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Antoine Pitrou commented on ARROW-2400: --------------------------------------- This patch seems to improve things by ~15% here on gcc 4.9: {code:c++} diff --git a/cpp/src/arrow/status.h b/cpp/src/arrow/status.h index 84f55e4..a2cf438 100644 --- a/cpp/src/arrow/status.h +++ b/cpp/src/arrow/status.h @@ -107,7 +107,11 @@ class ARROW_EXPORT Status { public: // Create a success status. Status() : state_(NULL) {} - ~Status() { delete state_; } + ~Status() { + if (ARROW_PREDICT_FALSE(state_ != NULL)) { + DeleteState(); + } + } Status(StatusCode code, const std::string& msg); @@ -207,6 +211,10 @@ class ARROW_EXPORT Status { // a `State` structure containing the error code and message(s) State* state_; + void DeleteState() { + delete state_; + state_ = NULL; + } void CopyFrom(const State* s); }; {code} > [C++] Status destructor is expensive > ------------------------------------ > > Key: ARROW-2400 > URL: https://issues.apache.org/jira/browse/ARROW-2400 > Project: Apache Arrow > Issue Type: Improvement > Affects Versions: 0.9.0 > Reporter: Antoine Pitrou > Priority: Major > > Let's take the following micro-benchmark (in Python): > {code:bash} > $ python -m timeit -s "import pyarrow as pa; data = [b'xx' for i in > range(10000)]" "pa.array(data, type=pa.binary())" > 1000 loops, best of 3: 784 usec per loop > {code} > If I replace the Status destructor with a no-op: > {code:c++} > ~Status() { } > {code} > then the benchmark result becomes: > {code:bash} > $ python -m timeit -s "import pyarrow as pa; data = [b'xx' for i in > range(10000)]" "pa.array(data, type=pa.binary())" > 1000 loops, best of 3: 561 usec per loop > {code} > This is almost a 30% win. I get similar results on the conversion benchmarks > in the benchmark suite. > I'm unsure about the explanation. In the common case, {{delete _state}} > should be extremely fast, since the state is NULL. Yet, it seems it adds > significant overhead. Perhaps because of exception handling? -- This message was sent by Atlassian JIRA (v7.6.3#76005)