use of org.apache.druid.segment.generator.SegmentGenerator in project druid by druid-io.
the class SqlVsNativeBenchmark method setup.
@Setup(Level.Trial)
public void setup() {
this.closer = Closer.create();
final GeneratorSchemaInfo schemaInfo = GeneratorBasicSchemas.SCHEMA_MAP.get("basic");
final DataSegment dataSegment = DataSegment.builder().dataSource("foo").interval(schemaInfo.getDataInterval()).version("1").shardSpec(new LinearShardSpec(0)).size(0).build();
final SegmentGenerator segmentGenerator = closer.register(new SegmentGenerator());
log.info("Starting benchmark setup using tmpDir[%s], rows[%,d].", segmentGenerator.getCacheDir(), rowsPerSegment);
final QueryableIndex index = segmentGenerator.generate(dataSegment, schemaInfo, Granularities.NONE, rowsPerSegment);
final QueryRunnerFactoryConglomerate conglomerate = QueryStackTests.createQueryRunnerFactoryConglomerate(closer);
final PlannerConfig plannerConfig = new PlannerConfig();
this.walker = closer.register(new SpecificSegmentsQuerySegmentWalker(conglomerate).add(dataSegment, index));
final DruidSchemaCatalog rootSchema = CalciteTests.createMockRootSchema(conglomerate, walker, plannerConfig, AuthTestUtils.TEST_AUTHORIZER_MAPPER);
plannerFactory = new PlannerFactory(rootSchema, CalciteTests.createMockQueryMakerFactory(walker, conglomerate), CalciteTests.createOperatorTable(), CalciteTests.createExprMacroTable(), plannerConfig, AuthTestUtils.TEST_AUTHORIZER_MAPPER, CalciteTests.getJsonMapper(), CalciteTests.DRUID_SCHEMA_NAME);
groupByQuery = GroupByQuery.builder().setDataSource("foo").setInterval(Intervals.ETERNITY).setDimensions(new DefaultDimensionSpec("dimZipf", "d0"), new DefaultDimensionSpec("dimSequential", "d1")).setAggregatorSpecs(new CountAggregatorFactory("c")).setGranularity(Granularities.ALL).build();
sqlQuery = "SELECT\n" + " dimZipf AS d0," + " dimSequential AS d1,\n" + " COUNT(*) AS c\n" + "FROM druid.foo\n" + "GROUP BY dimZipf, dimSequential";
}
use of org.apache.druid.segment.generator.SegmentGenerator in project druid by druid-io.
the class IndexedTableJoinCursorBenchmark method makeQueryableIndexSegment.
public static QueryableIndexSegment makeQueryableIndexSegment(Closer closer, String dataSource, int rowsPerSegment) {
final List<GeneratorColumnSchema> schemaColumnsInfo = ImmutableList.of(GeneratorColumnSchema.makeSequential("stringKey", ValueType.STRING, false, 1, null, 0, rowsPerSegment), GeneratorColumnSchema.makeSequential("longKey", ValueType.LONG, false, 1, null, 0, rowsPerSegment), GeneratorColumnSchema.makeLazyZipf("string1", ValueType.STRING, false, 1, 0.1, 0, rowsPerSegment, 2.0), GeneratorColumnSchema.makeLazyZipf("string2", ValueType.STRING, false, 1, 0.3, 0, 1000000, 1.5), GeneratorColumnSchema.makeLazyZipf("string3", ValueType.STRING, false, 1, 0.12, 0, 1000, 1.25), GeneratorColumnSchema.makeLazyZipf("string4", ValueType.STRING, false, 1, 0.22, 0, 12000, 3.0), GeneratorColumnSchema.makeLazyZipf("string5", ValueType.STRING, false, 1, 0.05, 0, 33333, 1.8), GeneratorColumnSchema.makeLazyZipf("long1", ValueType.LONG, false, 1, 0.1, 0, 1001, 2.0), GeneratorColumnSchema.makeLazyZipf("long2", ValueType.LONG, false, 1, 0.01, 0, 666666, 2.2), GeneratorColumnSchema.makeLazyZipf("long3", ValueType.LONG, false, 1, 0.12, 0, 1000000, 2.5), GeneratorColumnSchema.makeLazyZipf("long4", ValueType.LONG, false, 1, 0.4, 0, 23, 1.2), GeneratorColumnSchema.makeLazyZipf("long5", ValueType.LONG, false, 1, 0.33, 0, 9999, 1.5), GeneratorColumnSchema.makeLazyZipf("double1", ValueType.DOUBLE, false, 1, 0.1, 0, 333, 2.2), GeneratorColumnSchema.makeLazyZipf("double2", ValueType.DOUBLE, false, 1, 0.01, 0, 4021, 2.5), GeneratorColumnSchema.makeLazyZipf("double3", ValueType.DOUBLE, false, 1, 0.41, 0, 90210, 4.0), GeneratorColumnSchema.makeLazyZipf("double4", ValueType.DOUBLE, false, 1, 0.5, 0, 5555555, 1.2), GeneratorColumnSchema.makeLazyZipf("double5", ValueType.DOUBLE, false, 1, 0.23, 0, 80, 1.8), GeneratorColumnSchema.makeLazyZipf("float1", ValueType.FLOAT, false, 1, 0.11, 0, 1000000, 1.7), GeneratorColumnSchema.makeLazyZipf("float2", ValueType.FLOAT, false, 1, 0.4, 0, 10, 1.5), GeneratorColumnSchema.makeLazyZipf("float3", ValueType.FLOAT, false, 1, 0.8, 0, 5000, 2.3), GeneratorColumnSchema.makeLazyZipf("float4", ValueType.FLOAT, false, 1, 0.999, 0, 14440, 2.0), GeneratorColumnSchema.makeLazyZipf("float5", ValueType.FLOAT, false, 1, 0.001, 0, 1029, 1.5));
final List<AggregatorFactory> aggs = new ArrayList<>();
aggs.add(new CountAggregatorFactory("rows"));
final Interval interval = Intervals.of("2000-01-01/P1D");
final GeneratorSchemaInfo schema = new GeneratorSchemaInfo(schemaColumnsInfo, aggs, interval, false);
final DataSegment dataSegment = DataSegment.builder().dataSource(dataSource).interval(schema.getDataInterval()).version("1").shardSpec(new LinearShardSpec(0)).size(0).build();
final QueryableIndex index = closer.register(new SegmentGenerator()).generate(dataSegment, schema, Granularities.NONE, rowsPerSegment);
return closer.register(new QueryableIndexSegment(index, SegmentId.dummy(dataSource)));
}
use of org.apache.druid.segment.generator.SegmentGenerator in project druid by druid-io.
