12 Commits

Author SHA1 Message Date
lifengchao
5765edf671 TSG-22756 添加current_timestamp_millis udf输出当前时间戳 2024-10-17 18:26:38 +08:00
lifengchao
b754e83ba0 TSG-22473 对APPROX_QUANTILE_HDR结果列排序产生ClassCastException异常 2024-09-09 09:59:13 +08:00
lifengchao
8c546e20d7 TSG-22013 添加dimension_bucket函数,计算维度bucket 2024-08-09 11:30:47 +08:00
lifengchao
9a6c44112e GAL-617 Druid hdrhistogram扩展添加HDR_DESCRIBE、HDR_GET_PERCENTILES_DESCRIPTION函数 2024-07-11 09:56:14 +08:00
李奉超
38c22db84d Merge branch 'main' into 'develop'
Main

See merge request galaxy/platform/algorithm/druid-extensions!3
2024-07-10 01:29:58 +00:00
李奉超
25ab1b3f9d Merge branch 'druid_26.0.0' into 'main'
Druid 26.0.0

See merge request galaxy/platform/algorithm/druid-extensions!2
2024-07-10 01:27:28 +00:00
lifengchao
95e6e07ed9 TSG-19025 druid hdrhistogram精度默认值改为1 2024-02-06 13:41:07 +08:00
lifengchao
00db131a55 优化:getMaxIntermediateSize返回值初始化计算一次cache,getMaxIntermediateSize每行数据都会调用一次 2024-01-31 17:34:24 +08:00
lifengchao
eb64880203 测试 2023-11-03 19:53:21 +08:00
lifengchao
14d06ca0bc AggregatorFactory deserialize 方法需要判断null 2023-10-16 17:42:48 +08:00
lifengchao
ce13bd16de druid-hdrhistogram druid版本升级到26.0.0 2023-09-25 11:05:24 +08:00
lifengchao
26bb13fd74 druid hlld升级到26.0.0 2023-09-25 10:42:16 +08:00
46 changed files with 4794 additions and 3073 deletions

View File

@@ -5,7 +5,7 @@
<modelVersion>4.0.0</modelVersion>
<groupId>org.apache.druid.extensions</groupId>
<artifactId>druid-hdrhistogram_0.18.1</artifactId>
<artifactId>druid-hdrhistogram_26.0.0</artifactId>
<name>druid-hdrhistogram</name>
<version>1.0-SNAPSHOT</version>
@@ -14,7 +14,7 @@
<project.reporting.outputEncoding>UTF-8</project.reporting.outputEncoding>
<maven.compiler.source>1.8</maven.compiler.source>
<maven.compiler.target>1.8</maven.compiler.target>
<druid.version>0.18.1</druid.version>
<druid.version>26.0.0</druid.version>
</properties>
<dependencies>
@@ -45,6 +45,13 @@
</dependency>
<!-- Tests -->
<dependency>
<groupId>org.easymock</groupId>
<artifactId>easymock</artifactId>
<version>4.3</version>
<scope>test</scope>
</dependency>
<dependency>
<groupId>org.apache.druid</groupId>
<artifactId>druid-processing</artifactId>
@@ -54,9 +61,17 @@
</dependency>
<dependency>
<groupId>org.apache.druid</groupId>
<artifactId>druid-benchmarks</artifactId>
<artifactId>druid-server</artifactId>
<version>${druid.version}</version>
<scope>test</scope>
<type>test-jar</type>
</dependency>
<dependency>
<groupId>org.apache.druid</groupId>
<artifactId>druid-sql</artifactId>
<version>${druid.version}</version>
<type>test-jar</type>
<scope>test</scope>
</dependency>
<dependency>
<groupId>junit</groupId>

View File

@@ -8,9 +8,7 @@ package org.HdrHistogram; /**
import java.io.IOException;
import java.io.ObjectInputStream;
import java.nio.ByteBuffer;
import java.util.ArrayList;
import java.util.Arrays;
import java.util.List;
import java.util.*;
import java.util.zip.DataFormatException;
/**
@@ -305,6 +303,35 @@ public class ArrayHistogram extends AbstractHistogram implements Histogramer{
return percentiles;
}
@Override
public Map<String, Object> describe() {
long min = getMinValue();
long max = getMaxValue(); // max = this.maxValue;
long count = getTotalCount();
double mean = getMean();
long sum = (long) (mean * count);
mean = Math.round(mean * 100.0) / 100.0;
long p25 = getValueAtPercentile(25);
long p50 = getValueAtPercentile(50);
long p75 = getValueAtPercentile(75);
long p90 = getValueAtPercentile(90);
long p95 = getValueAtPercentile(95);
long p99 = getValueAtPercentile(99);
Map<String, Object> rst = new LinkedHashMap<>();
rst.put("count", count);
rst.put("mean", mean);
rst.put("sum", sum);
rst.put("min", min);
rst.put("p25", p25);
rst.put("p50", p50);
rst.put("p75", p75);
rst.put("p90", p90);
rst.put("p95", p95);
rst.put("p99", p99);
rst.put("max", max);
return rst;
}
@Override
public Histogramer resetHistogram() {
if(isAutoResize()){

View File

@@ -2,7 +2,9 @@ package org.HdrHistogram;
import java.nio.ByteBuffer;
import java.util.ArrayList;
import java.util.LinkedHashMap;
import java.util.List;
import java.util.Map;
public class DirectArrayHistogram extends AbstractHistogram implements Histogramer{
long totalCount;
@@ -172,6 +174,35 @@ public class DirectArrayHistogram extends AbstractHistogram implements Histogram
return percentiles;
}
@Override
public Map<String, Object> describe() {
long min = getMinValue();
long max = getMaxValue(); // max = this.maxValue;
long count = getTotalCount();
double mean = getMean();
long sum = (long) (mean * count);
mean = Math.round(mean * 100.0) / 100.0;
long p25 = getValueAtPercentile(25);
long p50 = getValueAtPercentile(50);
long p75 = getValueAtPercentile(75);
long p90 = getValueAtPercentile(90);
long p95 = getValueAtPercentile(95);
long p99 = getValueAtPercentile(99);
Map<String, Object> rst = new LinkedHashMap<>();
rst.put("count", count);
rst.put("mean", mean);
rst.put("sum", sum);
rst.put("min", min);
rst.put("p25", p25);
rst.put("p50", p50);
rst.put("p75", p75);
rst.put("p90", p90);
rst.put("p95", p95);
rst.put("p99", p99);
rst.put("max", max);
return rst;
}
@Override
public Histogramer resetHistogram() {
throw new UnsupportedOperationException("unsupported method");

View File

@@ -3,6 +3,7 @@ package org.HdrHistogram;
import java.nio.ByteBuffer;
import java.nio.ByteOrder;
import java.util.List;
import java.util.Map;
import java.util.zip.DataFormatException;
import java.util.zip.Inflater;
@@ -446,6 +447,11 @@ public class DirectMapHistogram implements Histogramer{
throw new UnsupportedOperationException("unsupported method");
}
@Override
public Map<String, Object> describe() {
throw new UnsupportedOperationException("unsupported method");
}
@Override
public Histogramer resetHistogram() {
throw new UnsupportedOperationException("unsupported method");

View File

@@ -2,6 +2,7 @@ package org.HdrHistogram;
import java.nio.ByteBuffer;
import java.util.List;
import java.util.Map;
public class HistogramSketch {
public Histogramer hisImpl = null;
@@ -59,6 +60,10 @@ public class HistogramSketch {
return hisImpl.percentileList(percentileTicksPerHalfDistance);
}
public Map<String, Object> describe(){
return hisImpl.describe();
}
public static final int getUpdatableSerializationBytes(long lowestDiscernibleValue, long highestTrackableValue, int numberOfSignificantValueDigits){
return DirectArrayHistogram.getUpdatableSerializationBytes(lowestDiscernibleValue, highestTrackableValue, numberOfSignificantValueDigits);
}

View File

@@ -2,6 +2,7 @@ package org.HdrHistogram;
import java.nio.ByteBuffer;
import java.util.List;
import java.util.Map;
public interface Histogramer {
long getTotalCount();
@@ -14,6 +15,8 @@ public interface Histogramer {
List<Percentile> percentileList(int percentileTicksPerHalfDistance);
Map<String, Object> describe();
Histogramer resetHistogram();
Histogramer merge(Histogramer histogram);

View File

@@ -38,4 +38,13 @@ public class Percentile {
public void setPercentile(double percentile) {
this.percentile = percentile;
}
@Override
public String toString() {
return "Percentile{" +
"value=" + value +
", count=" + count +
", percentile=" + percentile +
'}';
}
}

View File

@@ -1,8 +1,6 @@
package org.apache.druid.query.aggregation.sketch.HdrHistogram;
import com.fasterxml.jackson.annotation.JsonProperty;
import org.HdrHistogram.DirectHistogram;
import org.HdrHistogram.Histogram;
import org.HdrHistogram.HistogramSketch;
import org.HdrHistogram.HistogramUnion;
import org.apache.druid.java.util.common.IAE;
@@ -10,6 +8,7 @@ import org.apache.druid.query.aggregation.*;
import org.apache.druid.query.cache.CacheKeyBuilder;
import org.apache.druid.segment.ColumnSelectorFactory;
import org.apache.druid.segment.ColumnValueSelector;
import org.apache.druid.segment.column.ColumnType;
import javax.annotation.Nullable;
import java.util.Collections;
@@ -20,9 +19,9 @@ import java.util.Objects;
public class HdrHistogramAggregatorFactory extends AggregatorFactory {
public static final long DEFAULT_LOWEST = 1;
public static final long DEFAULT_HIGHEST = 2;
public static final int DEFAULT_SIGNIFICANT = 3;
public static final int DEFAULT_SIGNIFICANT = 1;
public static final boolean DEFAULT_AUTO_RESIZE = true;
public static final long BUFFER_AUTO_RESIZE_HIGHEST = 100000000L * 1000000L;
public static final long BUFFER_AUTO_RESIZE_HIGHEST = 100000000L * 100L;
public static final Comparator<HistogramSketch> COMPARATOR =
Comparator.nullsFirst(Comparator.comparingLong(HistogramSketch::getTotalCount));
@@ -32,6 +31,7 @@ public class HdrHistogramAggregatorFactory extends AggregatorFactory {
protected final long highestTrackableValue;
protected final int numberOfSignificantValueDigits;
protected final boolean autoResize; //默认是false
protected final int updatableSerializationBytes;
public HdrHistogramAggregatorFactory(
@JsonProperty("name") String name,
@@ -81,6 +81,7 @@ public class HdrHistogramAggregatorFactory extends AggregatorFactory {
this.highestTrackableValue = highestTrackableValue;
this.numberOfSignificantValueDigits = numberOfSignificantValueDigits;
this.autoResize = autoResize;
this.updatableSerializationBytes = getUpdatableSerializationBytes();
}
@Override
@@ -208,15 +209,30 @@ public class HdrHistogramAggregatorFactory extends AggregatorFactory {
);
}
@Override
public AggregatorFactory withName(String newName) {
return new HdrHistogramAggregatorFactory(newName, fieldName, lowestDiscernibleValue, highestTrackableValue, numberOfSignificantValueDigits, autoResize);
}
@Override
public Object deserialize(Object object) {
if (object == null) {
return null;
}
return HistogramUtils.deserializeHistogram(object);
}
@Override
public ColumnType getResultType() {
//return ColumnType.LONG;
return getIntermediateType();
}
@Nullable
@Override
public Object finalizeComputation(@Nullable Object object) {
return object == null ? null : ((HistogramSketch) object).getTotalCount();
//return object == null ? null : ((HistogramSketch) object).getTotalCount();
return object;
}
@Override
@@ -250,9 +266,16 @@ public class HdrHistogramAggregatorFactory extends AggregatorFactory {
return autoResize;
}
/*
没这个方法了, 新版本需要实现getIntermediateType方法
@Override
public String getTypeName() {
return HdrHistogramModule.HDRHISTOGRAM_TYPE_NAME;
}*/
@Override
public ColumnType getIntermediateType() {
return HdrHistogramModule.TYPE;
}
@Override
@@ -263,6 +286,10 @@ public class HdrHistogramAggregatorFactory extends AggregatorFactory {
@Override
public int getMaxIntermediateSize() {
return updatableSerializationBytes == 0? getUpdatableSerializationBytes():updatableSerializationBytes;
}
private int getUpdatableSerializationBytes(){
if(!autoResize){
/*Histogram histogram = new Histogram(lowestDiscernibleValue, highestTrackableValue, numberOfSignificantValueDigits);
histogram.setAutoResize(autoResize);

View File

@@ -1,9 +1,9 @@
package org.apache.druid.query.aggregation.sketch.HdrHistogram;
import com.fasterxml.jackson.annotation.JsonProperty;
import org.HdrHistogram.Histogram;
import org.HdrHistogram.HistogramSketch;
import org.apache.druid.query.aggregation.Aggregator;
import org.apache.druid.query.aggregation.AggregatorFactory;
import org.apache.druid.query.aggregation.BufferAggregator;
import org.apache.druid.query.cache.CacheKeyBuilder;
import org.apache.druid.segment.ColumnSelectorFactory;
@@ -48,6 +48,11 @@ public class HdrHistogramMergeAggregatorFactory extends HdrHistogramAggregatorFa
);
}
@Override
public AggregatorFactory withName(String newName) {
return new HdrHistogramMergeAggregatorFactory(newName, fieldName, lowestDiscernibleValue, highestTrackableValue, numberOfSignificantValueDigits, autoResize);
}
@Override
public byte[] getCacheKey() {
return new CacheKeyBuilder(HdrHistogramModule.CACHE_TYPE_ID_OFFSET).appendByte(HdrHistogramModule.QUANTILES_HDRHISTOGRAM_MERGE_CACHE_TYPE_ID)

View File

@@ -37,7 +37,7 @@ public class HdrHistogramMergeBufferAggregator implements BufferAggregator {
this.numberOfSignificantValueDigits = numberOfSignificantValueDigits;
this.autoResize = autoResize;
this.size = size;
LOG.error("HdrHistogramMergeBufferAggregator gene:" + Thread.currentThread().getName() + "-" + Thread.currentThread().getId());
//LOG.error("HdrHistogramMergeBufferAggregator gene:" + Thread.currentThread().getName() + "-" + Thread.currentThread().getId());
}
@Override
@@ -83,7 +83,7 @@ public class HdrHistogramMergeBufferAggregator implements BufferAggregator {
@Nullable
@Override
public synchronized HistogramSketch get(ByteBuffer buf, int position) {
LOG.error("HdrHistogramMergeBufferAggregator get:" + 0 + "-" + Thread.currentThread().getId() + "-" + this);
//LOG.error("HdrHistogramMergeBufferAggregator get:" + 0 + "-" + Thread.currentThread().getId() + "-" + this);
HistogramUnion union = histograms.get(buf).get(position);
//return histogram.copy();
return union.getResult().copy();

View File

@@ -7,13 +7,10 @@ import com.fasterxml.jackson.databind.jsontype.NamedType;
import com.fasterxml.jackson.databind.module.SimpleModule;
import com.google.common.annotations.VisibleForTesting;
import com.google.inject.Binder;
import org.HdrHistogram.Histogram;
import org.HdrHistogram.HistogramSketch;
import org.apache.druid.initialization.DruidModule;
import org.apache.druid.query.aggregation.sketch.HdrHistogram.sql.HdrHistogramObjectSqlAggregator;
import org.apache.druid.query.aggregation.sketch.HdrHistogram.sql.HdrHistogramPercentilesOperatorConversion;
import org.apache.druid.query.aggregation.sketch.HdrHistogram.sql.HdrHistogramQuantileSqlAggregator;
import org.apache.druid.query.aggregation.sketch.HdrHistogram.sql.HdrHistogramQuantilesOperatorConversion;
import org.apache.druid.query.aggregation.sketch.HdrHistogram.sql.*;
import org.apache.druid.segment.column.ColumnType;
import org.apache.druid.segment.serde.ComplexMetrics;
import org.apache.druid.sql.guice.SqlBindings;
@@ -27,8 +24,11 @@ public class HdrHistogramModule implements DruidModule {
public static final byte QUANTILES_HDRHISTOGRAM_TO_QUANTILE_CACHE_TYPE_ID = 0x03;
public static final byte QUANTILES_HDRHISTOGRAM_TO_QUANTILES_CACHE_TYPE_ID = 0x04;
public static final byte QUANTILES_HDRHISTOGRAM_TO_PERCENTILES_CACHE_TYPE_ID = 0x05;
public static final byte QUANTILES_HDRHISTOGRAM_TO_DESCRIBE_CACHE_TYPE_ID = 0x06;
public static final byte QUANTILES_HDRHISTOGRAM_TO_PERCENTILES_DESCRIBE_CACHE_TYPE_ID = 0x07;
public static final String HDRHISTOGRAM_TYPE_NAME = "HdrHistogramSketch";
public static final ColumnType TYPE = ColumnType.ofComplex(HDRHISTOGRAM_TYPE_NAME);
public static final ObjectMapper objectMapper = new ObjectMapper();
@@ -49,6 +49,8 @@ public class HdrHistogramModule implements DruidModule {
SqlBindings.addOperatorConversion(binder, HdrHistogramQuantilesOperatorConversion.class);
SqlBindings.addOperatorConversion(binder, HdrHistogramPercentilesOperatorConversion.class);
SqlBindings.addOperatorConversion(binder, HdrHistogramDescribeOperatorConversion.class);
SqlBindings.addOperatorConversion(binder, HdrHistogramPercentilesDescribeOperatorConversion.class);
}
@Override
@@ -60,7 +62,9 @@ public class HdrHistogramModule implements DruidModule {
new NamedType(HdrHistogramMergeAggregatorFactory.class, "HdrHistogramSketchMerge"),
new NamedType(HdrHistogramToQuantilePostAggregator.class, "HdrHistogramSketchToQuantile"),
new NamedType(HdrHistogramToQuantilesPostAggregator.class, "HdrHistogramSketchToQuantiles"),
new NamedType(HdrHistogramToPercentilesPostAggregator.class, "HdrHistogramSketchToPercentiles")
new NamedType(HdrHistogramToPercentilesPostAggregator.class, "HdrHistogramSketchToPercentiles"),
new NamedType(HdrHistogramToDescribePostAggregator.class, "HdrHistogramSketchToDescribe"),
new NamedType(HdrHistogramToPercentilesDescribePostAggregator.class, "HdrHistogramSketchToPercentilesDescription")
).addSerializer(HistogramSketch.class, new HistogramJsonSerializer())
);
}

View File

@@ -0,0 +1,108 @@
package org.apache.druid.query.aggregation.sketch.HdrHistogram;
import com.fasterxml.jackson.annotation.JsonCreator;
import com.fasterxml.jackson.annotation.JsonProperty;
import com.google.common.collect.Sets;
import org.HdrHistogram.HistogramSketch;
import org.apache.druid.java.util.common.IAE;
import org.apache.druid.query.aggregation.AggregatorFactory;
import org.apache.druid.query.aggregation.PostAggregator;
import org.apache.druid.query.cache.CacheKeyBuilder;
import org.apache.druid.segment.ColumnInspector;
import org.apache.druid.segment.column.ColumnType;
import javax.annotation.Nullable;
import java.util.*;
public class HdrHistogramToDescribePostAggregator implements PostAggregator {
private final String name;
private final String fieldName;
@JsonCreator
public HdrHistogramToDescribePostAggregator(
@JsonProperty("name") String name,
@JsonProperty("fieldName") String fieldName
){
this.name = name;
this.fieldName = fieldName;
}
@Override
public ColumnType getType(ColumnInspector signature){
return ColumnType.STRING;
}
@Override
@JsonProperty
public String getName() {
return name;
}
@JsonProperty
public String getFieldName() {
return fieldName;
}
@Nullable
@Override
public Object compute(Map<String, Object> values) {
HistogramSketch histogram = (HistogramSketch) values.get(fieldName);
if(histogram == null){
return "{}"; //"[]"
}
return HdrHistogramModule.toJson(histogram.describe());
}
@Override
public Comparator<double[]> getComparator()
{
throw new IAE("Comparing arrays of quantiles is not supported");
}
@Override
public Set<String> getDependentFields()
{
return Sets.newHashSet(fieldName);
}
@Override
public PostAggregator decorate(Map<String, AggregatorFactory> aggregators) {
return this;
}
@Override
public byte[] getCacheKey() {
CacheKeyBuilder builder = new CacheKeyBuilder(HdrHistogramModule.CACHE_TYPE_ID_OFFSET).appendByte(HdrHistogramModule.QUANTILES_HDRHISTOGRAM_TO_DESCRIBE_CACHE_TYPE_ID)
.appendString(fieldName);
return builder.build();
}
@Override
public boolean equals(Object o) {
if (this == o) {
return true;
}
if (o == null || getClass() != o.getClass()) {
return false;
}
HdrHistogramToDescribePostAggregator that = (HdrHistogramToDescribePostAggregator) o;
return name.equals(that.name) &&
fieldName.equals(that.fieldName);
}
@Override
public int hashCode() {
return Objects.hash(name, fieldName);
}
@Override
public String toString() {
return "HdrHistogramToDescribePostAggregator{" +
"name='" + name + '\'' +
", fieldName='" + fieldName + '\'' +
'}';
}
}

