chore: integrate goreleaser for user_scripts and restructuring (#6911)

* chore: integrate goreleaser for user_scripts and restructuring
* ci(goreleaser): add goreleaser workflow
* chore(goreleaser): update Makefile and config

---------

Signed-off-by: Prashant Shahi <prashant@signoz.io>

scripts/clickhouse/histogramquantile/.goreleaser.yaml

@@ -0,0 +1,45 @@
+# yaml-language-server: $schema=https://goreleaser.com/static/schema-pro.json
+# vim: set ts=2 sw=2 tw=0 fo=cnqoj
+version: 2
+
+project_name: histogram-quantile
+
+monorepo:
+  tag_prefix: histogram-quantile/
+
+before:
+  hooks:
+    - go mod tidy
+    - cp ../../../LICENSE .
+    - cp ../../../README.md .
+
+after:
+  hooks:
+    - rm LICENSE
+    - rm README.md
+
+builds:
+  - env:
+      - CGO_ENABLED=0
+    goos:
+      - linux
+      - darwin
+    goarch:
+      - amd64
+      - arm64
+
+archives:
+  - formats:
+      - tar.gz
+    name_template: >-
+      {{ .ProjectName }}_{{- .Os }}_{{- .Arch }}
+    files:
+      - README.md
+      - LICENSE
+
+release:
+  footer: >-
+
+    ---
+
+    Released by [GoReleaser](https://github.com/goreleaser/goreleaser).