the class ExpressionSelectorBenchmark method setup.
@Setup(Level.Trial)
public void setup() {
this.closer = Closer.create();
final GeneratorSchemaInfo schemaInfo = new GeneratorSchemaInfo(ImmutableList.of(GeneratorColumnSchema.makeZipf("n", ValueType.LONG, false, 1, 0d, 1000, 10000, 3d), GeneratorColumnSchema.makeZipf("s", ValueType.STRING, false, 1, 0d, 1000, 10000, 3d)), ImmutableList.of(), Intervals.of("2000/P1D"), false);
final DataSegment dataSegment = DataSegment.builder().dataSource("foo").interval(schemaInfo.getDataInterval()).version("1").shardSpec(new LinearShardSpec(0)).size(0).build();
final SegmentGenerator segmentGenerator = closer.register(new SegmentGenerator());
this.index = closer.register(segmentGenerator.generate(dataSegment, schemaInfo, Granularities.HOUR, rowsPerSegment));
}
use of org.apache.druid.segment.generator.SegmentGenerator in project druid by druid-io.
the class ExpressionVectorSelectorBenchmark method setup.
@Setup(Level.Trial)
public void setup() {
this.closer = Closer.create();
final GeneratorSchemaInfo schemaInfo = GeneratorBasicSchemas.SCHEMA_MAP.get("expression-testbench");
final DataSegment dataSegment = DataSegment.builder().dataSource("foo").interval(schemaInfo.getDataInterval()).version("1").shardSpec(new LinearShardSpec(0)).size(0).build();
final SegmentGenerator segmentGenerator = closer.register(new SegmentGenerator());
this.index = closer.register(segmentGenerator.generate(dataSegment, schemaInfo, Granularities.HOUR, rowsPerSegment));
Expr parsed = Parser.parse(expression, ExprMacroTable.nil());
outputType = parsed.getOutputType(new ColumnInspector() {
@Nullable
@Override
public ColumnCapabilities getColumnCapabilities(String column) {
return QueryableIndexStorageAdapter.getColumnCapabilities(index, column);
}
});
checkSanity();
}
use of org.apache.druid.segment.generator.SegmentGenerator in project druid by druid-io.
the class ExpressionAggregationBenchmark method setup.
@Setup(Level.Trial)
public void setup() {
this.closer = Closer.create();
final GeneratorSchemaInfo schemaInfo = new GeneratorSchemaInfo(ImmutableList.of(GeneratorColumnSchema.makeNormal("x", ValueType.FLOAT, false, 1, 0d, 0d, 10000d, false), GeneratorColumnSchema.makeNormal("y", ValueType.FLOAT, false, 1, 0d, 0d, 10000d, false)), ImmutableList.of(), Intervals.of("2000/P1D"), false);
final DataSegment dataSegment = DataSegment.builder().dataSource("foo").interval(schemaInfo.getDataInterval()).version("1").shardSpec(new LinearShardSpec(0)).size(0).build();
final SegmentGenerator segmentGenerator = closer.register(new SegmentGenerator());
this.index = closer.register(segmentGenerator.generate(dataSegment, schemaInfo, Granularities.NONE, rowsPerSegment));
this.javaScriptAggregatorFactory = new JavaScriptAggregatorFactory("name", ImmutableList.of("x", "y"), "function(current,x,y) { if (x > 0) { return current + x + 1 } else { return current + y + 1 } }", "function() { return 0 }", "function(a,b) { return a + b }", JavaScriptConfig.getEnabledInstance());
this.expressionAggregatorFactory = new DoubleSumAggregatorFactory("name", null, "if(x>0,1.0+x,y+1)", TestExprMacroTable.INSTANCE);
}
Aggregations