View File

@@ -0,0 +1,125 @@
package org.apache.druid.query.aggregation.sketch.HdrHistogram;
import com.fasterxml.jackson.annotation.JsonCreator;
import com.fasterxml.jackson.annotation.JsonProperty;
import com.google.common.collect.Sets;
import org.HdrHistogram.HistogramSketch;
import org.HdrHistogram.Percentile;
import org.apache.druid.java.util.common.IAE;
import org.apache.druid.query.aggregation.AggregatorFactory;
import org.apache.druid.query.aggregation.PostAggregator;
import org.apache.druid.query.cache.CacheKeyBuilder;
import org.apache.druid.segment.ColumnInspector;
import org.apache.druid.segment.column.ColumnType;
import javax.annotation.Nullable;
import java.util.*;
public class HdrHistogramToPercentilesDescribePostAggregator implements PostAggregator {
private final String name;
private final String fieldName;
private final int percentileTicksPerHalfDistance;
@JsonCreator
public HdrHistogramToPercentilesDescribePostAggregator(
@JsonProperty("name") String name,
@JsonProperty("fieldName") String fieldName,
@JsonProperty("percentileTicksPerHalfDistance") int percentileTicksPerHalfDistance
){
this.name = name;
this.fieldName = fieldName;
this.percentileTicksPerHalfDistance = percentileTicksPerHalfDistance;
}
@Override
public ColumnType getType(ColumnInspector signature){
return ColumnType.STRING;
}
@Override
@JsonProperty
public String getName() {
return name;
}
@JsonProperty
public String getFieldName() {
return fieldName;
}
@JsonProperty
public int getPercentileTicksPerHalfDistance() {
return percentileTicksPerHalfDistance;
}
@Nullable
@Override
public Object compute(Map<String, Object> values) {
HistogramSketch histogram = (HistogramSketch) values.get(fieldName);
if(histogram == null){
return "{\"percentiles\":[],\"describe\":{}}";
}
List<Percentile> percentiles = histogram.percentileList(percentileTicksPerHalfDistance);
Map<String, Object> describe = histogram.describe();
Map<String, Object> rst = new LinkedHashMap<>();
rst.put("percentiles", percentiles);
rst.put("description", describe);
return HdrHistogramModule.toJson(rst);
}
@Override
public Comparator<double[]> getComparator()
{
throw new IAE("Comparing object is not supported");
}
@Override
public Set<String> getDependentFields()
{
return Sets.newHashSet(fieldName);
}
@Override
public PostAggregator decorate(Map<String, AggregatorFactory> aggregators) {
return this;
}
@Override
public byte[] getCacheKey() {
CacheKeyBuilder builder = new CacheKeyBuilder(HdrHistogramModule.CACHE_TYPE_ID_OFFSET).appendByte(HdrHistogramModule.QUANTILES_HDRHISTOGRAM_TO_PERCENTILES_DESCRIBE_CACHE_TYPE_ID)
.appendString(fieldName);
builder.appendInt(percentileTicksPerHalfDistance);
return builder.build();
}
@Override
public boolean equals(Object o) {
if (this == o) {
return true;
}
if (o == null || getClass() != o.getClass()) {
return false;
}
HdrHistogramToPercentilesDescribePostAggregator that = (HdrHistogramToPercentilesDescribePostAggregator) o;
return percentileTicksPerHalfDistance == that.percentileTicksPerHalfDistance &&
name.equals(that.name) &&
fieldName.equals(that.fieldName);
}
@Override
public int hashCode() {
return Objects.hash(name, fieldName, percentileTicksPerHalfDistance);
}
@Override
public String toString() {
return "HdrHistogramToPercentilesDescribePostAggregator{" +
"name='" + name + '\'' +
", fieldName='" + fieldName + '\'' +
", probabilitys=" + percentileTicksPerHalfDistance +
'}';
}
}

View File

@@ -9,6 +9,8 @@ import org.apache.druid.java.util.common.IAE;
import org.apache.druid.query.aggregation.AggregatorFactory;
import org.apache.druid.query.aggregation.PostAggregator;
import org.apache.druid.query.cache.CacheKeyBuilder;
import org.apache.druid.segment.ColumnInspector;
import org.apache.druid.segment.column.ColumnType;
import javax.annotation.Nullable;
import java.util.*;
@@ -29,6 +31,11 @@ public class HdrHistogramToPercentilesPostAggregator implements PostAggregator {
this.percentileTicksPerHalfDistance = percentileTicksPerHalfDistance;
}
@Override
public ColumnType getType(ColumnInspector signature){
return ColumnType.STRING;
}
@Override
@JsonProperty
public String getName() {
@@ -49,6 +56,9 @@ public class HdrHistogramToPercentilesPostAggregator implements PostAggregator {
@Override
public Object compute(Map<String, Object> values) {
HistogramSketch histogram = (HistogramSketch) values.get(fieldName);
if(histogram == null){
return "[]"; //"[]"
}
List<Percentile> percentiles = histogram.percentileList(percentileTicksPerHalfDistance);
return HdrHistogramModule.toJson(percentiles);
}

View File

@@ -2,13 +2,16 @@ package org.apache.druid.query.aggregation.sketch.HdrHistogram;
import com.fasterxml.jackson.annotation.JsonCreator;
import com.fasterxml.jackson.annotation.JsonProperty;
import com.google.common.collect.Ordering;
import com.google.common.collect.Sets;
import org.HdrHistogram.Histogram;
import com.google.common.primitives.Longs;
import org.HdrHistogram.HistogramSketch;
import org.apache.druid.java.util.common.IAE;
import org.apache.druid.query.aggregation.AggregatorFactory;
import org.apache.druid.query.aggregation.PostAggregator;
import org.apache.druid.query.cache.CacheKeyBuilder;
import org.apache.druid.segment.ColumnInspector;
import org.apache.druid.segment.column.ColumnType;
import javax.annotation.Nullable;
import java.util.Comparator;
@@ -21,6 +24,14 @@ public class HdrHistogramToQuantilePostAggregator implements PostAggregator {
private final String fieldName;
private final float probability;
static final Comparator COMPARATOR = new Ordering(){
@Override
public int compare(Object o, Object o1)
{
return Longs.compare(((Number) o).longValue(), ((Number) o1).longValue());
}
}.nullsFirst();
@JsonCreator
public HdrHistogramToQuantilePostAggregator(
@JsonProperty("name") String name,
@@ -36,25 +47,28 @@ public class HdrHistogramToQuantilePostAggregator implements PostAggregator {
}
}
@Override
public ColumnType getType(ColumnInspector signature){
return ColumnType.LONG;
}
@Override
public Set<String> getDependentFields() {
return Sets.newHashSet(fieldName);
}
@Override
public Comparator getComparator() {
return new Comparator<Long>(){
@Override
public int compare(final Long a, final Long b){
return Long.compare(a, b);
}
};
public Comparator<Long> getComparator() {
return COMPARATOR;
}
@Nullable
@Override
public Object compute(Map<String, Object> values) {
HistogramSketch histogram = (HistogramSketch) values.get(fieldName);
if(histogram == null){
return null;
}
return histogram.getValueAtPercentile(probability * 100);
}

View File

@@ -9,6 +9,8 @@ import org.apache.druid.java.util.common.IAE;
import org.apache.druid.query.aggregation.AggregatorFactory;
import org.apache.druid.query.aggregation.PostAggregator;
import org.apache.druid.query.cache.CacheKeyBuilder;
import org.apache.druid.segment.ColumnInspector;
import org.apache.druid.segment.column.ColumnType;
import javax.annotation.Nullable;
import java.util.*;
@@ -29,6 +31,11 @@ public class HdrHistogramToQuantilesPostAggregator implements PostAggregator {
this.probabilitys = probabilitys;
}
@Override
public ColumnType getType(ColumnInspector signature){
return ColumnType.LONG_ARRAY;
}
@Override
@JsonProperty
public String getName() {
@@ -49,7 +56,11 @@ public class HdrHistogramToQuantilesPostAggregator implements PostAggregator {
@Override
public Object compute(Map<String, Object> values) {
HistogramSketch histogram = (HistogramSketch) values.get(fieldName);
final long[] counts = new long[probabilitys.length];
if(histogram == null){
//return null;
return new Long[probabilitys.length];
}
final Long[] counts = new Long[probabilitys.length];
for (int i = 0; i < probabilitys.length; i++) {
counts[i] = histogram.getValueAtPercentile(probabilitys[i] * 100);
}

View File

@@ -0,0 +1,77 @@
package org.apache.druid.query.aggregation.sketch.HdrHistogram.sql;
import org.apache.calcite.rex.RexCall;
import org.apache.calcite.rex.RexNode;
import org.apache.calcite.sql.SqlFunction;
import org.apache.calcite.sql.SqlOperator;
import org.apache.calcite.sql.type.ReturnTypes;
import org.apache.calcite.sql.type.SqlTypeFamily;
import org.apache.calcite.sql.type.SqlTypeName;
import org.apache.druid.java.util.common.StringUtils;
import org.apache.druid.query.aggregation.PostAggregator;
import org.apache.druid.query.aggregation.post.FieldAccessPostAggregator;
import org.apache.druid.query.aggregation.sketch.HdrHistogram.HdrHistogramToDescribePostAggregator;
import org.apache.druid.segment.column.RowSignature;
import org.apache.druid.sql.calcite.expression.DruidExpression;
import org.apache.druid.sql.calcite.expression.OperatorConversions;
import org.apache.druid.sql.calcite.expression.PostAggregatorVisitor;
import org.apache.druid.sql.calcite.expression.SqlOperatorConversion;
import org.apache.druid.sql.calcite.planner.PlannerContext;
import javax.annotation.Nullable;
import java.util.List;
public class HdrHistogramDescribeOperatorConversion implements SqlOperatorConversion {
private static final String FUNCTION_NAME = "HDR_DESCRIBE";
private static final SqlFunction SQL_FUNCTION = OperatorConversions
.operatorBuilder(StringUtils.toUpperCase(FUNCTION_NAME))
.operandTypes(SqlTypeFamily.ANY)
.requiredOperands(1)
.returnTypeInference(ReturnTypes.explicit(SqlTypeName.VARCHAR))
.build();
@Override
public SqlOperator calciteOperator()
{
return SQL_FUNCTION;
}
@Override
public DruidExpression toDruidExpression(
PlannerContext plannerContext,
RowSignature rowSignature,
RexNode rexNode
)
{
return null;
}
@Nullable
@Override
public PostAggregator toPostAggregator(
PlannerContext plannerContext,
RowSignature rowSignature,
RexNode rexNode,
PostAggregatorVisitor postAggregatorVisitor
)
{
final List<RexNode> operands = ((RexCall) rexNode).getOperands();
final PostAggregator postAgg = OperatorConversions.toPostAggregator(
plannerContext,
rowSignature,
operands.get(0),
postAggregatorVisitor,
true
);
if (postAgg == null) {
return null;
}
return new HdrHistogramToDescribePostAggregator(
postAggregatorVisitor.getOutputNamePrefix() + postAggregatorVisitor.getAndIncrementCounter(),
((FieldAccessPostAggregator)postAgg).getFieldName()
);
}
}

View File

@@ -18,6 +18,7 @@ import org.apache.druid.query.aggregation.AggregatorFactory;
import org.apache.druid.query.aggregation.sketch.HdrHistogram.HdrHistogramAggregatorFactory;
import org.apache.druid.query.aggregation.sketch.HdrHistogram.HdrHistogramMergeAggregatorFactory;
import org.apache.druid.segment.VirtualColumn;
import org.apache.druid.segment.column.ColumnType;
import org.apache.druid.segment.column.RowSignature;
import org.apache.druid.segment.column.ValueType;
import org.apache.druid.sql.calcite.aggregation.Aggregation;
@@ -118,11 +119,11 @@ public class HdrHistogramObjectSqlAggregator implements SqlAggregator {
}
// No existing match found. Create a new one.
final List<VirtualColumn> virtualColumns = new ArrayList<>();
// 新版本删除了final List<VirtualColumn> virtualColumns = new ArrayList<>();
if (input.isDirectColumnAccess()) {
// 参数是Histogram对象
if (rowSignature.getColumnType(input.getDirectColumn()).orElse(null) == ValueType.COMPLEX) {
if (rowSignature.getColumnType(input.getDirectColumn()).map(type -> type.is(ValueType.COMPLEX)).orElse(false)) {
aggregatorFactory = new HdrHistogramMergeAggregatorFactory(
histogramName,
input.getDirectColumn(),
@@ -142,12 +143,11 @@ public class HdrHistogramObjectSqlAggregator implements SqlAggregator {
);
}
} else {
final VirtualColumn virtualColumn =
virtualColumnRegistry.getOrCreateVirtualColumnForExpression(plannerContext, input, SqlTypeName.BIGINT);
virtualColumns.add(virtualColumn);
final String virtualColumnName =
virtualColumnRegistry.getOrCreateVirtualColumnForExpression(input, ColumnType.LONG);
aggregatorFactory = new HdrHistogramAggregatorFactory(
histogramName,
virtualColumn.getOutputName(),
virtualColumnName,
lowestDiscernibleValue,
highestTrackableValue,
numberOfSignificantValueDigits,
@@ -156,7 +156,6 @@ public class HdrHistogramObjectSqlAggregator implements SqlAggregator {
}
return Aggregation.create(
virtualColumns,
ImmutableList.of(aggregatorFactory),
null
);

View File

@@ -0,0 +1,88 @@
package org.apache.druid.query.aggregation.sketch.HdrHistogram.sql;
import org.apache.calcite.rex.RexCall;
import org.apache.calcite.rex.RexLiteral;
import org.apache.calcite.rex.RexNode;
import org.apache.calcite.sql.SqlFunction;
import org.apache.calcite.sql.SqlKind;
import org.apache.calcite.sql.SqlOperator;
import org.apache.calcite.sql.type.ReturnTypes;
import org.apache.calcite.sql.type.SqlTypeFamily;
import org.apache.calcite.sql.type.SqlTypeName;
import org.apache.druid.java.util.common.StringUtils;
import org.apache.druid.query.aggregation.PostAggregator;
import org.apache.druid.query.aggregation.post.FieldAccessPostAggregator;
import org.apache.druid.query.aggregation.sketch.HdrHistogram.HdrHistogramToPercentilesDescribePostAggregator;
import org.apache.druid.segment.column.RowSignature;
import org.apache.druid.sql.calcite.expression.DruidExpression;
import org.apache.druid.sql.calcite.expression.OperatorConversions;
import org.apache.druid.sql.calcite.expression.PostAggregatorVisitor;
import org.apache.druid.sql.calcite.expression.SqlOperatorConversion;
import org.apache.druid.sql.calcite.planner.PlannerContext;
import javax.annotation.Nullable;
import java.util.List;
public class HdrHistogramPercentilesDescribeOperatorConversion implements SqlOperatorConversion {
private static final String FUNCTION_NAME = "HDR_GET_PERCENTILES_DESCRIPTION";
private static final SqlFunction SQL_FUNCTION = OperatorConversions
.operatorBuilder(StringUtils.toUpperCase(FUNCTION_NAME))
.operandTypes(SqlTypeFamily.ANY, SqlTypeFamily.NUMERIC)
.requiredOperands(1)
.returnTypeInference(ReturnTypes.explicit(SqlTypeName.VARCHAR))
.build();
@Override
public SqlOperator calciteOperator()
{
return SQL_FUNCTION;
}
@Override
public DruidExpression toDruidExpression(
PlannerContext plannerContext,
RowSignature rowSignature,
RexNode rexNode
)
{
return null;
}
@Nullable
@Override
public PostAggregator toPostAggregator(
PlannerContext plannerContext,
RowSignature rowSignature,
RexNode rexNode,
PostAggregatorVisitor postAggregatorVisitor
)
{
final List<RexNode> operands = ((RexCall) rexNode).getOperands();
final PostAggregator postAgg = OperatorConversions.toPostAggregator(
plannerContext,
rowSignature,
operands.get(0),
postAggregatorVisitor,
true
);
if (postAgg == null) {
return null;
}
int percentileTicksPerHalfDistance = 5;
if (operands.size() == 2) {
if (!operands.get(1).isA(SqlKind.LITERAL)) {
return null;
}
percentileTicksPerHalfDistance = RexLiteral.intValue(operands.get(1));
}
return new HdrHistogramToPercentilesDescribePostAggregator(
postAggregatorVisitor.getOutputNamePrefix() + postAggregatorVisitor.getAndIncrementCounter(),
((FieldAccessPostAggregator)postAgg).getFieldName(),
percentileTicksPerHalfDistance
);
}
}

View File

@@ -14,16 +14,16 @@ import org.apache.druid.query.aggregation.sketch.HdrHistogram.HdrHistogramToPerc
import org.apache.druid.query.aggregation.PostAggregator;
import org.apache.druid.query.aggregation.post.FieldAccessPostAggregator;
import org.apache.druid.segment.column.RowSignature;
import org.apache.druid.sql.calcite.expression.DirectOperatorConversion;
import org.apache.druid.sql.calcite.expression.DruidExpression;
import org.apache.druid.sql.calcite.expression.OperatorConversions;
import org.apache.druid.sql.calcite.expression.PostAggregatorVisitor;
import org.apache.druid.sql.calcite.expression.SqlOperatorConversion;
import org.apache.druid.sql.calcite.planner.PlannerContext;
import javax.annotation.Nullable;
import java.util.List;
public class HdrHistogramPercentilesOperatorConversion extends DirectOperatorConversion {
public class HdrHistogramPercentilesOperatorConversion implements SqlOperatorConversion {
private static final String FUNCTION_NAME = "HDR_GET_PERCENTILES";
private static final SqlFunction SQL_FUNCTION = OperatorConversions
.operatorBuilder(StringUtils.toUpperCase(FUNCTION_NAME))
@@ -32,10 +32,6 @@ public class HdrHistogramPercentilesOperatorConversion extends DirectOperatorCon
.returnTypeInference(ReturnTypes.explicit(SqlTypeName.VARCHAR))
.build();
public HdrHistogramPercentilesOperatorConversion() {
super(SQL_FUNCTION, FUNCTION_NAME);
}
@Override
public SqlOperator calciteOperator()
{
@@ -66,7 +62,8 @@ public class HdrHistogramPercentilesOperatorConversion extends DirectOperatorCon
plannerContext,
rowSignature,
operands.get(0),
postAggregatorVisitor
postAggregatorVisitor,
true
);
if (postAgg == null) {

