Upload core stats to qps_test

1 files changed, 57 insertions, 0 deletions

diff --git a/tools/run_tests/performance/massage_qps_stats_helpers.py b/tools/run_tests/performance/massage_qps_stats_helpers.py
new file mode 100644
index 0000000000..c5d884344f
--- /dev/null
+++ b/tools/run_tests/performance/massage_qps_stats_helpers.py
@@ -0,0 +1,57 @@
+# Copyright 2017 gRPC authors.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import collections
+
+def threshold_for_count_below(buckets, boundaries, count_below):
+  count_so_far = 0
+  for lower_idx in range(0, len(buckets)):
+    count_so_far += buckets[lower_idx]
+    if count_so_far >= count_below:
+      break
+  if count_so_far == count_below:
+    # this bucket hits the threshold exactly... we should be midway through
+    # any run of zero values following the bucket
+    for upper_idx in range(lower_idx + 1, num_buckets):
+      if buckets[upper_idx] != 0:
+        break
+    return (boundaries[lower_idx] + boundaries[upper_idx]) / 2.0
+  else:
+    # treat values as uniform throughout the bucket, and find where this value
+    # should lie
+    lower_bound = boundaries[lower_idx]
+    upper_bound = boundaries[lower_idx + 1]
+    return (upper_bound -
+           (upper_bound - lower_bound) * (count_so_far - count_below) /
+               float(buckets[lower_idx]))
+
+def percentile(buckets, pctl, boundaries):
+  return threshold_for_count_below(
+      buckets, boundaries, sum(buckets) * pctl / 100.0)
+
+def counter(core_stats, name):
+  for stat in core_stats['metrics']:
+    if stat['name'] == name:
+      return int(stat.get('count', 0))
+
+Histogram = collections.namedtuple('Histogram', 'buckets boundaries')
+def histogram(core_stats, name):
+  for stat in core_stats['metrics']:
+    if stat['name'] == name:
+      buckets = []
+      boundaries = []
+      for b in stat['histogram']['buckets']:
+        buckets.append(int(b.get('count', 0)))
+        boundaries.append(int(b.get('start', 0)))
+  return Histogram(buckets=buckets, boundaries=boundaries)