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Fix Integration test flakiness in HoodieJavaStreamingApp (#1967)

This commit is contained in:
Balaji Varadarajan
2020-08-14 01:42:15 -07:00
committed by GitHub
parent 9bde6d616c
commit b8f4a30efd
5 changed files with 37 additions and 21 deletions

View File

@@ -19,6 +19,7 @@
package org.apache.hudi.integ;
import org.apache.hudi.common.model.HoodieTableType;
import org.apache.hudi.common.table.timeline.HoodieActiveTimeline;
import org.apache.hudi.common.util.Option;
import org.apache.hudi.common.util.collection.Pair;
@@ -34,20 +35,23 @@ import static org.junit.jupiter.api.Assertions.assertTrue;
*/
public class ITTestHoodieSanity extends ITTestBase {
private static final String HDFS_BASE_URL = "hdfs://namenode";
private static final String HDFS_STREAMING_SOURCE = HDFS_BASE_URL + "/streaming/source/";
private static final String HDFS_STREAMING_CKPT = HDFS_BASE_URL + "/streaming/ckpt/";
enum PartitionType {
SINGLE_KEY_PARTITIONED, MULTI_KEYS_PARTITIONED, NON_PARTITIONED,
}
@ParameterizedTest
@ValueSource(strings = { HOODIE_JAVA_APP, HOODIE_JAVA_STREAMING_APP })
@Test
/**
* A basic integration test that runs HoodieJavaApp to create a sample COW Hoodie with single partition key data-set
* and performs upserts on it. Hive integration and upsert functionality is checked by running a count query in hive
* console.
*/
public void testRunHoodieJavaAppOnSinglePartitionKeyCOWTable(String command) throws Exception {
String hiveTableName = "docker_hoodie_single_partition_key_cow_test";
testRunHoodieJavaApp(command, hiveTableName, HoodieTableType.COPY_ON_WRITE.name(),
public void testRunHoodieJavaAppOnSinglePartitionKeyCOWTable() throws Exception {
String hiveTableName = "docker_hoodie_single_partition_key_cow_test_" + HoodieActiveTimeline.createNewInstantTime();
testRunHoodieJavaApp(hiveTableName, HoodieTableType.COPY_ON_WRITE.name(),
PartitionType.SINGLE_KEY_PARTITIONED);
dropHiveTables(hiveTableName, HoodieTableType.COPY_ON_WRITE.name());
}
@@ -59,9 +63,9 @@ public class ITTestHoodieSanity extends ITTestBase {
* data-set and performs upserts on it. Hive integration and upsert functionality is checked by running a count query
* in hive console.
*/
public void testRunHoodieJavaAppOnMultiPartitionKeysCOWTable(String command) throws Exception {
String hiveTableName = "docker_hoodie_multi_partition_key_cow_test";
testRunHoodieJavaApp(command, hiveTableName, HoodieTableType.COPY_ON_WRITE.name(),
public void testRunHoodieJavaAppOnMultiPartitionKeysCOWTable() throws Exception {
String hiveTableName = "docker_hoodie_multi_partition_key_cow_test_" + HoodieActiveTimeline.createNewInstantTime();
testRunHoodieJavaApp(HOODIE_JAVA_APP, hiveTableName, HoodieTableType.COPY_ON_WRITE.name(),
PartitionType.MULTI_KEYS_PARTITIONED);
dropHiveTables(hiveTableName, HoodieTableType.COPY_ON_WRITE.name());
}
@@ -73,21 +77,20 @@ public class ITTestHoodieSanity extends ITTestBase {
* console.
*/
public void testRunHoodieJavaAppOnNonPartitionedCOWTable() throws Exception {
String hiveTableName = "docker_hoodie_non_partition_key_cow_test";
String hiveTableName = "docker_hoodie_non_partition_key_cow_test_" + HoodieActiveTimeline.createNewInstantTime();
testRunHoodieJavaApp(hiveTableName, HoodieTableType.COPY_ON_WRITE.name(), PartitionType.NON_PARTITIONED);
dropHiveTables(hiveTableName, HoodieTableType.COPY_ON_WRITE.name());
}
@ParameterizedTest
@ValueSource(strings = { HOODIE_JAVA_APP, HOODIE_JAVA_STREAMING_APP })
@Test
/**
* A basic integration test that runs HoodieJavaApp to create a sample MOR Hoodie with single partition key data-set
* and performs upserts on it. Hive integration and upsert functionality is checked by running a count query in hive
* console.
*/
public void testRunHoodieJavaAppOnSinglePartitionKeyMORTable(String command) throws Exception {
String hiveTableName = "docker_hoodie_single_partition_key_mor_test";
testRunHoodieJavaApp(command, hiveTableName, HoodieTableType.MERGE_ON_READ.name(),
public void testRunHoodieJavaAppOnSinglePartitionKeyMORTable() throws Exception {
String hiveTableName = "docker_hoodie_single_partition_key_mor_test_" + HoodieActiveTimeline.createNewInstantTime();
testRunHoodieJavaApp(hiveTableName, HoodieTableType.MERGE_ON_READ.name(),
PartitionType.SINGLE_KEY_PARTITIONED);
dropHiveTables(hiveTableName, HoodieTableType.MERGE_ON_READ.name());
}
@@ -100,7 +103,7 @@ public class ITTestHoodieSanity extends ITTestBase {
* in hive console.
*/
public void testRunHoodieJavaAppOnMultiPartitionKeysMORTable(String command) throws Exception {
String hiveTableName = "docker_hoodie_multi_partition_key_mor_test";
String hiveTableName = "docker_hoodie_multi_partition_key_mor_test_" + HoodieActiveTimeline.createNewInstantTime();
testRunHoodieJavaApp(command, hiveTableName, HoodieTableType.MERGE_ON_READ.name(),
PartitionType.MULTI_KEYS_PARTITIONED);
dropHiveTables(hiveTableName, HoodieTableType.MERGE_ON_READ.name());
@@ -113,7 +116,7 @@ public class ITTestHoodieSanity extends ITTestBase {
* console.
*/
public void testRunHoodieJavaAppOnNonPartitionedMORTable() throws Exception {
String hiveTableName = "docker_hoodie_non_partition_key_mor_test";
String hiveTableName = "docker_hoodie_non_partition_key_mor_test_" + HoodieActiveTimeline.createNewInstantTime();
testRunHoodieJavaApp(hiveTableName, HoodieTableType.MERGE_ON_READ.name(), PartitionType.NON_PARTITIONED);
dropHiveTables(hiveTableName, HoodieTableType.MERGE_ON_READ.name());
}
@@ -127,7 +130,7 @@ public class ITTestHoodieSanity extends ITTestBase {
throws Exception {
String hdfsPath = "/" + hiveTableName;
String hdfsUrl = "hdfs://namenode" + hdfsPath;
String hdfsUrl = HDFS_BASE_URL + hdfsPath;
// Drop Table if it exists
try {
@@ -155,6 +158,13 @@ public class ITTestHoodieSanity extends ITTestBase {
cmd = command + " --hive-sync --table-path " + hdfsUrl + " --hive-url " + HIVE_SERVER_JDBC_URL
+ " --table-type " + tableType + " --hive-table " + hiveTableName + " --non-partitioned";
}
if (command.equals(HOODIE_JAVA_STREAMING_APP)) {
String streamingSourcePath = HDFS_STREAMING_SOURCE + hiveTableName;
String streamingCkptPath = HDFS_STREAMING_CKPT + hiveTableName;
cmd = cmd + " --streaming-source-path " + streamingSourcePath
+ " --streaming-checkpointing-path " + streamingCkptPath;
}
executeCommandStringInDocker(ADHOC_1_CONTAINER, cmd, true);
String snapshotTableName = tableType.equals(HoodieTableType.MERGE_ON_READ.name())

