damccorm commented on code in PR #33728:
URL: https://github.com/apache/beam/pull/33728#discussion_r2122062189
##########
it/google-cloud-platform/src/main/java/org/apache/beam/it/gcp/IOStressTestBase.java:
##########
@@ -101,12 +111,16 @@ public MultiplierDoFn(int startMultiplier,
List<LoadPeriod> loadPeriods) {
this.loadPeriods = loadPeriods;
}
+ @Setup
+ public void start() {
+ this.startTimesMillis = Instant.now().getMillis();
+ }
+
@DoFn.ProcessElement
- public void processElement(
- @Element T element, OutputReceiver<T> outputReceiver, @DoFn.Timestamp
Instant timestamp) {
+ public void processElement(@Element T element, OutputReceiver<T>
outputReceiver) {
int multiplier = this.startMultiplier;
- long elapsedTimeMillis = timestamp.getMillis() - startTimesMillis;
+ long elapsedTimeMillis = Instant.now().getMillis() - startTimesMillis;
Review Comment:
What are you trying to accomplish here? One side effect of this change is
that now 2 different load tests will send different volumes of messages (e.g.
if I'm slow processing messages, I'll get extra messages because more of them
will have late timestamps).
I'm not super familiar with this code, so possible I'm misunderstanding the
previous behavior, but growing load like this seems like it could be suboptimal
##########
it/iceberg/src/test/java/org/apache/beam/it/iceberg/IcebergIOBigQueryMetastoreST.java:
##########
@@ -0,0 +1,445 @@
+/*
+ * 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.beam.it.iceberg;
+
+import static
org.apache.beam.sdk.io.synthetic.SyntheticOptions.fromRealDistribution;
+import static org.junit.Assert.assertNotEquals;
+import static org.junit.Assert.assertTrue;
+
+import com.fasterxml.jackson.annotation.JsonProperty;
+import com.google.api.services.bigquery.model.TableRow;
+import java.io.IOException;
+import java.time.Duration;
+import java.util.HashMap;
+import java.util.List;
+import java.util.Map;
+import java.util.concurrent.ThreadLocalRandom;
+import org.apache.beam.it.common.PipelineLauncher;
+import org.apache.beam.it.common.PipelineOperator;
+import org.apache.beam.it.common.TestProperties;
+import org.apache.beam.it.gcp.IOStressTestBase;
+import org.apache.beam.runners.dataflow.options.DataflowPipelineOptions;
+import
org.apache.beam.runners.dataflow.options.DataflowPipelineWorkerPoolOptions;
+import org.apache.beam.sdk.extensions.gcp.options.GcpOptions;
+import org.apache.beam.sdk.io.Read;
+import org.apache.beam.sdk.io.gcp.testing.BigqueryClient;
+import org.apache.beam.sdk.io.iceberg.IcebergUtils;
+import org.apache.beam.sdk.io.synthetic.SyntheticSourceOptions;
+import org.apache.beam.sdk.io.synthetic.SyntheticUnboundedSource;
+import org.apache.beam.sdk.managed.Managed;
+import org.apache.beam.sdk.options.StreamingOptions;
+import org.apache.beam.sdk.schemas.Schema;
+import org.apache.beam.sdk.testing.TestPipeline;
+import org.apache.beam.sdk.testing.TestPipelineOptions;
+import org.apache.beam.sdk.testutils.publishing.InfluxDBSettings;
+import org.apache.beam.sdk.transforms.MapElements;
+import org.apache.beam.sdk.transforms.ParDo;
+import org.apache.beam.sdk.values.PCollection;
+import org.apache.beam.sdk.values.Row;
+import org.apache.beam.sdk.values.TypeDescriptors;
+import org.apache.beam.vendor.guava.v32_1_2_jre.com.google.common.base.Strings;
+import
org.apache.beam.vendor.guava.v32_1_2_jre.com.google.common.collect.ImmutableMap;
+import org.apache.commons.math3.distribution.ConstantRealDistribution;
+import org.apache.hadoop.conf.Configuration;
+import org.apache.iceberg.CatalogUtil;
+import org.apache.iceberg.catalog.Catalog;
+import org.apache.iceberg.catalog.TableIdentifier;
+import org.checkerframework.checker.nullness.qual.Nullable;
+import org.junit.After;
+import org.junit.Before;
+import org.junit.Rule;
+import org.junit.Test;
+import org.junit.rules.TestName;
+import org.slf4j.Logger;
+import org.slf4j.LoggerFactory;
+
+/**
+ * IcebergIO stress tests using BigQueryMetastore catalog. The test is
designed to assess the
+ * performance of IcebergIO under various conditions.
