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Fixed mismatched schema regarding fixedVectorLen (#1866)
* fix(query) Fixed mismatched schema regarding fixedVectorLen. (#1855) * Fixed mismatched schema regarding fixedVectorLen. * Do not compare against colIds on schema match. --------- Co-authored-by: Yu Zhang <[email protected]> (cherry picked from commit 7169e1c) * bump up version for filodb bug fix. --------- Co-authored-by: Yu Zhang <[email protected]>
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179
query/src/test/scala/filodb/query/exec/LocalPartitionDistConcatExecSpec.scala
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| Original file line number | Diff line number | Diff line change |
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| package filodb.query.exec | ||
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| import com.typesafe.config.ConfigFactory | ||
| import filodb.core.binaryrecord2.RecordBuilder | ||
| import filodb.core.memstore.{FixedMaxPartitionsEvictionPolicy, SomeData, TimeSeriesMemStore} | ||
| import filodb.core.metadata.Column.ColumnType.{DoubleColumn, TimestampColumn} | ||
| import filodb.core.metadata.Schemas | ||
| import filodb.core.query._ | ||
| import filodb.core.store.{AllChunkScan, ChunkSource, InMemoryMetaStore, NullColumnStore, TimeRangeChunkScan} | ||
| import filodb.core.{DatasetRef, GlobalConfig, TestData} | ||
| import filodb.memory.MemFactory | ||
| import filodb.memory.format.{SeqRowReader, ZeroCopyUTF8String} | ||
| import filodb.query._ | ||
| import monix.eval.Task | ||
| import monix.execution.Scheduler | ||
| import monix.execution.Scheduler.Implicits.global | ||
| import monix.reactive.Observable | ||
| import org.scalatest.BeforeAndAfterAll | ||
| import org.scalatest.concurrent.ScalaFutures | ||
| import org.scalatest.funspec.AnyFunSpec | ||
| import org.scalatest.matchers.should.Matchers | ||
| import org.scalatest.time.{Millis, Seconds, Span} | ||
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| import scala.concurrent.duration._ | ||
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| object LocalPartitionDistConcatExecSpec { | ||
| val config = ConfigFactory.load("application_test.conf").getConfig("filodb") | ||
| val queryConfig = QueryConfig(config.getConfig("query")) | ||
| val querySession = QuerySession(QueryContext(), queryConfig) | ||
| val dummyDispatcher = new PlanDispatcher { | ||
| override def dispatch(plan: ExecPlanWithClientParams, source: ChunkSource) | ||
| (implicit sched: Scheduler): Task[QueryResponse] = { | ||
| plan.execPlan.execute(source, querySession)(global) | ||
| } | ||
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| override def clusterName: String = ??? | ||
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| override def isLocalCall: Boolean = ??? | ||
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| override def dispatchStreaming(plan: ExecPlanWithClientParams, | ||
| source: ChunkSource)(implicit sched: Scheduler): Observable[StreamQueryResponse] = ??? | ||
| } | ||
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| val dsRef = DatasetRef("raw-metrics") | ||
| val dummyPlan = MultiSchemaPartitionsExec(QueryContext(), dummyDispatcher, dsRef, 0, Nil, AllChunkScan, "_metric_") | ||
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| val builder = new RecordBuilder(MemFactory.onHeapFactory) | ||
| } | ||
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| class LocalPartitionDistConcatExecSpec extends AnyFunSpec with Matchers with ScalaFutures with BeforeAndAfterAll { | ||
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| import LocalPartitionDistConcatExecSpec._ | ||
| import Schemas.promCounter | ||
| import ZeroCopyUTF8String._ | ||
| import filodb.core.{MachineMetricsData => MMD} | ||
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| implicit val defaultPatience = PatienceConfig(timeout = Span(30, Seconds), interval = Span(250, Millis)) | ||