scripts/clickhouse/histogramquantile/main.go

@@ -0,0 +1,237 @@
+package main
+
+import (
+	"bufio"
+	"fmt"
+	"math"
+	"os"
+	"sort"
+	"strconv"
+	"strings"
+)
+
+// NOTE: executable must be built with target OS and architecture set to linux/amd64
+// env GOOS=linux GOARCH=amd64 go build -o histogramQuantile histogramQuantile.go
+
+// The following code is adapted from the following source:
+// https://github.com/prometheus/prometheus/blob/main/promql/quantile.go
+
+type bucket struct {
+	upperBound float64
+	count      float64
+}
+
+// buckets implements sort.Interface.
+type buckets []bucket
+
+func (b buckets) Len() int           { return len(b) }
+func (b buckets) Swap(i, j int)      { b[i], b[j] = b[j], b[i] }
+func (b buckets) Less(i, j int) bool { return b[i].upperBound < b[j].upperBound }
+
+// bucketQuantile calculates the quantile 'q' based on the given buckets. The
+// buckets will be sorted by upperBound by this function (i.e. no sorting
+// needed before calling this function). The quantile value is interpolated
+// assuming a linear distribution within a bucket. However, if the quantile
+// falls into the highest bucket, the upper bound of the 2nd highest bucket is
+// returned. A natural lower bound of 0 is assumed if the upper bound of the
+// lowest bucket is greater 0. In that case, interpolation in the lowest bucket
+// happens linearly between 0 and the upper bound of the lowest bucket.
+// However, if the lowest bucket has an upper bound less or equal 0, this upper
+// bound is returned if the quantile falls into the lowest bucket.
+//
+// There are a number of special cases (once we have a way to report errors
+// happening during evaluations of AST functions, we should report those
+// explicitly):
+//
+// If 'buckets' has 0 observations, NaN is returned.
+//
+// If 'buckets' has fewer than 2 elements, NaN is returned.
+//
+// If the highest bucket is not +Inf, NaN is returned.
+//
+// If q==NaN, NaN is returned.
+//
+// If q<0, -Inf is returned.
+//
+// If q>1, +Inf is returned.
+func bucketQuantile(q float64, buckets buckets) float64 {
+	if math.IsNaN(q) {
+		return math.NaN()
+	}
+	if q < 0 {
+		return math.Inf(-1)
+	}
+	if q > 1 {
+		return math.Inf(+1)
+	}
+	sort.Sort(buckets)
+	if !math.IsInf(buckets[len(buckets)-1].upperBound, +1) {
+		return math.NaN()
+	}
+
+	buckets = coalesceBuckets(buckets)
+	ensureMonotonic(buckets)
+
+	if len(buckets) < 2 {
+		return math.NaN()
+	}
+	observations := buckets[len(buckets)-1].count
+	if observations == 0 {
+		return math.NaN()
+	}
+	rank := q * observations
+	b := sort.Search(len(buckets)-1, func(i int) bool { return buckets[i].count >= rank })
+
+	if b == len(buckets)-1 {
+		return buckets[len(buckets)-2].upperBound
+	}
+	if b == 0 && buckets[0].upperBound <= 0 {
+		return buckets[0].upperBound
+	}
+	var (
+		bucketStart float64
+		bucketEnd   = buckets[b].upperBound
+		count       = buckets[b].count
+	)
+	if b > 0 {
+		bucketStart = buckets[b-1].upperBound
+		count -= buckets[b-1].count
+		rank -= buckets[b-1].count
+	}
+	return bucketStart + (bucketEnd-bucketStart)*(rank/count)
+}
+
+// coalesceBuckets merges buckets with the same upper bound.
+//
+// The input buckets must be sorted.
+func coalesceBuckets(buckets buckets) buckets {
+	last := buckets[0]
+	i := 0
+	for _, b := range buckets[1:] {
+		if b.upperBound == last.upperBound {
+			last.count += b.count
+		} else {
+			buckets[i] = last
+			last = b
+			i++
+		}
+	}
+	buckets[i] = last
+	return buckets[:i+1]
+}
+
+// The assumption that bucket counts increase monotonically with increasing
+// upperBound may be violated during:
+//
+//   * Recording rule evaluation of histogram_quantile, especially when rate()
+//      has been applied to the underlying bucket timeseries.
+//   * Evaluation of histogram_quantile computed over federated bucket
+//      timeseries, especially when rate() has been applied.
+//
+// This is because scraped data is not made available to rule evaluation or
+// federation atomically, so some buckets are computed with data from the
+// most recent scrapes, but the other buckets are missing data from the most
+// recent scrape.
+//
+// Monotonicity is usually guaranteed because if a bucket with upper bound
+// u1 has count c1, then any bucket with a higher upper bound u > u1 must
+// have counted all c1 observations and perhaps more, so that c  >= c1.
+//
+// Randomly interspersed partial sampling breaks that guarantee, and rate()
+// exacerbates it. Specifically, suppose bucket le=1000 has a count of 10 from
+// 4 samples but the bucket with le=2000 has a count of 7 from 3 samples. The
+// monotonicity is broken. It is exacerbated by rate() because under normal
+// operation, cumulative counting of buckets will cause the bucket counts to
+// diverge such that small differences from missing samples are not a problem.
+// rate() removes this divergence.)
+//
+// bucketQuantile depends on that monotonicity to do a binary search for the
+// bucket with the φ-quantile count, so breaking the monotonicity
+// guarantee causes bucketQuantile() to return undefined (nonsense) results.
+//
+// As a somewhat hacky solution until ingestion is atomic per scrape, we
+// calculate the "envelope" of the histogram buckets, essentially removing
+// any decreases in the count between successive buckets.
+
+func ensureMonotonic(buckets buckets) {
+	max := buckets[0].count
+	for i := 1; i < len(buckets); i++ {
+		switch {
+		case buckets[i].count > max:
+			max = buckets[i].count
+		case buckets[i].count < max:
+			buckets[i].count = max
+		}
+	}
+}
+
+// End of copied code.
+
+func readLines() []string {
+	r := bufio.NewReader(os.Stdin)
+	bytes := []byte{}
+	lines := []string{}
+	for {
+		line, isPrefix, err := r.ReadLine()
+		if err != nil {
+			break
+		}
+		bytes = append(bytes, line...)
+		if !isPrefix {
+			str := strings.TrimSpace(string(bytes))
+			if len(str) > 0 {
+				lines = append(lines, str)
+				bytes = []byte{}
+			}
+		}
+	}
+	if len(bytes) > 0 {
+		lines = append(lines, string(bytes))
+	}
+	return lines
+}
+
+func main() {
+	lines := readLines()
+	for _, text := range lines {
+		// Example input
+		// "[1, 2, 4, 8, 16]", "[1, 5, 8, 10, 14]", 0.9"
+		// bounds - counts - quantile
+		parts := strings.Split(text, "\",")
+
+		var bucketNumbers []float64
+		// Strip the ends with square brackets
+		text = parts[0][2 : len(parts[0])-1]
+		// Parse the bucket bounds
+		for _, num := range strings.Split(text, ",") {
+			num = strings.TrimSpace(num)
+			number, err := strconv.ParseFloat(num, 64)
+			if err == nil {
+				bucketNumbers = append(bucketNumbers, number)
+			}
+		}
+
+		var bucketCounts []float64
+		// Strip the ends with square brackets
+		text = parts[1][2 : len(parts[1])-1]
+		// Parse the bucket counts
+		for _, num := range strings.Split(text, ",") {
+			num = strings.TrimSpace(num)
+			number, err := strconv.ParseFloat(num, 64)
+			if err == nil {
+				bucketCounts = append(bucketCounts, number)
+			}
+		}
+
+		// Parse the quantile
+		q, err := strconv.ParseFloat(parts[2], 64)
+		var b buckets
+
+		if err == nil {
+			for i := 0; i < len(bucketNumbers); i++ {
+				b = append(b, bucket{upperBound: bucketNumbers[i], count: bucketCounts[i]})
+			}
+		}
+		fmt.Println(bucketQuantile(q, b))
+	}
+}