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authorDidier Durand <durand.didier@gmail.com>2020-09-21 06:33:28 +0200
committerGitHub <noreply@github.com>2020-09-21 06:33:28 +0200
commitbe86a915844ead7965afd1379e95ed680166e85f (patch)
tree58a512a1a3d6b71f3f0151abd58f81d32a2a5cc1
parent4197a26a3765a4b3b5dd10669e2f4f76742558fa (diff)
Update performance.md
@ianlewis: fixed according to your proposal
-rw-r--r--g3doc/architecture_guide/performance.md2
1 files changed, 1 insertions, 1 deletions
diff --git a/g3doc/architecture_guide/performance.md b/g3doc/architecture_guide/performance.md
index ae85f3ddd..b981f0c01 100644
--- a/g3doc/architecture_guide/performance.md
+++ b/g3doc/architecture_guide/performance.md
@@ -211,7 +211,7 @@ url="/performance/applications.csv" title="perf.py http.(node|ruby)
The above figure shows the result of simple `node` and `ruby` web services that
render a template upon receiving a request. Because these synthetic benchmarks
-do minimal work per request, most like the `redis` case, they suffer from high
+do minimal work per request, much like the `redis` case, they suffer from high
overheads. In practice, the more work an application does the smaller the impact
of **structural costs** become.