View File

@@ -16,6 +16,7 @@ import org.apache.druid.query.aggregation.sketch.HdrHistogram.HdrHistogramAggreg
import org.apache.druid.query.aggregation.sketch.HdrHistogram.HdrHistogramMergeAggregatorFactory;
import org.apache.druid.query.aggregation.sketch.HdrHistogram.HdrHistogramToQuantilePostAggregator;
import org.apache.druid.segment.VirtualColumn;
import org.apache.druid.segment.column.ColumnType;
import org.apache.druid.segment.column.RowSignature;
import org.apache.druid.segment.column.ValueType;
import org.apache.druid.segment.virtual.ExpressionVirtualColumn;
@@ -141,22 +142,16 @@ public class HdrHistogramQuantileSqlAggregator implements SqlAggregator {
// Check input for equivalence.
final boolean inputMatches;
final VirtualColumn virtualInput = existing.getVirtualColumns()
final DruidExpression virtualInput =
virtualColumnRegistry.findVirtualColumnExpressions(theFactory.requiredFields())
.stream()
.filter(
virtualColumn ->
virtualColumn.getOutputName()
.equals(theFactory.getFieldName())
)
.findFirst()
.orElse(null);
if (virtualInput == null) {
inputMatches = input.isDirectColumnAccess()
&& input.getDirectColumn().equals(theFactory.getFieldName());
inputMatches = input.isDirectColumnAccess() && input.getDirectColumn().equals(theFactory.getFieldName());
} else {
inputMatches = ((ExpressionVirtualColumn) virtualInput).getExpression()
.equals(input.getExpression());
inputMatches = virtualInput.equals(input);
}
final boolean matches = inputMatches
@@ -177,11 +172,11 @@ public class HdrHistogramQuantileSqlAggregator implements SqlAggregator {
}
// No existing match found. Create a new one.
final List<VirtualColumn> virtualColumns = new ArrayList<>();
//final List<VirtualColumn> virtualColumns = new ArrayList<>();
if (input.isDirectColumnAccess()) {
// 参数是Histogram对象
if (rowSignature.getColumnType(input.getDirectColumn()).orElse(null) == ValueType.COMPLEX) {
if (rowSignature.getColumnType(input.getDirectColumn()).map(type -> type.is(ValueType.COMPLEX)).orElse(false)) {
aggregatorFactory = new HdrHistogramMergeAggregatorFactory(
histogramName,
input.getDirectColumn(),
@@ -201,12 +196,11 @@ public class HdrHistogramQuantileSqlAggregator implements SqlAggregator {
);
}
} else {
final VirtualColumn virtualColumn =
virtualColumnRegistry.getOrCreateVirtualColumnForExpression(plannerContext, input, SqlTypeName.BIGINT);
virtualColumns.add(virtualColumn);
final String virtualColumnName =
virtualColumnRegistry.getOrCreateVirtualColumnForExpression(input, ColumnType.LONG);
aggregatorFactory = new HdrHistogramAggregatorFactory(
histogramName,
virtualColumn.getOutputName(),
virtualColumnName,
lowestDiscernibleValue,
highestTrackableValue,
numberOfSignificantValueDigits,
@@ -234,7 +228,6 @@ public class HdrHistogramQuantileSqlAggregator implements SqlAggregator {
}
return Aggregation.create(
virtualColumns,
ImmutableList.of(aggregatorFactory),
new HdrHistogramToQuantilePostAggregator(name, histogramName, probability)
);

View File

@@ -62,50 +62,30 @@ public class HdrHistogramQuantilesOperatorConversion implements SqlOperatorConve
{
final List<RexNode> operands = ((RexCall) rexNode).getOperands();
final float[] args = new float[operands.size() - 1];
PostAggregator postAgg = null;
int operandCounter = 0;
for (RexNode operand : operands) {
final PostAggregator convertedPostAgg = OperatorConversions.toPostAggregator(
// 新版本直接就从第一个参数取
final PostAggregator inputSketchPostAgg = OperatorConversions.toPostAggregator(
plannerContext,
rowSignature,
operand,
postAggregatorVisitor
operands.get(0),
postAggregatorVisitor,
true
);
if (convertedPostAgg == null) {
if (operandCounter > 0) {
try {
if (!operand.isA(SqlKind.LITERAL)) {
if (inputSketchPostAgg == null) {
return null;
}
float arg = ((Number) RexLiteral.value(operand)).floatValue();
args[operandCounter - 1] = arg;
}
catch (ClassCastException cce) {
return null;
}
} else {
return null;
}
} else {
if (operandCounter == 0) {
postAgg = convertedPostAgg;
} else {
if (!operand.isA(SqlKind.LITERAL)) {
return null;
}
}
}
operandCounter++;
}
if (postAgg == null) {
return null;
// 直接解析
for (int i = 1; i < operands.size(); i++) {
RexNode operand = operands.get(i);
float arg = ((Number) RexLiteral.value(operand)).floatValue();
args[i - 1] = arg;
}
return new HdrHistogramToQuantilesPostAggregator(
postAggregatorVisitor.getOutputNamePrefix() + postAggregatorVisitor.getAndIncrementCounter(),
((FieldAccessPostAggregator)postAgg).getFieldName(),
((FieldAccessPostAggregator)inputSketchPostAgg).getFieldName(),
args
);
}

View File

@@ -2,17 +2,13 @@ package org.apache.druid.query.aggregation.sketch.HdrHistogram;
import com.google.common.collect.ImmutableMap;
import org.HdrHistogram.*;
import org.apache.datasketches.theta.Sketches;
import org.apache.datasketches.theta.UpdateSketch;
import org.apache.druid.data.input.MapBasedRow;
import org.apache.druid.query.aggregation.AggregatorFactory;
import org.apache.druid.query.aggregation.BufferAggregator;
import org.apache.druid.query.aggregation.TestLongColumnSelector;
import org.apache.druid.query.aggregation.TestObjectColumnSelector;
import org.apache.druid.query.aggregation.datasketches.theta.SketchHolder;
import org.apache.druid.query.aggregation.datasketches.theta.SketchMergeAggregatorFactory;
import org.apache.druid.query.groupby.epinephelinae.GrouperTestUtil;
import org.apache.druid.query.groupby.epinephelinae.TestColumnSelectorFactory;
import org.apache.druid.query.groupby.epinephelinae.GroupByTestColumnSelectorFactory;
import org.apache.druid.segment.ColumnSelectorFactory;
import org.junit.Assert;
import org.junit.Test;
@@ -230,7 +226,7 @@ public class HdrHistogramBufferAggregatorTest {
@Test
public void testMergeAggregatorRelocate() {
final TestColumnSelectorFactory columnSelectorFactory = GrouperTestUtil.newColumnSelectorFactory();
final GroupByTestColumnSelectorFactory columnSelectorFactory = GrouperTestUtil.newColumnSelectorFactory();
HistogramSketch histogram = new HistogramSketch(3);
for (int i = 0; i < 100000; i++) {
histogram.recordValue(i);
@@ -252,7 +248,7 @@ public class HdrHistogramBufferAggregatorTest {
@Test
public void testAggregatorRelocate() {
final TestColumnSelectorFactory columnSelectorFactory = GrouperTestUtil.newColumnSelectorFactory();
final GroupByTestColumnSelectorFactory columnSelectorFactory = GrouperTestUtil.newColumnSelectorFactory();
HistogramSketch histogram = new HistogramSketch(3);
for (int i = 0; i < 100000; i++) {
histogram.recordValue(i);

View File

@@ -0,0 +1,79 @@
package org.apache.druid.query.aggregation.sketch.HdrHistogram;
import org.HdrHistogram.DirectArrayHistogram;
import org.HdrHistogram.HistogramSketch;
import org.HdrHistogram.Histogramer;
import org.HdrHistogram.Percentile;
import org.apache.commons.lang3.StringUtils;
import org.junit.Test;
import java.io.BufferedWriter;
import java.nio.ByteBuffer;
import java.nio.charset.StandardCharsets;
import java.nio.file.FileSystems;
import java.nio.file.Files;
import java.nio.file.Path;
import java.util.Random;
import java.util.concurrent.ThreadLocalRandom;
public class HistogramSketchTest {
@Test
public void describeTest() throws Exception{
DirectArrayHistogram histogram = new DirectArrayHistogram(1, 1000000, 3,
ByteBuffer.allocate(HistogramSketch.getUpdatableSerializationBytes(1, 1000000, 3)));
System.out.println(histogram.describe());
for (int i = 0; i < 10000; i++) {
histogram.recordValue(i);
}
System.out.println(histogram.describe());
for (Percentile percentile : histogram.percentileList(100)) {
System.out.println(percentile);
}
}
@Test
public void describeTest1() throws Exception{
HistogramSketch histogram = new HistogramSketch(1);
System.out.println(histogram.describe());
for (int i = 0; i < 10000; i++) {
histogram.recordValue(i);
}
System.out.println(histogram.describe());
for (Percentile percentile : histogram.percentileList(100)) {
System.out.println(percentile);
}
System.out.println(StringUtils.repeat('#', 100));
histogram = new HistogramSketch(1);
for (int i = 0; i < 10000; i++) {
histogram.recordValue(ThreadLocalRandom.current().nextLong(100000));
}
System.out.println(histogram.describe());
for (Percentile percentile : histogram.percentileList(100)) {
System.out.println(percentile);
}
}
@Test
public void describeTest3() throws Exception{
HistogramSketch histogram = new HistogramSketch(3);
System.out.println(histogram.describe());
for (int i = 0; i < 10000; i++) {
histogram.recordValue(i);
}
System.out.println(histogram.describe());
for (Percentile percentile : histogram.percentileList(100)) {
System.out.println(percentile);
}
System.out.println(StringUtils.repeat('#', 100));
histogram = new HistogramSketch(3);
for (int i = 0; i < 10000; i++) {
histogram.recordValue(ThreadLocalRandom.current().nextLong(100000));
}
System.out.println(histogram.describe());
for (Percentile percentile : histogram.percentileList(100)) {
System.out.println(percentile);
}
}
}

