feat(core): OTel Exponential Histograms

coordinator/src/main/scala/filodb.coordinator/NodeClusterActor.scala

@@ -55,14 +55,16 @@ object NodeClusterActor {
    * @param source the IngestionSource on each node.  Use noOpSource to not start ingestion and
    *               manually push records into NodeCoordinator.
    * @param storeConfig a StoreConfig for the MemStore.
+   * @param overrideSchema if true, will override the schema in the MetaStore with the schema in the Dataset.
    * @return DatasetVerified - meaning the dataset and columns are valid.  Does not mean ingestion is
    *                           setup on all nodes - for that, subscribe to ShardMapUpdate's
    */
   final case class SetupDataset(dataset: Dataset,
                                 resources: DatasetResourceSpec,
                                 source: IngestionSource,
                                 storeConfig: StoreConfig,
-                                downsampleConfig: DownsampleConfig = DownsampleConfig.disabled) {
+                                downsampleConfig: DownsampleConfig = DownsampleConfig.disabled,
+                                overrideSchema: Boolean = true) {
     import collection.JavaConverters._
     val resourceConfig = ConfigFactory.parseMap(
       Map("num-shards" -> resources.numShards, "min-num-nodes" -> resources.minNumNodes).asJava)

coordinator/src/main/scala/filodb.coordinator/NodeCoordinatorActor.scala

@@ -189,10 +189,10 @@ private[filodb] final class NodeCoordinatorActor(metaStore: MetaStore,
   }
 
   def ingestHandlers: Receive = LoggingReceive {
-    case SetupDataset(dataset, resources, source, storeConf, downsample) =>
+    case SetupDataset(dataset, resources, source, storeConf, downsample, overrideSchema) =>
       // used only in unit tests
       if (!(ingesters contains dataset.ref)) {
-        setupDataset(dataset, storeConf, resources.numShards, source, downsample, true)
+        setupDataset(dataset, storeConf, resources.numShards, source, downsample, overrideSchema)
       }
 
     case IngestRows(dataset, shard, rows) =>

coordinator/src/main/scala/filodb/coordinator/ProtoConverters.scala

@@ -898,6 +898,7 @@ object ProtoConverters {
         case filodb.query.InstantFunctionId.HistogramQuantile => GrpcMultiPartitionQueryService.InstantFunctionId.HISTOGRAM_QUANTILE
         case filodb.query.InstantFunctionId.HistogramMaxQuantile => GrpcMultiPartitionQueryService.InstantFunctionId.HISTOGRAM_MAX_QUANTILE
         case filodb.query.InstantFunctionId.HistogramBucket => GrpcMultiPartitionQueryService.InstantFunctionId.HISTOGRAM_BUCKET
+        case filodb.query.InstantFunctionId.HistogramFraction => GrpcMultiPartitionQueryService.InstantFunctionId.HISTOGRAM_FRACTION
         case filodb.query.InstantFunctionId.Ln => GrpcMultiPartitionQueryService.InstantFunctionId.LN
         case filodb.query.InstantFunctionId.Log10 => GrpcMultiPartitionQueryService.InstantFunctionId.LOG10
         case filodb.query.InstantFunctionId.Log2 => GrpcMultiPartitionQueryService.InstantFunctionId.LOG2
@@ -929,6 +930,7 @@ object ProtoConverters {
         case GrpcMultiPartitionQueryService.InstantFunctionId.HISTOGRAM_QUANTILE => filodb.query.InstantFunctionId.HistogramQuantile
         case GrpcMultiPartitionQueryService.InstantFunctionId.HISTOGRAM_MAX_QUANTILE => filodb.query.InstantFunctionId.HistogramMaxQuantile
         case GrpcMultiPartitionQueryService.InstantFunctionId.HISTOGRAM_BUCKET => filodb.query.InstantFunctionId.HistogramBucket
+        case GrpcMultiPartitionQueryService.InstantFunctionId.HISTOGRAM_FRACTION => filodb.query.InstantFunctionId.HistogramFraction
         case GrpcMultiPartitionQueryService.InstantFunctionId.LN => filodb.query.InstantFunctionId.Ln
         case GrpcMultiPartitionQueryService.InstantFunctionId.LOG10 => filodb.query.InstantFunctionId.Log10
         case GrpcMultiPartitionQueryService.InstantFunctionId.LOG2 => filodb.query.InstantFunctionId.Log2

