| /* |
| * Licensed to the Apache Software Foundation (ASF) under one or more |
| * contributor license agreements. See the NOTICE file distributed with |
| * this work for additional information regarding copyright ownership. |
| * The ASF licenses this file to You 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. |
| * |
| */ |
| |
| package org.apache.skywalking.oap.server.core.analysis.meter.function; |
| |
| import java.util.Comparator; |
| import java.util.List; |
| import java.util.Objects; |
| import java.util.stream.IntStream; |
| import lombok.Getter; |
| import lombok.RequiredArgsConstructor; |
| import lombok.Setter; |
| import lombok.extern.slf4j.Slf4j; |
| import org.apache.skywalking.oap.server.core.Const; |
| import org.apache.skywalking.oap.server.core.UnexpectedException; |
| import org.apache.skywalking.oap.server.core.analysis.meter.Meter; |
| import org.apache.skywalking.oap.server.core.analysis.meter.MeterEntity; |
| import org.apache.skywalking.oap.server.core.analysis.metrics.DataTable; |
| import org.apache.skywalking.oap.server.core.analysis.metrics.IntList; |
| import org.apache.skywalking.oap.server.core.analysis.metrics.Metrics; |
| import org.apache.skywalking.oap.server.core.analysis.metrics.MultiIntValuesHolder; |
| import org.apache.skywalking.oap.server.core.analysis.metrics.PercentileMetrics; |
| import org.apache.skywalking.oap.server.core.query.type.Bucket; |
| import org.apache.skywalking.oap.server.core.remote.grpc.proto.RemoteData; |
| import org.apache.skywalking.oap.server.core.storage.annotation.BanyanDB; |
| import org.apache.skywalking.oap.server.core.storage.annotation.Column; |
| import org.apache.skywalking.oap.server.core.storage.annotation.ElasticSearch; |
| import org.apache.skywalking.oap.server.core.storage.type.Convert2Entity; |
| import org.apache.skywalking.oap.server.core.storage.type.Convert2Storage; |
| import org.apache.skywalking.oap.server.core.storage.type.StorageBuilder; |
| |
| /** |
| * PercentileFunction is the implementation of {@link PercentileMetrics} in the meter system. The major difference is |
| * the PercentileFunction accepts the {@link PercentileArgument} as input rather than every single request. |
| */ |
| @MeterFunction(functionName = "percentile") |
| @Slf4j |
| public abstract class PercentileFunction extends Meter implements AcceptableValue<PercentileFunction.PercentileArgument>, MultiIntValuesHolder { |
| public static final String DATASET = "dataset"; |
| public static final String RANKS = "ranks"; |
| public static final String VALUE = "value"; |
| |
| @Setter |
| @Getter |
| @Column(columnName = ENTITY_ID, length = 512) |
| @BanyanDB.ShardingKey(index = 0) |
| private String entityId; |
| @Getter |
| @Setter |
| @Column(columnName = VALUE, dataType = Column.ValueDataType.LABELED_VALUE, storageOnly = true) |
| @ElasticSearch.Column(columnAlias = "datatable_value") |
| private DataTable percentileValues = new DataTable(10); |
| @Getter |
| @Setter |
| @Column(columnName = DATASET, storageOnly = true) |
| private DataTable dataset = new DataTable(30); |
| /** |
| * Rank |
| */ |
| @Getter |
| @Setter |
| @Column(columnName = RANKS, storageOnly = true) |
| private IntList ranks = new IntList(10); |
| |
| private boolean isCalculated = false; |
| |
| @Override |
| public void accept(final MeterEntity entity, final PercentileArgument value) { |
| if (dataset.size() > 0) { |
| if (!value.getBucketedValues().isCompatible(dataset)) { |
| throw new IllegalArgumentException( |
