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Merged
jihoonson merged 5 commits into from
Dec 20, 2019
Merged

benchmark schema with numeric dimensions and null column values #9036

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8a121b0
benchmark schema with null column values
clintropolis Nov 19, 2019
64d81e4
oops
clintropolis Dec 14, 2019
9e97972
adjustments
clintropolis Dec 18, 2019
45170c1
rename again, different null percentage so rows more variety
clintropolis Dec 18, 2019
85d3644
more schema
clintropolis Dec 18, 2019
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22 changes: 22 additions & 0 deletions benchmarks/src/main/java/org/apache/druid/benchmark/datagen/BenchmarkColumnSchema.java
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Expand Up @@ -19,6 +19,12 @@

package org.apache.druid.benchmark.datagen;

import org.apache.druid.data.input.impl.DimensionSchema;
import org.apache.druid.data.input.impl.DoubleDimensionSchema;
import org.apache.druid.data.input.impl.FloatDimensionSchema;
import org.apache.druid.data.input.impl.LongDimensionSchema;
import org.apache.druid.data.input.impl.StringDimensionSchema;
import org.apache.druid.java.util.common.IAE;
import org.apache.druid.segment.column.ValueType;

import java.util.List;
Expand Down Expand Up @@ -144,6 +150,22 @@ public BenchmarkColumnValueGenerator makeGenerator(long seed)
return new BenchmarkColumnValueGenerator(this, seed);
}

public DimensionSchema getDimensionSchema()
{
switch (type) {
case LONG:
return new LongDimensionSchema(name);
case FLOAT:
return new FloatDimensionSchema(name);
case DOUBLE:
return new DoubleDimensionSchema(name);
case STRING:
return new StringDimensionSchema(name);
default:
throw new IAE("unable to make dimension schema for %s", type);
}
}

public String getName()
{
return name;
Expand Down
7 changes: 7 additions & 0 deletions ...marks/src/main/java/org/apache/druid/benchmark/datagen/BenchmarkColumnValueGenerator.java
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Expand Up @@ -116,6 +116,13 @@ private Object convertType(Object input, ValueType type)
ret = Long.parseLong(input.toString());
}
break;
case DOUBLE:
if (input instanceof Number) {
ret = ((Number) input).doubleValue();
} else {
ret = Double.parseDouble(input.toString());
}
break;
case FLOAT:
if (input instanceof Number) {
ret = ((Number) input).floatValue();
Expand Down
13 changes: 13 additions & 0 deletions benchmarks/src/main/java/org/apache/druid/benchmark/datagen/BenchmarkSchemaInfo.java
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Expand Up @@ -19,10 +19,13 @@

package org.apache.druid.benchmark.datagen;

import org.apache.druid.data.input.impl.DimensionSchema;
import org.apache.druid.data.input.impl.DimensionsSpec;
import org.apache.druid.query.aggregation.AggregatorFactory;
import org.joda.time.Interval;

import java.util.List;
import java.util.stream.Collectors;

public class BenchmarkSchemaInfo
{
Expand All @@ -49,6 +52,16 @@ public List<BenchmarkColumnSchema> getColumnSchemas()
return columnSchemas;
}

public DimensionsSpec getDimensionsSpec()
{
List<DimensionSchema> specs = getColumnSchemas().stream()
.filter(x -> !x.isMetric())
.map(BenchmarkColumnSchema::getDimensionSchema)
.collect(Collectors.toList());

return new DimensionsSpec(specs);
}

public List<AggregatorFactory> getAggs()
{
return aggs;
Expand Down
69 changes: 69 additions & 0 deletions benchmarks/src/main/java/org/apache/druid/benchmark/datagen/BenchmarkSchemas.java
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Expand Up @@ -225,4 +225,73 @@ public class BenchmarkSchemas
);
SCHEMA_MAP.put("rollo", rolloSchema);
}

static { // simple schema with null valued rows, no aggs on numeric columns
List<BenchmarkColumnSchema> nullsSchemaColumns = ImmutableList.of(
// string dims with nulls
BenchmarkColumnSchema.makeZipf("stringZipf", ValueType.STRING, false, 1, 0.8, 1, 101, 1.5),
BenchmarkColumnSchema.makeDiscreteUniform("stringUniform", ValueType.STRING, false, 1, 0.3, 1, 100000),
BenchmarkColumnSchema.makeSequential("stringSequential", ValueType.STRING, false, 1, 0.5, 0, 1000),

// numeric dims with nulls
BenchmarkColumnSchema.makeSequential("longSequential", ValueType.LONG, false, 1, 0.45, 0, 10000),
BenchmarkColumnSchema.makeDiscreteUniform("longUniform", ValueType.LONG, false, 1, 0.25, 0, 500),
BenchmarkColumnSchema.makeZipf("doubleZipf", ValueType.DOUBLE, false, 1, 0.1, 0, 1000, 2.0),
BenchmarkColumnSchema.makeZipf("floatZipf", ValueType.FLOAT, false, 1, 0.1, 0, 1000, 2.0)
);

