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Merge pull request #152 from metamx/partition-distance 

DeterminePartitionsJob: Minimize distance from target instead of mean
This commit is contained in:
gianm 2013-05-18 17:26:18 -07:00
parent b0a58af05d 7f7ea485b1
commit 10bf25a66e
1 changed files with 14 additions and 16 deletions
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30
indexer/src/main/java/com/metamx/druid/indexer/DeterminePartitionsJob.java
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@ -90,8 +90,8 @@ import java.util.Set;
* put all those rows in the same partition, and that partition may be much larger than the target size.</li>
* </ul>
*
* "Best" means a very high cardinality dimension, or, if none exist, the dimension that minimizes segment size
* variance.
* "Best" means a very high cardinality dimension, or, if none exist, the dimension that minimizes variation of
* segment size relative to the target.
*/
public class DeterminePartitionsJob implements Jobby
{
@ -692,8 +692,8 @@ public class DeterminePartitionsJob implements Jobby
}
int maxCardinality = Integer.MIN_VALUE;
long minVariance = Long.MAX_VALUE;
DimPartitions minVariancePartitions = null;
long minDistance = Long.MAX_VALUE;
DimPartitions minDistancePartitions = null;
DimPartitions maxCardinalityPartitions = null;
for(final DimPartitions dimPartitions : dimPartitionss.values()) {
@ -722,16 +722,16 @@ public class DeterminePartitionsJob implements Jobby
}
final int cardinality = dimPartitions.getCardinality();
final long variance = dimPartitions.getVariance();
final long distance = dimPartitions.getDistanceSquaredFromTarget(config.getTargetPartitionSize());
if(cardinality > maxCardinality) {
maxCardinality = cardinality;
maxCardinalityPartitions = dimPartitions;
}
if(variance < minVariance) {
minVariance = variance;
minVariancePartitions = dimPartitions;
if(distance < minDistance) {
minDistance = distance;
minDistancePartitions = dimPartitions;
}
}
@ -745,7 +745,7 @@ public class DeterminePartitionsJob implements Jobby
final DimPartitions chosenPartitions = maxCardinality > HIGH_CARDINALITY_THRESHOLD
? maxCardinalityPartitions
: minVariancePartitions;
: minDistancePartitions;
final List<ShardSpec> chosenShardSpecs = Lists.transform(
chosenPartitions.partitions, new Function<DimPartition, ShardSpec>()
@ -824,17 +824,15 @@ public class DeterminePartitionsJob implements Jobby
return sum;
}
public long getVariance()
public long getDistanceSquaredFromTarget(long target)
{
final long meanRows = getRows() / partitions.size();
long variance = 0;
long distance = 0;
for(final DimPartition dimPartition : partitions) {
variance += (dimPartition.rows - meanRows) * (dimPartition.rows - meanRows);
distance += (dimPartition.rows - target) * (dimPartition.rows - target);
}
variance /= partitions.size();
return variance;
distance /= partitions.size();
return distance;
}
public int getRows()