documents.
size
(Optional, integer, default: 1) How many top entries to return.

Metric aggregations on INFINI Pizza

Avg aggregation

Avg aggregation #

Examples #

Cardinality aggregation

Cardinality aggregation #

Examples #

Parameters for cardinality #

Max aggregation

Max aggregation #

Examples #

Min aggregation

Min aggregation #

Examples #

Sum aggregation

Sum aggregation #

Examples #

Value count aggregation

Value count aggregation #

Median absolute deviation aggregation

Median absolute deviation aggregation #

Example #

Weighted average aggregation

Weighted average aggregation #

Example #

Stats aggregation

Stats aggregation #

Examples #

Parameters for stats #

Extended stats aggregation

Extended stats aggregation #

Example #

Parameters for extended_stats #

Percentiles aggregation

Percentiles aggregation #

Percentile ranks aggregation

Percentile ranks aggregation #

Example #

Boxplot aggregation

Boxplot aggregation #

Example #

String stats aggregation

String stats aggregation #

Example #

Matrix stats aggregation

Matrix stats aggregation #

Example #

T-test aggregation

T-test aggregation #

Example #

Parameters for t_test #

Rate aggregation

Rate aggregation #

Example #

Geo bounds aggregation

Geo bounds aggregation #

Example #

Parameters for geo_bounds #

Geo centroid aggregation

Geo centroid aggregation #

Example #

Parameters for geo_centroid #

Top hits aggregation

Top hits aggregation #

Examples #

Parameters for top_hits #

Top metrics aggregation

Top metrics aggregation #

Example #

Parameters for top_metrics #

Parameters for `cardinality` #

Parameters for `stats` #

Parameters for `extended_stats` #

Parameters for `t_test` #

Parameters for `geo_bounds` #

Parameters for `geo_centroid` #

Parameters for `top_hits` #

Parameters for `top_metrics` #