More aggresive version of BatchSpanProcessor (#1579)
* More aggresive version of BatchSpanProcessor * Add benchmark * Polish * Polish * Incorporated some changes from #1571 * Rollback one test change * Polish * Polish
This commit is contained in:
Nikita Salnikov-Tarnovski
GitHub
parent
88582202c4
commit
af39f35086
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@ -0,0 +1,157 @@
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/*
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* Copyright 2020, OpenTelemetry Authors
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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package io.opentelemetry.sdk.trace.export;
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import io.opentelemetry.OpenTelemetry;
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import io.opentelemetry.sdk.OpenTelemetrySdk;
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import io.opentelemetry.sdk.common.export.CompletableResultCode;
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import io.opentelemetry.sdk.metrics.data.MetricData;
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import io.opentelemetry.sdk.metrics.data.MetricData.LongPoint;
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import io.opentelemetry.sdk.metrics.data.MetricData.Point;
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import io.opentelemetry.sdk.metrics.export.MetricProducer;
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import io.opentelemetry.sdk.trace.ReadableSpan;
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import io.opentelemetry.sdk.trace.data.SpanData;
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import io.opentelemetry.trace.Tracer;
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import java.util.ArrayList;
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import java.util.Collection;
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import java.util.List;
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import org.openjdk.jmh.annotations.AuxCounters;
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import org.openjdk.jmh.annotations.Benchmark;
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import org.openjdk.jmh.annotations.BenchmarkMode;
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import org.openjdk.jmh.annotations.Fork;
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import org.openjdk.jmh.annotations.Level;
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import org.openjdk.jmh.annotations.Measurement;
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import org.openjdk.jmh.annotations.Mode;
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import org.openjdk.jmh.annotations.Scope;
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import org.openjdk.jmh.annotations.Setup;
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import org.openjdk.jmh.annotations.State;
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import org.openjdk.jmh.annotations.TearDown;
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import org.openjdk.jmh.annotations.Threads;
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import org.openjdk.jmh.annotations.Warmup;
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public class BatchSpanProcessorDroppedSpansBenchmark {
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private static class DelayingSpanExporter implements SpanExporter {
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@SuppressWarnings("FutureReturnValueIgnored")
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@Override
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public CompletableResultCode export(Collection<SpanData> spans) {
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return CompletableResultCode.ofSuccess();
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}
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@Override
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public CompletableResultCode flush() {
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return CompletableResultCode.ofSuccess();
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}
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@Override
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public void shutdown() {}
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}
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@State(Scope.Benchmark)
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public static class BenchmarkState {
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private final MetricProducer metricProducer =
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OpenTelemetrySdk.getMeterProvider().getMetricProducer();
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private BatchSpanProcessor processor;
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private Tracer tracer;
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private Collection<MetricData> allMetrics;
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@Setup(Level.Trial)
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public final void setup() {
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SpanExporter exporter = new DelayingSpanExporter();
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processor = BatchSpanProcessor.newBuilder(exporter).build();
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tracer = OpenTelemetry.getTracerProvider().get("benchmarkTracer");
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}
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@TearDown(Level.Trial)
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public final void tearDown() {
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processor.shutdown();
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}
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@TearDown(Level.Iteration)
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public final void recordMetrics() {
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allMetrics = metricProducer.collectAllMetrics();
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}
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}
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@State(Scope.Thread)
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@AuxCounters(AuxCounters.Type.EVENTS)
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public static class ThreadState {
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private Collection<MetricData> allMetrics;
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@TearDown(Level.Iteration)
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public final void recordMetrics(BenchmarkState benchmarkState) {
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allMetrics = benchmarkState.allMetrics;
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}
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/** Burn, checkstyle, burn. */
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public double dropRatio() {
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long exported = getMetric(true);
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long dropped = getMetric(false);
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long total = exported + dropped;
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if (total == 0) {
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return 0;
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} else {
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// Due to peculiarities of JMH reporting we have to divide this by the number of the
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// concurrent threads running the actual benchmark.
