本文整理汇总了Java中org.apache.flink.streaming.api.functions.AssignerWithPeriodicWatermarks类的典型用法代码示例。如果您正苦于以下问题：Java AssignerWithPeriodicWatermarks类的具体用法？Java AssignerWithPeriodicWatermarks怎么用？Java AssignerWithPeriodicWatermarks使用的例子？那么恭喜您, 这里精选的类代码示例或许可以为您提供帮助。
AssignerWithPeriodicWatermarks类属于org.apache.flink.streaming.api.functions包，在下文中一共展示了AssignerWithPeriodicWatermarks类的15个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Java代码示例。
示例1: Kafka08Fetcher
import org.apache.flink.streaming.api.functions.AssignerWithPeriodicWatermarks; //导入依赖的package包/类
public Kafka08Fetcher(
SourceContext<T> sourceContext,
Map<KafkaTopicPartition, Long> seedPartitionsWithInitialOffsets,
SerializedValue<AssignerWithPeriodicWatermarks<T>> watermarksPeriodic,
SerializedValue<AssignerWithPunctuatedWatermarks<T>> watermarksPunctuated,
StreamingRuntimeContext runtimeContext,
KeyedDeserializationSchema<T> deserializer,
Properties kafkaProperties,
long autoCommitInterval,
boolean useMetrics) throws Exception {
super(
sourceContext,
seedPartitionsWithInitialOffsets,
watermarksPeriodic,
watermarksPunctuated,
runtimeContext.getProcessingTimeService(),
runtimeContext.getExecutionConfig().getAutoWatermarkInterval(),
runtimeContext.getUserCodeClassLoader(),
useMetrics);
this.deserializer = checkNotNull(deserializer);
this.kafkaConfig = checkNotNull(kafkaProperties);
this.runtimeContext = runtimeContext;
this.invalidOffsetBehavior = getInvalidOffsetBehavior(kafkaProperties);
this.autoCommitInterval = autoCommitInterval;
}
示例2: createFetcher
import org.apache.flink.streaming.api.functions.AssignerWithPeriodicWatermarks; //导入依赖的package包/类
@Override
protected AbstractFetcher<T, ?> createFetcher(
SourceContext<T> sourceContext,
Map<KafkaTopicPartition, Long> assignedPartitionsWithInitialOffsets,
SerializedValue<AssignerWithPeriodicWatermarks<T>> watermarksPeriodic,
SerializedValue<AssignerWithPunctuatedWatermarks<T>> watermarksPunctuated,
StreamingRuntimeContext runtimeContext,
OffsetCommitMode offsetCommitMode) throws Exception {
boolean useMetrics = !PropertiesUtil.getBoolean(kafkaProperties, KEY_DISABLE_METRICS, false);
long autoCommitInterval = (offsetCommitMode == OffsetCommitMode.KAFKA_PERIODIC)
? PropertiesUtil.getLong(kafkaProperties, "auto.commit.interval.ms", 60000)
: -1; // this disables the periodic offset committer thread in the fetcher
return new Kafka08Fetcher<>(
sourceContext,
assignedPartitionsWithInitialOffsets,
watermarksPeriodic,
watermarksPunctuated,
runtimeContext,
deserializer,
kafkaProperties,
autoCommitInterval,
useMetrics);
}
示例3: createPartitionStateHolders
import org.apache.flink.streaming.api.functions.AssignerWithPeriodicWatermarks; //导入依赖的package包/类
/**
* Shortcut variant of {@link #createPartitionStateHolders(Map, int, SerializedValue, SerializedValue, ClassLoader)}
* that uses the same offset for all partitions when creating their state holders.