List<AggregatorFactory> simpleNullsSchemaIngestAggs = new ArrayList<>();
simpleNullsSchemaIngestAggs.add(new CountAggregatorFactory("rows"));

Interval nullsSchemaDataInterval = Intervals.of("2000-01-01/P1D");

BenchmarkSchemaInfo nullsSchema = new BenchmarkSchemaInfo(
nullsSchemaColumns,
simpleNullsSchemaIngestAggs,
nullsSchemaDataInterval,
false
);

SCHEMA_MAP.put("nulls", nullsSchema);
}

static { // simple schema with null valued rows, no aggs on numeric columns
List<BenchmarkColumnSchema> nullsSchemaColumns = ImmutableList.of(
// string dims
BenchmarkColumnSchema.makeZipf("stringZipf", ValueType.STRING, false, 1, null, 1, 101, 1.5),
BenchmarkColumnSchema.makeDiscreteUniform("stringUniform", ValueType.STRING, false, 1, null, 1, 100000),
BenchmarkColumnSchema.makeSequential("stringSequential", ValueType.STRING, false, 1, null, 0, 1000),

// numeric dims
BenchmarkColumnSchema.makeSequential("longSequential", ValueType.LONG, false, 1, null, 0, 10000),
BenchmarkColumnSchema.makeDiscreteUniform("longUniform", ValueType.LONG, false, 1, null, 0, 500),
BenchmarkColumnSchema.makeZipf("doubleZipf", ValueType.DOUBLE, false, 1, null, 0, 1000, 2.0),
BenchmarkColumnSchema.makeZipf("floatZipf", ValueType.FLOAT, false, 1, null, 0, 1000, 2.0),

// string dims with nulls
BenchmarkColumnSchema.makeZipf("stringZipfWithNulls", ValueType.STRING, false, 1, 0.8, 1, 101, 1.5),
BenchmarkColumnSchema.makeDiscreteUniform("stringUniformWithNulls", ValueType.STRING, false, 1, 0.3, 1, 100000),
BenchmarkColumnSchema.makeSequential("stringSequentialWithNulls", ValueType.STRING, false, 1, 0.5, 0, 1000),

// numeric dims with nulls
BenchmarkColumnSchema.makeSequential("longSequentialWithNulls", ValueType.LONG, false, 1, 0.45, 0, 10000),
BenchmarkColumnSchema.makeDiscreteUniform("longUniformWithNulls", ValueType.LONG, false, 1, 0.25, 0, 500),
BenchmarkColumnSchema.makeZipf("doubleZipfWithNulls", ValueType.DOUBLE, false, 1, 0.1, 0, 1000, 2.0),
BenchmarkColumnSchema.makeZipf("floatZipfWithNulls", ValueType.FLOAT, false, 1, 0.1, 0, 1000, 2.0)
);

List<AggregatorFactory> simpleNullsSchemaIngestAggs = new ArrayList<>();
simpleNullsSchemaIngestAggs.add(new CountAggregatorFactory("rows"));

Interval nullsSchemaDataInterval = Intervals.of("2000-01-01/P1D");

BenchmarkSchemaInfo nullsSchema = new BenchmarkSchemaInfo(
nullsSchemaColumns,
simpleNullsSchemaIngestAggs,
nullsSchemaDataInterval,
false
);

SCHEMA_MAP.put("nulls-and-non-nulls", nullsSchema);
}
}
33 changes: 2 additions & 31 deletions benchmarks/src/main/java/org/apache/druid/benchmark/datagen/SegmentGenerator.java
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Expand Up @@ -19,16 +19,9 @@

package org.apache.druid.benchmark.datagen;

import com.google.common.collect.ImmutableList;
import com.google.common.hash.Hashing;
import org.apache.druid.common.config.NullHandling;
import org.apache.druid.data.input.InputRow;
import org.apache.druid.data.input.impl.DimensionSchema;
import org.apache.druid.data.input.impl.DimensionsSpec;
import org.apache.druid.data.input.impl.DoubleDimensionSchema;
import org.apache.druid.data.input.impl.FloatDimensionSchema;
import org.apache.druid.data.input.impl.LongDimensionSchema;
import org.apache.druid.data.input.impl.StringDimensionSchema;
import org.apache.druid.java.util.common.FileUtils;
import org.apache.druid.java.util.common.ISE;
import org.apache.druid.java.util.common.StringUtils;
Expand Down Expand Up @@ -71,7 +64,7 @@ public class SegmentGenerator implements Closeable
static {
NullHandling.initializeForTests();
}

private final File cacheDir;
private final boolean cleanupCacheDir;