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return (double) dropped / total / 5;
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}
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}
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public long exportedSpans() {
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return getMetric(true);
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}
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public long droppedSpans() {
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return getMetric(false);
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}
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private long getMetric(boolean dropped) {
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String labelValue = String.valueOf(dropped);
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for (MetricData metricData : allMetrics) {
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if (metricData.getDescriptor().getName().equals("processedSpans")) {
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List<Point> points = new ArrayList<>(metricData.getPoints());
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if (points.isEmpty()) {
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return 0;
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} else {
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// Find latest point with given value of dropped label
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for (int i = points.size() - 1; i >= 0; i--) {
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LongPoint point = (LongPoint) points.get(i);
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if (labelValue.equals(point.getLabels().get("dropped"))) {
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return point.getValue();
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}
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}
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}
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}
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}
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return 0;
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}
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}
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/** Export spans through {@link io.opentelemetry.sdk.trace.export.BatchSpanProcessor}. */
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@Benchmark
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@Fork(1)
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@Threads(5)
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@Warmup(iterations = 5, time = 1)
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@Measurement(iterations = 5, time = 20)
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@BenchmarkMode(Mode.Throughput)
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public void export(
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BenchmarkState benchmarkState, @SuppressWarnings("unused") ThreadState threadState) {
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benchmarkState.processor.onEnd(
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(ReadableSpan) benchmarkState.tracer.spanBuilder("span").startSpan());
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}
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}
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@ -0,0 +1,118 @@
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/*
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* Copyright 2020, OpenTelemetry Authors
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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package io.opentelemetry.sdk.trace.export;
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import com.google.common.collect.ImmutableList;
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import io.opentelemetry.OpenTelemetry;
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import io.opentelemetry.sdk.common.export.CompletableResultCode;
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import io.opentelemetry.sdk.trace.ReadableSpan;
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import io.opentelemetry.sdk.trace.data.SpanData;
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import io.opentelemetry.trace.Span;
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import io.opentelemetry.trace.Tracer;
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import java.util.Collection;
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import java.util.List;
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import java.util.concurrent.Executors;
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import java.util.concurrent.ScheduledExecutorService;
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import java.util.concurrent.TimeUnit;
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import org.openjdk.jmh.annotations.Benchmark;
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import org.openjdk.jmh.annotations.Fork;
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import org.openjdk.jmh.annotations.Level;
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import org.openjdk.jmh.annotations.Measurement;
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import org.openjdk.jmh.annotations.OutputTimeUnit;
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import org.openjdk.jmh.annotations.Param;
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import org.openjdk.jmh.annotations.Scope;
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import org.openjdk.jmh.annotations.Setup;
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import org.openjdk.jmh.annotations.State;
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import org.openjdk.jmh.annotations.Threads;
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import org.openjdk.jmh.annotations.Warmup;
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@State(Scope.Benchmark)
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public class BatchSpanProcessorFlushBenchmark {
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private static class DelayingSpanExporter implements SpanExporter {
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private final ScheduledExecutorService executor;
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private final int delayMs;
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private DelayingSpanExporter(int delayMs) {
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executor = Executors.newScheduledThreadPool(5);
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this.delayMs = delayMs;
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}
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@SuppressWarnings("FutureReturnValueIgnored")
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@Override
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public CompletableResultCode export(Collection<SpanData> spans) {
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final CompletableResultCode result = new CompletableResultCode();
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executor.schedule(
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new Runnable() {
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@Override
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public void run() {
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result.succeed();
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}
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},
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delayMs,