| "Incompatible BucketedValues [" + value + "] for current PercentileFunction[" + dataset + "]"); |
| } |
| } |
| |
| for (final int rank : value.getRanks()) { |
| if (rank <= 0) { |
| throw new IllegalArgumentException("Illegal rank value " + rank + ", must be positive"); |
| } |
| } |
| |
| if (ranks.size() > 0) { |
| if (ranks.size() != value.getRanks().length) { |
| throw new IllegalArgumentException( |
| "Incompatible ranks size = [" + value.getRanks().length + "] for current PercentileFunction[" + ranks |
| .size() + "]"); |
| } else { |
| for (final int rank : value.getRanks()) { |
| if (!ranks.include(rank)) { |
| throw new IllegalArgumentException( |
| "Rank " + rank + " doesn't exist in the previous ranks " + ranks); |
| } |
| } |
| } |
| } else { |
| for (final int rank : value.getRanks()) { |
| ranks.add(rank); |
| } |
| } |
| |
| this.entityId = entity.id(); |
| |
| final long[] values = value.getBucketedValues().getValues(); |
| for (int i = 0; i < values.length; i++) { |
| final long bucket = value.getBucketedValues().getBuckets()[i]; |
| String bucketName = bucket == Long.MIN_VALUE ? Bucket.INFINITE_NEGATIVE : String.valueOf(bucket); |
| final long bucketValue = values[i]; |
| dataset.valueAccumulation(bucketName, bucketValue); |
| } |
| |
| this.isCalculated = false; |
| } |
| |
| @Override |
| public boolean combine(final Metrics metrics) { |
| PercentileFunction percentile = (PercentileFunction) metrics; |
| |
| if (!dataset.keysEqual(percentile.getDataset())) { |
| log.warn("Incompatible input [{}}] for current PercentileFunction[{}], entity {}", |
| percentile, this, entityId |
| ); |
| return true; |
| } |
| if (this.ranks.size() > 0) { |
| IntList ranksOfThat = percentile.getRanks(); |
| if (this.ranks.size() != ranksOfThat.size()) { |
| log.warn("Incompatible ranks size = [{}}] for current PercentileFunction[{}]", |
| ranksOfThat.size(), this.ranks.size() |
| ); |
| return true; |
| } else { |
| if (!this.ranks.equals(ranksOfThat)) { |
| log.warn("Rank {} doesn't exist in the previous ranks {}", ranksOfThat, this.ranks); |
| return true; |
| } |
| } |
| } |
| |
| this.dataset.append(percentile.dataset); |
| |
| this.isCalculated = false; |
| return true; |
| } |
| |
| @Override |
| public void calculate() { |
| if (!isCalculated) { |
| long total = dataset.sumOfValues(); |
| |
| int[] roofs = new int[ranks.size()]; |
| for (int i = 0; i < ranks.size(); i++) { |
| roofs[i] = Math.round(total * ranks.get(i) * 1.0f / 100); |
| } |
| |
| int count = 0; |
| final List<String> sortedKeys = dataset.sortedKeys(Comparator.comparingInt(Integer::parseInt)); |
| |
| int loopIndex = 0; |
| |
| for (String key : sortedKeys) { |
| final Long value = dataset.get(key); |
| |
| count += value; |
| for (int rankIdx = loopIndex; rankIdx < roofs.length; rankIdx++) { |
| int roof = roofs[rankIdx]; |
| |
| if (count >= roof) { |
| percentileValues.put(String.valueOf(ranks.get(rankIdx)), Long.parseLong(key)); |
| loopIndex++; |
| } else { |
| break; |
| } |
| } |
| } |
| } |
| } |
| |
| @Override |
| public Metrics toHour() { |
| PercentileFunction metrics = (PercentileFunction) createNew(); |
| metrics.setEntityId(getEntityId()); |
| metrics.setTimeBucket(toTimeBucketInHour()); |
| metrics.setDataset(getDataset()); |
| metrics.setRanks(getRanks()); |
| metrics.setPercentileValues(getPercentileValues()); |
| return metrics; |
| } |
| |
| @Override |
| public Metrics toDay() { |
| PercentileFunction metrics = (PercentileFunction) createNew(); |