Expand Down Expand Up @@ -145,30 +138,8 @@ public QueryableIndex generate(
numRows
);

final List<DimensionSchema> dimensions = new ArrayList<>();
for (BenchmarkColumnSchema columnSchema : schemaInfo.getColumnSchemas()) {
if (schemaInfo.getAggs().stream().noneMatch(agg -> agg.getName().equals(columnSchema.getName()))) {
switch (columnSchema.getType()) {
case STRING:
dimensions.add(new StringDimensionSchema(columnSchema.getName()));
break;
case LONG:
dimensions.add(new LongDimensionSchema(columnSchema.getName()));
break;
case DOUBLE:
dimensions.add(new DoubleDimensionSchema(columnSchema.getName()));
break;
case FLOAT:
dimensions.add(new FloatDimensionSchema(columnSchema.getName()));
break;
default:
throw new ISE("Unhandleable type[%s]", columnSchema.getType());
}
}
}

final IncrementalIndexSchema indexSchema = new IncrementalIndexSchema.Builder()
.withDimensionsSpec(new DimensionsSpec(dimensions, ImmutableList.of(), ImmutableList.of()))
.withDimensionsSpec(schemaInfo.getDimensionsSpec())
.withMetrics(schemaInfo.getAggsArray())
.withRollup(schemaInfo.isWithRollup())
.withQueryGranularity(granularity)
Expand Down
38 changes: 37 additions & 1 deletion benchmarks/src/main/java/org/apache/druid/benchmark/query/GroupByBenchmark.java
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Expand Up @@ -19,6 +19,7 @@

package org.apache.druid.benchmark.query;

import com.fasterxml.jackson.databind.InjectableValues;
import com.fasterxml.jackson.databind.ObjectMapper;
import com.fasterxml.jackson.dataformat.smile.SmileFactory;
import com.google.common.base.Supplier;
Expand All @@ -41,6 +42,7 @@
import org.apache.druid.java.util.common.granularity.Granularity;
import org.apache.druid.java.util.common.guava.Sequence;
import org.apache.druid.java.util.common.logger.Logger;
import org.apache.druid.math.expr.ExprMacroTable;
import org.apache.druid.offheap.OffheapBufferGenerator;
import org.apache.druid.query.DruidProcessingConfig;
import org.apache.druid.query.FinalizeResultsQueryRunner;
Expand All @@ -58,6 +60,7 @@
import org.apache.druid.query.aggregation.hyperloglog.HyperUniquesSerde;
import org.apache.druid.query.context.ResponseContext;
import org.apache.druid.query.dimension.DefaultDimensionSpec;
import org.apache.druid.query.expression.TestExprMacroTable;
import org.apache.druid.query.filter.BoundDimFilter;
import org.apache.druid.query.groupby.GroupByQuery;
import org.apache.druid.query.groupby.GroupByQueryConfig;
Expand Down Expand Up @@ -166,7 +169,11 @@ public class GroupByBenchmark
static {
JSON_MAPPER = new DefaultObjectMapper();
INDEX_IO = new IndexIO(
JSON_MAPPER,
JSON_MAPPER.setInjectableValues(
new InjectableValues.Std()
.addValue(ExprMacroTable.class.getName(), TestExprMacroTable.INSTANCE)
.addValue(ObjectMapper.class.getName(), JSON_MAPPER)
),
new ColumnConfig()
{
@Override
Expand Down Expand Up @@ -391,6 +398,34 @@ private void setupQueries()
simpleFloatQueries.put("A", queryA);
}
SCHEMA_QUERY_MAP.put("simpleFloat", simpleFloatQueries);

// simple one column schema, for testing performance difference between querying on numeric values as Strings and
// directly as longs
Map<String, GroupByQuery> nullQueries = new LinkedHashMap<>();
BenchmarkSchemaInfo nullSchema = BenchmarkSchemas.SCHEMA_MAP.get("nulls");

{ // simple-null
QuerySegmentSpec intervalSpec = new MultipleIntervalSegmentSpec(Collections.singletonList(nullSchema.getDataInterval()));
List<AggregatorFactory> queryAggs = new ArrayList<>();
queryAggs.add(new DoubleSumAggregatorFactory(
"doubleSum",
"doubleZipf"
));
GroupByQuery queryA = GroupByQuery
.builder()
.setDataSource("blah")
.setQuerySegmentSpec(intervalSpec)
.setDimensions(new DefaultDimensionSpec("stringZipf", "stringZipf", ValueType.STRING))
.setAggregatorSpecs(
queryAggs
)
.setGranularity(Granularity.fromString(queryGranularity))
.setContext(ImmutableMap.of("vectorize", vectorize))
.build();

nullQueries.put("A", queryA);
}
SCHEMA_QUERY_MAP.put("nulls", nullQueries);
}

@Setup(Level.Trial)
Expand Down Expand Up @@ -549,6 +584,7 @@ private IncrementalIndex makeIncIndex(boolean withRollup)
return new IncrementalIndex.Builder()
.setIndexSchema(
new IncrementalIndexSchema.Builder()
.withDimensionsSpec(schemaInfo.getDimensionsSpec())
.withMetrics(schemaInfo.getAggsArray())
.withRollup(withRollup)
.build()
Expand Down