*/
private List<KafkaTopicPartitionState<KPH>> createPartitionStateHolders(
List<KafkaTopicPartition> partitions,
long initialOffset,
int timestampWatermarkMode,
SerializedValue<AssignerWithPeriodicWatermarks<T>> watermarksPeriodic,
SerializedValue<AssignerWithPunctuatedWatermarks<T>> watermarksPunctuated,
ClassLoader userCodeClassLoader) throws IOException, ClassNotFoundException {
Map<KafkaTopicPartition, Long> partitionsToInitialOffset = new HashMap<>(partitions.size());
for (KafkaTopicPartition partition : partitions) {
partitionsToInitialOffset.put(partition, initialOffset);
}
return createPartitionStateHolders(
partitionsToInitialOffset,
timestampWatermarkMode,
watermarksPeriodic,
watermarksPunctuated,
userCodeClassLoader);
}
示例4: TestFetcher
import org.apache.flink.streaming.api.functions.AssignerWithPeriodicWatermarks; //导入依赖的package包/类
protected TestFetcher(
SourceContext<T> sourceContext,
Map<KafkaTopicPartition, Long> assignedPartitionsWithStartOffsets,
SerializedValue<AssignerWithPeriodicWatermarks<T>> watermarksPeriodic,
SerializedValue<AssignerWithPunctuatedWatermarks<T>> watermarksPunctuated,
ProcessingTimeService processingTimeProvider,
long autoWatermarkInterval) throws Exception {
super(
sourceContext,
assignedPartitionsWithStartOffsets,
watermarksPeriodic,
watermarksPunctuated,
processingTimeProvider,
autoWatermarkInterval,
TestFetcher.class.getClassLoader(),
false);
}
示例5: TestFetcher
import org.apache.flink.streaming.api.functions.AssignerWithPeriodicWatermarks; //导入依赖的package包/类
protected TestFetcher(
SourceContext<T> sourceContext,
Map<KafkaTopicPartition, Long> assignedPartitionsWithStartOffsets,
SerializedValue<AssignerWithPeriodicWatermarks<T>> watermarksPeriodic,
SerializedValue<AssignerWithPunctuatedWatermarks<T>> watermarksPunctuated,
ProcessingTimeService processingTimeProvider,
long autoWatermarkInterval) throws Exception
{
super(
sourceContext,
assignedPartitionsWithStartOffsets,
watermarksPeriodic,
watermarksPunctuated,
processingTimeProvider,
autoWatermarkInterval,
TestFetcher.class.getClassLoader(),
false);
}
示例6: createFetcher
import org.apache.flink.streaming.api.functions.AssignerWithPeriodicWatermarks; //导入依赖的package包/类
@Override
protected AbstractFetcher<T, ?> createFetcher(
SourceContext<T> sourceContext,
List<KafkaTopicPartition> thisSubtaskPartitions,
SerializedValue<AssignerWithPeriodicWatermarks<T>> watermarksPeriodic,
SerializedValue<AssignerWithPunctuatedWatermarks<T>> watermarksPunctuated,
StreamingRuntimeContext runtimeContext) throws Exception {
boolean useMetrics = !Boolean.valueOf(properties.getProperty(KEY_DISABLE_METRICS, "false"));
return new Kafka010Fetcher<>(
sourceContext,
thisSubtaskPartitions,
watermarksPeriodic,
watermarksPunctuated,
runtimeContext.getProcessingTimeService(),
runtimeContext.getExecutionConfig().getAutoWatermarkInterval(),
runtimeContext.getUserCodeClassLoader(),
runtimeContext.isCheckpointingEnabled(),
runtimeContext.getTaskNameWithSubtasks(),
runtimeContext.getMetricGroup(),
deserializer,
properties,
pollTimeout,
useMetrics);
}
示例7: createFetcher
import org.apache.flink.streaming.api.functions.AssignerWithPeriodicWatermarks; //导入依赖的package包/类
@Override
protected AbstractFetcher<T, ?> createFetcher(
SourceContext<T> sourceContext,
Map<KafkaTopicPartition, Long> assignedPartitionsWithInitialOffsets,
SerializedValue<AssignerWithPeriodicWatermarks<T>> watermarksPeriodic,
SerializedValue<AssignerWithPunctuatedWatermarks<T>> watermarksPunctuated,
StreamingRuntimeContext runtimeContext,
OffsetCommitMode offsetCommitMode) throws Exception {
boolean useMetrics = !PropertiesUtil.getBoolean(properties, KEY_DISABLE_METRICS, false);
// make sure that auto commit is disabled when our offset commit mode is ON_CHECKPOINTS;
