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Do index compaction in batches of 10000 in order to allow greater rea…
…d/write throughput when the index tree is large (greater than 1M entries)
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Original file line number | Diff line number | Diff line change |
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package mvcc | ||
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import ( | ||
"testing" | ||
) | ||
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func BenchmarkIndexCompact1(b *testing.B) { benchmarkIndexCompact(b, 1) } | ||
func BenchmarkIndexCompact100(b *testing.B) { benchmarkIndexCompact(b, 100) } | ||
func BenchmarkIndexCompact10000(b *testing.B) { benchmarkIndexCompact(b, 10000) } | ||
func BenchmarkIndexCompact100000(b *testing.B) { benchmarkIndexCompact(b, 100000) } | ||
func BenchmarkIndexCompact1000000(b *testing.B) { benchmarkIndexCompact(b, 1000000) } | ||
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func benchmarkIndexCompact(b *testing.B, size int) { | ||
plog.SetLevel(0) // suppress log entries | ||
kvindex := newTreeIndex() | ||
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bytesN := 64 | ||
keys := createBytesSlice(bytesN, size) | ||
for i := 1; i < size; i++ { | ||
kvindex.Put(keys[i], revision {main: int64(i), sub: int64(i)}) | ||
} | ||
b.ResetTimer() | ||
for i := 1; i < b.N; i++ { | ||
kvindex.Compact(int64(i)) | ||
} | ||
} |