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TimeUnit.MILLISECONDS);
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return result;
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}
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@Override
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public CompletableResultCode flush() {
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return CompletableResultCode.ofSuccess();
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}
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@Override
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public void shutdown() {}
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}
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@Param({"0", "1", "5"})
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private int delayMs;
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@Param({"1000", "2000", "5000"})
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private int spanCount;
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private List<Span> spans;
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private BatchSpanProcessor processor;
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@Setup(Level.Trial)
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public final void setup() {
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SpanExporter exporter = new DelayingSpanExporter(delayMs);
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processor = BatchSpanProcessor.newBuilder(exporter).build();
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ImmutableList.Builder<Span> spans = ImmutableList.builderWithExpectedSize(spanCount);
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Tracer tracer = OpenTelemetry.getTracerProvider().get("benchmarkTracer");
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for (int i = 0; i < spanCount; i++) {
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spans.add(tracer.spanBuilder("span").startSpan());
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}
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this.spans = spans.build();
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}
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/** Export spans through {@link io.opentelemetry.sdk.trace.export.BatchSpanProcessor}. */
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@Benchmark
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@Fork(1)
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@Threads(5)
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@Warmup(iterations = 5, time = 1)
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@Measurement(iterations = 10, time = 1)
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@OutputTimeUnit(TimeUnit.SECONDS)
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public void export() {
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for (Span span : spans) {
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processor.onEnd((ReadableSpan) span);
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}
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processor.flush().join(10, TimeUnit.MINUTES);
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}
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}
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@ -24,7 +24,8 @@ dependencies {
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testCompile project(path: ':opentelemetry-sdk-common', configuration: 'testClasses')
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testImplementation project(':opentelemetry-testing-internal')
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testImplementation libraries.junit_pioneer
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testImplementation libraries.junit_pioneer,
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libraries.awaitility
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signature "org.codehaus.mojo.signature:java17:1.0@signature"
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signature "net.sf.androidscents.signature:android-api-level-24:7.0_r2@signature"
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@ -31,28 +31,22 @@ import io.opentelemetry.sdk.trace.ReadableSpan;
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import io.opentelemetry.sdk.trace.SpanProcessor;
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import io.opentelemetry.sdk.trace.data.SpanData;
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import java.util.ArrayList;
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import java.util.Collections;
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import java.util.List;
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import java.util.Map;
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import java.util.Timer;
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import java.util.TimerTask;
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import java.util.concurrent.atomic.AtomicBoolean;
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import java.util.concurrent.ArrayBlockingQueue;
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import java.util.concurrent.BlockingQueue;
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import java.util.concurrent.TimeUnit;
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import java.util.concurrent.atomic.AtomicReference;
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import java.util.logging.Level;
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import java.util.logging.Logger;
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import javax.annotation.concurrent.GuardedBy;
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/**
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* Implementation of the {@link SpanProcessor} that batches spans exported by the SDK then pushes
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* them to the exporter pipeline.
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*
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* <p>All spans reported by the SDK implementation are first added to a synchronized queue (with a
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* {@code maxQueueSize} maximum size, after the size is reached spans are dropped) and exported
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* every {@code scheduleDelayMillis} to the exporter pipeline in batches of {@code
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* maxExportBatchSize}. Spans may also be dropped when it becomes time to export again, and there is
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* an export in progress.
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*
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* <p>If the queue gets half full a preemptive notification is sent to the worker thread that
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* exports the spans to wake up and start a new export cycle.
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* {@code maxQueueSize} maximum size, if queue is full spans are dropped). Spans are exported either
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* when there are {@code maxExportBatchSize} pending spans or {@code scheduleDelayMillis} has passed
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* since the last export finished.
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*
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* <p>This batch {@link SpanProcessor} can cause high contention in a very high traffic service.
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* TODO: Add a link to the SpanProcessor that uses Disruptor as alternative with low contention.