core/src/main/scala/filodb.core/metadata/Schemas.scala

@@ -284,7 +284,7 @@ final case class Schemas(part: PartitionSchema,
   }
 
   private def bytesPerSampleSwagString = bytesPerSampleSwag.map { case (k, v) =>
-    s"${schemaName(k._1)} ColId:${k._2} : $v"
+    s"${schemaName(k._1)} ${k._1} ColId:${k._2} : $v"
   }
 
   Schemas._log.info(s"bytesPerSampleSwag: $bytesPerSampleSwagString")

core/src/test/scala/filodb.core/TestData.scala

@@ -356,6 +356,10 @@ object MachineMetricsData {
                             Seq("timestamp:ts", "count:long", "sum:long", "h:hist:counter=false"),
                             options = DatasetOptions(shardKeyColumns = Seq("_ws_", "_ns_", "metric"), "metric"))
 
+  val expHistDataset = Dataset("histogram", Seq("metric:string", "tags:map"),
+    Seq("timestamp:ts", "count:long", "sum:long", "min:long", "max:long", "h:hist:counter=false"),
+    options = DatasetOptions(shardKeyColumns = Seq("_ws_", "_ns_", "metric"), "metric"))
+
   var histBucketScheme: bv.HistogramBuckets = _
   def linearHistSeries(startTs: Long = 100000L, numSeries: Int = 10, timeStep: Int = 1000, numBuckets: Int = 8,
                        infBucket: Boolean = false, ws: String = "demo"):
@@ -383,6 +387,29 @@ object MachineMetricsData {
     }
   }
 
+  def otelDeltaExponentialHistSeries(startTs: Long = 100000L, numSeries: Int = 10,
+                                     timeStep: Int = 10000, numBuckets: Int = 160, ws: String = "demo"):
+  Stream[Seq[Any]] = {
+    histBucketScheme = bv.Base2ExpHistogramBuckets(3, -20, numBuckets - 1)
+    val buckets = new Array[Long](numBuckets)
+    def updateBuckets(bucketNo: Int): Unit = {
+      for { b <- bucketNo until numBuckets } {
+        buckets(b) += 1
+      }
+    }
+    Stream.from(0).map { n =>
+      updateBuckets(n % numBuckets)
+      Seq(startTs + n * timeStep,
+        (1 + n).toLong,
+        buckets.sum,
+        buckets.min,
+        buckets.max,
+        bv.LongHistogram(histBucketScheme, buckets.map(x => x)),
+        "request-latency",
+        extraTags ++ Map("_ws_".utf8 -> ws.utf8, "_ns_".utf8 -> "testapp".utf8, "dc".utf8 -> s"${n % numSeries}".utf8))
+    }
+  }
+
   // Data usable with prom-histogram schema
   def linearPromHistSeries(startTs: Long = 100000L, numSeries: Int = 10, timeStep: Int = 1000, numBuckets: Int = 8):
   Stream[Seq[Any]] = linearHistSeries(startTs, numSeries, timeStep, numBuckets).map { d =>