// this overwrites whatever setting the user configured in the properties
if (offsetCommitMode == OffsetCommitMode.ON_CHECKPOINTS || offsetCommitMode == OffsetCommitMode.DISABLED) {
properties.setProperty(ConsumerConfig.ENABLE_AUTO_COMMIT_CONFIG, "false");
}
return new Kafka09Fetcher<>(
sourceContext,
assignedPartitionsWithInitialOffsets,
watermarksPeriodic,
watermarksPunctuated,
runtimeContext.getProcessingTimeService(),
runtimeContext.getExecutionConfig().getAutoWatermarkInterval(),
runtimeContext.getUserCodeClassLoader(),
runtimeContext.getTaskNameWithSubtasks(),
runtimeContext.getMetricGroup(),
deserializer,
properties,
pollTimeout,
useMetrics);
}
示例8: Kafka010Fetcher
import org.apache.flink.streaming.api.functions.AssignerWithPeriodicWatermarks; //导入依赖的package包/类
public Kafka010Fetcher(
SourceContext<T> sourceContext,
Map<KafkaTopicPartition, Long> assignedPartitionsWithInitialOffsets,
SerializedValue<AssignerWithPeriodicWatermarks<T>> watermarksPeriodic,
SerializedValue<AssignerWithPunctuatedWatermarks<T>> watermarksPunctuated,
ProcessingTimeService processingTimeProvider,
long autoWatermarkInterval,
ClassLoader userCodeClassLoader,
String taskNameWithSubtasks,
MetricGroup metricGroup,
KeyedDeserializationSchema<T> deserializer,
Properties kafkaProperties,
long pollTimeout,
boolean useMetrics) throws Exception {
super(
sourceContext,
assignedPartitionsWithInitialOffsets,
watermarksPeriodic,
watermarksPunctuated,
processingTimeProvider,
autoWatermarkInterval,
userCodeClassLoader,
taskNameWithSubtasks,
metricGroup,
deserializer,
kafkaProperties,
pollTimeout,
useMetrics);
}
示例9: createFetcher
import org.apache.flink.streaming.api.functions.AssignerWithPeriodicWatermarks; //导入依赖的package包/类
@Override
protected AbstractFetcher<T, ?> createFetcher(
SourceContext<T> sourceContext,
Map<KafkaTopicPartition, Long> assignedPartitionsWithInitialOffsets,
SerializedValue<AssignerWithPeriodicWatermarks<T>> watermarksPeriodic,
SerializedValue<AssignerWithPunctuatedWatermarks<T>> watermarksPunctuated,
StreamingRuntimeContext runtimeContext,
OffsetCommitMode offsetCommitMode) throws Exception {
boolean useMetrics = !PropertiesUtil.getBoolean(properties, KEY_DISABLE_METRICS, false);
// make sure that auto commit is disabled when our offset commit mode is ON_CHECKPOINTS;
// this overwrites whatever setting the user configured in the properties
if (offsetCommitMode == OffsetCommitMode.ON_CHECKPOINTS || offsetCommitMode == OffsetCommitMode.DISABLED) {
properties.setProperty(ConsumerConfig.ENABLE_AUTO_COMMIT_CONFIG, "false");
}
return new Kafka010Fetcher<>(
sourceContext,
assignedPartitionsWithInitialOffsets,
watermarksPeriodic,
watermarksPunctuated,
runtimeContext.getProcessingTimeService(),
runtimeContext.getExecutionConfig().getAutoWatermarkInterval(),
runtimeContext.getUserCodeClassLoader(),
runtimeContext.getTaskNameWithSubtasks(),
runtimeContext.getMetricGroup(),
deserializer,
properties,
pollTimeout,
useMetrics);
}
示例10: KafkaTopicPartitionStateWithPeriodicWatermarks
import org.apache.flink.streaming.api.functions.AssignerWithPeriodicWatermarks; //导入依赖的package包/类
public KafkaTopicPartitionStateWithPeriodicWatermarks(
KafkaTopicPartition partition, KPH kafkaPartitionHandle,
AssignerWithPeriodicWatermarks<T> timestampsAndWatermarks) {
super(partition, kafkaPartitionHandle);
this.timestampsAndWatermarks = timestampsAndWatermarks;
this.partitionWatermark = Long.MIN_VALUE;
}
示例11: testPeriodicWatermarksWithNoSubscribedPartitionsShouldYieldNoWatermarks
import org.apache.flink.streaming.api.functions.AssignerWithPeriodicWatermarks; //导入依赖的package包/类
@Test
public void testPeriodicWatermarksWithNoSubscribedPartitionsShouldYieldNoWatermarks() throws Exception {
final String testTopic = "test topic name";
