More efficient SegmentMetadataQuery

This commit is contained in:
jon-wei 2015-12-17 12:45:14 -08:00
parent f8cf84f466
commit 356b07c6c3
11 changed files with 86 additions and 17 deletions

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@ -19,6 +19,7 @@
package io.druid.common.guava; package io.druid.common.guava;
import com.google.common.base.Function;
import com.google.common.collect.Ordering; import com.google.common.collect.Ordering;
import com.metamx.common.guava.Accumulator; import com.metamx.common.guava.Accumulator;
import com.metamx.common.guava.Sequence; import com.metamx.common.guava.Sequence;
@ -37,25 +38,29 @@ public class CombiningSequence<T> implements Sequence<T>
public static <T> CombiningSequence<T> create( public static <T> CombiningSequence<T> create(
Sequence<T> baseSequence, Sequence<T> baseSequence,
Ordering<T> ordering, Ordering<T> ordering,
BinaryFn<T, T, T> mergeFn BinaryFn<T, T, T> mergeFn,
Function transformFn
) )
{ {
return new CombiningSequence<T>(baseSequence, ordering, mergeFn); return new CombiningSequence<T>(baseSequence, ordering, mergeFn, transformFn);
} }
private final Sequence<T> baseSequence; private final Sequence<T> baseSequence;
private final Ordering<T> ordering; private final Ordering<T> ordering;
private final BinaryFn<T, T, T> mergeFn; private final BinaryFn<T, T, T> mergeFn;
private final Function transformFn;
public CombiningSequence( public CombiningSequence(
Sequence<T> baseSequence, Sequence<T> baseSequence,
Ordering<T> ordering, Ordering<T> ordering,
BinaryFn<T, T, T> mergeFn BinaryFn<T, T, T> mergeFn,
Function transformFn
) )
{ {
this.baseSequence = baseSequence; this.baseSequence = baseSequence;
this.ordering = ordering; this.ordering = ordering;
this.mergeFn = mergeFn; this.mergeFn = mergeFn;
this.transformFn = transformFn;
} }
@Override @Override
@ -117,6 +122,9 @@ public class CombiningSequence<T> implements Sequence<T>
@Override @Override
public OutType get() public OutType get()
{ {
if (transformFn != null) {
return (OutType) transformFn.apply(retVal);
}
return retVal; return retVal;
} }

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@ -214,7 +214,8 @@ public class CombiningSequenceTest
return Pair.of(lhs.lhs, lhs.rhs + rhs.rhs); return Pair.of(lhs.lhs, lhs.rhs + rhs.rhs);
} }
} },
null
); );
List<Pair<Integer, Integer>> merged = Sequences.toList(seq, Lists.<Pair<Integer, Integer>>newArrayList()); List<Pair<Integer, Integer>> merged = Sequences.toList(seq, Lists.<Pair<Integer, Integer>>newArrayList());

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@ -30,7 +30,7 @@ There are several main parts to a segment metadata query:
|toInclude|A JSON Object representing what columns should be included in the result. Defaults to "all".|no| |toInclude|A JSON Object representing what columns should be included in the result. Defaults to "all".|no|
|merge|Merge all individual segment metadata results into a single result|no| |merge|Merge all individual segment metadata results into a single result|no|
|context|See [Context](../querying/query-context.html)|no| |context|See [Context](../querying/query-context.html)|no|
|analysisTypes|A list of Strings specifying what column properties (e.g. cardinality, size) should be calculated and returned in the result. Defaults to ["cardinality", "size"]. See section [analysisTypes](#analysistypes) for more details.|no| |analysisTypes|A list of Strings specifying what column properties (e.g. cardinality, size) should be calculated and returned in the result. Defaults to ["cardinality", "size", "interval"]. See section [analysisTypes](#analysistypes) for more details.|no|
The format of the result is: The format of the result is:
@ -96,7 +96,7 @@ This is a list of properties that determines the amount of information returned
By default, all analysis types will be used. If a property is not needed, omitting it from this list will result in a more efficient query. By default, all analysis types will be used. If a property is not needed, omitting it from this list will result in a more efficient query.
There are 2 types of column analyses: There are 3 types of column analyses:
#### cardinality #### cardinality
@ -107,3 +107,7 @@ There are 2 types of column analyses:
* Estimated byte size for the segment columns if they were stored in a flat format * Estimated byte size for the segment columns if they were stored in a flat format
* Estimated total segment byte size in if it was stored in a flat format * Estimated total segment byte size in if it was stored in a flat format
#### interval
* If present, the SegmentMetadataQuery will return the list of intervals associated with the queried segments.