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@ -85,10 +79,7 @@ public final class BatchSpanProcessor implements SpanProcessor {
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private static final String WORKER_THREAD_NAME =
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BatchSpanProcessor.class.getSimpleName() + "_WorkerThread";
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private static final String TIMER_THREAD_NAME =
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BatchSpanProcessor.class.getSimpleName() + "_TimerThread";
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private final Worker worker;
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private final Thread workerThread;
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private final boolean sampled;
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private BatchSpanProcessor(
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@ -102,11 +93,11 @@ public final class BatchSpanProcessor implements SpanProcessor {
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new Worker(
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spanExporter,
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scheduleDelayMillis,
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maxQueueSize,
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maxExportBatchSize,
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exporterTimeoutMillis);
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this.workerThread = new DaemonThreadFactory(WORKER_THREAD_NAME).newThread(worker);
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this.workerThread.start();
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exporterTimeoutMillis,
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new ArrayBlockingQueue<ReadableSpan>(maxQueueSize));
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Thread workerThread = new DaemonThreadFactory(WORKER_THREAD_NAME).newThread(worker);
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workerThread.start();
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this.sampled = sampled;
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}
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@ -133,7 +124,6 @@ public final class BatchSpanProcessor implements SpanProcessor {
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@Override
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public void shutdown() {
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workerThread.interrupt();
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worker.shutdown();
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}
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@ -142,169 +132,148 @@ public final class BatchSpanProcessor implements SpanProcessor {
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worker.forceFlush();
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}
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// TODO remove this when this.forceFlush returns CompletableResultCode
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@VisibleForTesting
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CompletableResultCode flush() {
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return worker.forceFlush();
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}
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// Worker is a thread that batches multiple spans and calls the registered SpanExporter to export
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// the data.
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//
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// The list of batched data is protected by an explicit monitor object which ensures full
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// concurrency.
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private static final class Worker implements Runnable {
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static {
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Meter meter = OpenTelemetry.getMeter("io.opentelemetry.sdk.trace");
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LongCounter droppedSpansCounter =
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LongCounter processedSpansCounter =
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meter
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.longCounterBuilder("droppedSpans")
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.longCounterBuilder("processedSpans")
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.setUnit("1")
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.setDescription(
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"The number of spans dropped by the BatchSpanProcessor due to high throughput.")
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.setConstantLabels(
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Labels.of("spanProcessorType", BatchSpanProcessor.class.getSimpleName()))
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.build();
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droppedSpans =
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droppedSpansCounter.bind(
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Labels.of("spanProcessorType", BatchSpanProcessor.class.getSimpleName()));
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droppedSpans = processedSpansCounter.bind(Labels.of("dropped", "true"));
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exportedSpans = processedSpansCounter.bind(Labels.of("dropped", "false"));
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}
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private static final BoundLongCounter droppedSpans;
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private final Timer timer = new Timer(TIMER_THREAD_NAME, /* isDaemon= */ true);
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private static final BoundLongCounter exportedSpans;
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private static final Logger logger = Logger.getLogger(Worker.class.getName());
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private final SpanExporter spanExporter;
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private final long scheduleDelayMillis;
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private final int maxQueueSize;
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private final long scheduleDelayNanos;
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private final int maxExportBatchSize;
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private final int halfMaxQueueSize;
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private final Object monitor = new Object();
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private final int exporterTimeoutMillis;
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private final AtomicBoolean exportAvailable = new AtomicBoolean(true);
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@GuardedBy("monitor")
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private final List<ReadableSpan> spansList;
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private long nextExportTime;
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private final BlockingQueue<ReadableSpan> queue;
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private final AtomicReference<CompletableResultCode> flushRequested = new AtomicReference<>();
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private volatile boolean continueWork = true;
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private final ArrayList<SpanData> batch;
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private Worker(
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SpanExporter spanExporter,
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long scheduleDelayMillis,
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int maxQueueSize,
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int maxExportBatchSize,
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int exporterTimeoutMillis) {
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int exporterTimeoutMillis,
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BlockingQueue<ReadableSpan> queue) {
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this.spanExporter = spanExporter;
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this.scheduleDelayMillis = scheduleDelayMillis;
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this.maxQueueSize = maxQueueSize;
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this.halfMaxQueueSize = maxQueueSize >> 1;
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this.scheduleDelayNanos = TimeUnit.MILLISECONDS.toNanos(scheduleDelayMillis);
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this.maxExportBatchSize = maxExportBatchSize;
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this.exporterTimeoutMillis = exporterTimeoutMillis;
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this.spansList = new ArrayList<>(maxQueueSize);
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this.queue = queue;
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this.batch = new ArrayList<>(this.maxExportBatchSize);
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}
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private void addSpan(ReadableSpan span) {
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synchronized (monitor) {
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if (spansList.size() == maxQueueSize) {
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if (!queue.offer(span)) {
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droppedSpans.add(1);
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return;
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}
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// TODO: Record a gauge for referenced spans.