gateway/src/main/scala/filodb/gateway/GatewayServer.scala

@@ -84,6 +84,8 @@ object GatewayServer extends StrictLogging {
               descrYes = "Generate otel-cumulative-histogram schema test data and exit")
     val genOtelDeltaHistData = toggle(noshort = true,
               descrYes = "Generate otel-delta-histogram schema test data and exit")
+    val genOtelExpDeltaHistData = toggle(noshort = true,
+      descrYes = "Generate otel-exponential-delta-histogram schema test data and exit")
     val genGaugeData = toggle(noshort = true, descrYes = "Generate Prometheus gauge-schema test data and exit")
     val genCounterData = toggle(noshort = true, descrYes = "Generate Prometheus counter-schema test data and exit")
     val genDeltaCounterData = toggle(noshort = true, descrYes = "Generate delta-counter-schema test data and exit")
@@ -140,9 +142,11 @@ object GatewayServer extends StrictLogging {
     val genDeltaCounterData = userOpts.genDeltaCounterData.getOrElse(false)
     val genOtelCumulativeHistData = userOpts.genOtelCumulativeHistData.getOrElse(false)
     val genOtelDeltaHistData = userOpts.genOtelDeltaHistData.getOrElse(false)
+    val genOtelExpDeltaHistData = userOpts.genOtelExpDeltaHistData.getOrElse(false)
 
     if (genHist || genGaugeData || genDeltaHist
-          || genCounterData || genDeltaCounterData || genOtelDeltaHistData || genOtelCumulativeHistData) {
+          || genCounterData || genDeltaCounterData || genOtelDeltaHistData ||
+          genOtelExpDeltaHistData || genOtelCumulativeHistData) {
       val startTime = System.currentTimeMillis
       logger.info(s"Generating $numSamples samples starting at $startTime....")
 
@@ -151,7 +155,10 @@ object GatewayServer extends StrictLogging {
                                                   otelCumulativeHistogram)
                    else if (genOtelDeltaHistData) TestTimeseriesProducer.genHistogramData(startTime, numSeries,
                                                   otelDeltaHistogram)
-                   else if (genDeltaHist) TestTimeseriesProducer.genHistogramData(startTime, numSeries, deltaHistogram)
+                   else if (genOtelExpDeltaHistData) TestTimeseriesProducer.genHistogramData(startTime, numSeries,
+                     otelDeltaHistogram, otelExponential = true)
+                   else if (genDeltaHist)
+                     TestTimeseriesProducer.genHistogramData(startTime, numSeries, deltaHistogram)
                    else if (genGaugeData) TestTimeseriesProducer.timeSeriesData(startTime, numSeries,
                                         userOpts.numMetrics(), userOpts.publishIntervalSecs(), gauge)
                    else if (genDeltaCounterData) TestTimeseriesProducer.timeSeriesData(startTime, numSeries,
@@ -170,8 +177,8 @@ object GatewayServer extends StrictLogging {
       }
       Thread sleep 10000
       TestTimeseriesProducer.logQueryHelp(dataset.name, userOpts.numMetrics(), numSamples, numSeries,
-        startTime, genHist, genDeltaHist, genGaugeData, genCounterData, genOtelCumulativeHistData, genOtelDeltaHistData,
-        userOpts.publishIntervalSecs())
+        startTime, genHist, genDeltaHist, genGaugeData, genCounterData, genOtelCumulativeHistData,
+        genOtelDeltaHistData, genOtelExpDeltaHistData, userOpts.publishIntervalSecs())
       logger.info(s"Waited for containers to be sent, exiting...")
       sys.exit(0)
     } else {
@@ -260,7 +267,7 @@ object GatewayServer extends StrictLogging {
                                         producing(shard) = false
                                         output
                                       }
-                                    }
+                                    }.filter { case (_, j) => j.nonEmpty }
     logger.info(s"Created $numShards container builder queues with $parallelism parallel workers...")
     (shardQueues, containerStream)
   }

gateway/src/main/scala/filodb/gateway/conversion/InputRecord.scala

@@ -5,7 +5,7 @@ import remote.RemoteStorage.TimeSeries
 import filodb.core.binaryrecord2.RecordBuilder
 import filodb.core.metadata.{DatasetOptions, Schema}
 import filodb.memory.format.{SeqRowReader, ZeroCopyUTF8String => ZCUTF8}
-import filodb.memory.format.vectors.{CustomBuckets, LongHistogram}
+import filodb.memory.format.vectors.{Base2ExpHistogramBuckets, CustomBuckets, LongHistogram}
 
