ffastdb_analytics 0.1.2

Analytical functions layer for ffastdb — groupBy, histogram, percentile, stddev, topN, rank, rolling average, cumulative sum, and pivot tables.

Changelog

All notable changes to this project will be documented in this file.

0.1.0 — 2026-04-25

Initial release.

Added

Aggregation

• groupBy(field, aggregations) — groups documents by a field and computes aggregations per group.
• Aggregation expressions: aggSum, aggAvg, aggCount, aggMin, aggMax.

Distribution

• percentile(field, p) — value at rank p (0.0–1.0) for any numeric field.
• stddev(field) — population standard deviation.
• histogram(field, {bins}) — equal-width frequency distribution.

Ranking

• topN(field, {n, ascending}) — top-N documents sorted by a field.
• rank(field, {ascending}) — dense rank with standard competition tie handling (1, 1, 3…).

Window functions

• rollingAvg(valueField, {window, orderBy}) — sliding window moving average.
• cumulativeSum(valueField, {orderBy}) — running cumulative sum.

Pivot

• pivot(rowField, colField, valueField, {agg}) — cross-tabulation (row × col → value) with sum, avg, count, min, or max.

Scoping

• AnalyticsCollection.all — runs analytics over the entire collection.
• AnalyticsCollection.where(filter) — pre-filters documents using any ffastdb query before analytics.

0.1.1 — 2026-04-26

Added

Window functions

• rollingAvgStream(valueField, {window, orderBy}) — lazily computes sliding window average as a stream.
• cumulativeSumStream(valueField, {orderBy}) — lazily computes running cumulative sum as a stream.
• rollingStdDev(valueField, {window, orderBy}) — sliding window standard deviation.
• rollingVariance(valueField, {window, orderBy}) — sliding window variance.
• rollingMin(valueField, {window, orderBy}) — sliding window minimum.
• rollingMax(valueField, {window, orderBy}) — sliding window maximum.
• rollingMedian(valueField, {window, orderBy}) — sliding window median.

Fixed

• Some tests failed in Windows due to Windows-specific line endings in test golden files.

0.1.2 - 2026-05-26

featured

• migrate to ffastdb 0.2.7