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spansList.add(span);
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// Notify the worker thread that at half of the queue is available. It will take
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// time anyway for the thread to wake up.
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if (spansList.size() >= halfMaxQueueSize) {
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monitor.notifyAll();
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}
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}
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}
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@Override
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public void run() {
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while (!Thread.currentThread().isInterrupted()) {
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// Copy all the batched spans in a separate list to release the monitor lock asap to
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// avoid blocking the producer thread.
|
||||
ArrayList<ReadableSpan> spansCopy;
|
||||
synchronized (monitor) {
|
||||
// If still maxExportBatchSize elements in the queue better to execute an extra
|
||||
if (spansList.size() < maxExportBatchSize) {
|
||||
do {
|
||||
// In the case of a spurious wakeup we export only if we have at least one span in
|
||||
// the batch. It is acceptable because batching is a best effort mechanism here.
|
||||
updateNextExportTime();
|
||||
|
||||
while (continueWork) {
|
||||
if (flushRequested.get() != null) {
|
||||
flush();
|
||||
}
|
||||
|
||||
try {
|
||||
monitor.wait(scheduleDelayMillis);
|
||||
} catch (InterruptedException ie) {
|
||||
// Preserve the interruption status as per guidance and stop doing any work.
|
||||
ReadableSpan lastElement = queue.poll(100, TimeUnit.MILLISECONDS);
|
||||
if (lastElement != null) {
|
||||
batch.add(lastElement.toSpanData());
|
||||
}
|
||||
} catch (InterruptedException e) {
|
||||
Thread.currentThread().interrupt();
|
||||
return;
|
||||
}
|
||||
} while (spansList.isEmpty());
|
||||
|
||||
if (batch.size() >= maxExportBatchSize || System.nanoTime() >= nextExportTime) {
|
||||
exportCurrentBatch();
|
||||
updateNextExportTime();
|
||||
}
|
||||
spansCopy = new ArrayList<>(spansList);
|
||||
spansList.clear();
|
||||
}
|
||||
// Execute the batch export outside the synchronized to not block all producers.
|
||||
exportBatches(spansCopy);
|
||||
}
|
||||
|
||||
private void flush() {
|
||||
int spansToFlush = queue.size();
|
||||
while (spansToFlush > 0) {
|
||||
ReadableSpan span = queue.poll();
|
||||
assert span != null;
|
||||
batch.add(span.toSpanData());
|
||||
spansToFlush--;
|
||||
if (batch.size() >= maxExportBatchSize) {
|
||||
exportCurrentBatch();
|
||||
}
|
||||
}
|
||||
exportCurrentBatch();
|
||||
flushRequested.get().succeed();
|
||||
flushRequested.set(null);
|
||||
}
|
||||
|
||||
private void updateNextExportTime() {
|
||||
nextExportTime = System.nanoTime() + scheduleDelayNanos;
|
||||
}
|
||||
|
||||
private void shutdown() {
|
||||
forceFlush();
|
||||
timer.cancel();
|
||||
long pendingBatchesCountInQueue = queue.size() / maxExportBatchSize + 1L;
|
||||
long pendingBatchesCount = pendingBatchesCountInQueue + 1;
|
||||
long shutdownTimeout = pendingBatchesCount * exporterTimeoutMillis;
|
||||
|
||||
forceFlush().join(shutdownTimeout, TimeUnit.MILLISECONDS);
|
||||
|
||||
spanExporter.shutdown();
|
||||
continueWork = false;
|
||||
}
|
||||
|
||||
private void forceFlush() {
|
||||
ArrayList<ReadableSpan> spansCopy;
|
||||
synchronized (monitor) {
|
||||
spansCopy = new ArrayList<>(spansList);
|
||||
spansList.clear();
|
||||
}
|
||||
// Execute the batch export outside the synchronized to not block all producers.