View File

@@ -1,12 +1,15 @@
package org.apache.druid.query.aggregation.sketch.HdrHistogram.sql;
import com.alibaba.fastjson2.JSON;
import com.fasterxml.jackson.databind.Module;
import com.google.common.collect.ImmutableList;
import com.google.common.collect.ImmutableMap;
import com.google.common.collect.ImmutableSet;
import com.google.common.collect.Iterables;
import com.google.inject.Injector;
import org.apache.calcite.schema.SchemaPlus;
import org.apache.druid.data.input.InputRow;
import org.apache.druid.guice.DruidInjectorBuilder;
import org.apache.druid.java.util.common.granularity.Granularities;
import org.apache.druid.java.util.common.io.Closer;
import org.apache.druid.query.Druids;
@@ -27,66 +30,49 @@ import org.apache.druid.query.spec.MultipleIntervalSegmentSpec;
import org.apache.druid.segment.IndexBuilder;
import org.apache.druid.segment.QueryableIndex;
import org.apache.druid.segment.TestHelper;
import org.apache.druid.segment.column.ColumnType;
import org.apache.druid.segment.column.ValueType;
import org.apache.druid.segment.incremental.IncrementalIndexSchema;
import org.apache.druid.segment.join.JoinableFactoryWrapper;
import org.apache.druid.segment.virtual.ExpressionVirtualColumn;
import org.apache.druid.segment.writeout.OffHeapMemorySegmentWriteOutMediumFactory;
import org.apache.druid.server.QueryStackTests;
import org.apache.druid.server.security.AuthTestUtils;
import org.apache.druid.server.security.AuthenticationResult;
import org.apache.druid.sql.SqlLifecycle;
import org.apache.druid.sql.SqlLifecycleFactory;
import org.apache.druid.sql.calcite.BaseCalciteQueryTest;
import org.apache.druid.sql.calcite.QueryTestBuilder;
import org.apache.druid.sql.calcite.QueryTestRunner;
import org.apache.druid.sql.calcite.filtration.Filtration;
import org.apache.druid.sql.calcite.planner.DruidOperatorTable;
import org.apache.druid.sql.calcite.planner.PlannerConfig;
import org.apache.druid.sql.calcite.planner.PlannerContext;
import org.apache.druid.sql.calcite.planner.PlannerFactory;
import org.apache.druid.sql.calcite.util.CalciteTestBase;
import org.apache.druid.sql.calcite.util.CalciteTests;
import org.apache.druid.sql.calcite.util.QueryLogHook;
import org.apache.druid.sql.calcite.util.SpecificSegmentsQuerySegmentWalker;
import org.apache.druid.sql.calcite.util.*;
import org.apache.druid.timeline.DataSegment;
import org.apache.druid.timeline.partition.LinearShardSpec;
import org.junit.*;
import org.junit.rules.TemporaryFolder;
import java.io.File;
import java.io.IOException;
import java.util.Arrays;
import java.util.List;
import java.util.Map;
import java.util.*;
public class HdrHistogramQuantileSqlAggregatorTest extends CalciteTestBase {
private static final String DATA_SOURCE = "foo";
private static QueryRunnerFactoryConglomerate conglomerate;
private static Closer resourceCloser;
private static AuthenticationResult authenticationResult = CalciteTests.REGULAR_USER_AUTH_RESULT;
private static final Map<String, Object> QUERY_CONTEXT_DEFAULT = ImmutableMap.of(
PlannerContext.CTX_SQL_QUERY_ID, "dummy"
);
@Rule
public TemporaryFolder temporaryFolder = new TemporaryFolder();
@Rule
public QueryLogHook queryLogHook = QueryLogHook.create();
private SpecificSegmentsQuerySegmentWalker walker;
private SqlLifecycleFactory sqlLifecycleFactory;
@BeforeClass
public static void setUpClass() {
resourceCloser = Closer.create();
conglomerate = QueryStackTests.createQueryRunnerFactoryConglomerate(resourceCloser);
public class HdrHistogramQuantileSqlAggregatorTest extends BaseCalciteQueryTest {
@Override
public void gatherProperties(Properties properties)
{
super.gatherProperties(properties);
}
@AfterClass
public static void tearDownClass() throws IOException {
resourceCloser.close();
@Override
public void configureGuice(DruidInjectorBuilder builder)
{
super.configureGuice(builder);
builder.addModule(new HdrHistogramModule());
}
public static final List<InputRow> ROWS1 = ImmutableList.of(
CalciteTests.createRow(
TestDataBuilder.createRow(
ImmutableMap.<String, Object>builder()
.put("t", "2000-01-01")
.put("m1", "1")
@@ -96,7 +82,7 @@ public class HdrHistogramQuantileSqlAggregatorTest extends CalciteTestBase {
.put("dim3", ImmutableList.of("a", "b"))
.build()
),
CalciteTests.createRow(
TestDataBuilder.createRow(
ImmutableMap.<String, Object>builder()
.put("t", "2000-01-02")
.put("m1", "2.0")
@@ -106,7 +92,7 @@ public class HdrHistogramQuantileSqlAggregatorTest extends CalciteTestBase {
.put("dim3", ImmutableList.of("b", "c"))
.build()
),
CalciteTests.createRow(
TestDataBuilder.createRow(
ImmutableMap.<String, Object>builder()
.put("t", "2000-01-03")
.put("m1", "3.0")
@@ -116,7 +102,7 @@ public class HdrHistogramQuantileSqlAggregatorTest extends CalciteTestBase {
.put("dim3", ImmutableList.of("d"))
.build()
),
CalciteTests.createRow(
TestDataBuilder.createRow(
ImmutableMap.<String, Object>builder()
.put("t", "2001-01-01")
.put("m1", "4.0")
@@ -126,7 +112,7 @@ public class HdrHistogramQuantileSqlAggregatorTest extends CalciteTestBase {
.put("dim3", ImmutableList.of(""))
.build()
),
CalciteTests.createRow(
TestDataBuilder.createRow(
ImmutableMap.<String, Object>builder()
.put("t", "2001-01-02")
.put("m1", "5.0")
@@ -136,7 +122,7 @@ public class HdrHistogramQuantileSqlAggregatorTest extends CalciteTestBase {
.put("dim3", ImmutableList.of())
.build()
),
CalciteTests.createRow(
TestDataBuilder.createRow(
ImmutableMap.<String, Object>builder()
.put("t", "2001-01-03")
.put("m1", "6.0")
@@ -146,15 +132,20 @@ public class HdrHistogramQuantileSqlAggregatorTest extends CalciteTestBase {
)
);
@Before
public void setUp() throws Exception {
@SuppressWarnings("resource")
@Override
public SpecificSegmentsQuerySegmentWalker createQuerySegmentWalker(
final QueryRunnerFactoryConglomerate conglomerate,
final JoinableFactoryWrapper joinableFactory,
final Injector injector
) throws IOException{
HdrHistogramModule.registerSerde();
for (Module mod : new HdrHistogramModule().getJacksonModules()) {
CalciteTests.getJsonMapper().registerModule(mod);
TestHelper.JSON_MAPPER.registerModule(mod);
}
final QueryableIndex index = IndexBuilder.create()
//final QueryableIndex index = TestHelper.getTestIndexIO().loadIndex(new File("D:/doc/datas/testIndex-6201298"));
/*final QueryableIndex index = IndexBuilder.create()
.tmpDir(temporaryFolder.newFolder())
.segmentWriteOutMediumFactory(OffHeapMemorySegmentWriteOutMediumFactory.instance())
.schema(
@@ -176,59 +167,159 @@ public class HdrHistogramQuantileSqlAggregatorTest extends CalciteTestBase {
)
//.rows(CalciteTests.ROWS1)
.rows(ROWS1)
.buildMMappedIndex();
.buildMMappedIndex();*/
walker = new SpecificSegmentsQuerySegmentWalker(conglomerate).add(
String[] files = new String[]{
"D:\\doc\\datas\\statistics_rule_segments\\2023-10-16T00_00_00.000Z_2023-10-17T00_00_00.000Z\\2023-10-16T07_51_47.981Z\\0\\17a457e4-599d-49c2-86e7-6655851bb99a\\index",
"D:\\doc\\datas\\statistics_rule_segments\\2023-10-15T00_00_00.000Z_2023-10-16T00_00_00.000Z\\2023-10-15T00_00_04.240Z\\15\\9a766f6c-779d-4f9f-9ff5-6a12c19b8c6c\\index"
};
files = new String[]{
"D:/doc/datas/testIndex-6201298"
};
SpecificSegmentsQuerySegmentWalker walker = new SpecificSegmentsQuerySegmentWalker(conglomerate);
for (int i = 0; i < files.length; i++) {
QueryableIndex index = TestHelper.getTestIndexIO().loadIndex(new File(files[i]));
return walker.add(
DataSegment.builder()
.dataSource(DATA_SOURCE)
.dataSource(CalciteTests.DATASOURCE1)
.interval(index.getDataInterval())
.version("1")
.shardSpec(new LinearShardSpec(0))
.shardSpec(new LinearShardSpec(i))
.size(0)
.build(),
index
);
final PlannerConfig plannerConfig = new PlannerConfig();
final DruidOperatorTable operatorTable = new DruidOperatorTable(
ImmutableSet.of(
new HdrHistogramQuantileSqlAggregator(),
new HdrHistogramObjectSqlAggregator()
),
ImmutableSet.of(
new HdrHistogramQuantilesOperatorConversion(),
new HdrHistogramPercentilesOperatorConversion()
)
);
SchemaPlus rootSchema =
CalciteTests.createMockRootSchema(conglomerate, walker, plannerConfig, AuthTestUtils.TEST_AUTHORIZER_MAPPER);
sqlLifecycleFactory = CalciteTests.createSqlLifecycleFactory(
new PlannerFactory(
rootSchema,
CalciteTests.createMockQueryLifecycleFactory(walker, conglomerate),
operatorTable,
CalciteTests.createExprMacroTable(),
plannerConfig,
AuthTestUtils.TEST_AUTHORIZER_MAPPER,
CalciteTests.getJsonMapper(),
CalciteTests.DRUID_SCHEMA_NAME
)
);
}
@After
public void tearDown() throws Exception {
walker.close();
walker = null;
return walker;
}
@Test
public void testCount0() throws Exception {
String sql = "select count(1) cnt, APPROX_QUANTILE_HDR(hist_m1, 0.5, 1, 100, 2) from druid.foo where dim1 = 'aaa'";
QueryTestBuilder builder = testBuilder().sql(sql).skipVectorize();
builder.run();
QueryTestRunner.QueryResults queryResults = builder.results();
List<Object[]> results = queryResults.results;
for (Object[] result : results) {
System.out.println(Arrays.toString(result));
}
}
@Test
public void testSqlQueryError() throws Exception {
String sql = "select min(__time) min_time,max(__time) max_time, HDR_HISTOGRAM(latency_ms_sketch) hdr from druid.foo";
QueryTestBuilder builder = testBuilder().sql(sql).skipVectorize();
builder.run();
QueryTestRunner.QueryResults queryResults = builder.results();
List<Object[]> results = queryResults.results;
for (Object[] result : results) {
System.out.println(Arrays.toString(result));
}
}
@Test
public void testSqlDESCRIBE() throws Exception {
String sql = "select HDR_GET_QUANTILES(HDR_HISTOGRAM(m1, 1, 100, 2), 0, 0.25, 0.5, 0.75, 1) a, HDR_DESCRIBE(HDR_HISTOGRAM(m1, 1, 100, 2)) b, HDR_DESCRIBE(HDR_HISTOGRAM(hist_m1, 1, 100, 2)) c from druid.foo";
QueryTestBuilder builder = testBuilder().sql(sql).skipVectorize();
builder.run();
QueryTestRunner.QueryResults queryResults = builder.results();
List<Object[]> results = queryResults.results;
for (Object[] result : results) {
System.out.println(Arrays.toString(result));
}
}
@Test
public void testSqlDESCRIBE2() throws Exception {
String sql = "select HDR_GET_QUANTILES(HDR_HISTOGRAM(m1, 1, 100, 2), 0, 0.25, 0.5, 0.75, 1) a, HDR_GET_PERCENTILES_DESCRIPTION(HDR_HISTOGRAM(m1, 1, 100, 2)) b, HDR_GET_PERCENTILES_DESCRIPTION(HDR_HISTOGRAM(hist_m1, 1, 100, 2)) c from druid.foo";
QueryTestBuilder builder = testBuilder().sql(sql).skipVectorize();
builder.run();
QueryTestRunner.QueryResults queryResults = builder.results();
List<Object[]> results = queryResults.results;
for (Object[] result : results) {
System.out.println(Arrays.toString(result));
}
}
@Test
public void testSqlQuery() throws Exception {
SqlLifecycle sqlLifecycle = sqlLifecycleFactory.factorize();
String sql = "select * from druid.foo";
final List<Object[]> results =
sqlLifecycle.runSimple(sql, QUERY_CONTEXT_DEFAULT, DEFAULT_PARAMETERS, authenticationResult).toList();
String[] columns = new String[]{"__time", "dim1", "dim2", "dim3", "cnt", "hist_m1", "m1"};
String sql = "select " + String.join(",", columns) + " from druid.foo";
QueryTestBuilder builder = testBuilder().sql(sql);
builder.run();
QueryTestRunner.QueryResults queryResults = builder.results();
List<Object[]> results = queryResults.results;
for (Object[] result : results) {
Map row = new LinkedHashMap();
for (int i = 0; i < result.length; i++) {
row.put(columns[i], result[i]);
}
System.out.println(JSON.toJSONString(row));
// System.out.println(Arrays.toString(result));
}
for (int i = 0; i < columns.length; i++) {
Object[] values = new Object[results.size()];
for (int j = 0; j < results.size(); j++) {
values[j] = results.get(j)[i];
}
System.out.println(columns[i] + ":" + Arrays.toString(values));
}
}
@Test
public void testSqlQuery3() throws Exception {
//cannotVectorize();
//String sql = "select HLLD_ESTIMATE(HLLD(hll_dim1)) from druid.foo where dim1 = ''";
String sql = "select HDR_HISTOGRAM(hist_m1) hdr from druid.foo ";
QueryTestBuilder builder = testBuilder().sql(sql).skipVectorize();
builder.run();
QueryTestRunner.QueryResults queryResults = builder.results();
List<Object[]> results = queryResults.results;
for (Object[] result : results) {
System.out.println(Arrays.toString(result));
}
}
@Test
public void testSqlQuery4() throws Exception {
//cannotVectorize();
//String sql = "select HLLD_ESTIMATE(HLLD(hll_dim1)) from druid.foo where dim1 = ''";
String sql = "select APPROX_QUANTILE_HDR (hdr, 0.95) as p95th_tcp_latency_ms from (select HDR_HISTOGRAM(hist_m1) hdr from druid.foo) t ";
QueryTestBuilder builder = testBuilder().sql(sql).skipVectorize();
builder.run();
QueryTestRunner.QueryResults queryResults = builder.results();
List<Object[]> results = queryResults.results;
for (Object[] result : results) {
System.out.println(Arrays.toString(result));
}
}
@Test
public void testSqlQuery5() throws Exception {
//cannotVectorize();
//String sql = "select HLLD_ESTIMATE(HLLD(hll_dim1)) from druid.foo where dim1 = ''";
String sql = "select dim1, APPROX_QUANTILE_HDR (hdr, 0.95) as p95th_tcp_latency_ms from (select dim1, HDR_HISTOGRAM(hist_m1) hdr from druid.foo group by dim1) t group by dim1";
QueryTestBuilder builder = testBuilder().sql(sql).skipVectorize();
builder.run();
QueryTestRunner.QueryResults queryResults = builder.results();
List<Object[]> results = queryResults.results;
for (Object[] result : results) {
System.out.println(Arrays.toString(result));
}
}
@Test
public void testSqlQuery6() throws Exception {
//cannotVectorize();
//String sql = "select HLLD_ESTIMATE(HLLD(hll_dim1)) from druid.foo where dim1 = ''";
//String sql = "select dim1, APPROX_QUANTILE_HDR (hdr, 0.95) as p95th_tcp_latency_ms from (select dim1, HDR_HISTOGRAM(hist_m1) hdr from druid.foo group by dim1 limit 10) t group by dim1";
String sql = "select dim1, HDR_GET_QUANTILES(HDR_HISTOGRAM(hdr), 0.95) as p95th_tcp_latency_ms from (select dim1, HDR_HISTOGRAM(hist_m1) hdr from druid.foo group by dim1 limit 10) t group by dim1";
QueryTestBuilder builder = testBuilder().sql(sql).skipVectorize();
builder.run();
QueryTestRunner.QueryResults queryResults = builder.results();
List<Object[]> results = queryResults.results;
for (Object[] result : results) {
System.out.println(Arrays.toString(result));
}
@@ -236,10 +327,11 @@ public class HdrHistogramQuantileSqlAggregatorTest extends CalciteTestBase {
@Test
public void testGroup() throws Exception {
SqlLifecycle sqlLifecycle = sqlLifecycleFactory.factorize();
String sql = "select cnt, APPROX_QUANTILE_HDR(hist_m1, 0.5, 1, 100, 2) from druid.foo group by cnt";
final List<Object[]> results =
sqlLifecycle.runSimple(sql, QUERY_CONTEXT_DEFAULT, DEFAULT_PARAMETERS, authenticationResult).toList();
QueryTestBuilder builder = testBuilder().sql(sql).skipVectorize();
builder.run();
QueryTestRunner.QueryResults queryResults = builder.results();
List<Object[]> results = queryResults.results;
for (Object[] result : results) {
System.out.println(Arrays.toString(result));
}
@@ -247,10 +339,35 @@ public class HdrHistogramQuantileSqlAggregatorTest extends CalciteTestBase {
@Test
public void testGroup2() throws Exception {
SqlLifecycle sqlLifecycle = sqlLifecycleFactory.factorize();
String sql = "select HDR_HISTOGRAM(hist_m1) from druid.foo";
final List<Object[]> results =
sqlLifecycle.runSimple(sql, QUERY_CONTEXT_DEFAULT, DEFAULT_PARAMETERS, authenticationResult).toList();
QueryTestBuilder builder = testBuilder().sql(sql).skipVectorize();
builder.run();
QueryTestRunner.QueryResults queryResults = builder.results();
List<Object[]> results = queryResults.results;
for (Object[] result : results) {
System.out.println(Arrays.toString(result));
}
}
@Test
public void testGroup3() throws Exception {
String sql = "select APPROX_QUANTILE_HDR(h, 0.5) from(select HDR_HISTOGRAM(hist_m1) h from druid.foo) t";
QueryTestBuilder builder = testBuilder().sql(sql).skipVectorize();
builder.run();
QueryTestRunner.QueryResults queryResults = builder.results();
List<Object[]> results = queryResults.results;
for (Object[] result : results) {
System.out.println(Arrays.toString(result));
}
}
@Test
public void testGroup4() throws Exception {
String sql = "select hdr_get_quantiles(h, 0.1, 0.2, 0.3, 0.5, 0.9, 0.99, 1) from(select HDR_HISTOGRAM(hist_m1) h from druid.foo) t";
QueryTestBuilder builder = testBuilder().sql(sql).skipVectorize();
builder.run();
QueryTestRunner.QueryResults queryResults = builder.results();
List<Object[]> results = queryResults.results;
for (Object[] result : results) {
System.out.println(Arrays.toString(result));
}
@@ -258,10 +375,11 @@ public class HdrHistogramQuantileSqlAggregatorTest extends CalciteTestBase {
@Test
public void testSqlQueryGeneHdr() throws Exception {
SqlLifecycle sqlLifecycle = sqlLifecycleFactory.factorize();
String sql = "select HDR_HISTOGRAM(hist_m1, 1, 100, 2), HDR_HISTOGRAM(cnt, 1, 100, 2) from druid.foo";
final List<Object[]> results =
sqlLifecycle.runSimple(sql, QUERY_CONTEXT_DEFAULT, DEFAULT_PARAMETERS, authenticationResult).toList();
QueryTestBuilder builder = testBuilder().sql(sql).skipVectorize();
builder.run();
QueryTestRunner.QueryResults queryResults = builder.results();
List<Object[]> results = queryResults.results;
for (Object[] result : results) {
System.out.println(Arrays.toString(result));
}
@@ -269,11 +387,12 @@ public class HdrHistogramQuantileSqlAggregatorTest extends CalciteTestBase {
@Test
public void testSqlQueryGeneHdr2() throws Exception {
SqlLifecycle sqlLifecycle = sqlLifecycleFactory.factorize();
// HDR_HISTOGRAM(hist_m1, 1, 100, 2),
String sql = "select HDR_GET_QUANTILES(HDR_HISTOGRAM(m1, 1, 100, 2), 0.1, 0.2, 0.3, 0.5, 0.9, 1) from druid.foo";
final List<Object[]> results =
sqlLifecycle.runSimple(sql, QUERY_CONTEXT_DEFAULT, DEFAULT_PARAMETERS, authenticationResult).toList();
QueryTestBuilder builder = testBuilder().sql(sql).skipVectorize();
builder.run();
QueryTestRunner.QueryResults queryResults = builder.results();
List<Object[]> results = queryResults.results;
for (Object[] result : results) {
System.out.println(Arrays.toString(result));
}
@@ -281,14 +400,15 @@ public class HdrHistogramQuantileSqlAggregatorTest extends CalciteTestBase {
@Test
public void testSqlQueryGeneHdrArgs() throws Exception {
SqlLifecycle sqlLifecycle = sqlLifecycleFactory.factorize();
String sql = "select HDR_GET_QUANTILEs(HDR_HISTOGRAM(m1), 0.1, 0.2, 0.3, 0.5, 0.9, 1), "
+ "HDR_GET_QUANTILEs(HDR_HISTOGRAM(m1, 2), 0.1, 0.2, 0.3, 0.5, 0.9, 1) ,\n"
+ "HDR_GET_QUANTILEs(HDR_HISTOGRAM(m1, 1, 110, 2), 0.1, 0.2, 0.3, 0.5, 0.9, 1) ,\n"
+ "HDR_GET_QUANTILEs(HDR_HISTOGRAM(m1, 1, 110, 2, false), 0.1, 0.2, 0.3, 0.5, 0.9, 1) \n"
+ "from druid.foo";
final List<Object[]> results =
sqlLifecycle.runSimple(sql, QUERY_CONTEXT_DEFAULT, DEFAULT_PARAMETERS, authenticationResult).toList();
QueryTestBuilder builder = testBuilder().sql(sql).skipVectorize();
builder.run();
QueryTestRunner.QueryResults queryResults = builder.results();
List<Object[]> results = queryResults.results;
for (Object[] result : results) {
System.out.println(Arrays.toString(result));
}
@@ -296,14 +416,15 @@ public class HdrHistogramQuantileSqlAggregatorTest extends CalciteTestBase {
@Test
public void testSqlQueryGeneHdrArgs2() throws Exception {
SqlLifecycle sqlLifecycle = sqlLifecycleFactory.factorize();
String sql = "select APPROX_QUANTILE_HDR(m1, 0.1), "
+ "APPROX_QUANTILE_HDR(m1, 0.1, 2) ,\n"
+ "APPROX_QUANTILE_HDR(m1, 0.1, 1, 110, 2) ,\n"
+ "APPROX_QUANTILE_HDR(m1, 0.1, 1, 110, 2, false)\n"
+ "from druid.foo";
final List<Object[]> results =
sqlLifecycle.runSimple(sql, QUERY_CONTEXT_DEFAULT, DEFAULT_PARAMETERS, authenticationResult).toList();
QueryTestBuilder builder = testBuilder().sql(sql).skipVectorize();
builder.run();
QueryTestRunner.QueryResults queryResults = builder.results();
List<Object[]> results = queryResults.results;
for (Object[] result : results) {
System.out.println(Arrays.toString(result));
}
@@ -311,14 +432,15 @@ public class HdrHistogramQuantileSqlAggregatorTest extends CalciteTestBase {
@Test
public void testSqlQueryGeneHdr3() throws Exception {
SqlLifecycle sqlLifecycle = sqlLifecycleFactory.factorize();
// 函数不区分大小写
// HDR_HISTOGRAM(hist_m1, 1, 100, 2),
//String sql = "select HDR_GET_PERCENTILES(HDR_HISTOGRAM(m1, 1, 100, 2)) from druid.foo";
//String sql = "select hdr_get_percentiles(hdr_histogram(m1, 1, 100, 2)) from druid.foo";
String sql = "select hdr_get_percentiles(hdr_histogram(hist_m1, 1, 100, 2)) from druid.foo";
final List<Object[]> results =
sqlLifecycle.runSimple(sql, QUERY_CONTEXT_DEFAULT, DEFAULT_PARAMETERS, authenticationResult).toList();
QueryTestBuilder builder = testBuilder().sql(sql).skipVectorize();
builder.run();
QueryTestRunner.QueryResults queryResults = builder.results();
List<Object[]> results = queryResults.results;
for (Object[] result : results) {
System.out.println(Arrays.toString(result));
}
@@ -326,7 +448,6 @@ public class HdrHistogramQuantileSqlAggregatorTest extends CalciteTestBase {
@Test
public void testSqlQueryQuantiles() throws Exception {
SqlLifecycle sqlLifecycle = sqlLifecycleFactory.factorize();
String sql = "SELECT\n"
+ "APPROX_QUANTILE_HDR(m1, 0.01, 1, 100, 2),\n"
+ "APPROX_QUANTILE_HDR(m1, 0.5, 1, 100, 2),\n"
@@ -338,9 +459,10 @@ public class HdrHistogramQuantileSqlAggregatorTest extends CalciteTestBase {
+ "APPROX_QUANTILE_HDR(m1, 0.999, 1, 100, 2) FILTER(WHERE dim1 = 'abc'),\n"
+ "APPROX_QUANTILE_HDR(cnt, 0.5, 1, 100, 2)\n"
+ "FROM foo";
final List<Object[]> results =
sqlLifecycle.runSimple(sql, QUERY_CONTEXT_DEFAULT, DEFAULT_PARAMETERS, authenticationResult).toList();
System.out.println(sql);
QueryTestBuilder builder = testBuilder().sql(sql).skipVectorize();
builder.run();
QueryTestRunner.QueryResults queryResults = builder.results();
List<Object[]> results = queryResults.results;
for (Object[] result : results) {
System.out.println(Arrays.toString(result));
}
@@ -348,7 +470,6 @@ public class HdrHistogramQuantileSqlAggregatorTest extends CalciteTestBase {
@Test
public void testSqlQueryQuantilesOnComplexColumn() throws Exception {
SqlLifecycle sqlLifecycle = sqlLifecycleFactory.factorize();
String sql = "SELECT\n"
+ "APPROX_QUANTILE_HDR(hist_m1, 0.01, 1, 100, 2),\n"
+ "APPROX_QUANTILE_HDR(hist_m1, 0.5, 1, 100, 2),\n"
@@ -358,9 +479,10 @@ public class HdrHistogramQuantileSqlAggregatorTest extends CalciteTestBase {
+ "APPROX_QUANTILE_HDR(hist_m1, 0.999, 1, 100, 2) FILTER(WHERE dim1 <> 'abc'),\n"
+ "APPROX_QUANTILE_HDR(hist_m1, 0.999, 1, 100, 2) FILTER(WHERE dim1 = 'abc')\n"
+ "FROM foo";
final List<Object[]> results =
sqlLifecycle.runSimple(sql, QUERY_CONTEXT_DEFAULT, DEFAULT_PARAMETERS, authenticationResult).toList();
System.out.println(sql);
QueryTestBuilder builder = testBuilder().sql(sql).skipVectorize();
builder.run();
QueryTestRunner.QueryResults queryResults = builder.results();
List<Object[]> results = queryResults.results;
for (Object[] result : results) {
System.out.println(Arrays.toString(result));
}
@@ -373,7 +495,6 @@ public class HdrHistogramQuantileSqlAggregatorTest extends CalciteTestBase {
@Test
public void testQuantileOnFloatAndLongs() throws Exception {
SqlLifecycle sqlLifecycle = sqlLifecycleFactory.factorize();
String sql = "SELECT\n"
+ "APPROX_QUANTILE_HDR(m1, 0.01, 1, 100, 2),\n"
+ "APPROX_QUANTILE_HDR(m1, 0.5, 1, 100, 2),\n"
@@ -385,16 +506,8 @@ public class HdrHistogramQuantileSqlAggregatorTest extends CalciteTestBase {
+ "APPROX_QUANTILE_HDR(m1, 0.999, 1, 100, 2) FILTER(WHERE dim1 = 'abc'),\n"
+ "APPROX_QUANTILE_HDR(cnt, 0.5, 1, 100, 2)\n"
+ "FROM foo";
final List<Object[]> results =
sqlLifecycle.runSimple(sql, QUERY_CONTEXT_DEFAULT, DEFAULT_PARAMETERS, authenticationResult).toList();
System.out.println(sql);
for (Object[] result : results) {
System.out.println(Arrays.toString(result));
}
// Verify query
Assert.assertEquals(
Druids.newTimeseriesQueryBuilder()
QueryTestBuilder builder = testBuilder().sql(sql).skipVectorize();
builder = builder.expectedQueries(Collections.singletonList(Druids.newTimeseriesQueryBuilder()
.dataSource(CalciteTests.DATASOURCE1)
.intervals(new MultipleIntervalSegmentSpec(ImmutableList.of(Filtration.eternity())))
.granularity(Granularities.ALL)
@@ -402,7 +515,7 @@ public class HdrHistogramQuantileSqlAggregatorTest extends CalciteTestBase {
new ExpressionVirtualColumn(
"v0",
"(\"m1\" * 2)",
ValueType.LONG,
ColumnType.LONG,
TestExprMacroTable.INSTANCE
)
)
@@ -430,15 +543,18 @@ public class HdrHistogramQuantileSqlAggregatorTest extends CalciteTestBase {
new HdrHistogramToQuantilePostAggregator("a7", "a5:agg", 0.999f),
new HdrHistogramToQuantilePostAggregator("a8", "a8:agg", 0.50f)
)
.context(ImmutableMap.of("skipEmptyBuckets", true, PlannerContext.CTX_SQL_QUERY_ID, "dummy"))
.build(),
Iterables.getOnlyElement(queryLogHook.getRecordedQueries())
);
.context(QUERY_CONTEXT_DEFAULT)
.build()));
builder.run();
QueryTestRunner.QueryResults queryResults = builder.results();
List<Object[]> results = queryResults.results;
for (Object[] result : results) {
System.out.println(Arrays.toString(result));
}
}
@Test
public void testQuantileOnComplexColumn() throws Exception{
SqlLifecycle sqlLifecycle = sqlLifecycleFactory.factorize();
String sql = "SELECT\n"
+ "APPROX_QUANTILE_HDR(hist_m1, 0.01, 1, 100, 2),\n"
+ "APPROX_QUANTILE_HDR(hist_m1, 0.5, 1, 100, 2),\n"
@@ -448,16 +564,8 @@ public class HdrHistogramQuantileSqlAggregatorTest extends CalciteTestBase {
+ "APPROX_QUANTILE_HDR(hist_m1, 0.999, 1, 100, 2) FILTER(WHERE dim1 <> 'abc'),\n"
+ "APPROX_QUANTILE_HDR(hist_m1, 0.999, 1, 100, 2) FILTER(WHERE dim1 = 'abc')\n"
+ "FROM foo";
final List<Object[]> results =
sqlLifecycle.runSimple(sql, QUERY_CONTEXT_DEFAULT, DEFAULT_PARAMETERS, authenticationResult).toList();
System.out.println(sql);
for (Object[] result : results) {
System.out.println(Arrays.toString(result));
}
// Verify query
Assert.assertEquals(
Druids.newTimeseriesQueryBuilder()
QueryTestBuilder builder = testBuilder().sql(sql).skipVectorize();
builder = builder.expectedQueries(Collections.singletonList(Druids.newTimeseriesQueryBuilder()
.dataSource(CalciteTests.DATASOURCE1)
.intervals(new MultipleIntervalSegmentSpec(ImmutableList.of(Filtration.eternity())))
.granularity(Granularities.ALL)
@@ -481,10 +589,17 @@ public class HdrHistogramQuantileSqlAggregatorTest extends CalciteTestBase {
new HdrHistogramToQuantilePostAggregator("a5", "a5:agg", 0.999f),
new HdrHistogramToQuantilePostAggregator("a6", "a4:agg", 0.999f)
)
.context(ImmutableMap.of("skipEmptyBuckets", true, PlannerContext.CTX_SQL_QUERY_ID, "dummy"))
.build(),
Iterables.getOnlyElement(queryLogHook.getRecordedQueries())
);
.context(QUERY_CONTEXT_DEFAULT)
.build()));
builder.run();
QueryTestRunner.QueryResults queryResults = builder.results();
List<Object[]> results = queryResults.results;
for (Object[] result : results) {
System.out.println(Arrays.toString(result));
}
}
private static PostAggregator makeFieldAccessPostAgg(String name) {