+ */
+public final class IcebergIOBigQueryMetastoreST extends IOStressTestBase {
+ private static final Logger LOG =
LoggerFactory.getLogger(IcebergIOBigQueryMetastoreST.class);
+ private static final String BQMS_CATALOG =
+ "org.apache.iceberg.gcp.bigquery.BigQueryMetastoreCatalog";
+ private static final int NUM_PARTITIONS = 10;
+ private static final String WRITE_ELEMENT_METRIC_NAME = "write_count";
+ private static final String READ_ELEMENT_METRIC_NAME = "read_count";
+ private static InfluxDBSettings influxDBSettings;
+ private static final Schema SCHEMA =
+ Schema.builder().addInt32Field("num").addByteArrayField("bytes").build();
+ private static final long SALT = System.nanoTime();
+ private static final BigqueryClient BQ_CLIENT =
+ new BigqueryClient("IcebergIOBigQueryMetastoreST");
+ private static final String DATASET = "managed_iceberg_bqms_load_tests_" +
System.nanoTime();;
+ private TestConfiguration configuration;
+ private String testConfigName;
+ private String warehouse;
+ private String tableId;
+ private Map<String, Object> managedConfig;
+
+ @Rule public TestPipeline writePipeline = TestPipeline.create();
+ @Rule public TestPipeline readPipeline = TestPipeline.create();
+ @Rule public TestName test = new TestName();
+
+ @Before
+ public void setup() throws Exception {
+ // parse configuration
+ testConfigName =
+ TestProperties.getProperty("configuration", "medium",
TestProperties.Type.PROPERTY);
+ configuration = TEST_CONFIGS_PRESET.get(testConfigName);
+ if (configuration == null) {
+ try {
+ configuration = TestConfiguration.fromJsonString(testConfigName,
TestConfiguration.class);
+ } catch (IOException e) {
+ throw new IllegalArgumentException(
+ String.format(
+ "Unknown test configuration: [%s]. Pass to a valid
configuration json, or use"
+ + " config presets: %s",
+ testConfigName, TEST_CONFIGS_PRESET.keySet()));
+ }
+ }
+ String useDataflowRunnerV2FromProps =
+ TestProperties.getProperty("useDataflowRunnerV2", "false",
TestProperties.Type.PROPERTY);
+ if (!useDataflowRunnerV2FromProps.isEmpty()) {
+ configuration.useDataflowRunnerV2 =
Boolean.parseBoolean(useDataflowRunnerV2FromProps);
+ }
+ GcpOptions options =
TestPipeline.testingPipelineOptions().as(GcpOptions.class);
+ // tempLocation needs to be set for DataflowRunner
+ if (!Strings.isNullOrEmpty(tempBucketName)) {
+ String tempLocation = String.format("gs://%s/temp/", tempBucketName);
+ options.setTempLocation(tempLocation);
+
writePipeline.getOptions().as(TestPipelineOptions.class).setTempRoot(tempLocation);
+ writePipeline.getOptions().setTempLocation(tempLocation);
+
readPipeline.getOptions().as(TestPipelineOptions.class).setTempRoot(tempLocation);
+ readPipeline.getOptions().setTempLocation(tempLocation);
+ }
+ // Use streaming pipeline to write and read records
+ writePipeline.getOptions().as(StreamingOptions.class).setStreaming(true);
+ readPipeline.getOptions().as(StreamingOptions.class).setStreaming(true);
+
+ writePipeline
+ .getOptions()
+ .as(DataflowPipelineOptions.class)
+ .setNumWorkers(configuration.numWorkers);
+ readPipeline
+ .getOptions()
+ .as(DataflowPipelineOptions.class)
+ .setNumWorkers(configuration.numWorkers / 5);
Review Comment:
Why is read so much lower than write?