|
||||
exportBatches(spansCopy);
|
||||
private CompletableResultCode forceFlush() {
|
||||
CompletableResultCode flushResult = new CompletableResultCode();
|
||||
this.flushRequested.compareAndSet(null, flushResult);
|
||||
return this.flushRequested.get();
|
||||
}
|
||||
|
||||
private void exportBatches(ArrayList<ReadableSpan> spanList) {
|
||||
// TODO: Record a counter for pushed spans.
|
||||
for (int i = 0; i < spanList.size(); ) {
|
||||
int lastIndexToTake = Math.min(i + maxExportBatchSize, spanList.size());
|
||||
onBatchExport(createSpanDataForExport(spanList, i, lastIndexToTake));
|
||||
i = lastIndexToTake;
|
||||
}
|
||||
private void exportCurrentBatch() {
|
||||
if (batch.isEmpty()) {
|
||||
return;
|
||||
}
|
||||
|
||||
private static List<SpanData> createSpanDataForExport(
|
||||
List<ReadableSpan> spanList, int startIndex, int endIndex) {
|
||||
List<SpanData> spanDataBuffer = new ArrayList<>(endIndex - startIndex);
|
||||
for (int i = startIndex; i < endIndex; i++) {
|
||||
spanDataBuffer.add(spanList.get(i).toSpanData());
|
||||
// Remove the reference to the ReadableSpan to allow GC to free the memory.
|
||||
spanList.set(i, null);
|
||||
}
|
||||
return Collections.unmodifiableList(spanDataBuffer);
|
||||
}
|
||||
|
||||
// Exports the list of SpanData to the SpanExporter.
|
||||
@SuppressWarnings("BooleanParameter")
|
||||
private void onBatchExport(final List<SpanData> spans) {
|
||||
if (exportAvailable.compareAndSet(true, false)) {
|
||||
try {
|
||||
final CompletableResultCode result = spanExporter.export(spans);
|
||||
result.whenComplete(
|
||||
new Runnable() {
|
||||
@Override
|
||||
public void run() {
|
||||
if (!result.isSuccess()) {
|
||||
final CompletableResultCode result = spanExporter.export(batch);
|
||||
result.join(exporterTimeoutMillis, TimeUnit.MILLISECONDS);
|
||||
if (result.isSuccess()) {
|
||||
exportedSpans.add(batch.size());
|
||||
} else {
|
||||
logger.log(Level.FINE, "Exporter failed");
|
||||
}
|
||||
exportAvailable.set(true);
|
||||
}
|
||||
});
|
||||
timer.schedule(
|
||||
new TimerTask() {
|
||||
@Override
|
||||
public void run() {
|
||||
result.fail();
|
||||
}
|
||||
},
|
||||
exporterTimeoutMillis);
|
||||
} catch (Exception e) {
|
||||
logger.log(Level.WARNING, "Exporter threw an Exception", e);
|
||||
}
|
||||
} else {
|
||||
logger.log(Level.FINE, "Exporter busy. Dropping spans.");
|
||||
} finally {
|
||||
batch.clear();
|
||||
}
|
||||
}
|
||||
}
|
||||
|
|
|
|||
|
|
@ -151,8 +151,13 @@ class TracerSdkTest {
|
|||
StressTestRunner.Operation.create(2_000, 1, new SimpleSpanOperation(tracer)));
|
||||
}
|
||||
|
||||
// Needs to correlate with the BatchSpanProcessor.Builder's default, which is the only thing
|
||||
// this test can guarantee
|
||||
final int defaultMaxQueueSize = 2048;
|
||||
|
||||
stressTestBuilder.build().run();
|
||||
assertThat(countingSpanExporter.numberOfSpansExported.get()).isEqualTo(8_000);
|
||||
assertThat(countingSpanExporter.numberOfSpansExported.get())
|
||||
.isGreaterThanOrEqualTo(defaultMaxQueueSize);
|
||||
}
|
||||
|
||||
private static class CountingSpanProcessor implements SpanProcessor {
|
||||
|
|
|
|||
|
|
@ -17,6 +17,7 @@
|
|||
package io.opentelemetry.sdk.trace.export;
|
||||
|
||||
import static org.assertj.core.api.Assertions.assertThat;
|
||||
import static org.awaitility.Awaitility.await;
|
||||
import static org.mockito.Mockito.doThrow;
|
||||
|
||||
import io.opentelemetry.sdk.common.export.CompletableResultCode;
|
||||
|
|