View File

@@ -5,7 +5,7 @@
<modelVersion>4.0.0</modelVersion>
<groupId>org.apache.druid.extensions</groupId>
<artifactId>druid-hlld_0.18.1</artifactId>
<artifactId>druid-hlld_26.0.0</artifactId>
<name>druid-hlld</name>
<version>1.0-SNAPSHOT</version>
@@ -14,7 +14,7 @@
<project.reporting.outputEncoding>UTF-8</project.reporting.outputEncoding>
<maven.compiler.source>1.8</maven.compiler.source>
<maven.compiler.target>1.8</maven.compiler.target>
<druid.version>0.18.1</druid.version>
<druid.version>26.0.0</druid.version>
</properties>
<dependencies>
@@ -33,6 +33,14 @@
</dependency>
<!-- Tests -->
<dependency>
<groupId>org.easymock</groupId>
<artifactId>easymock</artifactId>
<version>4.3</version>
<scope>test</scope>
</dependency>
<dependency>
<groupId>org.apache.druid</groupId>
<artifactId>druid-processing</artifactId>
@@ -42,9 +50,17 @@
</dependency>
<dependency>
<groupId>org.apache.druid</groupId>
<artifactId>druid-benchmarks</artifactId>
<artifactId>druid-server</artifactId>
<version>${druid.version}</version>
<scope>test</scope>
<type>test-jar</type>
</dependency>
<dependency>
<groupId>org.apache.druid</groupId>
<artifactId>druid-sql</artifactId>
<version>${druid.version}</version>
<type>test-jar</type>
<scope>test</scope>
</dependency>
<dependency>
<groupId>junit</groupId>

View File

@@ -9,6 +9,7 @@ import org.apache.druid.query.aggregation.*;
import org.apache.druid.query.cache.CacheKeyBuilder;
import org.apache.druid.segment.ColumnSelectorFactory;
import org.apache.druid.segment.ColumnValueSelector;
import org.apache.druid.segment.column.ColumnType;
import javax.annotation.Nullable;
import java.util.Collections;
@@ -27,6 +28,7 @@ public class HllAggregatorFactory extends AggregatorFactory {
protected final String fieldName;
protected final int precision;
protected final boolean round;
protected final int updatableSerializationBytes;
public HllAggregatorFactory(
@JsonProperty("name") final String name,
@@ -44,6 +46,7 @@ public class HllAggregatorFactory extends AggregatorFactory {
this.fieldName = fieldName;
this.precision = precision == null ? DEFAULT_PRECISION : precision;
this.round = round == null ? DEFAULT_ROUND : round;
this.updatableSerializationBytes = getUpdatableSerializationBytes();
}
@Override
@@ -145,9 +148,9 @@ public class HllAggregatorFactory extends AggregatorFactory {
Math.max(precision, castedOther.precision),
round || castedOther.round
);
} else {
throw new AggregatorFactoryNotMergeableException(this, other);
}
throw new AggregatorFactoryNotMergeableException(this, other);
}
@Override
@@ -157,25 +160,42 @@ public class HllAggregatorFactory extends AggregatorFactory {
);
}
@Override
public AggregatorFactory withName(String newName) {
return new HllAggregatorFactory(newName, fieldName, precision, round);
}
@Override
public Object deserialize(Object object) {
if (object == null) {
return null;
}
return HllUtils.deserializeHll(object);
}
@Override
public ColumnType getResultType() {
//return round ? ColumnType.LONG : ColumnType.DOUBLE;
return getIntermediateType();
}
@Nullable
@Override
public Object finalizeComputation(@Nullable Object object) {
if (object == null) {
return null;
}
final Hll hll = (Hll) object;
return object;
/*final Hll hll = (Hll) object;
final double estimate = hll.size();
if (round) {
return Math.round(estimate);
} else {
return estimate;
}
}*/
}
@Override
@@ -199,9 +219,16 @@ public class HllAggregatorFactory extends AggregatorFactory {
return round;
}
/*
没这个方法了, 新版本需要实现getIntermediateType方法
@Override
public String getTypeName() {
return HllModule.HLLD_BUILD_TYPE_NAME;
}*/
@Override
public ColumnType getIntermediateType() {
return HllModule.BUILD_TYPE;
}
@Override
@@ -211,6 +238,10 @@ public class HllAggregatorFactory extends AggregatorFactory {
@Override
public int getMaxIntermediateSize() {
return updatableSerializationBytes == 0? getUpdatableSerializationBytes():updatableSerializationBytes;
}
protected int getUpdatableSerializationBytes(){
return Hll.getUpdatableSerializationBytes(precision);
}

View File

@@ -4,10 +4,12 @@ import com.fasterxml.jackson.annotation.JsonProperty;
import com.zdjz.galaxy.sketch.hlld.Hll;
import com.zdjz.galaxy.sketch.hlld.HllUnion;
import org.apache.druid.query.aggregation.Aggregator;
import org.apache.druid.query.aggregation.AggregatorFactory;
import org.apache.druid.query.aggregation.BufferAggregator;
import org.apache.druid.query.cache.CacheKeyBuilder;
import org.apache.druid.segment.ColumnSelectorFactory;
import org.apache.druid.segment.ColumnValueSelector;
import org.apache.druid.segment.column.ColumnType;
import javax.annotation.Nullable;
@@ -21,9 +23,16 @@ public class HllMergeAggregatorFactory extends HllAggregatorFactory{
super(name, fieldName, precision, round);
}
/*
没这个方法了, 新版本需要实现getIntermediateType方法
@Override
public String getTypeName(){
return HllModule.HLLD_TYPE_NAME;
}*/
@Override
public ColumnType getIntermediateType() {
return HllModule.TYPE;
}
@Override
@@ -44,6 +53,11 @@ public class HllMergeAggregatorFactory extends HllAggregatorFactory{
);
}
@Override
public AggregatorFactory withName(String newName) {
return new HllMergeAggregatorFactory(newName, fieldName, precision, round);
}
@Override
public byte[] getCacheKey() {
return new CacheKeyBuilder(HllModule.CACHE_TYPE_ID_OFFSET).appendByte(HllModule.HLLD_MERGE_CACHE_TYPE_ID)
@@ -53,7 +67,7 @@ public class HllMergeAggregatorFactory extends HllAggregatorFactory{
}
@Override
public int getMaxIntermediateSize() {
protected int getUpdatableSerializationBytes() {
return HllUnion.getUpdatableSerializationBytes(precision);
}
}

View File

@@ -10,6 +10,7 @@ import org.apache.druid.initialization.DruidModule;
import org.apache.druid.query.aggregation.sketch.hlld.sql.HllApproxCountDistinctSqlAggregator;
import org.apache.druid.query.aggregation.sketch.hlld.sql.HllEstimateOperatorConversion;
import org.apache.druid.query.aggregation.sketch.hlld.sql.HllObjectSqlAggregator;
import org.apache.druid.segment.column.ColumnType;
import org.apache.druid.segment.serde.ComplexMetrics;
import org.apache.druid.sql.guice.SqlBindings;
@@ -24,6 +25,9 @@ public class HllModule implements DruidModule {
public static final String HLLD_TYPE_NAME = "HLLDSketch";
public static final String HLLD_BUILD_TYPE_NAME = "HLLDSketchBuild";
public static final ColumnType TYPE = ColumnType.ofComplex(HLLD_TYPE_NAME);
public static final ColumnType BUILD_TYPE = ColumnType.ofComplex(HLLD_BUILD_TYPE_NAME);
@Override
public void configure(Binder binder) {

View File

@@ -7,6 +7,8 @@ import org.apache.druid.query.aggregation.AggregatorFactory;
import org.apache.druid.query.aggregation.PostAggregator;
import org.apache.druid.query.aggregation.post.ArithmeticPostAggregator;
import org.apache.druid.query.cache.CacheKeyBuilder;
import org.apache.druid.segment.ColumnInspector;
import org.apache.druid.segment.column.ColumnType;
import java.util.Comparator;
import java.util.Map;
@@ -29,6 +31,12 @@ public class HllToEstimatePostAggregator implements PostAggregator {
this.round = round;
}
// 新版本需要实现的方法
@Override
public ColumnType getType(ColumnInspector signature) {
return round ? ColumnType.LONG : ColumnType.DOUBLE;
}
@Override
@JsonProperty
public String getName() {
@@ -58,6 +66,9 @@ public class HllToEstimatePostAggregator implements PostAggregator {
@Override
public Object compute(final Map<String, Object> combinedAggregators) {
final Hll sketch = (Hll) field.compute(combinedAggregators);
if(sketch == null){
return round ? 0L: 0D;
}
return round ? Math.round(sketch.size()) : sketch.size();
}

View File

@@ -5,36 +5,44 @@ import org.apache.calcite.sql.SqlFunctionCategory;
import org.apache.calcite.sql.SqlKind;
import org.apache.calcite.sql.type.*;
import org.apache.druid.query.aggregation.AggregatorFactory;
import org.apache.druid.query.aggregation.post.FieldAccessPostAggregator;
import org.apache.druid.query.aggregation.post.FinalizingFieldAccessPostAggregator;
import org.apache.druid.segment.VirtualColumn;
import org.apache.druid.query.aggregation.sketch.hlld.HllAggregatorFactory;
import org.apache.druid.query.aggregation.sketch.hlld.HllToEstimatePostAggregator;
import org.apache.druid.sql.calcite.aggregation.Aggregation;
import java.util.Collections;
import java.util.List;
public class HllApproxCountDistinctSqlAggregator extends HllBaseSqlAggregator {
private static final SqlAggFunction FUNCTION_INSTANCE = new CPCSketchApproxCountDistinctSqlAggFunction();
private static final String NAME = "APPROX_COUNT_DISTINCT_HLLD";
public HllApproxCountDistinctSqlAggregator(){
super(true);
}
@Override
public SqlAggFunction calciteFunction() {
return FUNCTION_INSTANCE;
}
// 新版本参数少了virtualColumns
@Override
protected Aggregation toAggregation(
String name,
boolean finalizeAggregations,
List<VirtualColumn> virtualColumns,
AggregatorFactory aggregatorFactory
) {
return Aggregation.create(
virtualColumns,
Collections.singletonList(aggregatorFactory),
//感觉是否是最外层的函数吧
finalizeAggregations ? new FinalizingFieldAccessPostAggregator(
finalizeAggregations ? new HllToEstimatePostAggregator(
name,
new FieldAccessPostAggregator(
aggregatorFactory.getName(),
aggregatorFactory.getName()
),
((HllAggregatorFactory)aggregatorFactory).isRound()
) : null
);
}

View File

@@ -2,6 +2,7 @@ package org.apache.druid.query.aggregation.sketch.hlld.sql;
import org.apache.calcite.rel.core.AggregateCall;
import org.apache.calcite.rel.core.Project;
import org.apache.calcite.rel.type.RelDataType;
import org.apache.calcite.rex.RexBuilder;
import org.apache.calcite.rex.RexLiteral;
import org.apache.calcite.rex.RexNode;
@@ -14,6 +15,7 @@ import org.apache.druid.query.aggregation.sketch.hlld.HllMergeAggregatorFactory;
import org.apache.druid.query.dimension.DefaultDimensionSpec;
import org.apache.druid.query.dimension.DimensionSpec;
import org.apache.druid.segment.VirtualColumn;
import org.apache.druid.segment.column.ColumnType;
import org.apache.druid.segment.column.RowSignature;
import org.apache.druid.segment.column.ValueType;
import org.apache.druid.sql.calcite.aggregation.Aggregation;
@@ -29,6 +31,13 @@ import java.util.ArrayList;
import java.util.List;
public abstract class HllBaseSqlAggregator implements SqlAggregator {
private final boolean finalizeSketch;
protected HllBaseSqlAggregator(boolean finalizeSketch){
this.finalizeSketch = finalizeSketch;
}
@Nullable
@Override
public Aggregation toDruidAggregation(
@@ -93,13 +102,14 @@ public abstract class HllBaseSqlAggregator implements SqlAggregator {
round = HllAggregatorFactory.DEFAULT_ROUND;
}
final List<VirtualColumn> virtualColumns = new ArrayList<>();
// 新版本删除了final List<VirtualColumn> virtualColumns = new ArrayList<>();
final AggregatorFactory aggregatorFactory;
final String aggregatorName = finalizeAggregations ? Calcites.makePrefixedName(name, "a") : name;
//final String aggregatorName = finalizeAggregations ? Calcites.makePrefixedName(name, "a") : name;
final String aggregatorName = finalizeSketch ? Calcites.makePrefixedName(name, "a") : name;
// 输入是Cpc返回HllMergeAggregatorFactory
// 输入是Hll返回HllSketchMergeAggregatorFactory
if (columnArg.isDirectColumnAccess()
&& rowSignature.getColumnType(columnArg.getDirectColumn()).orElse(null) == ValueType.COMPLEX) {
&& rowSignature.getColumnType(columnArg.getDirectColumn()).map(type -> type.is(ValueType.COMPLEX)).orElse(false)) {
// 这就是具体的聚合函数吧
aggregatorFactory = new HllMergeAggregatorFactory(
aggregatorName,
@@ -109,10 +119,10 @@ public abstract class HllBaseSqlAggregator implements SqlAggregator {
);
} else {
// 输入是regular columnHllBuildAggregatorFactory
final SqlTypeName sqlTypeName = columnRexNode.getType().getSqlTypeName();
final ValueType inputType = Calcites.getValueTypeForSqlTypeName(sqlTypeName);
final RelDataType dataType = columnRexNode.getType();
final ColumnType inputType = Calcites.getColumnTypeForRelDataType(dataType);
if (inputType == null) {
throw new ISE("Cannot translate sqlTypeName[%s] to Druid type for field[%s]", sqlTypeName, aggregatorName);
throw new ISE("Cannot translate sqlTypeName[%s] to Druid type for field[%s]", dataType.getSqlTypeName(), aggregatorName);
}
final DimensionSpec dimensionSpec;
@@ -120,15 +130,22 @@ public abstract class HllBaseSqlAggregator implements SqlAggregator {
if (columnArg.isDirectColumnAccess()) {
dimensionSpec = columnArg.getSimpleExtraction().toDimensionSpec(null, inputType);
} else {
VirtualColumn virtualColumn = virtualColumnRegistry.getOrCreateVirtualColumnForExpression(
plannerContext,
String virtualColumnName = virtualColumnRegistry.getOrCreateVirtualColumnForExpression(
columnArg,
sqlTypeName
dataType
);
dimensionSpec = new DefaultDimensionSpec(virtualColumn.getOutputName(), null, inputType);
virtualColumns.add(virtualColumn);
dimensionSpec = new DefaultDimensionSpec(virtualColumnName, null, inputType);
}
// 新版本的判断输入是Hll
if (inputType.is(ValueType.COMPLEX)) {
aggregatorFactory = new HllMergeAggregatorFactory(
aggregatorName,
dimensionSpec.getOutputName(),
precision,
round
);
} else {
aggregatorFactory = new HllAggregatorFactory(
aggregatorName,
dimensionSpec.getDimension(),
@@ -136,11 +153,11 @@ public abstract class HllBaseSqlAggregator implements SqlAggregator {
round
);
}
}
return toAggregation(
name,
finalizeAggregations,
virtualColumns,
finalizeSketch,
aggregatorFactory
);
}
@@ -148,7 +165,6 @@ public abstract class HllBaseSqlAggregator implements SqlAggregator {
protected abstract Aggregation toAggregation(
String name,
boolean finalizeAggregations,
List<VirtualColumn> virtualColumns,
AggregatorFactory aggregatorFactory
);
}

View File

@@ -13,16 +13,15 @@ import org.apache.druid.query.aggregation.PostAggregator;
import org.apache.druid.query.aggregation.sketch.hlld.HllAggregatorFactory;
import org.apache.druid.query.aggregation.sketch.hlld.HllToEstimatePostAggregator;
import org.apache.druid.segment.column.RowSignature;
import org.apache.druid.sql.calcite.expression.DirectOperatorConversion;
import org.apache.druid.sql.calcite.expression.DruidExpression;
import org.apache.druid.sql.calcite.expression.OperatorConversions;
import org.apache.druid.sql.calcite.expression.PostAggregatorVisitor;
import org.apache.druid.sql.calcite.expression.*;
import org.apache.druid.sql.calcite.planner.PlannerContext;
import javax.annotation.Nullable;
import java.util.List;
public class HllEstimateOperatorConversion extends DirectOperatorConversion {
// postAggregator, toDruidExpression返回null。相当于post udf和普通udf是不一样的。
// 新版本直接修改了父类
public class HllEstimateOperatorConversion implements SqlOperatorConversion {
private static final String FUNCTION_NAME = "HLLD_ESTIMATE";
private static final SqlFunction SQL_FUNCTION = OperatorConversions
.operatorBuilder(StringUtils.toUpperCase(FUNCTION_NAME))
@@ -32,9 +31,7 @@ public class HllEstimateOperatorConversion extends DirectOperatorConversion {
.returnTypeInference(ReturnTypes.DOUBLE)
.build();
public HllEstimateOperatorConversion() {
super(SQL_FUNCTION, FUNCTION_NAME);
}
// 新版本少了构造函数
@Override
public SqlOperator calciteOperator() {
@@ -63,7 +60,8 @@ public class HllEstimateOperatorConversion extends DirectOperatorConversion {
plannerContext,
rowSignature,
operands.get(0),
postAggregatorVisitor
postAggregatorVisitor,
true // 新版本多了个参数
);
if (firstOperand == null) {

View File

@@ -5,16 +5,18 @@ import org.apache.calcite.sql.SqlFunctionCategory;
import org.apache.calcite.sql.SqlKind;
import org.apache.calcite.sql.type.*;
import org.apache.druid.query.aggregation.AggregatorFactory;
import org.apache.druid.segment.VirtualColumn;
import org.apache.druid.sql.calcite.aggregation.Aggregation;
import java.util.Collections;
import java.util.List;
public class HllObjectSqlAggregator extends HllBaseSqlAggregator {
private static final SqlAggFunction FUNCTION_INSTANCE = new CpcSketchSqlAggFunction();
private static final String NAME = "HLLD";
public HllObjectSqlAggregator(){
super(false);
}
@Override
public SqlAggFunction calciteFunction() {
return FUNCTION_INSTANCE;
@@ -24,11 +26,9 @@ public class HllObjectSqlAggregator extends HllBaseSqlAggregator {
protected Aggregation toAggregation(
String name,
boolean finalizeAggregations,
List<VirtualColumn> virtualColumns,
AggregatorFactory aggregatorFactory
) {
return Aggregation.create(
virtualColumns,
Collections.singletonList(aggregatorFactory),
null
);