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@ -40,7 +40,7 @@ public abstract class ResultMergeQueryRunner<T> extends BySegmentSkippingQueryRu
@Override @Override
public Sequence<T> doRun(QueryRunner<T> baseRunner, Query<T> query, Map<String, Object> context) public Sequence<T> doRun(QueryRunner<T> baseRunner, Query<T> query, Map<String, Object> context)
{ {
return CombiningSequence.create(baseRunner.run(query, context), makeOrdering(query), createMergeFn(query)); return CombiningSequence.create(baseRunner.run(query, context), makeOrdering(query), createMergeFn(query), null);
} }
protected abstract Ordering<T> makeOrdering(Query<T> query); protected abstract Ordering<T> makeOrdering(Query<T> query);

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@ -281,4 +281,8 @@ public class SegmentAnalyzer
return analysisTypes.contains(SegmentMetadataQuery.AnalysisType.CARDINALITY); return analysisTypes.contains(SegmentMetadataQuery.AnalysisType.CARDINALITY);
} }
private boolean analysisHasInterva(EnumSet<SegmentMetadataQuery.AnalysisType> analysisTypes) {
return analysisTypes.contains(SegmentMetadataQuery.AnalysisType.INTERVAL);
}
} }

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@ -34,7 +34,9 @@ import com.metamx.common.guava.Sequence;
import com.metamx.common.guava.nary.BinaryFn; import com.metamx.common.guava.nary.BinaryFn;
import com.metamx.emitter.service.ServiceMetricEvent; import com.metamx.emitter.service.ServiceMetricEvent;
import io.druid.collections.OrderedMergeSequence; import io.druid.collections.OrderedMergeSequence;
import io.druid.common.guava.CombiningSequence;
import io.druid.common.utils.JodaUtils; import io.druid.common.utils.JodaUtils;
import io.druid.data.input.Row;
import io.druid.query.CacheStrategy; import io.druid.query.CacheStrategy;
import io.druid.query.DruidMetrics; import io.druid.query.DruidMetrics;
import io.druid.query.Query; import io.druid.query.Query;
@ -77,6 +79,36 @@ public class SegmentMetadataQueryQueryToolChest extends QueryToolChest<SegmentAn
{ {
return new ResultMergeQueryRunner<SegmentAnalysis>(runner) return new ResultMergeQueryRunner<SegmentAnalysis>(runner)
{ {
private Function<SegmentAnalysis, SegmentAnalysis> transformFn = new Function<SegmentAnalysis, SegmentAnalysis>()
{
@Override
public SegmentAnalysis apply(SegmentAnalysis analysis)
{
return new SegmentAnalysis(
analysis.getId(),
JodaUtils.condenseIntervals(analysis.getIntervals()),
analysis.getColumns(),
analysis.getSize(),
analysis.getNumRows()
);
}
};
@Override
public Sequence<SegmentAnalysis> doRun(
QueryRunner<SegmentAnalysis> baseRunner,
Query<SegmentAnalysis> query,
Map<String, Object> context
)
{
return CombiningSequence.create(
baseRunner.run(query, context),
makeOrdering(query),
createMergeFn(query),
transformFn
);
}
@Override @Override
protected Ordering<SegmentAnalysis> makeOrdering(Query<SegmentAnalysis> query) protected Ordering<SegmentAnalysis> makeOrdering(Query<SegmentAnalysis> query)
{ {
@ -115,9 +147,11 @@ public class SegmentMetadataQueryQueryToolChest extends QueryToolChest<SegmentAn
return arg1; return arg1;
} }
List<Interval> newIntervals = JodaUtils.condenseIntervals( List<Interval> newIntervals = null;
Iterables.concat(arg1.getIntervals(), arg2.getIntervals()) if (query.hasInterval()) {
); newIntervals = arg1.getIntervals();
newIntervals.addAll(arg2.getIntervals());
}
final Map<String, ColumnAnalysis> leftColumns = arg1.getColumns(); final Map<String, ColumnAnalysis> leftColumns = arg1.getColumns();
final Map<String, ColumnAnalysis> rightColumns = arg2.getColumns(); final Map<String, ColumnAnalysis> rightColumns = arg2.getColumns();

