org.sparklinedata.druid.metadata.DruidMetadataCache.scala Maven / Gradle / Ivy
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* 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.sparklinedata.druid.metadata
import org.apache.spark.sql.{DataFrame, SQLContext}
import org.apache.spark.util.SparklineThreadUtils
import org.joda.time.Interval
import org.sparklinedata.druid.DruidDataSourceException
import scala.collection.mutable.{Map => MMap}
import scala.concurrent.{Await, ExecutionContext, Future}
import scala.collection.mutable.{Map => MMap}
import scala.concurrent.duration.Duration
import scala.util.{Failure, Success}
import org.sparklinedata.druid.client.{CuratorConnection, DruidCoordinatorClient, DruidQueryServerClient}
case class ModuleInfo(
name : String,
artifact : String,
version : String
)
case class ServerMemory(
maxMemory: Long,
totalMemory: Long,
freeMemory: Long,
usedMemory: Long
)
case class ServerStatus(
version : String,
modules : List[ModuleInfo],
memory : ServerMemory
)
case class DruidNode(name: String,
id: String,
address: String,
port: Int)
case class ShardSpec(
`type`: String,
partitionNum: Option[Int],
partitions: Option[Int]
)
case class DruidSegmentInfo(dataSource: String,
interval: String,
version: String,
binaryVersion: String,
size: Long,
identifier: String,
shardSpec: Option[ShardSpec]
) {
lazy val _interval = Interval.parse(interval)
def overlaps(in: Interval) = _interval.overlaps(in)
}
case class HistoricalServerInfo(host: String,
maxSize: Long,
`type`: String,
tier: String,
priority: Int,
segments: Map[String, DruidSegmentInfo],
currSize: Long) {
def handlesSegment(segId: String) = segments.contains(segId)
}
case class DataSourceSegmentInfo(name: String,
properties: Map[String, String],
segments: List[DruidSegmentInfo]
) {
def segmentsToScan(in: Interval): List[DruidSegmentInfo] = segments.filter(_.overlaps(in))
}
case class DruidClusterInfo(host: String,
curatorConnection: CuratorConnection,
coordinatorStatus : ServerStatus,
druidDataSources: scala.collection.Map[String,
(DataSourceSegmentInfo, DruidDataSource)],
histServers: List[HistoricalServerInfo]) {
def historicalServers(dRName: DruidRelationName, ins: List[Interval]):
List[HistoricalServerAssignment] = {
val m: MMap[String, (HistoricalServerInfo, List[(DruidSegmentInfo, Interval)])] = MMap()
/**
* - favor the higher priority server
* - when the priorities are equal
* - favor the server with least work.
*/
implicit val o = new Ordering[HistoricalServerInfo] {
override def compare(x: HistoricalServerInfo, y: HistoricalServerInfo): Int = {
if (x.priority == y.priority) {
(m.get(x.host), m.get(y.host)) match {
case (None, None) => 0 // x
case (None, _) => -1 // x
case (_, None) => 1 // y
case (Some((i1, l1)), Some((i2, l2))) => l1.size - l2.size
}
} else {
y.priority - x.priority
}
}
}
for (in <- ins) {
druidDataSources(dRName.druidDataSource)._1.segmentsToScan(in).map { seg =>
val segIn = seg._interval.overlap(in)
val s = histServers.filter(_.handlesSegment(seg.identifier)).sorted.head
if (m.contains(s.host)) {
val v = m(s.host)
val segInTuple = (seg, segIn)
m(s.host) = (v._1, segInTuple :: v._2)
} else {
m(s.host) = (s, List((seg, segIn)))
}
}
}
m.map {
case (h, t) => HistoricalServerAssignment(t._1, t._2)
}.toList
}
}
trait DruidMetadataCache {
type DruidDataSourceInfo = (DataSourceSegmentInfo, DruidDataSource)
def getDruidClusterInfo(druidRelName: DruidRelationName,
options: DruidRelationOptions): DruidClusterInfo
def getDataSourceInfo(druidRelName: DruidRelationName,
options: DruidRelationOptions): DruidDataSourceInfo