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| val policy = new FixedMaxPartitionsEvictionPolicy(20) | ||
| val memStore = new TimeSeriesMemStore(config, new NullColumnStore, new InMemoryMetaStore(), Some(policy)) | ||
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| val metric = "http_req_total" | ||
| val partKeyLabelValues = Map("job" -> "myCoolService", "instance" -> "someHost:8787", "host" -> "host-1") | ||
| val partKeyKVWithMetric = partKeyLabelValues ++ Map("_metric_" -> metric) | ||
| val partTagsUTF8 = partKeyLabelValues.map { case (k, v) => (k.utf8, v.utf8) } | ||
| val now = System.currentTimeMillis() | ||
| val numRawSamples = 1000 | ||
| val reportingInterval = 10000 | ||
| val tuples = (numRawSamples until 0).by(-1).map { n => | ||
| (now - n * reportingInterval, n.toDouble) | ||
| } | ||
| val schemas = Schemas(promCounter.partition, | ||
| Map(promCounter.name -> promCounter, | ||
| "histogram" -> MMD.histDataset.schema, | ||
| Schemas.dsGauge.name -> Schemas.dsGauge)) | ||
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| // NOTE: due to max-chunk-size in storeConf = 100, this will make (numRawSamples / 100) chunks | ||
| // Be sure to reset the builder; it is in an Object so static and shared amongst tests | ||
| builder.reset() | ||
| tuples.map { t => SeqRowReader(Seq(t._1, t._2, metric.utf8, partTagsUTF8)) } | ||
| .foreach(builder.addFromReader(_, promCounter)) | ||
| val container = builder.allContainers.head | ||
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| val mmdBuilder = new RecordBuilder(MemFactory.onHeapFactory) | ||
| val mmdTuples = MMD.linearMultiSeries().take(100) | ||
| val mmdSomeData = MMD.records(MMD.dataset1, mmdTuples) | ||
| val histData = MMD.linearHistSeries().take(100) | ||
| val histMaxMinData = MMD.histMaxMin(histData) | ||
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| val histDataDisabledWS = MMD.linearHistSeries(ws = GlobalConfig.workspacesDisabledForMaxMin.get.head).take(100) | ||
| val histMaxMinDataDisabledWS = MMD.histMaxMin(histDataDisabledWS) | ||
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| implicit val execTimeout = 5.seconds | ||
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| override def beforeAll(): Unit = { | ||
| memStore.setup(dsRef, schemas, 0, TestData.storeConf, 2) | ||
| memStore.ingest(dsRef, 0, SomeData(container, 0)) | ||
| memStore.ingest(dsRef, 0, MMD.records(MMD.histDataset, histData)) | ||
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| // set up shard, but do not ingest data to simulate an empty shard | ||
| memStore.setup(dsRef, schemas, 1, TestData.storeConf, 2) | ||
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| memStore.setup(MMD.dataset1.ref, Schemas(MMD.schema1), 0, TestData.storeConf, 1) | ||
| memStore.ingest(MMD.dataset1.ref, 0, mmdSomeData) | ||
| memStore.setup(MMD.histMaxMinDS.ref, Schemas(MMD.histMaxMinDS.schema), 0, TestData.storeConf, 1) | ||
| memStore.ingest(MMD.histMaxMinDS.ref, 0, MMD.records(MMD.histMaxMinDS, histMaxMinData)) | ||
| memStore.ingest(MMD.histMaxMinDS.ref, 0, MMD.records(MMD.histMaxMinDS, histMaxMinDataDisabledWS)) | ||
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| memStore.refreshIndexForTesting(dsRef) | ||
| memStore.refreshIndexForTesting(MMD.dataset1.ref) | ||
| memStore.refreshIndexForTesting(MMD.histMaxMinDS.ref) | ||
| } | ||
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| override def afterAll(): Unit = { | ||
| memStore.shutdown() | ||
| } | ||
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| it("should be able to hande complex query like sum(topk + sum)") { | ||
| val startTime = now - numRawSamples * reportingInterval | ||
| val endTime = now - (numRawSamples - 10) * reportingInterval | ||
| val filters = Seq(ColumnFilter("_metric_", Filter.Equals("http_req_total".utf8))) | ||
| val leafExecPlan = MultiSchemaPartitionsExec(QueryContext(), dummyDispatcher, | ||