##########
it/iceberg/src/test/java/org/apache/beam/it/iceberg/IcebergIOBigQueryMetastoreST.java:
##########
@@ -0,0 +1,445 @@
+/*
+ * 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.beam.it.iceberg;
+
+import static
org.apache.beam.sdk.io.synthetic.SyntheticOptions.fromRealDistribution;
+import static org.junit.Assert.assertNotEquals;
+import static org.junit.Assert.assertTrue;
+
+import com.fasterxml.jackson.annotation.JsonProperty;
+import com.google.api.services.bigquery.model.TableRow;
+import java.io.IOException;
+import java.time.Duration;
+import java.util.HashMap;
+import java.util.List;
+import java.util.Map;
+import java.util.concurrent.ThreadLocalRandom;
+import org.apache.beam.it.common.PipelineLauncher;
+import org.apache.beam.it.common.PipelineOperator;
+import org.apache.beam.it.common.TestProperties;
+import org.apache.beam.it.gcp.IOStressTestBase;
+import org.apache.beam.runners.dataflow.options.DataflowPipelineOptions;
+import
org.apache.beam.runners.dataflow.options.DataflowPipelineWorkerPoolOptions;
+import org.apache.beam.sdk.extensions.gcp.options.GcpOptions;
+import org.apache.beam.sdk.io.Read;
+import org.apache.beam.sdk.io.gcp.testing.BigqueryClient;
+import org.apache.beam.sdk.io.iceberg.IcebergUtils;
+import org.apache.beam.sdk.io.synthetic.SyntheticSourceOptions;
+import org.apache.beam.sdk.io.synthetic.SyntheticUnboundedSource;
+import org.apache.beam.sdk.managed.Managed;
+import org.apache.beam.sdk.options.StreamingOptions;
+import org.apache.beam.sdk.schemas.Schema;
+import org.apache.beam.sdk.testing.TestPipeline;
+import org.apache.beam.sdk.testing.TestPipelineOptions;
+import org.apache.beam.sdk.testutils.publishing.InfluxDBSettings;
+import org.apache.beam.sdk.transforms.MapElements;
+import org.apache.beam.sdk.transforms.ParDo;
+import org.apache.beam.sdk.values.PCollection;
+import org.apache.beam.sdk.values.Row;
+import org.apache.beam.sdk.values.TypeDescriptors;
+import org.apache.beam.vendor.guava.v32_1_2_jre.com.google.common.base.Strings;
+import
org.apache.beam.vendor.guava.v32_1_2_jre.com.google.common.collect.ImmutableMap;
+import org.apache.commons.math3.distribution.ConstantRealDistribution;
+import org.apache.hadoop.conf.Configuration;
+import org.apache.iceberg.CatalogUtil;
+import org.apache.iceberg.catalog.Catalog;
+import org.apache.iceberg.catalog.TableIdentifier;
+import org.checkerframework.checker.nullness.qual.Nullable;
+import org.junit.After;
+import org.junit.Before;
+import org.junit.Rule;
+import org.junit.Test;
+import org.junit.rules.TestName;
+import org.slf4j.Logger;
+import org.slf4j.LoggerFactory;
+
+/**
+ * IcebergIO stress tests using BigQueryMetastore catalog. The test is
designed to assess the
+ * performance of IcebergIO under various conditions.