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@ -45,9 +45,11 @@ import io.druid.query.metadata.metadata.SegmentMetadataQuery;
import io.druid.segment.QueryableIndex; import io.druid.segment.QueryableIndex;
import io.druid.segment.Segment; import io.druid.segment.Segment;
import io.druid.segment.StorageAdapter; import io.druid.segment.StorageAdapter;
import org.joda.time.Interval;
import java.util.ArrayList; import java.util.ArrayList;
import java.util.Arrays; import java.util.Arrays;
import java.util.List;
import java.util.Map; import java.util.Map;
import java.util.concurrent.CancellationException; import java.util.concurrent.CancellationException;
import java.util.concurrent.ExecutionException; import java.util.concurrent.ExecutionException;
@ -117,12 +119,13 @@ public class SegmentMetadataQueryRunnerFactory implements QueryRunnerFactory<Seg
columns.put(columnName, column); columns.put(columnName, column);
} }
} }
List<Interval> retIntervals = query.hasInterval() ? Arrays.asList(segment.getDataInterval()) : null;
return Sequences.simple( return Sequences.simple(
Arrays.asList( Arrays.asList(
new SegmentAnalysis( new SegmentAnalysis(
segment.getIdentifier(), segment.getIdentifier(),
Arrays.asList(segment.getDataInterval()), retIntervals,
columns, columns,
totalSize, totalSize,
numRows numRows

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@ -50,7 +50,8 @@ public class SegmentMetadataQuery extends BaseQuery<SegmentAnalysis>
public enum AnalysisType public enum AnalysisType
{ {
CARDINALITY, CARDINALITY,
SIZE; SIZE,
INTERVAL;
@JsonValue @JsonValue
@Override @Override
@ -77,7 +78,8 @@ public class SegmentMetadataQuery extends BaseQuery<SegmentAnalysis>
public static final EnumSet<AnalysisType> DEFAULT_ANALYSIS_TYPES = EnumSet.of( public static final EnumSet<AnalysisType> DEFAULT_ANALYSIS_TYPES = EnumSet.of(
AnalysisType.CARDINALITY, AnalysisType.CARDINALITY,
AnalysisType.SIZE AnalysisType.SIZE,
AnalysisType.INTERVAL
); );
private final ColumnIncluderator toInclude; private final ColumnIncluderator toInclude;
@ -163,6 +165,11 @@ public class SegmentMetadataQuery extends BaseQuery<SegmentAnalysis>
return analysisTypes.contains(AnalysisType.SIZE); return analysisTypes.contains(AnalysisType.SIZE);
} }
public boolean hasInterval()
{
return analysisTypes.contains(AnalysisType.INTERVAL);
}
public byte[] getAnalysisTypesCacheKey() public byte[] getAnalysisTypesCacheKey()
{ {
int size = 1; int size = 1;
@ -259,6 +266,10 @@ public class SegmentMetadataQuery extends BaseQuery<SegmentAnalysis>
if (usingDefaultInterval != that.usingDefaultInterval) { if (usingDefaultInterval != that.usingDefaultInterval) {
return false; return false;
} }
if (!analysisTypes.equals(that.analysisTypes)) {
return false;
}
return !(toInclude != null ? !toInclude.equals(that.toInclude) : that.toInclude != null); return !(toInclude != null ? !toInclude.equals(that.toInclude) : that.toInclude != null);
} }
@ -270,6 +281,7 @@ public class SegmentMetadataQuery extends BaseQuery<SegmentAnalysis>
result = 31 * result + (toInclude != null ? toInclude.hashCode() : 0); result = 31 * result + (toInclude != null ? toInclude.hashCode() : 0);
result = 31 * result + (merge ? 1 : 0); result = 31 * result + (merge ? 1 : 0);
result = 31 * result + (usingDefaultInterval ? 1 : 0); result = 31 * result + (usingDefaultInterval ? 1 : 0);
result = 31 * result + analysisTypes.hashCode();
return result; return result;
} }
} }