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@@ -74,7 +74,7 @@ public class HoodieDataSourceHelpers {
if (metaClient.getTableType().equals(HoodieTableType.MERGE_ON_READ)) {
return metaClient.getActiveTimeline().getTimelineOfActions(
CollectionUtils.createSet(HoodieActiveTimeline.COMMIT_ACTION,
HoodieActiveTimeline.DELTA_COMMIT_ACTION));
HoodieActiveTimeline.DELTA_COMMIT_ACTION)).filterCompletedInstants();
} else {
return metaClient.getCommitTimeline().filterCompletedInstants();
}

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@@ -16,6 +16,7 @@
* limitations under the License.
*/
import org.apache.hadoop.fs.Path;
import org.apache.hudi.DataSourceReadOptions;
import org.apache.hudi.DataSourceWriteOptions;
import org.apache.hudi.HoodieDataSourceHelpers;
@@ -120,6 +121,9 @@ public class HoodieJavaApp {
dataGen = new HoodieTestDataGenerator();
}
// Explicitly clear up the hoodie table path if it exists.
fs.delete(new Path(tablePath), true);
/**
* Commit with only inserts
*/

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@@ -273,7 +273,9 @@ public class HoodieJavaStreamingApp {
public int addInputAndValidateIngestion(SparkSession spark, FileSystem fs, String srcPath,
int initialCommits, int expRecords,
Dataset<Row> inputDF1, Dataset<Row> inputDF2, boolean instantTimeValidation) throws Exception {
inputDF1.write().mode(SaveMode.Append).json(srcPath);
// Ensure, we always write only one file. This is very important to ensure a single batch is reliably read
// atomically by one iteration of spark streaming.
inputDF1.coalesce(1).write().mode(SaveMode.Append).json(srcPath);
int numExpCommits = initialCommits + 1;
// wait for spark streaming to process one microbatch

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@@ -102,7 +102,7 @@ class TestStructuredStreaming extends HoodieClientTestBase {
}
val f2 = Future {
inputDF1.write.mode(SaveMode.Append).json(sourcePath)
inputDF1.coalesce(1).write.mode(SaveMode.Append).json(sourcePath)
// wait for spark streaming to process one microbatch
val currNumCommits = waitTillAtleastNCommits(fs, destPath, 1, 120, 5)
assertTrue(HoodieDataSourceHelpers.hasNewCommits(fs, destPath, "000"))
@@ -112,7 +112,7 @@ class TestStructuredStreaming extends HoodieClientTestBase {
.load(destPath + "/*/*/*/*")
assert(hoodieROViewDF1.count() == 100)
inputDF2.write.mode(SaveMode.Append).json(sourcePath)
inputDF2.coalesce(1).write.mode(SaveMode.Append).json(sourcePath)
// wait for spark streaming to process one microbatch
waitTillAtleastNCommits(fs, destPath, currNumCommits + 1, 120, 5)
val commitInstantTime2 = HoodieDataSourceHelpers.latestCommit(fs, destPath)