| metrics.setEntityId(getEntityId()); |
| metrics.setTimeBucket(toTimeBucketInDay()); |
| metrics.setDataset(getDataset()); |
| metrics.setRanks(getRanks()); |
| metrics.setPercentileValues(getPercentileValues()); |
| return metrics; |
| } |
| |
| @Override |
| public int[] getValues() { |
| return percentileValues.sortedValues(Comparator.comparingInt(Integer::parseInt)) |
| .stream() |
| .flatMapToInt(l -> IntStream.of(l.intValue())) |
| .toArray(); |
| } |
| |
| @Override |
| public int remoteHashCode() { |
| return entityId.hashCode(); |
| } |
| |
| @Override |
| public void deserialize(final RemoteData remoteData) { |
| this.setTimeBucket(remoteData.getDataLongs(0)); |
| |
| this.setEntityId(remoteData.getDataStrings(0)); |
| |
| this.setDataset(new DataTable(remoteData.getDataObjectStrings(0))); |
| this.setRanks(new IntList(remoteData.getDataObjectStrings(1))); |
| this.setPercentileValues(new DataTable(remoteData.getDataObjectStrings(2))); |
| } |
| |
| @Override |
| public RemoteData.Builder serialize() { |
| RemoteData.Builder remoteBuilder = RemoteData.newBuilder(); |
| remoteBuilder.addDataLongs(getTimeBucket()); |
| |
| remoteBuilder.addDataStrings(entityId); |
| |
| remoteBuilder.addDataObjectStrings(dataset.toStorageData()); |
| remoteBuilder.addDataObjectStrings(ranks.toStorageData()); |
| remoteBuilder.addDataObjectStrings(percentileValues.toStorageData()); |
| |
| return remoteBuilder; |
| } |
| |
| @Override |
| protected String id0() { |
| return getTimeBucket() + Const.ID_CONNECTOR + entityId; |
| } |
| |
| @Override |
| public Class<? extends StorageBuilder> builder() { |
| return PercentileFunctionBuilder.class; |
| } |
| |
| @RequiredArgsConstructor |
| @Getter |
| public static class PercentileArgument { |
| private final BucketedValues bucketedValues; |
| private final int[] ranks; |
| } |
| |
| public static class PercentileFunctionBuilder implements StorageBuilder<PercentileFunction> { |
| @Override |
| public PercentileFunction storage2Entity(final Convert2Entity converter) { |
| PercentileFunction metrics = new PercentileFunction() { |
| @Override |
| public AcceptableValue<PercentileArgument> createNew() { |
| throw new UnexpectedException("createNew should not be called"); |
| } |
| }; |
| metrics.setDataset(new DataTable((String) converter.get(DATASET))); |
| metrics.setRanks(new IntList((String) converter.get(RANKS))); |
| metrics.setPercentileValues(new DataTable((String) converter.get(VALUE))); |
| metrics.setTimeBucket(((Number) converter.get(TIME_BUCKET)).longValue()); |
| metrics.setEntityId((String) converter.get(ENTITY_ID)); |
| return metrics; |
| } |
| |
| @Override |
| public void entity2Storage(final PercentileFunction storageData, final Convert2Storage converter) { |
| converter.accept(DATASET, storageData.getDataset()); |
| converter.accept(RANKS, storageData.getRanks()); |
| converter.accept(VALUE, storageData.getPercentileValues()); |
| converter.accept(TIME_BUCKET, storageData.getTimeBucket()); |
| converter.accept(ENTITY_ID, storageData.getEntityId()); |
| } |
| } |
| |
| @Override |
| public boolean equals(Object o) { |
| if (this == o) |
| return true; |
| if (!(o instanceof PercentileFunction)) |
| return false; |
| PercentileFunction function = (PercentileFunction) o; |
| return Objects.equals(entityId, function.entityId) && |
| getTimeBucket() == function.getTimeBucket(); |
| } |
| |
| @Override |
| public int hashCode() { |
| return Objects.hash(entityId, getTimeBucket()); |
| } |
| } |