| dsRef, 0, filters, TimeRangeChunkScan(startTime, endTime), "_metric_") | ||
| val transformer = PeriodicSamplesMapper(startTime, reportingInterval, endTime, None, None, QueryContext()) | ||
| leafExecPlan.addRangeVectorTransformer(transformer) | ||
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| val topK = LocalPartitionReduceAggregateExec(QueryContext(), dummyDispatcher, | ||
| Array[ExecPlan](leafExecPlan), AggregationOperator.TopK, Seq(1.0)) | ||
| val sum = LocalPartitionReduceAggregateExec(QueryContext(), dummyDispatcher, | ||
| Array[ExecPlan](leafExecPlan), AggregationOperator.Sum, Seq(0)) | ||
| val binaryjoin1 = BinaryJoinExec(QueryContext(), dummyDispatcher, | ||
| Seq(topK), Seq(sum), BinaryOperator.ADD, Cardinality.OneToOne, | ||
| None, Nil, Nil, "__name__", Some(RvRange(startMs = 0, endMs = 19, stepMs = 1))) | ||
| val binaryjoin2 = BinaryJoinExec(QueryContext(), dummyDispatcher, | ||
| Seq(sum), Seq(topK), BinaryOperator.ADD, Cardinality.OneToOne, | ||
| None, Nil, Nil, "__name__", Some(RvRange(startMs = 0, endMs = 19, stepMs = 1))) | ||
| val execPlan = LocalPartitionReduceAggregateExec(QueryContext(), dummyDispatcher, | ||
| Seq(binaryjoin1, binaryjoin2), AggregationOperator.Sum, Seq(0)) | ||
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| val resp = execPlan.execute(memStore, querySession).runToFuture.futureValue | ||
| val result = resp.asInstanceOf[QueryResult] | ||
| result.resultSchema.columns.map(_.colType) shouldEqual Seq(TimestampColumn, DoubleColumn) | ||
| result.resultSchema.fixedVectorLen.nonEmpty shouldEqual true | ||
| result.resultSchema.fixedVectorLen.get shouldEqual 11 | ||
| } | ||
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| it("should be able to hande complex query like sum(count + sum)") { | ||
| val startTime = now - numRawSamples * reportingInterval | ||
| val endTime = now - (numRawSamples - 10) * reportingInterval | ||
| val filters = Seq(ColumnFilter("_metric_", Filter.Equals("http_req_total".utf8))) | ||
| val leafExecPlan = MultiSchemaPartitionsExec(QueryContext(), dummyDispatcher, | ||
| dsRef, 0, filters, TimeRangeChunkScan(startTime, endTime), "_metric_") | ||
| val transformer = PeriodicSamplesMapper(startTime, reportingInterval, endTime, None, None, QueryContext()) | ||
| leafExecPlan.addRangeVectorTransformer(transformer) | ||
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| val count = LocalPartitionReduceAggregateExec(QueryContext(), dummyDispatcher, | ||
| Array[ExecPlan](leafExecPlan), AggregationOperator.Count, Seq(1.0)) | ||
| val sum = LocalPartitionReduceAggregateExec(QueryContext(), dummyDispatcher, | ||
| Array[ExecPlan](leafExecPlan), AggregationOperator.Sum, Seq(0)) | ||
| val binaryjoin1 = BinaryJoinExec(QueryContext(), dummyDispatcher, | ||
| Seq(count), Seq(sum), BinaryOperator.ADD, Cardinality.OneToOne, | ||
| None, Nil, Nil, "__name__", Some(RvRange(startMs = 0, endMs = 19, stepMs = 1))) | ||
| val binaryjoin2 = BinaryJoinExec(QueryContext(), dummyDispatcher, | ||
| Seq(sum), Seq(count), BinaryOperator.ADD, Cardinality.OneToOne, | ||
| None, Nil, Nil, "__name__", Some(RvRange(startMs = 0, endMs = 19, stepMs = 1))) | ||
| val execPlan = LocalPartitionReduceAggregateExec(QueryContext(), dummyDispatcher, | ||
| Seq(binaryjoin1, binaryjoin2), AggregationOperator.Sum, Seq(0)) | ||
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| val resp = execPlan.execute(memStore, querySession).runToFuture.futureValue | ||
| val result = resp.asInstanceOf[QueryResult] | ||
| result.resultSchema.columns.map(_.colType) shouldEqual Seq(TimestampColumn, DoubleColumn) | ||
| result.resultSchema.fixedVectorLen.nonEmpty shouldEqual true | ||
| result.resultSchema.fixedVectorLen.get shouldEqual 11 | ||
| } | ||
| } |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -1 +1 @@ | ||
| version in ThisBuild := "0.9.27.3" | ||
| version in ThisBuild := "0.9.27.4" |