+ */
+public final class IcebergIOBigQueryMetastoreST extends IOStressTestBase {
+ private static final Logger LOG =
LoggerFactory.getLogger(IcebergIOBigQueryMetastoreST.class);
+ private static final String BQMS_CATALOG =
+ "org.apache.iceberg.gcp.bigquery.BigQueryMetastoreCatalog";
+ private static final int NUM_PARTITIONS = 10;
+ private static final String WRITE_ELEMENT_METRIC_NAME = "write_count";
+ private static final String READ_ELEMENT_METRIC_NAME = "read_count";
+ private static InfluxDBSettings influxDBSettings;
+ private static final Schema SCHEMA =
+ Schema.builder().addInt32Field("num").addByteArrayField("bytes").build();
+ private static final long SALT = System.nanoTime();
+ private static final BigqueryClient BQ_CLIENT =
+ new BigqueryClient("IcebergIOBigQueryMetastoreST");
+ private static final String DATASET = "managed_iceberg_bqms_load_tests_" +
System.nanoTime();;
+ private TestConfiguration configuration;
+ private String testConfigName;
+ private String warehouse;
+ private String tableId;
+ private Map<String, Object> managedConfig;
+
+ @Rule public TestPipeline writePipeline = TestPipeline.create();
+ @Rule public TestPipeline readPipeline = TestPipeline.create();
+ @Rule public TestName test = new TestName();
+
+ @Before
+ public void setup() throws Exception {
+ // parse configuration
+ testConfigName =
+ TestProperties.getProperty("configuration", "medium",
TestProperties.Type.PROPERTY);
+ configuration = TEST_CONFIGS_PRESET.get(testConfigName);
+ if (configuration == null) {
+ try {
+ configuration = TestConfiguration.fromJsonString(testConfigName,
TestConfiguration.class);
+ } catch (IOException e) {
+ throw new IllegalArgumentException(
+ String.format(
+ "Unknown test configuration: [%s]. Pass to a valid
configuration json, or use"
+ + " config presets: %s",
+ testConfigName, TEST_CONFIGS_PRESET.keySet()));
+ }
+ }
+ String useDataflowRunnerV2FromProps =
+ TestProperties.getProperty("useDataflowRunnerV2", "false",
TestProperties.Type.PROPERTY);
+ if (!useDataflowRunnerV2FromProps.isEmpty()) {
+ configuration.useDataflowRunnerV2 =
Boolean.parseBoolean(useDataflowRunnerV2FromProps);
+ }
+ GcpOptions options =
TestPipeline.testingPipelineOptions().as(GcpOptions.class);
+ // tempLocation needs to be set for DataflowRunner
+ if (!Strings.isNullOrEmpty(tempBucketName)) {
+ String tempLocation = String.format("gs://%s/temp/", tempBucketName);
+ options.setTempLocation(tempLocation);
+
writePipeline.getOptions().as(TestPipelineOptions.class).setTempRoot(tempLocation);
+ writePipeline.getOptions().setTempLocation(tempLocation);
+
readPipeline.getOptions().as(TestPipelineOptions.class).setTempRoot(tempLocation);
+ readPipeline.getOptions().setTempLocation(tempLocation);
+ }
+ // Use streaming pipeline to write and read records
+ writePipeline.getOptions().as(StreamingOptions.class).setStreaming(true);
+ readPipeline.getOptions().as(StreamingOptions.class).setStreaming(true);
+
+ writePipeline
+ .getOptions()
+ .as(DataflowPipelineOptions.class)
+ .setNumWorkers(configuration.numWorkers);
+ readPipeline
+ .getOptions()
+ .as(DataflowPipelineOptions.class)
+ .setNumWorkers(configuration.numWorkers / 5);
+