def assignHistoricalServers(druidRelName: DruidRelationName,
options: DruidRelationOptions,
intervals: List[Interval]): List[HistoricalServerAssignment]
def register(druidRelName: DruidRelationName,
options: DruidRelationOptions): Unit
def clearCache(host: String): Unit
}
trait DruidRelationInfoCache {
self: DruidMetadataCache =>
// scalastyle:off parameter.number
def druidRelation(sqlContext: SQLContext,
sourceDFName: String,
sourceDF: DataFrame,
dsName: String,
timeDimensionCol: String,
druidHost: String,
columnMapping: Map[String, String],
functionalDeps: List[FunctionalDependency],
starSchema: StarSchema,
options: DruidRelationOptions): DruidRelationInfo = {
val fullName = DruidRelationName(starSchema.factTable.name, druidHost, dsName)
val druidDS = getDataSourceInfo(
fullName,
options)._2
val sourceToDruidMapping =
MappingBuilder.buildMapping(sqlContext, sourceDFName,
starSchema, columnMapping, timeDimensionCol, druidDS)
val fd = new FunctionalDependencies(druidDS, functionalDeps,
DependencyGraph(druidDS, functionalDeps))
val dr = DruidRelationInfo(fullName,
sourceDFName,
timeDimensionCol,
druidDS,
sourceToDruidMapping,
fd,
starSchema,
options)
dr
}
}
case class HistoricalServerAssignment(server: HistoricalServerInfo,
segmentIntervals: List[(DruidSegmentInfo, Interval)])
object DruidMetadataCache extends DruidMetadataCache with DruidRelationInfoCache {
private[metadata] val cache: MMap[String, DruidClusterInfo] = MMap()
val thrdPool = SparklineThreadUtils.newDaemonCachedThreadPool("druidMD", 5)
implicit val ec = ExecutionContext.fromExecutor(thrdPool)
def getDruidClusterInfo(dRName: DruidRelationName,
options: DruidRelationOptions): DruidClusterInfo = {
cache.synchronized {
if (cache.contains(dRName.druidHost)) {
cache(dRName.druidHost)
} else {
val host = dRName.druidHost
val cc = new CuratorConnection(host, options, this, this.thrdPool)
val svr = cc.getCoordinator
val dc = new DruidCoordinatorClient(svr)
val ss = dc.serverStatus
val r = dc.serversInfo.filter(_.`type` == "historical")
val dCI = new DruidClusterInfo(host, cc, ss, MMap[String, DruidDataSourceInfo](), r)
cache(dCI.host) = dCI
dCI
}
}
}
def getDataSourceInfo(dRName: DruidRelationName,
options: DruidRelationOptions): DruidDataSourceInfo = {
val dCI = getDruidClusterInfo(dRName, options)
dCI.synchronized {
if (dCI.druidDataSources.contains(dRName.druidDataSource)) {
dCI.druidDataSources(dRName.druidDataSource)
} else {
val dc = new DruidCoordinatorClient(dCI.curatorConnection.getCoordinator)
val r = dc.dataSourceInfo(dRName.druidDataSource)
val bC = new DruidQueryServerClient(dCI.curatorConnection.getBroker)
var dds: DruidDataSource = bC.metadata(dRName.druidDataSource,
options.loadMetadataFromAllSegments)
dds = dds.copy(druidVersion = dCI.coordinatorStatus.version)
val i: DruidDataSourceInfo = (r, dds)
val m = dCI.druidDataSources.asInstanceOf[MMap[String, DruidDataSourceInfo]]
m(i._1.name) = i
i
}
}
}
def hostKey(coordinator: String,
port: Int) = s"$coordinator:$port"
def assignHistoricalServers(dRName: DruidRelationName,
options: DruidRelationOptions,
intervals: List[Interval]): List[HistoricalServerAssignment] = {
getDataSourceInfo(dRName, options)
getDruidClusterInfo(dRName, options
).historicalServers(dRName, intervals)
}
def register(dRName: DruidRelationName,
options: DruidRelationOptions): Unit = {
getDataSourceInfo(dRName, options)
}
def clearCache: Unit = cache.synchronized(cache.clear())
def clearCache(host: String): Unit = clearCache
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