1 files changed, 115 insertions, 0 deletions
diff --git a/src/fluent-bit/lib/librdkafka-2.1.0/tests/performance_plot.py b/src/fluent-bit/lib/librdkafka-2.1.0/tests/performance_plot.py
new file mode 100755
index 000000000..b699377f1
--- /dev/null
+++ b/src/fluent-bit/lib/librdkafka-2.1.0/tests/performance_plot.py
@@ -0,0 +1,115 @@
+#!/usr/bin/env python3
+#
+
+import sys
+import json
+import numpy as np
+import matplotlib.pyplot as plt
+
+from collections import defaultdict
+
+
+def semver2int(semver):
+    if semver == 'trunk':
+        semver = '0.10.0.0'
+    vi = 0
+    i = 0
+    for v in reversed(semver.split('.')):
+        vi += int(v) * (i * 10)
+        i += 1
+    return vi
+
+
+def get_perf_data(perfname, stats):
+    """ Return [labels,x,y,errs] for perfname 'mb_per_sec' as a numpy arrays
+        labels: broker versions
+        x: list with identical value (to plot on same x point)
+        y: perfname counter (average)
+        errs: errors
+    """
+    ver = defaultdict(list)
+
+    # Per version:
+    #  * accumulate values
+    #  * calculate average
+    #  * calculate error
+
+    # Accumulate values per version
+    for x in stats:
+        v = str(x[0])
+        ver[v].append(x[1][perfname])
+    print('%s is %s' % (perfname, ver))
+
+    labels0 = sorted(ver.keys(), key=semver2int)
+    y0 = list()
+    errs0 = list()
+
+    # Maintain order by using labels0
+    for v in labels0:
+        # Calculate average
+        avg = sum(ver[v]) / float(len(ver[v]))
+        y0.append(avg)
+        # Calculate error
+        errs0.append(max(ver[v]) - avg)
+
+    labels = np.array(labels0)
+    y1 = np.array(y0)
+    x1 = np.array(range(0, len(labels)))
+    errs = np.array(errs0)
+    return [labels, x1, y1, errs]
+
+
+def plot(description, name, stats, perfname, outfile=None):
+    labels, x, y, errs = get_perf_data(perfname, stats)
+    plt.title('%s: %s %s' % (description, name, perfname))
+    plt.xlabel('Kafka version')
+    plt.ylabel(perfname)
+    plt.errorbar(x, y, yerr=errs, alpha=0.5)
+    plt.xticks(x, labels, rotation='vertical')
+    plt.margins(0.2)
+    plt.subplots_adjust(bottom=0.2)
+    if outfile is None:
+        plt.show()
+    else:
+        plt.savefig(outfile, bbox_inches='tight')
+    return
+
+
+if __name__ == '__main__':
+
+    outfile = sys.argv[1]
+
+    reports = []
+    for rf in sys.argv[2:]:
+        with open(rf) as f:
+            reports.append(json.load(f))
+
+    stats = defaultdict(list)
+
+    # Extract performance test data
+    for rep in reports:
+        perfs = rep.get(
+            'tests',
+            dict()).get(
+            '0038_performance',
+            list).get(
+            'report',
+            None)
+        if perfs is None:
+            continue
+
+        for perf in perfs:
+            for n in ['producer', 'consumer']:
+                o = perf.get(n, None)
+                if o is None:
+                    print('no %s in %s' % (n, perf))
+                    continue
+
+                stats[n].append((rep.get('broker_version', 'unknown'), o))
+
+    for t in ['producer', 'consumer']:
+        for perfname in ['mb_per_sec', 'records_per_sec']:
+            plot('librdkafka 0038_performance test: %s (%d samples)' %
+                 (outfile, len(reports)),
+                 t, stats[t], perfname, outfile='%s_%s_%s.png' % (
+                     outfile, t, perfname))