View File

@@ -1,83 +1,64 @@
package org.apache.druid.query.aggregation.sketch.hlld.sql;
import com.alibaba.fastjson2.JSON;
import com.fasterxml.jackson.databind.Module;
import com.google.common.collect.ImmutableMap;
import com.google.common.collect.ImmutableSet;
import org.apache.calcite.schema.SchemaPlus;
import org.apache.druid.java.util.common.io.Closer;
import com.google.inject.Injector;
import org.apache.druid.guice.DruidInjectorBuilder;
import org.apache.druid.query.QueryRunnerFactoryConglomerate;
import org.apache.druid.query.aggregation.CountAggregatorFactory;
import org.apache.druid.query.aggregation.DoubleSumAggregatorFactory;
import org.apache.druid.query.aggregation.sketch.hlld.HllAggregatorFactory;
import org.apache.druid.query.aggregation.sketch.hlld.HllModule;
import org.apache.druid.segment.IndexBuilder;
import org.apache.druid.segment.QueryableIndex;
import org.apache.druid.segment.TestHelper;
import org.apache.druid.segment.incremental.IncrementalIndexSchema;
import org.apache.druid.segment.writeout.OffHeapMemorySegmentWriteOutMediumFactory;
import org.apache.druid.server.QueryStackTests;
import org.apache.druid.server.security.AuthTestUtils;
import org.apache.druid.server.security.AuthenticationResult;
import org.apache.druid.sql.SqlLifecycle;
import org.apache.druid.sql.SqlLifecycleFactory;
import org.apache.druid.sql.calcite.planner.DruidOperatorTable;
import org.apache.druid.sql.calcite.planner.PlannerConfig;
import org.apache.druid.sql.calcite.planner.PlannerContext;
import org.apache.druid.sql.calcite.planner.PlannerFactory;
import org.apache.druid.sql.calcite.util.CalciteTestBase;
import org.apache.druid.segment.join.JoinableFactoryWrapper;
import org.apache.druid.sql.calcite.BaseCalciteQueryTest;
import org.apache.druid.sql.calcite.QueryTestBuilder;
import org.apache.druid.sql.calcite.QueryTestRunner;
import org.apache.druid.sql.calcite.util.CalciteTests;
import org.apache.druid.sql.calcite.util.QueryLogHook;
import org.apache.druid.sql.calcite.util.SpecificSegmentsQuerySegmentWalker;
import org.apache.druid.timeline.DataSegment;
import org.apache.druid.timeline.partition.LinearShardSpec;
import org.junit.*;
import org.junit.rules.TemporaryFolder;
import java.io.File;
import java.io.IOException;
import java.util.Arrays;
import java.util.List;
import java.util.Map;
import java.util.*;
public class HllApproxCountDistinctSqlAggregatorTest extends CalciteTestBase {
private static final String DATA_SOURCE = "foo";
// 新版本父类直接变了,实现更简单了
public class HllApproxCountDistinctSqlAggregatorTest extends BaseCalciteQueryTest {
private static final boolean ROUND = true;
private static final Map<String, Object> QUERY_CONTEXT_DEFAULT = ImmutableMap.of(
PlannerContext.CTX_SQL_QUERY_ID, "dummy"
);
private static QueryRunnerFactoryConglomerate conglomerate;
private static Closer resourceCloser;
private static AuthenticationResult authenticationResult = CalciteTests.REGULAR_USER_AUTH_RESULT;
@Rule
public TemporaryFolder temporaryFolder = new TemporaryFolder();
@Rule
public QueryLogHook queryLogHook = QueryLogHook.create(TestHelper.JSON_MAPPER);
private SpecificSegmentsQuerySegmentWalker walker;
private SqlLifecycleFactory sqlLifecycleFactory;
@BeforeClass
public static void setUpClass() {
resourceCloser = Closer.create();
conglomerate = QueryStackTests.createQueryRunnerFactoryConglomerate(resourceCloser);
@Override
public void gatherProperties(Properties properties)
{
super.gatherProperties(properties);
}
@AfterClass
public static void tearDownClass() throws IOException {
resourceCloser.close();
@Override
public void configureGuice(DruidInjectorBuilder builder)
{
super.configureGuice(builder);
builder.addModule(new HllModule());
}
@Before
public void setUp() throws Exception {
@SuppressWarnings("resource")
@Override
public SpecificSegmentsQuerySegmentWalker createQuerySegmentWalker(
final QueryRunnerFactoryConglomerate conglomerate,
final JoinableFactoryWrapper joinableFactory,
final Injector injector
) throws IOException
{
HllModule.registerSerde();
for (Module mod : new HllModule().getJacksonModules()) {
CalciteTests.getJsonMapper().registerModule(mod);
TestHelper.JSON_MAPPER.registerModule(mod);
}
final QueryableIndex index = IndexBuilder.create()
final QueryableIndex index = TestHelper.getTestIndexIO().loadIndex(new File("D:/doc/datas/testIndex-1369101812"));
//final QueryableIndex index = TestHelper.getTestIndexIO().loadIndex(new File("D:/doc/datas/9_index"));
/*final QueryableIndex index = IndexBuilder.create()
.tmpDir(temporaryFolder.newFolder())
.segmentWriteOutMediumFactory(OffHeapMemorySegmentWriteOutMediumFactory.instance())
.schema(
@@ -95,12 +76,12 @@ public class HllApproxCountDistinctSqlAggregatorTest extends CalciteTestBase {
.withRollup(false)
.build()
)
.rows(CalciteTests.ROWS1)
.buildMMappedIndex();
.rows(TestDataBuilder.ROWS1)
.buildMMappedIndex();*/
walker = new SpecificSegmentsQuerySegmentWalker(conglomerate).add(
return new SpecificSegmentsQuerySegmentWalker(conglomerate).add(
DataSegment.builder()
.dataSource(DATA_SOURCE)
.dataSource(CalciteTests.DATASOURCE1)
.interval(index.getDataInterval())
.version("1")
.shardSpec(new LinearShardSpec(0))
@@ -108,45 +89,80 @@ public class HllApproxCountDistinctSqlAggregatorTest extends CalciteTestBase {
.build(),
index
);
final PlannerConfig plannerConfig = new PlannerConfig();
final DruidOperatorTable operatorTable = new DruidOperatorTable(
ImmutableSet.of(
new HllApproxCountDistinctSqlAggregator(),
new HllObjectSqlAggregator()
),
ImmutableSet.of(
new HllEstimateOperatorConversion()
)
);
SchemaPlus rootSchema = CalciteTests.createMockRootSchema(conglomerate, walker, plannerConfig, AuthTestUtils.TEST_AUTHORIZER_MAPPER);
sqlLifecycleFactory = CalciteTests.createSqlLifecycleFactory(
new PlannerFactory(
rootSchema,
CalciteTests.createMockQueryLifecycleFactory(walker, conglomerate),
operatorTable,
CalciteTests.createExprMacroTable(),
plannerConfig,
AuthTestUtils.TEST_AUTHORIZER_MAPPER,
CalciteTests.getJsonMapper(),
CalciteTests.DRUID_SCHEMA_NAME
)
);
}
@After
public void tearDown() throws Exception {
walker.close();
walker = null;
}
@Test
public void testSqlQuery() throws Exception {
SqlLifecycle sqlLifecycle = sqlLifecycleFactory.factorize();
String sql = "select * from druid.foo";
final List<Object[]> results =
sqlLifecycle.runSimple(sql, QUERY_CONTEXT_DEFAULT, DEFAULT_PARAMETERS, authenticationResult).toList();
// Can't vectorize due to SUBSTRING expression.
cannotVectorize();
String[] columns = new String[]{"__time", "dim1", "dim2", "dim3", "cnt", "hll_dim1", "m1"};
String sql = "select " + String.join(",", columns) + " from druid.foo";
QueryTestBuilder builder = testBuilder().sql(sql);
builder.run();
QueryTestRunner.QueryResults queryResults = builder.results();
List<Object[]> results = queryResults.results;
for (Object[] result : results) {
Map row = new LinkedHashMap();
for (int i = 0; i < result.length; i++) {
row.put(columns[i], result[i]);
}
System.out.println(JSON.toJSONString(row));
// System.out.println(Arrays.toString(result));
}
for (int i = 0; i < columns.length; i++) {
Object[] values = new Object[results.size()];
for (int j = 0; j < results.size(); j++) {
values[j] = results.get(j)[i];
}
System.out.println(columns[i] + ":" + Arrays.toString(values));
}
}
@Test
public void testSqlQuery11() throws Exception {
// Can't vectorize due to SUBSTRING expression.
//cannotVectorize();
String sql = "select HLLD(hll_dim1) hll_dim1 from (select hll_dim1 from druid.foo limit 5) t ";
//sql = "select HLLD(hll_dim1) hll_dim1 from druid.foo t ";
QueryTestBuilder builder = testBuilder().sql(sql).skipVectorize();;
builder.run();
QueryTestRunner.QueryResults queryResults = builder.results();
List<Object[]> results = queryResults.results;
for (Object[] result : results) {
System.out.println(Arrays.toString(result));
}
}
@Test
public void testSqlQuery12() throws Exception {
// Can't vectorize due to SUBSTRING expression.
cannotVectorize();
String sql = "select * from (select * from druid.foo limit 6) t where __time >= '1970-12-15 07:00:28' and __time < '2023-12-15 08:10:28' ";
QueryTestBuilder builder = testBuilder().sql(sql);
builder.run();
QueryTestRunner.QueryResults queryResults = builder.results();
List<Object[]> results = queryResults.results;
for (Object[] result : results) {
System.out.println(Arrays.toString(result));
}
}
@Test
public void testSqlQuery1() throws Exception {
// Can't vectorize due to SUBSTRING expression.
cannotVectorize();
String sql = "select dim1 from druid.foo";
QueryTestBuilder builder = testBuilder().sql(sql);
builder.run();
QueryTestRunner.QueryResults queryResults = builder.results();
List<Object[]> results = queryResults.results;
for (Object[] result : results) {
System.out.println(Arrays.toString(result));
}
@@ -154,10 +170,100 @@ public class HllApproxCountDistinctSqlAggregatorTest extends CalciteTestBase {
@Test
public void testSqlQuery2() throws Exception {
SqlLifecycle sqlLifecycle = sqlLifecycleFactory.factorize();
String sql = "select HLLD_ESTIMATE(HLLD(hll_dim1)) from druid.foo where dim1 = ''";
final List<Object[]> results =
sqlLifecycle.runSimple(sql, QUERY_CONTEXT_DEFAULT, DEFAULT_PARAMETERS, authenticationResult).toList();
//cannotVectorize();
//String sql = "select HLLD_ESTIMATE(HLLD(hll_dim1)) from druid.foo where dim1 = '1'";
// Caused by: org.apache.calcite.sql.validate.SqlValidatorException: Aggregate expressions cannot be nested
//String sql = "select HLLD_ESTIMATE(HLLD(hll_dim1)), APPROX_COUNT_DISTINCT_HLLD(HLLD(hll_dim1)), HLLD(hll_dim1) from druid.foo";
String sql = "select HLLD_ESTIMATE(HLLD(hll_dim1)), APPROX_COUNT_DISTINCT_HLLD(hll_dim1), HLLD(hll_dim1) from (select HLLD(hll_dim1) hll_dim1 from druid.foo) t";
QueryTestBuilder builder = testBuilder().sql(sql).skipVectorize();
builder.run();
QueryTestRunner.QueryResults queryResults = builder.results();
List<Object[]> results = queryResults.results;
for (Object[] result : results) {
System.out.println(Arrays.toString(result));
}
}
@Test
public void testSqlQuery3() throws Exception {
//cannotVectorize();
//String sql = "select HLLD_ESTIMATE(HLLD(hll_dim1)) from druid.foo where dim1 = ''";
String sql = "select APPROX_COUNT_DISTINCT_HLLD(hll, 12) from (select HLLD(hll_dim1) hll from druid.foo where dim1 = '1') t ";
QueryTestBuilder builder = testBuilder().sql(sql).skipVectorize();
builder.run();
QueryTestRunner.QueryResults queryResults = builder.results();
List<Object[]> results = queryResults.results;
for (Object[] result : results) {
System.out.println(Arrays.toString(result));
}
}
@Test
public void testSqlQuery4() throws Exception {
//cannotVectorize();
//String sql = "select HLLD_ESTIMATE(HLLD(hll_dim1)) from druid.foo where dim1 = ''";
String sql = "select APPROX_COUNT_DISTINCT_HLLD(hll, 12) from (select HLLD(hll_dim1) hll from druid.foo where dim1 = '1') t ";
QueryTestBuilder builder = testBuilder().sql(sql).skipVectorize();
builder.run();
QueryTestRunner.QueryResults queryResults = builder.results();
List<Object[]> results = queryResults.results;
for (Object[] result : results) {
System.out.println(Arrays.toString(result));
}
}
@Test
public void testSqlQuery5() throws Exception {
//cannotVectorize();
//String sql = "select HLLD_ESTIMATE(HLLD(hll_dim1)) from druid.foo where dim1 = ''";
String sql = "select dim1,APPROX_COUNT_DISTINCT_HLLD(hll, 12) from (select dim1,HLLD(hll_dim1) hll from druid.foo where dim1 = '1' group by dim1) t group by dim1";
QueryTestBuilder builder = testBuilder().sql(sql).skipVectorize();
builder.run();
QueryTestRunner.QueryResults queryResults = builder.results();
List<Object[]> results = queryResults.results;
for (Object[] result : results) {
System.out.println(Arrays.toString(result));
}
}
@Test
public void testSqlQuery6() throws Exception {
//cannotVectorize();
//String sql = "select HLLD_ESTIMATE(HLLD(hll_dim1)) from druid.foo where dim1 = ''";
String sql = "select dim1,APPROX_COUNT_DISTINCT_HLLD(hll, 12) from (select dim1,HLLD(dim1) hll from druid.foo where dim1 = '1' group by dim1 limit 10) t group by dim1";
//String sql = "select dim1,HLLD_ESTIMATE(HLLD(hll), false) from (select dim1,HLLD(dim1) hll from druid.foo where dim1 = '1' group by dim1 limit 10) t group by dim1";
QueryTestBuilder builder = testBuilder().sql(sql).skipVectorize();
builder.run();
QueryTestRunner.QueryResults queryResults = builder.results();
List<Object[]> results = queryResults.results;
for (Object[] result : results) {
System.out.println(Arrays.toString(result));
}
}
@Test
public void testSqlQuery62() throws Exception {
//cannotVectorize();
//String sql = "select HLLD_ESTIMATE(HLLD(hll_dim1)) from druid.foo where dim1 = ''";
String sql = "select dim1,APPROX_COUNT_DISTINCT_HLLD(hll) from (select dim1,HLLD(dim1) hll from druid.foo where dim1 = '1' group by dim1 limit 10) t group by dim1";
QueryTestBuilder builder = testBuilder().sql(sql).skipVectorize();
builder.run();
QueryTestRunner.QueryResults queryResults = builder.results();
List<Object[]> results = queryResults.results;
for (Object[] result : results) {
System.out.println(Arrays.toString(result));
}
}
@Test
public void testSqlQuery7() throws Exception {
//cannotVectorize();
//String sql = "select HLLD_ESTIMATE(HLLD(hll_dim1)) from druid.foo where dim1 = ''";
String sql = "select dim1,APPROX_COUNT_DISTINCT_HLLD(hll, 12) from (select dim1,HLLD(dim1) hll from druid.foo where dim1 = '1' group by dim1) t group by dim1 limit 10";
QueryTestBuilder builder = testBuilder().sql(sql).skipVectorize();
builder.run();
QueryTestRunner.QueryResults queryResults = builder.results();
List<Object[]> results = queryResults.results;
for (Object[] result : results) {
System.out.println(Arrays.toString(result));
}
@@ -165,26 +271,23 @@ public class HllApproxCountDistinctSqlAggregatorTest extends CalciteTestBase {
@Test
public void testAgg() throws Exception {
SqlLifecycle sqlLifecycle = sqlLifecycleFactory.factorize();
final String sql = "SELECT\n"
+ " SUM(cnt),\n"
+ " APPROX_COUNT_DISTINCT_HLLD(hll_dim1)\n"
+ "FROM druid.foo";
final List<Object[]> results =
sqlLifecycle.runSimple(sql, QUERY_CONTEXT_DEFAULT, DEFAULT_PARAMETERS, authenticationResult).toList();
QueryTestBuilder builder = testBuilder().sql(sql).skipVectorize();
builder.run();
QueryTestRunner.QueryResults queryResults = builder.results();
List<Object[]> results = queryResults.results;
for (Object[] result : results) {
System.out.println(Arrays.toString(result));
}
}
@Test
public void testDistinct() throws Exception {
SqlLifecycle sqlLifecycle = sqlLifecycleFactory.factorize();
final String sql = "SELECT\n"
+ " SUM(cnt),\n"
+ " APPROX_COUNT_DISTINCT_HLLD(dim2),\n" // uppercase
@@ -195,18 +298,17 @@ public class HllApproxCountDistinctSqlAggregatorTest extends CalciteTestBase {
+ " APPROX_COUNT_DISTINCT_HLLD(hll_dim1)\n" // on native HllSketch column
+ "FROM druid.foo";
final List<Object[]> results =
sqlLifecycle.runSimple(sql, QUERY_CONTEXT_DEFAULT, DEFAULT_PARAMETERS, authenticationResult).toList();
QueryTestBuilder builder = testBuilder().sql(sql).skipVectorize();
builder.run();
QueryTestRunner.QueryResults queryResults = builder.results();
List<Object[]> results = queryResults.results;
for (Object[] result : results) {
System.out.println(Arrays.toString(result));
}
}
@Test
public void testDistinct2() throws Exception {
SqlLifecycle sqlLifecycle = sqlLifecycleFactory.factorize();
final String sql = "SELECT\n"
+ " SUM(cnt),\n"
+ " APPROX_COUNT_DISTINCT_HLLD(dim2),\n"
@@ -219,8 +321,26 @@ public class HllApproxCountDistinctSqlAggregatorTest extends CalciteTestBase {
+ " APPROX_COUNT_DISTINCT_HLLD(hll_dim1)\n" // on native HllSketch column
+ "FROM druid.foo";
final List<Object[]> results =
sqlLifecycle.runSimple(sql, QUERY_CONTEXT_DEFAULT, DEFAULT_PARAMETERS, authenticationResult).toList();
QueryTestBuilder builder = testBuilder().sql(sql).skipVectorize();
builder.run();
QueryTestRunner.QueryResults queryResults = builder.results();
List<Object[]> results = queryResults.results;
for (Object[] result : results) {
System.out.println(Arrays.toString(result));
}
}
@Test
public void testDistinctDebug2() throws Exception {
final String sql = "SELECT\n"
+ " dim1, dim2\n"
+ "FROM druid.foo";
QueryTestBuilder builder = testBuilder().sql(sql).skipVectorize();
builder.run();
QueryTestRunner.QueryResults queryResults = builder.results();
List<Object[]> results = queryResults.results;
for (Object[] result : results) {
System.out.println(Arrays.toString(result));
}
@@ -229,15 +349,15 @@ public class HllApproxCountDistinctSqlAggregatorTest extends CalciteTestBase {
@Test
public void testDistinctDebug() throws Exception {
SqlLifecycle sqlLifecycle = sqlLifecycleFactory.factorize();
final String sql = "SELECT\n"
+ " SUM(cnt),\n"
+ " APPROX_COUNT_DISTINCT_HLLD(dim2)\n"
+ "FROM druid.foo";
final List<Object[]> results =
sqlLifecycle.runSimple(sql, QUERY_CONTEXT_DEFAULT, DEFAULT_PARAMETERS, authenticationResult).toList();
QueryTestBuilder builder = testBuilder().sql(sql).skipVectorize();
builder.run();
QueryTestRunner.QueryResults queryResults = builder.results();
List<Object[]> results = queryResults.results;
for (Object[] result : results) {
System.out.println(Arrays.toString(result));
}
@@ -246,14 +366,14 @@ public class HllApproxCountDistinctSqlAggregatorTest extends CalciteTestBase {
@Test
public void testDeser() throws Exception {
SqlLifecycle sqlLifecycle = sqlLifecycleFactory.factorize();
final String sql = "SELECT\n"
+ " APPROX_COUNT_DISTINCT_HLLD(hll_dim1) cnt\n"
+ "FROM druid.foo";
final List<Object[]> results =
sqlLifecycle.runSimple(sql, QUERY_CONTEXT_DEFAULT, DEFAULT_PARAMETERS, authenticationResult).toList();
QueryTestBuilder builder = testBuilder().sql(sql).skipVectorize();
builder.run();
QueryTestRunner.QueryResults queryResults = builder.results();
List<Object[]> results = queryResults.results;
for (Object[] result : results) {
System.out.println(Arrays.toString(result));
}
@@ -263,30 +383,29 @@ public class HllApproxCountDistinctSqlAggregatorTest extends CalciteTestBase {
@Test
public void testGroupBy() throws Exception {
SqlLifecycle sqlLifecycle = sqlLifecycleFactory.factorize();
final String sql = "SELECT cnt,\n"
+ " APPROX_COUNT_DISTINCT_HLLD(hll_dim1, 14) cnt2\n"
+ "FROM druid.foo group by cnt";
final List<Object[]> results =
sqlLifecycle.runSimple(sql, QUERY_CONTEXT_DEFAULT, DEFAULT_PARAMETERS, authenticationResult).toList();
QueryTestBuilder builder = testBuilder().sql(sql).skipVectorize();
builder.run();
QueryTestRunner.QueryResults queryResults = builder.results();
List<Object[]> results = queryResults.results;
for (Object[] result : results) {
System.out.println(Arrays.toString(result));
}
}
@Test
public void testGroupBy1() throws Exception {
SqlLifecycle sqlLifecycle = sqlLifecycleFactory.factorize();
final String sql = "SELECT __time,\n"
+ " APPROX_COUNT_DISTINCT_HLLD(hll_dim1, 14) cnt\n"
+ "FROM druid.foo group by __time";
final List<Object[]> results =
sqlLifecycle.runSimple(sql, QUERY_CONTEXT_DEFAULT, DEFAULT_PARAMETERS, authenticationResult).toList();
QueryTestBuilder builder = testBuilder().sql(sql).skipVectorize();
builder.run();
QueryTestRunner.QueryResults queryResults = builder.results();
List<Object[]> results = queryResults.results;
for (Object[] result : results) {
System.out.println(Arrays.toString(result));
}
@@ -295,14 +414,13 @@ public class HllApproxCountDistinctSqlAggregatorTest extends CalciteTestBase {
@Test
public void testGroupBy2() throws Exception {
SqlLifecycle sqlLifecycle = sqlLifecycleFactory.factorize();
final String sql = "SELECT __time,\n"
+ " APPROX_COUNT_DISTINCT_HLLD(hll_dim1, 14) cnt\n"
+ "FROM druid.foo group by __time order by cnt desc";
final List<Object[]> results =
sqlLifecycle.runSimple(sql, QUERY_CONTEXT_DEFAULT, DEFAULT_PARAMETERS, authenticationResult).toList();
QueryTestBuilder builder = testBuilder().sql(sql).skipVectorize();
builder.run();
QueryTestRunner.QueryResults queryResults = builder.results();
List<Object[]> results = queryResults.results;
for (Object[] result : results) {
System.out.println(Arrays.toString(result));
}