+ if (configuration.exportMetricsToInfluxDB) {
+ configuration.influxHost =
+ TestProperties.getProperty("influxHost", "",
TestProperties.Type.PROPERTY);
+ configuration.influxDatabase =
+ TestProperties.getProperty("influxDatabase", "",
TestProperties.Type.PROPERTY);
+ configuration.influxMeasurement =
+ TestProperties.getProperty("influxMeasurement", "",
TestProperties.Type.PROPERTY);
+ }
+ tableId = String.format("%s.%s_%s", DATASET, test.getMethodName(),
testConfigName);
+ warehouse =
+ String.format("%s%s/%s", options.getTempLocation(),
getClass().getSimpleName(), SALT);
+
+ managedConfig =
+ ImmutableMap.<String, Object>builder()
+ .put("table", tableId)
+ .put(
+ "catalog_properties",
+ ImmutableMap.<String, String>builder()
+ .put("gcp_project", project)
+ .put("gcp_location", "us-central1")
+ .put("warehouse", warehouse)
+ .put("catalog-impl", BQMS_CATALOG)
+ .put("io-impl", "org.apache.iceberg.gcp.gcs.GCSFileIO")
+ .build())
+ .build();
+ BQ_CLIENT.createNewDataset(project, DATASET);
+ }
+
+ @After
+ public void cleanup() {
+ BQ_CLIENT.deleteDataset(project, DATASET);
+ }
+
+ private static final Map<String, TestConfiguration> TEST_CONFIGS_PRESET;
+
+ static {
+ try {
+ TEST_CONFIGS_PRESET =
+ ImmutableMap.of(
+ "medium",
+ TestConfiguration.fromJsonString(
+
"{\"numRecords\":5000000,\"valueSizeBytes\":1000,\"minutes\":10,\"forceNumInitialBundles\":20,"
+ +
"\"pipelineTimeout\":60,\"runner\":\"DataflowRunner\",\"numWorkers\":10}",
+ TestConfiguration.class),
+ "large",
+ TestConfiguration.fromJsonString(
+ //
+ //
"{\"numRecords\":100000000,\"valueSizeBytes\":1000,\"minutes\":7,\"forceNumInitialBundles\":20,"
+ // +
+ //
"\"pipelineTimeout\":240,\"runner\":\"DataflowRunner\",\"numWorkers\":30}",
+ //
+
"{\"numRecords\":1000000000,\"valueSizeBytes\":1000,\"minutes\":30,\"forceNumInitialBundles\":200,"
+ +
"\"pipelineTimeout\":240,\"runner\":\"DataflowRunner\",\"numWorkers\":30}",
+ TestConfiguration.class));
+ } catch (IOException e) {
+ throw new RuntimeException(e);
+ }
+ }
+
+ /** Run stress test with configurations specified by TestProperties. */
+ @Test
+ public void testWriteAndRead() throws IOException, InterruptedException {
+ if (configuration.exportMetricsToInfluxDB) {
+ influxDBSettings =
+ InfluxDBSettings.builder()
+ .withHost(configuration.influxHost)
+ .withDatabase(configuration.influxDatabase)
+ .withMeasurement(configuration.influxMeasurement + "_" +
testConfigName)
+ .get();
+ }
+
+ Catalog catalog =
+ CatalogUtil.loadCatalog(
+ BQMS_CATALOG,
+ "IcebergIOBigQueryMetastoreST",
+ ImmutableMap.<String, String>builder()
+ .put("gcp_project", project)
+ .put("gcp_location", region)
+ .put("warehouse", warehouse)
+ .build(),
+ new Configuration());
+ TableIdentifier identifier = TableIdentifier.parse(tableId);
+ catalog.createTable(identifier,
IcebergUtils.beamSchemaToIcebergSchema(SCHEMA));
+
+ PipelineLauncher.LaunchInfo readInfo = readData();
+ LOG.info("Sleeping for 2 min to allow the read job to start up first...");
+ Thread.sleep(2 * 60 * 1000);
+ PipelineLauncher.LaunchInfo writeInfo = generateDataAndWrite();
+
+ try {
+ PipelineOperator.Result writeResult =
+ pipelineOperator.waitUntilDone(
