905f8d763a
This reduces the overhead of the method instrumentation code primarily by reducing the number of method calls. There are also some other small optimisations such as not casting timing values to Floats (there's no particular need for this), using Symbols for method call metric names, and reducing the number of Hash lookups for instrumented methods. The exact impact depends on the code being executed. For example, for a method that's only called once the difference won't be very noticeable. However, for methods that are called many times the difference can be more significant. For example, the loading time of a large commit (nrclark/dummy_project@81ebdea5df) was reduced from around 19 seconds to around 15 seconds using these changes.
52 lines
1.3 KiB
Ruby
52 lines
1.3 KiB
Ruby
module Gitlab
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module Metrics
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# Class for tracking timing information about method calls
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class MethodCall
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attr_reader :real_time, :cpu_time, :call_count
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# name - The full name of the method (including namespace) such as
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# `User#sign_in`.
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#
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# series - The series to use for storing the data.
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def initialize(name, series)
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@name = name
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@series = series
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@real_time = 0
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@cpu_time = 0
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@call_count = 0
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end
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# Measures the real and CPU execution time of the supplied block.
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def measure
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start_real = System.monotonic_time
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start_cpu = System.cpu_time
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retval = yield
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@real_time += System.monotonic_time - start_real
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@cpu_time += System.cpu_time - start_cpu
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@call_count += 1
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retval
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end
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# Returns a Metric instance of the current method call.
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def to_metric
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Metric.new(
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@series,
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{
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duration: real_time,
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cpu_duration: cpu_time,
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call_count: call_count
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},
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method: @name
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)
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end
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# Returns true if the total runtime of this method exceeds the method call
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# threshold.
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def above_threshold?
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real_time >= Metrics.method_call_threshold
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end
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end
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end
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end
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