143
druid-udf/pom.xml Normal file
View File

@@ -0,0 +1,143 @@
<?xml version="1.0" encoding="UTF-8"?>
<project xmlns="http://maven.apache.org/POM/4.0.0"
xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
<modelVersion>4.0.0</modelVersion>
<groupId>org.example</groupId>
<artifactId>druid-udf_26.0.0</artifactId>
<name>druid-udf</name>
<version>1.0-SNAPSHOT</version>
<properties>
<maven.compiler.source>11</maven.compiler.source>
<maven.compiler.target>11</maven.compiler.target>
<project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
<druid.version>26.0.0</druid.version>
</properties>
<dependencies>
<dependency>
<groupId>org.apache.druid</groupId>
<artifactId>druid-server</artifactId>
<version>${druid.version}</version>
<scope>provided</scope>
</dependency>
<dependency>
<groupId>org.apache.druid</groupId>
<artifactId>druid-sql</artifactId>
<version>${druid.version}</version>
<scope>provided</scope>
</dependency>
<!-- Tests -->
<dependency>
<groupId>org.easymock</groupId>
<artifactId>easymock</artifactId>
<version>4.3</version>
<scope>test</scope>
</dependency>
<dependency>
<groupId>org.apache.druid</groupId>
<artifactId>druid-processing</artifactId>
<version>${druid.version}</version>
<type>test-jar</type>
<scope>test</scope>
</dependency>
<dependency>
<groupId>org.apache.druid</groupId>
<artifactId>druid-server</artifactId>
<version>${druid.version}</version>
<scope>test</scope>
<type>test-jar</type>
</dependency>
<dependency>
<groupId>org.apache.druid</groupId>
<artifactId>druid-sql</artifactId>
<version>${druid.version}</version>
<type>test-jar</type>
<scope>test</scope>
</dependency>
<dependency>
<groupId>junit</groupId>
<artifactId>junit</artifactId>
<version>4.12</version>
<scope>test</scope>
</dependency>
<dependency>
<groupId>com.alibaba.fastjson2</groupId>
<artifactId>fastjson2</artifactId>
<version>2.0.34</version>
<scope>test</scope>
</dependency>
</dependencies>
<build>
<plugins>
<plugin>
<groupId>org.apache.maven.plugins</groupId>
<artifactId>maven-compiler-plugin</artifactId>
<version>3.1</version>
<configuration>
<compilerArgument>-Xlint:unchecked</compilerArgument>
<source>11</source>
<target>11</target>
</configuration>
</plugin>
<plugin>
<groupId>org.apache.maven.plugins</groupId>
<artifactId>maven-surefire-plugin</artifactId>
<version>2.19.1</version>
<configuration>
<argLine>-Duser.timezone=UTC</argLine>
<redirectTestOutputToFile>true</redirectTestOutputToFile>
</configuration>
</plugin>
<plugin>
<groupId>org.apache.maven.plugins</groupId>
<artifactId>maven-assembly-plugin</artifactId>
<version>2.5.5</version>
<executions>
<execution>
<id>distro-assembly</id>
<phase>package</phase>
<goals>
<goal>single</goal>
</goals>
<configuration>
<finalName>${project.artifactId}-${project.version}</finalName>
<tarLongFileMode>posix</tarLongFileMode>
<descriptors>
<descriptor>src/assembly/assembly.xml</descriptor>
</descriptors>
</configuration>
</execution>
</executions>
</plugin>
<plugin>
<artifactId>maven-release-plugin</artifactId>
<version>2.5.3</version>
<dependencies>
<dependency>
<groupId>org.apache.maven.scm</groupId>
<artifactId>maven-scm-provider-gitexe</artifactId>
<version>1.9.4</version>
</dependency>
</dependencies>
</plugin>
<plugin>
<groupId>org.apache.maven.plugins</groupId>
<artifactId>maven-jar-plugin</artifactId>
<version>3.0.2</version>
<configuration>
<archive>
<addMavenDescriptor>false</addMavenDescriptor>
</archive>
</configuration>
</plugin>
</plugins>
</build>
</project>

View File

@@ -0,0 +1,54 @@
<?xml version="1.0"?>
<!--
~ Copyright 2016 Imply Data, Inc.
~
~ Licensed under the Apache License, Version 2.0 (the "License");
~ you may not use this file except in compliance with the License.
~ You may obtain a copy of the License at
~
~ http://www.apache.org/licenses/LICENSE-2.0
~
~ Unless required by applicable law or agreed to in writing, software
~ distributed under the License is distributed on an "AS IS" BASIS,
~ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
~ See the License for the specific language governing permissions and
~ limitations under the License.
-->
<assembly xmlns="http://maven.apache.org/plugins/maven-assembly-plugin/assembly/1.1.3"
xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
xsi:schemaLocation="http://maven.apache.org/plugins/maven-assembly-plugin/assembly/1.1.3 http://maven.apache.org/xsd/assembly-1.1.3.xsd">
<id>bin</id>
<formats>
<format>tar.gz</format>
</formats>
<baseDirectory>${project.name}</baseDirectory>
<dependencySets>
<dependencySet>
<useProjectArtifact>false</useProjectArtifact>
<useTransitiveDependencies>true</useTransitiveDependencies>
<outputDirectory>.</outputDirectory>
<unpack>false</unpack>
</dependencySet>
</dependencySets>
<fileSets>
<fileSet>
<directory>.</directory>
<outputDirectory/>
<includes>
<include>README.md</include>
<include>LICENSE</include>
</includes>
</fileSet>
<fileSet>
<directory>${project.build.directory}</directory>
<outputDirectory>.</outputDirectory>
<includes>
<include>*.jar</include>
</includes>
</fileSet>
</fileSets>
</assembly>

View File

@@ -0,0 +1,27 @@
package org.apache.druid.query.udf;
import com.google.inject.Binder;
import org.apache.druid.guice.ExpressionModule;
import org.apache.druid.initialization.DruidModule;
import org.apache.druid.query.udf.expressions.CurrentTimestampMillisExprMacro;
import org.apache.druid.query.udf.expressions.DimensionBucketExprMacro;
import org.apache.druid.query.udf.sql.CurrentTimestampMillisOperatorConversion;
import org.apache.druid.query.udf.sql.DimensionBucketOperatorConversion;
import org.apache.druid.sql.guice.SqlBindings;
public class UdfModule implements DruidModule {
@Override
public void configure(Binder binder) {
SqlBindings.addOperatorConversion(binder, DimensionBucketOperatorConversion.class);
SqlBindings.addOperatorConversion(binder, CurrentTimestampMillisOperatorConversion.class);
ExpressionModule.addExprMacro(binder, DimensionBucketExprMacro.class);
ExpressionModule.addExprMacro(binder, CurrentTimestampMillisExprMacro.class);
}
/*@Override
public List<? extends Module> getJacksonModules() {
// Register Jackson module for any classes we need to be able to use in JSON queries or ingestion specs.
return Collections.<Module>singletonList(new SimpleModule("UdfModule"));
}*/
}

View File

@@ -0,0 +1,57 @@
package org.apache.druid.query.udf.expressions;
import org.apache.druid.math.expr.*;
import javax.annotation.Nullable;
import java.util.List;
public class CurrentTimestampMillisExprMacro implements ExprMacroTable.ExprMacro {
private static final String NAME = "current_timestamp_millis"; // current_timestamp_millis
@Override
public String name() {
return NAME;
}
@Override
public Expr apply(List<Expr> args) {
validationHelperCheckArgumentCount(args, 0);
class CurrentTimestampMillisExpr implements Expr {
@Override
public ExprEval eval(ObjectBinding bindings) {
return ExprEval.of(System.currentTimeMillis());
}
@Override
public String stringify() {
return "current_timestamp_millis";
}
@Override
public Expr visit(Shuttle shuttle) {
return shuttle.visit(this);
}
@Override
public BindingAnalysis analyzeInputs() {
return BindingAnalysis.EMTPY;
}
@Nullable
@Override
public ExpressionType getOutputType(InputBindingInspector inspector) {
return ExpressionType.LONG;
}
@Override
public boolean canVectorize(InputBindingInspector inspector) {
return false;
}
}
return new CurrentTimestampMillisExpr();
}
}

View File

@@ -0,0 +1,82 @@
package org.apache.druid.query.udf.expressions;
import org.apache.druid.math.expr.*;
import org.apache.druid.math.expr.ExprMacroTable.ExprMacro;
import javax.annotation.Nullable;
import java.util.List;
import java.util.stream.Collectors;
public class DimensionBucketExprMacro implements ExprMacro {
private static final String NAME = "dimension_bucket";
@Override
public String name() {
return NAME;
}
@Override
public Expr apply(List<Expr> args) {
validationHelperCheckMinArgumentCount(args, 2);
Expr bucketCnt = args.get(0);
if(!bucketCnt.isLiteral()|| bucketCnt.eval(InputBindings.nilBindings()).asInt() <= 0) {
throw validationFailed("first bucketCount argument must is int literal and > 0");
}
return new DimensionBucketExpr(args);
}
static class DimensionBucketExpr extends ExprMacroTable.BaseScalarMacroFunctionExpr {
private final int bucketCount;
public DimensionBucketExpr(List<Expr> args) {
super(NAME, args);
bucketCount = args.get(0).eval(InputBindings.nilBindings()).asInt();
}
@Override
public ExprEval eval(ObjectBinding bindings) {
int result = 1;
for (int i = 1; i < args.size(); i++) {
ExprEval eval = args.get(i).eval(bindings);
Object element = eval.value();
if(element instanceof Object[]){
for (Object ele : (Object[]) element) {
result = 31 * result + (ele == null ? 0 : ele.hashCode());
}
}else{
result = 31 * result + (element == null ? 0 : element.hashCode());
}
/*else if (element instanceof Number) {
//result = 31 * result + Integer.hashCode(((Number)element).intValue());
result = 31 * result + Long.hashCode(((Number)element).longValue());
}*/
}
int bucket = Math.abs(result) % bucketCount;
return ExprEval.of(IntToHexUtil.uInt16ToHexStringFast(bucket));
}
@Override
public Expr visit(Shuttle shuttle) {
List<Expr> newArgs = args.stream().map(x -> x.visit(shuttle)).collect(Collectors.toList());
return shuttle.visit(new DimensionBucketExpr(newArgs));
}
@Override
public BindingAnalysis analyzeInputs() {
return super.analyzeInputs();
}
@Nullable
@Override
public ExpressionType getOutputType(InputBindingInspector inspector) {
return ExpressionType.STRING;
}
@Override
public boolean canVectorize(InputBindingInspector inspector) {
return false;
}
}
}

View File

@@ -0,0 +1,45 @@
package org.apache.druid.query.udf.expressions;
import java.nio.charset.StandardCharsets;
public class IntToHexUtil {
static final byte[] digits = {
'0' , '1' , '2' , '3' , '4' , '5' ,
'6' , '7' , '8' , '9' , 'a' , 'b' ,
'c' , 'd' , 'e' , 'f' , 'g' , 'h' ,
'i' , 'j' , 'k' , 'l' , 'm' , 'n' ,
'o' , 'p' , 'q' , 'r' , 's' , 't' ,
'u' , 'v' , 'w' , 'x' , 'y' , 'z'
};
static final String[] uInt16HexsCache;
static final int uInt16HexsCacheSize = 8192;
static{
uInt16HexsCache = new String[uInt16HexsCacheSize];
for (int i = 0; i < uInt16HexsCacheSize; i++) {
uInt16HexsCache[i] = uInt16ToHexString(i);
}
}
public static String uInt16ToHexStringFast(int i){
if(i < uInt16HexsCacheSize){
return uInt16HexsCache[i];
}else{
return uInt16ToHexString(i);
}
}
private static String uInt16ToHexString(int i){
byte[] bytes = new byte[4];
int mask = 15; // 16 - 1
int value = i;
bytes[3] = digits[value & mask];
value >>>= 4;
bytes[2] = digits[value & mask];
value >>>= 4;
bytes[1] = digits[value & mask];
value >>>= 4;
bytes[0] = digits[value & mask];
return new String(bytes, StandardCharsets.US_ASCII);
}
}

View File

@@ -0,0 +1,35 @@
package org.apache.druid.query.udf.sql;
import org.apache.calcite.rex.RexNode;
import org.apache.calcite.sql.SqlFunction;
import org.apache.calcite.sql.SqlFunctionCategory;
import org.apache.calcite.sql.SqlOperator;
import org.apache.calcite.sql.type.*;
import org.apache.druid.segment.column.RowSignature;
import org.apache.druid.sql.calcite.expression.DruidExpression;
import org.apache.druid.sql.calcite.expression.OperatorConversions;
import org.apache.druid.sql.calcite.expression.SqlOperatorConversion;
import org.apache.druid.sql.calcite.planner.PlannerContext;
import javax.annotation.Nullable;
public class CurrentTimestampMillisOperatorConversion implements SqlOperatorConversion {
private static final SqlFunction SQL_FUNCTION = OperatorConversions
.operatorBuilder("CURRENT_TIMESTAMP_MILLIS")
.operandTypes(SqlTypeFamily.ANY)
.requiredOperands(0)
.returnTypeNonNull(SqlTypeName.BIGINT)
.functionCategory(SqlFunctionCategory.USER_DEFINED_FUNCTION)
.build();
@Override
public SqlOperator calciteOperator() {
return SQL_FUNCTION;
}
@Nullable
@Override
public DruidExpression toDruidExpression(PlannerContext plannerContext, RowSignature rowSignature, RexNode rexNode) {
return OperatorConversions.convertDirectCall(plannerContext, rowSignature, rexNode, "current_timestamp_millis");
}
}

View File

@@ -0,0 +1,43 @@
package org.apache.druid.query.udf.sql;
import org.apache.calcite.rex.RexNode;
import org.apache.calcite.sql.SqlFunction;
import org.apache.calcite.sql.SqlFunctionCategory;
import org.apache.calcite.sql.SqlKind;
import org.apache.calcite.sql.SqlOperator;
import org.apache.calcite.sql.type.OperandTypes;
import org.apache.calcite.sql.type.ReturnTypes;
import org.apache.calcite.sql.type.SqlOperandCountRanges;
import org.apache.calcite.sql.type.SqlTypeName;
import org.apache.druid.segment.column.RowSignature;
import org.apache.druid.sql.calcite.expression.DruidExpression;
import org.apache.druid.sql.calcite.expression.OperatorConversions;
import org.apache.druid.sql.calcite.expression.SqlOperatorConversion;
import org.apache.druid.sql.calcite.planner.Calcites;
import org.apache.druid.sql.calcite.planner.PlannerContext;
import javax.annotation.Nullable;
public class DimensionBucketOperatorConversion implements SqlOperatorConversion {
private static final SqlFunction SQL_FUNCTION = new SqlFunction(
"DIMENSION_BUCKET",
SqlKind.OTHER_FUNCTION,
ReturnTypes.explicit(
factory -> Calcites.createSqlTypeWithNullability(factory, SqlTypeName.VARCHAR, true)
),
null,
OperandTypes.variadic(SqlOperandCountRanges.from(2)),
SqlFunctionCategory.USER_DEFINED_FUNCTION
);
@Override
public SqlOperator calciteOperator() {
return SQL_FUNCTION;
}
@Nullable
@Override
public DruidExpression toDruidExpression(PlannerContext plannerContext, RowSignature rowSignature, RexNode rexNode) {
return OperatorConversions.convertDirectCall(plannerContext, rowSignature, rexNode, "dimension_bucket");
}
}