Map<KafkaTopicPartition, Long> originalPartitions = new HashMap<>();
TestSourceContext<Long> sourceContext = new TestSourceContext<>();
TestProcessingTimeService processingTimeProvider = new TestProcessingTimeService();
TestFetcher<Long> fetcher = new TestFetcher<>(
sourceContext,
originalPartitions,
new SerializedValue<AssignerWithPeriodicWatermarks<Long>>(new PeriodicTestExtractor()),
null, /* punctuated watermarks assigner*/
processingTimeProvider,
10);
processingTimeProvider.setCurrentTime(10);
// no partitions; when the periodic watermark emitter fires, no watermark should be emitted
assertFalse(sourceContext.hasWatermark());
// counter-test that when the fetcher does actually have partitions,
// when the periodic watermark emitter fires again, a watermark really is emitted
fetcher.addDiscoveredPartitions(Collections.singletonList(new KafkaTopicPartition(testTopic, 0)));
fetcher.emitRecord(100L, fetcher.subscribedPartitionStates().get(0), 3L);
processingTimeProvider.setCurrentTime(20);
assertEquals(100, sourceContext.getLatestWatermark().getTimestamp());
}
示例12: createFetcher
import org.apache.flink.streaming.api.functions.AssignerWithPeriodicWatermarks; //导入依赖的package包/类
@Override
protected AbstractFetcher<T, ?> createFetcher(
SourceContext<T> sourceContext,
Map<KafkaTopicPartition, Long> thisSubtaskPartitionsWithStartOffsets,
SerializedValue<AssignerWithPeriodicWatermarks<T>> watermarksPeriodic,
SerializedValue<AssignerWithPunctuatedWatermarks<T>> watermarksPunctuated,
StreamingRuntimeContext runtimeContext,
OffsetCommitMode offsetCommitMode) throws Exception {
return fetcher;
}
示例13: createFetcher
import org.apache.flink.streaming.api.functions.AssignerWithPeriodicWatermarks; //导入依赖的package包/类
@Override
@SuppressWarnings("unchecked")
protected AbstractFetcher<T, ?> createFetcher(
SourceContext<T> sourceContext,
Map<KafkaTopicPartition, Long> thisSubtaskPartitionsWithStartOffsets,
SerializedValue<AssignerWithPeriodicWatermarks<T>> watermarksPeriodic,
SerializedValue<AssignerWithPunctuatedWatermarks<T>> watermarksPunctuated,
StreamingRuntimeContext runtimeContext,
OffsetCommitMode offsetCommitMode) throws Exception {
return this.testFetcher;
}
示例14: createFetcher
import org.apache.flink.streaming.api.functions.AssignerWithPeriodicWatermarks; //导入依赖的package包/类
@Override
protected AbstractFetcher<T, ?> createFetcher(
SourceContext<T> sourceContext,
Map<KafkaTopicPartition, Long> thisSubtaskPartitionsWithStartOffsets,
SerializedValue<AssignerWithPeriodicWatermarks<T>> watermarksPeriodic,
SerializedValue<AssignerWithPunctuatedWatermarks<T>> watermarksPunctuated,
StreamingRuntimeContext runtimeContext,
OffsetCommitMode offsetCommitMode) throws Exception {
return mock(AbstractFetcher.class);
}
示例15: createFetcher
import org.apache.flink.streaming.api.functions.AssignerWithPeriodicWatermarks; //导入依赖的package包/类
@Override
protected AbstractFetcher<T, ?> createFetcher(
SourceContext<T> sourceContext,
List<KafkaTopicPartition> thisSubtaskPartitions,
SerializedValue<AssignerWithPeriodicWatermarks<T>> watermarksPeriodic,
SerializedValue<AssignerWithPunctuatedWatermarks<T>> watermarksPunctuated,
StreamingRuntimeContext runtimeContext) throws Exception {
boolean useMetrics = !Boolean.valueOf(properties.getProperty(KEY_DISABLE_METRICS, "false"));
return new Kafka09Fetcher<>(
sourceContext,
thisSubtaskPartitions,
watermarksPeriodic,
watermarksPunctuated,
runtimeContext.getProcessingTimeService(),
runtimeContext.getExecutionConfig().getAutoWatermarkInterval(),
runtimeContext.getUserCodeClassLoader(),
runtimeContext.isCheckpointingEnabled(),
runtimeContext.getTaskNameWithSubtasks(),
runtimeContext.getMetricGroup(),
deserializer,
properties,
pollTimeout,
useMetrics);
}