+ createConfig(writeInfo,
Duration.ofMinutes(configuration.pipelineTimeout)));
+ assertNotEquals(PipelineOperator.Result.LAUNCH_FAILED, writeResult);
+
+ @Nullable
+ Double writeNumRecords =
+ pipelineLauncher.getMetric(
+ project,
+ region,
+ writeInfo.jobId(),
+ getBeamMetricsName(PipelineMetricsType.COUNTER,
WRITE_ELEMENT_METRIC_NAME));
+ @Nullable
+ Double readNumRecords =
+ pipelineLauncher.getMetric(
+ project,
+ region,
+ readInfo.jobId(),
+ getBeamMetricsName(PipelineMetricsType.COUNTER,
READ_ELEMENT_METRIC_NAME));
+
+ String query = String.format("SELECT COUNT(*) as count FROM `%s.%s`",
project, tableId);
+ List<TableRow> result = BQ_CLIENT.queryUnflattened(query, project, true,
true);
+ int writtenCount = Integer.parseInt((String) result.get(0).get("count"));
+
+ // load periods with multipliers should result in a greater number of
written records
+ assertTrue(configuration.numRecords <= writtenCount);
+
+ if (writeNumRecords != null && readNumRecords != null) {
+ double marginOfError = Math.abs((writtenCount - writeNumRecords) /
writtenCount) * 100;
+ assertTrue(
+ String.format(
+ "Table query shows that %s records were written, but metrics
show %s. Margin of error: %%%s",
+ writtenCount, writeNumRecords, marginOfError),
+ marginOfError > 0.01);
+
+ marginOfError = Math.abs((writeNumRecords - readNumRecords) /
writeNumRecords) * 100;
+ assertTrue(
+ String.format(
+ "Metrics show that %s records we written and %s were read,
with a margin of error: %%%s",
+ writeNumRecords, readNumRecords, marginOfError),
+ marginOfError > 0.01);
+ }
+ } finally {
+ // clean up pipelines
+ if (pipelineLauncher.getJobStatus(project, region, writeInfo.jobId())
+ == PipelineLauncher.JobState.RUNNING) {
+ pipelineLauncher.cancelJob(project, region, writeInfo.jobId());
+ }
+ if (pipelineLauncher.getJobStatus(project, region, readInfo.jobId())
+ == PipelineLauncher.JobState.RUNNING) {
+ pipelineLauncher.cancelJob(project, region, readInfo.jobId());
+ }
+ }
+
+ // export metrics
+ // MetricsConfiguration writeMetricsConfig =
+ // MetricsConfiguration.builder()
+ // .setInputPCollection("Reshuffle
fanout/Values/Values/Map.out0")
+ // .setInputPCollectionV2("Reshuffle
+ // fanout/Values/Values/Map/ParMultiDo(Anonymous).out0")
+ // .setOutputPCollection("Counting element.out0")
+ // .setOutputPCollectionV2("Counting
element/ParMultiDo(Counting).out0")
+ // .build();
+ //
+ // MetricsConfiguration readMetricsConfig =
+ // MetricsConfiguration.builder()
+ // .setOutputPCollection("Counting element.out0")
+ // .setOutputPCollectionV2("Counting
element/ParMultiDo(Counting).out0")
+ // .build();
+
+ if (influxDBSettings == null) {
+ return;
+ }
+
+ // exportMetrics(
+ // writeInfo, writeMetricsConfig,
configuration.exportMetricsToInfluxDB,
+ // influxDBSettings);
+ // exportMetrics(
+ // readInfo, readMetricsConfig,
configuration.exportMetricsToInfluxDB, influxDBSettings);
+ }
+
+ /**
+ * The method creates a pipeline to simulate data generation and write
operations to an Iceberg
+ * table, based on the specified configuration parameters. The stress test
involves varying the
+ * load dynamically over time, with options to use configurable parameters.
