1 files changed, 0 insertions, 115 deletions
diff --git a/fluent-bit/lib/librdkafka-2.1.0/tests/performance_plot.py b/fluent-bit/lib/librdkafka-2.1.0/tests/performance_plot.py
deleted file mode 100755
index b699377f1..000000000
--- a/fluent-bit/lib/librdkafka-2.1.0/tests/performance_plot.py
+++ /dev/null
@@ -1,115 +0,0 @@
-#!/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))