* Was encountering weird errors when fast writes were coming in while queries were happening.
* Added unit tests which tend to cause concurrency query problems
- For now uses a hardcoded ratio of aggregator to timeanddim buffer sizes
- canAppendRow is a workaround for realtime index since the
Firehose currently does not have a way of rolling back the last event in
case of error
- canAppendRow needs a fudge factor; there is a race between checking
if we can add a row and actually adding a row, because of the way MapDB
reports its size.
Change serializer / deserializer for HyperLogLog
* Changed DirectDruidClient's InputStream handling. Is now ~10% faster for data heavy queries, and has lower variance in execution speed.
* Changed HLL Collector's toByteStream() method to be better optimized for small values. Is notably faster for small result quantities which fall into the sparse HLL bucket codepath.
* No change for dense HLL which just uses a direct bytestream of the underlying byte data.
TopNNumericResultBuilder semi-aggressive loop unrolling for metricVals
Benchmark for HLL for sparse packing (small HLL bucket population):
HyperLogLogSerdeBenchmarkTest.benchmarkToByteBuffer[0]: [measured 100000 out of 100100 rounds, threads: 1 (sequential)]
round: 0.00 [+- 0.00], round.block: 0.00 [+- 0.00], round.gc: 0.00 [+- 0.00], GC.calls: 216, GC.time: 0.42, time.total: 15.96, time.warmup: 0.22, time.bench: 15.74
HyperLogLogSerdeBenchmarkTest.benchmarkToByteBuffer[1]: [measured 100000 out of 100100 rounds, threads: 1 (sequential)]
round: 0.00 [+- 0.00], round.block: 0.00 [+- 0.00], round.gc: 0.00 [+- 0.00], GC.calls: 217, GC.time: 0.45, time.total: 13.87, time.warmup: 0.02, time.bench: 13.85
HyperLogLogSerdeBenchmarkTest.benchmarkToByteBuffer[2]: [measured 100000 out of 100100 rounds, threads: 1 (sequential)]
round: 0.00 [+- 0.00], round.block: 0.00 [+- 0.00], round.gc: 0.00 [+- 0.00], GC.calls: 55, GC.time: 0.16, time.total: 4.13, time.warmup: 0.00, time.bench: 4.12
HyperLogLogSerdeBenchmarkTest.benchmarkToByteBuffer[3]: [measured 100000 out of 100100 rounds, threads: 1 (sequential)]
round: 0.00 [+- 0.00], round.block: 0.00 [+- 0.00], round.gc: 0.00 [+- 0.00], GC.calls: 55, GC.time: 0.16, time.total: 4.30, time.warmup: 0.00, time.bench: 4.30
HyperLogLogSerdeBenchmarkTest.benchmarkToByteBuffer[4]: [measured 100000 out of 100100 rounds, threads: 1 (sequential)]
round: 0.00 [+- 0.00], round.block: 0.00 [+- 0.00], round.gc: 0.00 [+- 0.00], GC.calls: 8, GC.time: 0.03, time.total: 1.10, time.warmup: 0.00, time.bench: 1.09
HyperLogLogSerdeBenchmarkTest.benchmarkToByteBuffer[5]: [measured 100000 out of 100100 rounds, threads: 1 (sequential)]
round: 0.00 [+- 0.00], round.block: 0.00 [+- 0.00], round.gc: 0.00 [+- 0.00], GC.calls: 8, GC.time: 0.03, time.total: 0.72, time.warmup: 0.00, time.bench: 0.72
HyperLogLogSerdeBenchmarkTest.benchmarkToByteBuffer[6]: [measured 100000 out of 100100 rounds, threads: 1 (sequential)]
round: 0.00 [+- 0.00], round.block: 0.00 [+- 0.00], round.gc: 0.00 [+- 0.00], GC.calls: 1, GC.time: 0.00, time.total: 0.60, time.warmup: 0.00, time.bench: 0.60
HyperLogLogSerdeBenchmarkTest.benchmarkToByteBuffer[7]: [measured 100000 out of 100100 rounds, threads: 1 (sequential)]
round: 0.00 [+- 0.00], round.block: 0.00 [+- 0.00], round.gc: 0.00 [+- 0.00], GC.calls: 2, GC.time: 0.01, time.total: 0.26, time.warmup: 0.00, time.bench: 0.25
Updates to HyperLogLogCollector toByteBuffer() based on code review
Removed changes from DirectDruidClient from this branch and put it in another branch.
Changed HyperLogLogCollector to have protected getters and setters
Remove unused ByteOrder from HyperLogLogCollector
Copyright header on HyperLogLogSerdeBenchmarkTest
Now with less ass!
Reformat in TopNNumericResultsBuilder. No code change
Removed unused import in HyperLogLogCollector
Replace AppendableByteArrayInputStream in DirectDruidClient
* Replace with SequenceInputStream fueled by an enumeration of ChannelBufferInputStream which directly wrap the response context ChannelBuffer
Modify TopNQueryQueryToolChest to use Arrays instead of Lists
Modify TopNQueryQueryToolChest to use Arrays instead of Lists
Revert accidental changes to DirectDruidClient
They should be in another merge request:
https://github.com/metamx/druid/pull/893
Fixes from code review
* Extracting names from AggregatorFactory classes now done with TopNQueryQueryToolChest.extractFactoryName
* Renamed variable in TopNNumericResultBuilder
* Added more unit tests
* Now properly uses safe / fast decompressor for LZ4
* Now chooses fastest lz4 instance instead of only looking at Java implmentations
* Encapsulate ResourceHolder in try-with-resources to make sure they close correctly