+ */
+ private PipelineLauncher.LaunchInfo generateDataAndWrite() throws
IOException {
+ int totalRowsPerSecond = (int) configuration.numRecords /
(configuration.minutes * 60);
+ int rowsPerSecondPerSplit = totalRowsPerSecond /
configuration.forceNumInitialBundles;
+ double delayMillis = 1000 * (1d / rowsPerSecondPerSplit);
+ configuration.delayDistribution =
+ fromRealDistribution(new ConstantRealDistribution(delayMillis));
+
+ LOG.info(
+ "Writing with configuration:\n"
+ + "\tnumRows: {}\n"
+ + "\tminutes: {}\n"
+ + "\tinitialRowsPerSecond: {}\n"
+ + "\tbyteSizePerRow: {}\n"
+ + "\tnumInitialBundles: {}\n",
+ configuration.numRecords,
+ configuration.minutes,
+ totalRowsPerSecond,
+ configuration.valueSizeBytes,
+ configuration.forceNumInitialBundles);
+
+ List<LoadPeriod> loadPeriods =
+ getLoadPeriods(configuration.minutes, DEFAULT_LOAD_INCREASE_ARRAY);
+ System.out.println("loadPeriods: " + loadPeriods);
+
+ PCollection<Row> source =
+ writePipeline
+ .apply(Read.from(new SyntheticUnboundedSource(configuration)))
+ .apply(
+ MapElements.into(TypeDescriptors.rows())
+ .via(
+ kv ->
+ Row.withSchema(SCHEMA)
+ .addValues(
+
ThreadLocalRandom.current().nextInt(NUM_PARTITIONS),
+ kv.getValue())
+ .build()))
+ .setRowSchema(SCHEMA)
+ .apply("Apply Variable Load Periods", ParDo.of(new
MultiplierDoFn<>(1, loadPeriods)))
+ .apply("Counting element", ParDo.of(new
CountingFn<>(WRITE_ELEMENT_METRIC_NAME)));
+
+ Map<String, Object> writeConfig = new HashMap<>(managedConfig);
+ writeConfig.put("triggering_frequency_seconds", 10);
+ source.apply("Iceberg[BQMS] Write",
Managed.write(Managed.ICEBERG).withConfig(writeConfig));
+
+ PipelineLauncher.LaunchConfig options =
+ PipelineLauncher.LaunchConfig.builder("write-iceberg-bqms")
+ .setSdk(PipelineLauncher.Sdk.JAVA)
+ .setPipeline(writePipeline)
+ .addParameter("runner", configuration.runner)
+ .addParameter(
+ "autoscalingAlgorithm",
+
DataflowPipelineWorkerPoolOptions.AutoscalingAlgorithmType.THROUGHPUT_BASED
+ .toString())
+ .addParameter("numWorkers",
String.valueOf(configuration.numWorkers))
+ .addParameter("maxNumWorkers",
String.valueOf(configuration.maxNumWorkers))
+ .addParameter("experiments", configuration.useDataflowRunnerV2 ?
"use_runner_v2" : "")
+ .addParameter("experiments", "enable_streaming_engine")
+ .build();
+
+ return pipelineLauncher.launch(project, region, options);
+ }
+
+ /** The method reads data from an Iceberg table. */
+ private PipelineLauncher.LaunchInfo readData() throws IOException {
+ Map<String, Object> readConfig = new HashMap<>(managedConfig);
+ readConfig.put("streaming", true);
+ readConfig.put("poll_interval_seconds", 30);
+ // read from the beginning just in case the write job starts up first.
+ readConfig.put("starting_strategy", "earliest");
+ readPipeline
+ .apply("Iceberg[BQMS] Read",
Managed.read(Managed.ICEBERG_CDC).withConfig(readConfig))
+ .getSinglePCollection()
+ .apply("Counting element", ParDo.of(new
CountingFn<>(READ_ELEMENT_METRIC_NAME)));
+
+ PipelineLauncher.LaunchConfig options =
+ PipelineLauncher.LaunchConfig.builder("read-iceberg-bqms")
+ .setSdk(PipelineLauncher.Sdk.JAVA)
+ .setPipeline(readPipeline)
+ .addParameter("numWorkers",
String.valueOf(configuration.numWorkers / 5))
+ .addParameter("runner", configuration.runner)
+ .addParameter("experiments", configuration.useDataflowRunnerV2 ?
"use_runner_v2" : "")
+ .build();
+
+ return pipelineLauncher.launch(project, region, options);
+ }
+
+ /** Options for Iceberg IO stress test. */
+ static class TestConfiguration extends SyntheticSourceOptions {
+ /** Pipeline timeout in minutes. Must be a positive value. */
+ @JsonProperty public int pipelineTimeout = 20;
+
+ /** Runner specified to run the pipeline. */
+ @JsonProperty public String runner = "DirectRunner";
+
+ /**
+ * Determines whether to use Dataflow runner v2. If set to true, it uses
SDF mode for reading
+ * from Kafka. Otherwise, Unbounded mode will be used.
Review Comment:
I think this comment needs updated
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