@ -154,10 +155,9 @@ class BatchSpanProcessorTest {
|
|||
|
||||
@Test
|
||||
void exportMoreSpansThanTheBufferSize() {
|
||||
WaitingSpanExporter waitingSpanExporter =
|
||||
new WaitingSpanExporter(6, CompletableResultCode.ofSuccess());
|
||||
CompletableSpanExporter spanExporter = new CompletableSpanExporter();
|
||||
BatchSpanProcessor batchSpanProcessor =
|
||||
BatchSpanProcessor.newBuilder(waitingSpanExporter)
|
||||
BatchSpanProcessor.newBuilder(spanExporter)
|
||||
.setMaxQueueSize(6)
|
||||
.setMaxExportBatchSize(2)
|
||||
.setScheduleDelayMillis(MAX_SCHEDULE_DELAY_MILLIS)
|
||||
|
|
@ -171,25 +171,32 @@ class BatchSpanProcessorTest {
|
|||
ReadableSpan span4 = createSampledEndedSpan(SPAN_NAME_1);
|
||||
ReadableSpan span5 = createSampledEndedSpan(SPAN_NAME_1);
|
||||
ReadableSpan span6 = createSampledEndedSpan(SPAN_NAME_1);
|
||||
List<SpanData> exported = waitingSpanExporter.waitForExport();
|
||||
assertThat(exported)
|
||||
|
||||
spanExporter.succeed();
|
||||
|
||||
await()
|
||||
.untilAsserted(
|
||||
() ->
|
||||
assertThat(spanExporter.getExported())
|
||||
.containsExactly(
|
||||
span1.toSpanData(),
|
||||
span2.toSpanData(),
|
||||
span3.toSpanData(),
|
||||
span4.toSpanData(),
|
||||
span5.toSpanData(),
|
||||
span6.toSpanData());
|
||||
span6.toSpanData()));
|
||||
}
|
||||
|
||||
@Test
|
||||
void forceExport() {
|
||||
WaitingSpanExporter waitingSpanExporter =
|
||||
new WaitingSpanExporter(1, CompletableResultCode.ofSuccess(), 1);
|
||||
new WaitingSpanExporter(100, CompletableResultCode.ofSuccess(), 1);
|
||||
BatchSpanProcessor batchSpanProcessor =
|
||||
BatchSpanProcessor.newBuilder(waitingSpanExporter)
|
||||
.setMaxQueueSize(10_000)
|
||||
.setMaxExportBatchSize(2_000)
|
||||
// Force flush should send all spans, make sure the number of spans we check here is
|
||||
// not divisible by the batch size.
|
||||
.setMaxExportBatchSize(49)
|
||||
.setScheduleDelayMillis(10_000) // 10s
|
||||
.build();
|
||||
|
||||
|
|
@ -199,11 +206,12 @@ class BatchSpanProcessorTest {
|
|||
}
|
||||
List<SpanData> exported = waitingSpanExporter.waitForExport();
|
||||
assertThat(exported).isNotNull();
|
||||
assertThat(exported.size()).isEqualTo(0);
|
||||
batchSpanProcessor.forceFlush();
|
||||
exported = waitingSpanExporter.waitForExport();
|
||||
assertThat(exported.size()).isEqualTo(98);
|
||||
|
||||
batchSpanProcessor.flush().join(10, TimeUnit.SECONDS);
|
||||
exported = waitingSpanExporter.getExported();
|
||||
assertThat(exported).isNotNull();
|
||||
assertThat(exported.size()).isEqualTo(100);
|
||||
assertThat(exported.size()).isEqualTo(2);
|
||||
}
|
||||
|
||||
@Test
|
||||
|
|
@ -424,20 +432,20 @@ class BatchSpanProcessorTest {
|
|||
|
||||
@Test
|
||||
@Timeout(10)
|
||||
public void shutdownFlushes() {
|
||||
void shutdownFlushes() {
|
||||
WaitingSpanExporter waitingSpanExporter =
|
||||
new WaitingSpanExporter(1, CompletableResultCode.ofSuccess());
|
||||
// Set the export delay to zero, for no timeout, in order to confirm the #flush() below works
|
||||
// Set the export delay to large value, in order to confirm the #flush() below works
|
||||
|
||||
tracerSdkFactory.addSpanProcessor(
|
||||
BatchSpanProcessor.newBuilder(waitingSpanExporter).setScheduleDelayMillis(0).build());
|
||||
BatchSpanProcessor.newBuilder(waitingSpanExporter).setScheduleDelayMillis(10_000).build());
|
||||
|
||||
ReadableSpan span2 = createSampledEndedSpan(SPAN_NAME_2);
|
||||
|
||||
// Force a shutdown, without this, the #waitForExport() call below would block indefinitely.