View File

@@ -0,0 +1 @@
org.apache.druid.query.udf.UdfModule

View File

@@ -0,0 +1,148 @@
package org.apache.druid.query.udf.expressions;
import com.google.common.collect.ImmutableMap;
import org.apache.druid.math.expr.*;
import org.apache.druid.testing.InitializedNullHandlingTest;
import org.junit.Test;
import java.util.Collections;
public class CurrentTimestampMillisExprTest extends InitializedNullHandlingTest {
private final ExprMacroTable exprMacroTable = new ExprMacroTable(Collections.singletonList(new CurrentTimestampMillisExprMacro()));
Expr.ObjectBinding inputBindings = InputBindings.forInputSuppliers(
new ImmutableMap.Builder<String, InputBindings.InputSupplier>()
.put("string", InputBindings.inputSupplier(ExpressionType.STRING, () -> "abcdef"))
.put("long", InputBindings.inputSupplier(ExpressionType.LONG, () -> 1234L))
.put("double", InputBindings.inputSupplier(ExpressionType.DOUBLE, () -> 1.234))
.put("array1", InputBindings.inputSupplier(ExpressionType.STRING_ARRAY, () -> new Object[]{"1", "2", "3"}))
.put("array2", InputBindings.inputSupplier(ExpressionType.STRING_ARRAY, () -> new String[]{"1", "2", "3"}))
.put("nullString", InputBindings.inputSupplier(ExpressionType.STRING, () -> null))
.put("nullLong", InputBindings.inputSupplier(ExpressionType.LONG, () -> null))
.put("nullDouble", InputBindings.inputSupplier(ExpressionType.DOUBLE, () -> null))
.build()
);
Expr.ObjectBinding[] inputBindingArray = new Expr.ObjectBinding[]{
InputBindings.forInputSuppliers(
new ImmutableMap.Builder<String, InputBindings.InputSupplier>()
.put("device_id", InputBindings.inputSupplier(ExpressionType.STRING, () -> "1"))
.put("rule_id", InputBindings.inputSupplier(ExpressionType.LONG, () -> 81))
.put("template_id", InputBindings.inputSupplier(ExpressionType.LONG, () -> 81))
.put("chart_id", InputBindings.inputSupplier(ExpressionType.LONG, () -> 81))
.put("version", InputBindings.inputSupplier(ExpressionType.LONG, () -> 1))
.put("client_ip_object", InputBindings.inputSupplier(ExpressionType.STRING_ARRAY, () -> null))
.put("server_ip_object", InputBindings.inputSupplier(ExpressionType.STRING_ARRAY, () -> null))
.put("fqdn_category", InputBindings.inputSupplier(ExpressionType.STRING_ARRAY, () -> null))
.put("client_ip", InputBindings.inputSupplier(ExpressionType.STRING, () -> null))
.put("server_ip", InputBindings.inputSupplier(ExpressionType.STRING, () -> null))
.put("server_fqdn", InputBindings.inputSupplier(ExpressionType.STRING, () -> null))
.put("server_domain", InputBindings.inputSupplier(ExpressionType.STRING, () -> null))
.put("application", InputBindings.inputSupplier(ExpressionType.STRING, () -> null))
.build()
),
InputBindings.forInputSuppliers(
new ImmutableMap.Builder<String, InputBindings.InputSupplier>()
.put("device_id", InputBindings.inputSupplier(ExpressionType.STRING, () -> "1"))
.put("rule_id", InputBindings.inputSupplier(ExpressionType.LONG, () -> 101))
.put("template_id", InputBindings.inputSupplier(ExpressionType.LONG, () -> 101))
.put("chart_id", InputBindings.inputSupplier(ExpressionType.LONG, () -> 101))
.put("version", InputBindings.inputSupplier(ExpressionType.LONG, () -> 1))
.put("client_ip_object", InputBindings.inputSupplier(ExpressionType.STRING_ARRAY, () -> new Object[]{"5","7","8"}))
.put("server_ip_object", InputBindings.inputSupplier(ExpressionType.STRING_ARRAY, () -> null))
.put("fqdn_category", InputBindings.inputSupplier(ExpressionType.STRING_ARRAY, () -> null))
.put("client_ip", InputBindings.inputSupplier(ExpressionType.STRING, () -> null))
.put("server_ip", InputBindings.inputSupplier(ExpressionType.STRING, () -> null))
.put("server_fqdn", InputBindings.inputSupplier(ExpressionType.STRING, () -> null))
.put("server_domain", InputBindings.inputSupplier(ExpressionType.STRING, () -> null))
.put("application", InputBindings.inputSupplier(ExpressionType.STRING, () -> null))
.build()
),
InputBindings.forInputSuppliers(
new ImmutableMap.Builder<String, InputBindings.InputSupplier>()
.put("device_id", InputBindings.inputSupplier(ExpressionType.STRING, () -> "1"))
.put("rule_id", InputBindings.inputSupplier(ExpressionType.LONG, () -> 271L))
.put("template_id", InputBindings.inputSupplier(ExpressionType.LONG, () -> 271L))
.put("chart_id", InputBindings.inputSupplier(ExpressionType.LONG, () -> 271L))
.put("version", InputBindings.inputSupplier(ExpressionType.LONG, () -> 1L))
.put("client_ip_object", InputBindings.inputSupplier(ExpressionType.STRING_ARRAY, () -> null))
.put("server_ip_object", InputBindings.inputSupplier(ExpressionType.STRING_ARRAY, () -> null))
.put("fqdn_category", InputBindings.inputSupplier(ExpressionType.STRING_ARRAY, () -> null))
.put("client_ip", InputBindings.inputSupplier(ExpressionType.STRING, () -> null))
.put("server_ip", InputBindings.inputSupplier(ExpressionType.STRING, () -> "5.245.228.51"))
.put("server_fqdn", InputBindings.inputSupplier(ExpressionType.STRING, () -> null))
.put("server_domain", InputBindings.inputSupplier(ExpressionType.STRING, () -> null))
.put("application", InputBindings.inputSupplier(ExpressionType.STRING, () -> null))
.build()
),
// ...
InputBindings.forInputSuppliers(
new ImmutableMap.Builder<String, InputBindings.InputSupplier>()
.put("device_id", InputBindings.inputSupplier(ExpressionType.STRING, () -> "1"))
.put("rule_id", InputBindings.inputSupplier(ExpressionType.LONG, () -> 81))
.put("template_id", InputBindings.inputSupplier(ExpressionType.LONG, () -> 81))
.put("chart_id", InputBindings.inputSupplier(ExpressionType.LONG, () -> 81))
.put("version", InputBindings.inputSupplier(ExpressionType.LONG, () -> 1))
.put("client_ip_object", InputBindings.inputSupplier(ExpressionType.STRING, () -> null))
.put("server_ip_object", InputBindings.inputSupplier(ExpressionType.STRING, () -> null))
.put("fqdn_category", InputBindings.inputSupplier(ExpressionType.STRING, () -> null))
.put("client_ip", InputBindings.inputSupplier(ExpressionType.STRING, () -> null))
.put("server_ip", InputBindings.inputSupplier(ExpressionType.STRING, () -> null))
.put("server_fqdn", InputBindings.inputSupplier(ExpressionType.STRING, () -> null))
.put("server_domain", InputBindings.inputSupplier(ExpressionType.STRING, () -> null))
.put("application", InputBindings.inputSupplier(ExpressionType.STRING, () -> null))
.build()
),
InputBindings.forInputSuppliers(
new ImmutableMap.Builder<String, InputBindings.InputSupplier>()
.put("device_id", InputBindings.inputSupplier(ExpressionType.STRING, () -> "1"))
.put("rule_id", InputBindings.inputSupplier(ExpressionType.LONG, () -> 101))
.put("template_id", InputBindings.inputSupplier(ExpressionType.LONG, () -> 101))
.put("chart_id", InputBindings.inputSupplier(ExpressionType.LONG, () -> 101))
.put("version", InputBindings.inputSupplier(ExpressionType.LONG, () -> 1))
.put("client_ip_object", InputBindings.inputSupplier(ExpressionType.STRING, () -> "5,7,8"))
.put("server_ip_object", InputBindings.inputSupplier(ExpressionType.STRING, () -> null))
.put("fqdn_category", InputBindings.inputSupplier(ExpressionType.STRING, () -> null))
.put("client_ip", InputBindings.inputSupplier(ExpressionType.STRING, () -> null))
.put("server_ip", InputBindings.inputSupplier(ExpressionType.STRING, () -> null))
.put("server_fqdn", InputBindings.inputSupplier(ExpressionType.STRING, () -> null))
.put("server_domain", InputBindings.inputSupplier(ExpressionType.STRING, () -> null))
.put("application", InputBindings.inputSupplier(ExpressionType.STRING, () -> null))
.build()
),
InputBindings.forInputSuppliers(
new ImmutableMap.Builder<String, InputBindings.InputSupplier>()
.put("device_id", InputBindings.inputSupplier(ExpressionType.STRING, () -> "1"))
.put("rule_id", InputBindings.inputSupplier(ExpressionType.LONG, () -> 271L))
.put("template_id", InputBindings.inputSupplier(ExpressionType.LONG, () -> 271L))
.put("chart_id", InputBindings.inputSupplier(ExpressionType.LONG, () -> 271L))
.put("version", InputBindings.inputSupplier(ExpressionType.LONG, () -> 1L))
.put("client_ip_object", InputBindings.inputSupplier(ExpressionType.STRING, () -> null))
.put("server_ip_object", InputBindings.inputSupplier(ExpressionType.STRING, () -> null))
.put("fqdn_category", InputBindings.inputSupplier(ExpressionType.STRING, () -> null))
.put("client_ip", InputBindings.inputSupplier(ExpressionType.STRING, () -> null))
.put("server_ip", InputBindings.inputSupplier(ExpressionType.STRING, () -> "5.245.228.51"))
.put("server_fqdn", InputBindings.inputSupplier(ExpressionType.STRING, () -> null))
.put("server_domain", InputBindings.inputSupplier(ExpressionType.STRING, () -> null))
.put("application", InputBindings.inputSupplier(ExpressionType.STRING, () -> null))
.build()
),
};
@Test
public void test() throws Exception{
Expr expr = Parser.parse("current_timestamp_millis()", exprMacroTable);
System.out.println(expr.analyzeInputs().getRequiredBindings());
ExprEval eval = expr.eval(inputBindings);
System.out.println(eval.value());
Thread.sleep(1000);
eval = expr.eval(inputBindings);
System.out.println(eval.value());
Thread.sleep(1000);
expr = Parser.parse("current_timestamp_millis()", exprMacroTable);
eval = expr.eval(inputBindings);
System.out.println(eval.value());
}
}

View File

@@ -0,0 +1,146 @@
package org.apache.druid.query.udf.expressions;
import com.google.common.collect.ImmutableMap;
import org.apache.druid.math.expr.*;
import org.apache.druid.testing.InitializedNullHandlingTest;
import org.junit.Test;
import java.util.Collections;
public class DimensionBucketExprTest extends InitializedNullHandlingTest {
private final ExprMacroTable exprMacroTable = new ExprMacroTable(Collections.singletonList(new DimensionBucketExprMacro()));
Expr.ObjectBinding inputBindings = InputBindings.forInputSuppliers(
new ImmutableMap.Builder<String, InputBindings.InputSupplier>()
.put("string", InputBindings.inputSupplier(ExpressionType.STRING, () -> "abcdef"))
.put("long", InputBindings.inputSupplier(ExpressionType.LONG, () -> 1234L))
.put("double", InputBindings.inputSupplier(ExpressionType.DOUBLE, () -> 1.234))
.put("array1", InputBindings.inputSupplier(ExpressionType.STRING_ARRAY, () -> new Object[]{"1", "2", "3"}))
.put("array2", InputBindings.inputSupplier(ExpressionType.STRING_ARRAY, () -> new String[]{"1", "2", "3"}))
.put("nullString", InputBindings.inputSupplier(ExpressionType.STRING, () -> null))
.put("nullLong", InputBindings.inputSupplier(ExpressionType.LONG, () -> null))
.put("nullDouble", InputBindings.inputSupplier(ExpressionType.DOUBLE, () -> null))
.build()
);
Expr.ObjectBinding[] inputBindingArray = new Expr.ObjectBinding[]{
InputBindings.forInputSuppliers(
new ImmutableMap.Builder<String, InputBindings.InputSupplier>()
.put("device_id", InputBindings.inputSupplier(ExpressionType.STRING, () -> "1"))
.put("rule_id", InputBindings.inputSupplier(ExpressionType.LONG, () -> 81))
.put("template_id", InputBindings.inputSupplier(ExpressionType.LONG, () -> 81))
.put("chart_id", InputBindings.inputSupplier(ExpressionType.LONG, () -> 81))
.put("version", InputBindings.inputSupplier(ExpressionType.LONG, () -> 1))
.put("client_ip_object", InputBindings.inputSupplier(ExpressionType.STRING_ARRAY, () -> null))
.put("server_ip_object", InputBindings.inputSupplier(ExpressionType.STRING_ARRAY, () -> null))
.put("fqdn_category", InputBindings.inputSupplier(ExpressionType.STRING_ARRAY, () -> null))
.put("client_ip", InputBindings.inputSupplier(ExpressionType.STRING, () -> null))
.put("server_ip", InputBindings.inputSupplier(ExpressionType.STRING, () -> null))
.put("server_fqdn", InputBindings.inputSupplier(ExpressionType.STRING, () -> null))
.put("server_domain", InputBindings.inputSupplier(ExpressionType.STRING, () -> null))
.put("application", InputBindings.inputSupplier(ExpressionType.STRING, () -> null))
.build()
),
InputBindings.forInputSuppliers(
new ImmutableMap.Builder<String, InputBindings.InputSupplier>()
.put("device_id", InputBindings.inputSupplier(ExpressionType.STRING, () -> "1"))
.put("rule_id", InputBindings.inputSupplier(ExpressionType.LONG, () -> 101))
.put("template_id", InputBindings.inputSupplier(ExpressionType.LONG, () -> 101))
.put("chart_id", InputBindings.inputSupplier(ExpressionType.LONG, () -> 101))
.put("version", InputBindings.inputSupplier(ExpressionType.LONG, () -> 1))
.put("client_ip_object", InputBindings.inputSupplier(ExpressionType.STRING_ARRAY, () -> new Object[]{"5","7","8"}))
.put("server_ip_object", InputBindings.inputSupplier(ExpressionType.STRING_ARRAY, () -> null))
.put("fqdn_category", InputBindings.inputSupplier(ExpressionType.STRING_ARRAY, () -> null))
.put("client_ip", InputBindings.inputSupplier(ExpressionType.STRING, () -> null))
.put("server_ip", InputBindings.inputSupplier(ExpressionType.STRING, () -> null))
.put("server_fqdn", InputBindings.inputSupplier(ExpressionType.STRING, () -> null))
.put("server_domain", InputBindings.inputSupplier(ExpressionType.STRING, () -> null))
.put("application", InputBindings.inputSupplier(ExpressionType.STRING, () -> null))
.build()
),
InputBindings.forInputSuppliers(
new ImmutableMap.Builder<String, InputBindings.InputSupplier>()
.put("device_id", InputBindings.inputSupplier(ExpressionType.STRING, () -> "1"))
.put("rule_id", InputBindings.inputSupplier(ExpressionType.LONG, () -> 271L))
.put("template_id", InputBindings.inputSupplier(ExpressionType.LONG, () -> 271L))
.put("chart_id", InputBindings.inputSupplier(ExpressionType.LONG, () -> 271L))
.put("version", InputBindings.inputSupplier(ExpressionType.LONG, () -> 1L))
.put("client_ip_object", InputBindings.inputSupplier(ExpressionType.STRING_ARRAY, () -> null))
.put("server_ip_object", InputBindings.inputSupplier(ExpressionType.STRING_ARRAY, () -> null))
.put("fqdn_category", InputBindings.inputSupplier(ExpressionType.STRING_ARRAY, () -> null))
.put("client_ip", InputBindings.inputSupplier(ExpressionType.STRING, () -> null))
.put("server_ip", InputBindings.inputSupplier(ExpressionType.STRING, () -> "5.245.228.51"))
.put("server_fqdn", InputBindings.inputSupplier(ExpressionType.STRING, () -> null))
.put("server_domain", InputBindings.inputSupplier(ExpressionType.STRING, () -> null))
.put("application", InputBindings.inputSupplier(ExpressionType.STRING, () -> null))
.build()
),
// ...
InputBindings.forInputSuppliers(
new ImmutableMap.Builder<String, InputBindings.InputSupplier>()
.put("device_id", InputBindings.inputSupplier(ExpressionType.STRING, () -> "1"))
.put("rule_id", InputBindings.inputSupplier(ExpressionType.LONG, () -> 81))
.put("template_id", InputBindings.inputSupplier(ExpressionType.LONG, () -> 81))
.put("chart_id", InputBindings.inputSupplier(ExpressionType.LONG, () -> 81))
.put("version", InputBindings.inputSupplier(ExpressionType.LONG, () -> 1))
.put("client_ip_object", InputBindings.inputSupplier(ExpressionType.STRING, () -> null))
.put("server_ip_object", InputBindings.inputSupplier(ExpressionType.STRING, () -> null))
.put("fqdn_category", InputBindings.inputSupplier(ExpressionType.STRING, () -> null))
.put("client_ip", InputBindings.inputSupplier(ExpressionType.STRING, () -> null))
.put("server_ip", InputBindings.inputSupplier(ExpressionType.STRING, () -> null))
.put("server_fqdn", InputBindings.inputSupplier(ExpressionType.STRING, () -> null))
.put("server_domain", InputBindings.inputSupplier(ExpressionType.STRING, () -> null))
.put("application", InputBindings.inputSupplier(ExpressionType.STRING, () -> null))
.build()
),
InputBindings.forInputSuppliers(
new ImmutableMap.Builder<String, InputBindings.InputSupplier>()
.put("device_id", InputBindings.inputSupplier(ExpressionType.STRING, () -> "1"))
.put("rule_id", InputBindings.inputSupplier(ExpressionType.LONG, () -> 101))
.put("template_id", InputBindings.inputSupplier(ExpressionType.LONG, () -> 101))
.put("chart_id", InputBindings.inputSupplier(ExpressionType.LONG, () -> 101))
.put("version", InputBindings.inputSupplier(ExpressionType.LONG, () -> 1))
.put("client_ip_object", InputBindings.inputSupplier(ExpressionType.STRING, () -> "5,7,8"))
.put("server_ip_object", InputBindings.inputSupplier(ExpressionType.STRING, () -> null))
.put("fqdn_category", InputBindings.inputSupplier(ExpressionType.STRING, () -> null))
.put("client_ip", InputBindings.inputSupplier(ExpressionType.STRING, () -> null))
.put("server_ip", InputBindings.inputSupplier(ExpressionType.STRING, () -> null))
.put("server_fqdn", InputBindings.inputSupplier(ExpressionType.STRING, () -> null))
.put("server_domain", InputBindings.inputSupplier(ExpressionType.STRING, () -> null))
.put("application", InputBindings.inputSupplier(ExpressionType.STRING, () -> null))
.build()
),
InputBindings.forInputSuppliers(
new ImmutableMap.Builder<String, InputBindings.InputSupplier>()
.put("device_id", InputBindings.inputSupplier(ExpressionType.STRING, () -> "1"))
.put("rule_id", InputBindings.inputSupplier(ExpressionType.LONG, () -> 271L))
.put("template_id", InputBindings.inputSupplier(ExpressionType.LONG, () -> 271L))
.put("chart_id", InputBindings.inputSupplier(ExpressionType.LONG, () -> 271L))
.put("version", InputBindings.inputSupplier(ExpressionType.LONG, () -> 1L))
.put("client_ip_object", InputBindings.inputSupplier(ExpressionType.STRING, () -> null))
.put("server_ip_object", InputBindings.inputSupplier(ExpressionType.STRING, () -> null))
.put("fqdn_category", InputBindings.inputSupplier(ExpressionType.STRING, () -> null))
.put("client_ip", InputBindings.inputSupplier(ExpressionType.STRING, () -> null))
.put("server_ip", InputBindings.inputSupplier(ExpressionType.STRING, () -> "5.245.228.51"))
.put("server_fqdn", InputBindings.inputSupplier(ExpressionType.STRING, () -> null))
.put("server_domain", InputBindings.inputSupplier(ExpressionType.STRING, () -> null))
.put("application", InputBindings.inputSupplier(ExpressionType.STRING, () -> null))
.build()
),
};
@Test
public void test() {
Expr expr = Parser.parse("dimension_bucket(1024, 100, 'aaa', string,long,double,array1, array2, nullString, nullLong)", exprMacroTable);
ExprEval eval = expr.eval(inputBindings);
System.out.println(eval.value());
}
@Test
public void test2() {
for (Expr.ObjectBinding objectBinding : inputBindingArray) {
Expr expr = Parser.parse("dimension_bucket(1024, device_id, rule_id, template_id, chart_id, version, client_ip_object, server_ip_object, fqdn_category, client_ip, server_ip, server_fqdn, server_domain, application)", exprMacroTable);
ExprEval eval = expr.eval(objectBinding);
System.out.println(objectBinding.get("rule_id") + ", bucket_id:" + eval.value());
}
}
}