 /**
  * An InputRecord represents one "record" of timeseries data for input to FiloDB system.
@@ -182,7 +182,7 @@ object InputRecord {
   }
 
   /**
-   * Writes a delta non-increasing histogram record, along with the sum, count, min and max
+   * Writes a delta non-decreasing histogram record, along with the sum, count, min and max
    */
   def writeOtelDeltaHistRecord(builder: RecordBuilder,
                                metric: String,
@@ -230,6 +230,64 @@ object InputRecord {
     }
   }
 
+  /**
+   * Writes a non-decreasing histogram record, along with the sum, count, min and max
+   */
+  //scalastyle:off method.length
+  def writeOtelExponentialHistRecord(builder: RecordBuilder,
+                                     metric: String,
+                                     tags: Map[String, String],
+                                     timestamp: Long,
+                                     kvs: Seq[(String, Double)],
+                                     isDelta: Boolean): Unit = {
+    var sum = Double.NaN
+    var count = Double.NaN
+    var min = Double.NaN
+    var max = Double.NaN
+    var posBucketOffset = Double.NaN
+    var scale = Double.NaN
+
+    // Filter out sum and count, then convert and sort buckets
+    val sortedBuckets = kvs.filter {
+      case ("sum", v) => sum = v
+        false
+      case ("count", v) => count = v
+        false
+      case ("min", v) => min = v
+        false
+      case ("max", v) => max = v
+        false
+      case ("posBucketOffset", v) => posBucketOffset = v
+        false
+      case ("scale", v) => scale = v
+        false
+      case other => true
+    }.map {
+      case (k, v) => (k.toInt, v.toLong)
+    }.sorted
+
+    val bucketValues = sortedBuckets.map(_._2).toArray
+
+    if (sortedBuckets.nonEmpty) {
+      // length - 1 because the zero bucket is not included in the positive bucket count
+      val buckets = Base2ExpHistogramBuckets(scale.toInt, posBucketOffset.toInt, sortedBuckets.length - 1)
+      val hist = LongHistogram(buckets, bucketValues)
+
+      // Now, write out histogram
+      builder.startNewRecord(if (isDelta) otelDeltaHistogram else otelCumulativeHistogram)
+      builder.addLong(timestamp)
+      builder.addDouble(sum)
+      builder.addDouble(count)
+      builder.addBlob(hist.serialize())
+      builder.addDouble(min)
+      builder.addDouble(max)
+
+      builder.addString(metric)
+      builder.addMap(tags.map { case (k, v) => (k.utf8, v.utf8) })
+      builder.endRecord()
+    }
+  }
+
   /**
    * Writes a delta non-increasing histogram record, along with the sum and count,
    * using the delta-histogram schema, storing the entire histogram together for efficiency.

gateway/src/main/scala/filodb/timeseries/TestTimeseriesProducer.scala

@@ -64,15 +64,17 @@ object TestTimeseriesProducer extends StrictLogging {
   //scalastyle:off method.length parameter.number
   def logQueryHelp(dataset: String, numMetrics: Int, numSamples: Int, numTimeSeries: Int, startTimeMs: Long,
                    genHist: Boolean, genDeltaHist: Boolean, genGauge: Boolean,
-                   genPromCounter: Boolean, genOtelCumulativeHistData: Boolean, genOtelDeltaHistData: Boolean,
+                   genPromCounter: Boolean, genOtelCumulativeHistData: Boolean,
+                   genOtelDeltaHistData: Boolean, genOtelExpDeltaHistData: Boolean,
                    publishIntervalSec: Int): Unit = {
     val startQuery = startTimeMs / 1000
     val endQuery = startQuery + (numSamples / numMetrics / numTimeSeries) * publishIntervalSec
     logger.info(s"Finished producing $numSamples records for ${(endQuery-startQuery).toDouble/60} minutes")
 
