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Continued experiments [#CLICKHOUSE-2]

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This commit is contained in:
Alexey Milovidov 2018-01-16 05:04:02 +03:00
parent 2fa8992e2c
commit 846de85799
1 changed files with 10 additions and 10 deletions
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20
dbms/src/IO/LZ4_decompress_faster.h
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@ -9,15 +9,15 @@ namespace LZ4
{
/** There are many implementation details of LZ4 decompression loop, that affect performance.
* For example: copy by 8 or by 16 bytes at once; use shuffle instruction to replicate match or not.
* For example: copy by 8 or by 16 (SSE2) bytes at once; use shuffle (SSSE3) instruction to replicate match or not.
*
* The optimal algorithm is dependent:
* The optimal algorithm is dependent on:
*
* - on CPU architecture
* 1. CPU architecture.
* (example: on Skylake it's almost always better to copy by 16 bytes and use shuffle,
* but on Westmere using shuffle is worse and copy by 16 bytes is better only for high compression ratios)
*
* - on data distribution
* 2. Data distribution.
* (example: when compression ratio is higher than 10.20,
* it's usually better to copy by 16 bytes rather than 8).
*
@ -49,22 +49,22 @@ struct PerformanceStatistics
double count = 0;
double sum = 0;
double adjusted_count() const
double adjustedCount() const
{
return count - NUM_INVOCATIONS_TO_THROW_OFF;
}
double mean() const
{
return sum / adjusted_count();
return sum / adjustedCount();
}
/// For better convergence, we don't use proper estimate of stddev.
/// We want to eventually choose between two algorithms even in case
/// We want to eventually separate between two algorithms even in case
/// when there is no statistical significant difference between them.
double sigma() const
{
return mean() / sqrt(adjusted_count());
return mean() / sqrt(adjustedCount());
}
void update(double seconds, double bytes)
@ -80,8 +80,8 @@ struct PerformanceStatistics
/// If there is a variant with not enough statistics, always choose it.
/// And in that case prefer variant with less number of invocations.
if (adjusted_count() < 2)
return adjusted_count() - 1;
if (adjustedCount() < 2)
return adjustedCount() - 1;
else
return std::normal_distribution<>(mean(), sigma())(rng);
}