|
||||
// Force a shutdown, which forces processing of all remaining spans.
|
||||
tracerSdkFactory.shutdown();
|
||||
|
||||
List<SpanData> exported = waitingSpanExporter.waitForExport();
|
||||
List<SpanData> exported = waitingSpanExporter.getExported();
|
||||
assertThat(exported).containsExactly(span2.toSpanData());
|
||||
assertThat(waitingSpanExporter.shutDownCalled.get()).isTrue();
|
||||
}
|
||||
|
|
@ -502,6 +510,49 @@ class BatchSpanProcessorTest {
|
|||
}
|
||||
}
|
||||
|
||||
private static class CompletableSpanExporter implements SpanExporter {
|
||||
|
||||
private final List<CompletableResultCode> results = new ArrayList<>();
|
||||
|
||||
private final List<SpanData> exported = new ArrayList<>();
|
||||
|
||||
private volatile boolean succeeded;
|
||||
|
||||
List<SpanData> getExported() {
|
||||
return exported;
|
||||
}
|
||||
|
||||
void succeed() {
|
||||
succeeded = true;
|
||||
results.forEach(CompletableResultCode::succeed);
|
||||
}
|
||||
|
||||
@Override
|
||||
public CompletableResultCode export(Collection<SpanData> spans) {
|
||||
exported.addAll(spans);
|
||||
if (succeeded) {
|
||||
return CompletableResultCode.ofSuccess();
|
||||
}
|
||||
CompletableResultCode result = new CompletableResultCode();
|
||||
results.add(result);
|
||||
return result;
|
||||
}
|
||||
|
||||
@Override
|
||||
public CompletableResultCode flush() {
|
||||
if (succeeded) {
|
||||
return CompletableResultCode.ofSuccess();
|
||||
} else {
|
||||
return CompletableResultCode.ofFailure();
|
||||
}
|
||||
}
|
||||
|
||||
@Override
|
||||
public void shutdown() {
|
||||
flush();
|
||||
}
|
||||
}
|
||||
|
||||
static class WaitingSpanExporter implements SpanExporter {
|
||||
|
||||
private final List<SpanData> spanDataList = new ArrayList<>();
|
||||
|
|
@ -522,6 +573,12 @@ class BatchSpanProcessorTest {
|
|||
this.timeout = timeout;
|
||||
}
|
||||
|
||||
List<SpanData> getExported() {
|
||||
List<SpanData> result = new ArrayList<>(spanDataList);
|
||||
spanDataList.clear();
|
||||
return result;
|
||||
}
|
||||
|
||||
/**
|
||||
* Waits until we received numberOfSpans spans to export. Returns the list of exported {@link
|
||||
* SpanData} objects, otherwise {@code null} if the current thread is interrupted.
|
||||
|
|
@ -538,9 +595,7 @@ class BatchSpanProcessorTest {
|
|||
Thread.currentThread().interrupt();
|
||||
return null;
|
||||
}
|
||||
List<SpanData> result = new ArrayList<>(spanDataList);
|
||||
spanDataList.clear();
|
||||
return result;
|
||||
return getExported();
|
||||
}
|
||||
|
||||
@Override
|
||||
|
|
|
|||
Loading…
Reference in New Issue