     val metricName = if (genGauge) "heap_usage0"
                       else if (genHist || genOtelCumulativeHistData) "http_request_latency"
-                      else if (genDeltaHist || genOtelDeltaHistData) "http_request_latency_delta"
+                      else if (genDeltaHist || genOtelDeltaHistData || genOtelExpDeltaHistData)
+                        "http_request_latency_delta"
                       else if (genPromCounter) "heap_usage_counter0"
                       else "heap_usage_delta0"
 
@@ -98,15 +100,19 @@ object TestTimeseriesProducer extends StrictLogging {
                                dataset: Dataset,
                                shardMapper: ShardMapper,
                                spread: Int,
-                               publishIntervalSec: Int): (Future[Unit], Observable[(Int, Seq[Array[Byte]])]) = {
+                               publishIntervalSec: Int,
+                               expHist: Boolean = false,
+                               numBuckets: Int = 20): (Future[Unit], Observable[(Int, Seq[Array[Byte]])]) = {
     val (shardQueues, containerStream) = GatewayServer.shardingPipeline(GlobalConfig.systemConfig, numShards, dataset)
 
     val producingFut = Future {
-      timeSeriesData(startTimeMs, numTimeSeries, numMetricNames, publishIntervalSec, gauge)
-        .take(numSamples)
+      val data = if (expHist) genHistogramData(startTimeMs, numTimeSeries,
+        Schemas.otelDeltaHistogram, numBuckets = numBuckets, otelExponential = true)
+      else timeSeriesData(startTimeMs, numTimeSeries, numMetricNames, publishIntervalSec, gauge)
+      data.take(numSamples)
         .foreach { rec =>
           val shard = shardMapper.ingestionShard(rec.shardKeyHash, rec.partitionKeyHash, spread)
-          while (!shardQueues(shard).offer(rec)) { Thread sleep 50 }
+          while (!shardQueues(shard).offer(rec)) {  Thread sleep 50 }
         }
     }
     (producingFut, containerStream)
@@ -203,18 +209,20 @@ object TestTimeseriesProducer extends StrictLogging {
    * Note: the set of "instance" tags is unique for each invocation of genHistogramData.  This helps increase
    * the cardinality of time series for testing purposes.
    */
-  def genHistogramData(startTime: Long, numTimeSeries: Int = 16, histSchema: Schema): Stream[InputRecord] = {
-    val numBuckets = 10
-    val histBucketScheme = bv.GeometricBuckets(2.0, 3.0, numBuckets)
-    var buckets = new Array[Long](numBuckets)
+  def genHistogramData(startTime: Long, numTimeSeries: Int = 16, histSchema: Schema,
+                       numBuckets : Int = 20,
+                       otelExponential: Boolean = false): Stream[InputRecord] = {
+    val histBucketScheme = if (otelExponential) bv.Base2ExpHistogramBuckets(3, -numBuckets/2, numBuckets)
+                           else bv.GeometricBuckets(2.0, 3.0, numBuckets)
+    var buckets = new Array[Long](histBucketScheme.numBuckets)
     val metric = if (Schemas.deltaHistogram == histSchema || Schemas.otelDeltaHistogram == histSchema) {
                   "http_request_latency_delta"
                  } else {
                   "http_request_latency"
                  }
 