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@ -54,7 +54,7 @@ public class SegmentMetadataQueryQueryToolChestTest
new SegmentMetadataQueryQueryToolChest(null).getCacheStrategy(query); new SegmentMetadataQueryQueryToolChest(null).getCacheStrategy(query);
// Test cache key generation // Test cache key generation
byte[] expectedKey = {0x04, 0x01, (byte) 0xFF, 0x00, 0x01}; byte[] expectedKey = {0x04, 0x01, (byte) 0xFF, 0x00, 0x01, 0x02};
byte[] actualKey = strategy.computeCacheKey(query); byte[] actualKey = strategy.computeCacheKey(query);
Assert.assertArrayEquals(expectedKey, actualKey); Assert.assertArrayEquals(expectedKey, actualKey);

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@ -1025,6 +1025,7 @@ public class RealtimePlumber implements Plumber
final File persistedFile = indexMerger.persist( final File persistedFile = indexMerger.persist(
indexToPersist.getIndex(), indexToPersist.getIndex(),
interval,
new File(computePersistDir(schema, interval), String.valueOf(indexToPersist.getCount())), new File(computePersistDir(schema, interval), String.valueOf(indexToPersist.getCount())),
metaData, metaData,
indexSpec indexSpec

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@ -396,21 +396,23 @@ public class RealtimePlumberSchoolTest
Map<Long, Sink> sinks = restoredPlumber.getSinks(); Map<Long, Sink> sinks = restoredPlumber.getSinks();
Assert.assertEquals(1, sinks.size()); Assert.assertEquals(1, sinks.size());
List<FireHydrant> hydrants = Lists.newArrayList(sinks.get(new Long(0))); List<FireHydrant> hydrants = Lists.newArrayList(sinks.get(new Long(0)));
DateTime startTime = new DateTime("1970-01-01T00:00:00.000Z"); DateTime startTime = new DateTime("1970-01-01T00:00:00.000Z");
Interval expectedInterval = new Interval(startTime, new DateTime("1971-01-01T00:00:00.000Z"));
Assert.assertEquals(0, hydrants.get(0).getCount()); Assert.assertEquals(0, hydrants.get(0).getCount());
Assert.assertEquals( Assert.assertEquals(
new Interval(startTime, new DateTime("1970-01-01T00:00:00.001Z")), expectedInterval,
hydrants.get(0).getSegment().getDataInterval() hydrants.get(0).getSegment().getDataInterval()
); );
Assert.assertEquals(2, hydrants.get(1).getCount()); Assert.assertEquals(2, hydrants.get(1).getCount());
Assert.assertEquals( Assert.assertEquals(
new Interval(startTime, new DateTime("1970-03-01T00:00:00.001Z")), expectedInterval,
hydrants.get(1).getSegment().getDataInterval() hydrants.get(1).getSegment().getDataInterval()
); );
Assert.assertEquals(4, hydrants.get(2).getCount()); Assert.assertEquals(4, hydrants.get(2).getCount());
Assert.assertEquals( Assert.assertEquals(
new Interval(startTime, new DateTime("1970-05-01T00:00:00.001Z")), expectedInterval,
hydrants.get(2).getSegment().getDataInterval() hydrants.get(2).getSegment().getDataInterval()
); );