     def updateBuckets(bucketNo: Int): Unit = {
-      for { b <- bucketNo until numBuckets } {
+      for { b <- bucketNo until histBucketScheme.numBuckets } {
         buckets(b) += 1
       }
     }
@@ -232,9 +240,9 @@ object TestTimeseriesProducer extends StrictLogging {
       if ( (Schemas.deltaHistogram == histSchema || Schemas.otelDeltaHistogram == histSchema )
           && prevTimestamp != timestamp) {
         prevTimestamp = timestamp
-        buckets = new Array[Long](numBuckets)
+        buckets = new Array[Long](histBucketScheme.numBuckets)
       }
-      updateBuckets(n % numBuckets)
+      updateBuckets(n % histBucketScheme.numBuckets)
       val hist = bv.LongHistogram(histBucketScheme, buckets.map(x => x))
       val count = util.Random.nextInt(100).toDouble
       val sum = buckets.sum.toDouble

gateway/src/test/scala/filodb/gateway/conversion/InputRecordBuilderSpec.scala

@@ -4,13 +4,14 @@ package filodb.gateway.conversion
 import filodb.core.binaryrecord2.RecordBuilder
 import filodb.core.metadata.Schemas
 import filodb.memory.MemFactory
-import filodb.memory.format.vectors.{CustomBuckets, LongHistogram}
+import filodb.memory.format.vectors.{Base2ExpHistogramBuckets, CustomBuckets, LongHistogram}
 import org.scalatest.funspec.AnyFunSpec
 import org.scalatest.matchers.should.Matchers
 
 class InputRecordBuilderSpec extends AnyFunSpec with Matchers {
   val builder = new RecordBuilder(MemFactory.onHeapFactory)
   val builder2 = new RecordBuilder(MemFactory.onHeapFactory)
+  val builder3 = new RecordBuilder(MemFactory.onHeapFactory)
 
   val baseTags = Map("dataset" -> "timeseries",
                      "host" -> "MacBook-Pro-229.local",
@@ -97,6 +98,32 @@ class InputRecordBuilderSpec extends AnyFunSpec with Matchers {
     }
   }
 
+  it("should otelExpDeltaHistogram to BR and be able to deserialize it") {
+    val bucketScheme = Base2ExpHistogramBuckets(3, -5, 10)
+    val bucketsCounts = Array(1L, 2, 3,4, 5, 6, 7, 8, 9, 10, 11) // require cumulative counts
+    val expected = LongHistogram(bucketScheme, bucketsCounts)
+
+    val bucketKVs = bucketsCounts.zipWithIndex.map {
+      case (bucketCount, i) => i.toString -> bucketCount.toDouble
+    }.toSeq
+
+    // add posBucketOffset and scale
+    val more = Seq("posBucketOffset" -> bucketScheme.startIndexPositiveBuckets.toDouble,
+                   "scale" -> bucketScheme.scale.toDouble)
+
+    InputRecord.writeOtelExponentialHistRecord(builder3, metric, baseTags, 100000L,
+                                               bucketKVs ++ sumCountMinMaxKVs ++ more, isDelta = true)
+    builder3.allContainers.head.iterate(Schemas.otelDeltaHistogram.ingestionSchema).foreach { row =>
+      row.getDouble(1) shouldEqual sum
+      row.getDouble(2) shouldEqual count
+      row.getDouble(4) shouldEqual min
+      row.getDouble(5) shouldEqual max
+      val hist = row.getHistogram(3).asInstanceOf[LongHistogram]
+      hist.buckets shouldEqual expected.buckets
+      hist.values shouldEqual Array(1L, 2, 3,4, 5, 6, 7, 8, 9, 10, 11)
+    }
+  }
+
   it("should skip empty histograms via writePromHistRecord, and write subsequent records") {
     builder.reset()
     InputRecord.writePromHistRecord(builder, metric, baseTags, 100000L, sumCountKVs)

grpc/src/main/protobuf/query_service.proto

@@ -597,6 +597,7 @@ enum InstantFunctionId {
   MONTH                   = 20;
   YEAR                    = 21;
   OR_VECTOR_DOUBLE        = 22;
+  HISTOGRAM_FRACTION      = 23;
 }
 
 enum ScalarFunctionId {