使用 StreamManagerClient 处理流 - Amazon IoT Greengrass
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使用 StreamManagerClient 处理流

在 Greengrass 核心设备上运行的用户定义的 Greengrass 组件可以使用StreamManagerClientStream Manager SDK 中的对象,用于在流管理器然后与直播互动。当组件创建流时,它会定义Amazon Web Services 云该流的目标、优先级以及其他导出和数据保留策略。要将数据发送到直播管理器,组件会将数据附加到直播。如果为流定义了导出目标,流管理器会自动导出流。

注意

通常,流管理器的客户端是用户定义的 Greengrass 组件。如果您的业务案例需要它,您还可以允许在 Greengrass 核心上运行的非组件进程(例如 Docker 容器)与流管理器交互。有关更多信息,请参阅 客户端身份验证

本主题中的代码段向您展示客户端的呼叫方式。StreamManagerClient处理流的方法。有关方法及其参数的实现详细信息,请使用指向每个片段后面列出的开发工具包参考的链接。

如果您在 Lambda 函数中使用流管理器,您的 Lambda 函数应该实例化StreamManagerClient在函数处理程序之外。如果在处理程序中进行实例化,该函数每次被调用时都会创建一个 client 并连接到流管理器。

注意

如果在处理程序中实例化 StreamManagerClient,则必须在 client 完成其工作时显式调用 close() 方法。否则,client 会保持连接打开,并且另一个线程一直运行,直到脚本退出。

StreamManagerClient 支持以下操作:

创建消息流

要创建流,用户定义的 Greengrass 组件调用 create 方法并传入MessageStreamDefinition对象。此对象指定流的唯一名称,并定义当达到最大流大小时流管理器应如何处理新数据。您可以使用 MessageStreamDefinition 及其数据类型(如 ExportDefinitionStrategyOnFullPersistence)来定义其他流属性。其中包括:

  • 目标Amazon IoT Analytics,Kinesis Data Streams,Amazon IoT SiteWise,以及用于自动导出的 Amazon S3 目标。有关更多信息,请参阅 导出配置以获得支持Amazon Web Services 云目的地

  • 导出优先级。流管理器先导出优先级较高的流,然后导出优先级较低的流。

  • 的最大批处理大小和批处理间隔Amazon IoT Analytics、Kinesis Data StreamsAmazon IoT SiteWise目标。当满足任一条件时,流管理器导出消息。

  • 生存时间 (TTL)。保证流数据可用于处理的时间量。您应确保数据可以在此时间段内使用。这不是删除策略。TTL 期限后可能不会立即删除数据。

  • 流持久性。选择将流保存到文件系统,以便在核心重新启动期间保留数据或将流保存在内存中。

  • 起始序列号。指定要在导出中用作起始消息的消息的序列号。

有关 的更多信息MessageStreamDefinition,请参阅目标语言的开发工具包参考:

注意

StreamManagerClient还提供了一个可用于将流导出到 HTTP 服务器的目标。此目标仅用于测试目的。它不稳定或支持在生产环境中使用。

创建流后,Greengrass 组件可以添加消息转到直播以发送数据进行导出和读取消息从直播中进行本地处理。您创建的流数量取决于您的硬件功能和业务案例。一种策略是为中的每个目标通道创建一个流。Amazon IoT Analytics或 Kinesis 数据流,尽管您可以为一个流定义多个目标。流具有持久的使用寿命。

要求

此操作具有以下要求:

  • 流管理器开发工具包版本:Python:1.1.0 | Java:1.1.0 | Node.js:1.1.0

示例

以下代码段创建一个名为 StreamName 的流。它在中定义流属性MessageStreamDefinition以及从属数据类型。

Python
client = StreamManagerClient() try: client.create_message_stream(MessageStreamDefinition( name="StreamName", # Required. max_size=268435456, # Default is 256 MB. stream_segment_size=16777216, # Default is 16 MB. time_to_live_millis=None, # By default, no TTL is enabled. strategy_on_full=StrategyOnFull.OverwriteOldestData, # Required. persistence=Persistence.File, # Default is File. flush_on_write=False, # Default is false. export_definition=ExportDefinition( # Optional. Choose where/how the stream is exported to the Amazon Web Services 云. kinesis=None, iot_analytics=None, iot_sitewise=None, s3_task_executor=None ) )) except StreamManagerException: pass # Properly handle errors. except ConnectionError or asyncio.TimeoutError: pass # Properly handle errors.

Python 开发工具包参考:create_message_stream|MessageStreamDefinition

Java
try (final StreamManagerClient client = StreamManagerClientFactory.standard().build()) { client.createMessageStream( new MessageStreamDefinition() .withName("StreamName") // Required. .withMaxSize(268435456L) // Default is 256 MB. .withStreamSegmentSize(16777216L) // Default is 16 MB. .withTimeToLiveMillis(null) // By default, no TTL is enabled. .withStrategyOnFull(StrategyOnFull.OverwriteOldestData) // Required. .withPersistence(Persistence.File) // Default is File. .withFlushOnWrite(false) // Default is false. .withExportDefinition( // Optional. Choose where/how the stream is exported to the Amazon Web Services 云. new ExportDefinition() .withKinesis(null) .withIotAnalytics(null) .withIotSiteWise(null) .withS3(null) ) ); } catch (StreamManagerException e) { // Properly handle exception. }

Java SDK 参考:createMessageStream|MessageStreamDefinition

Node.js
const client = new StreamManagerClient(); client.onConnected(async () => { try { await client.createMessageStream( new MessageStreamDefinition() .withName("StreamName") // Required. .withMaxSize(268435456) // Default is 256 MB. .withStreamSegmentSize(16777216) // Default is 16 MB. .withTimeToLiveMillis(null) // By default, no TTL is enabled. .withStrategyOnFull(StrategyOnFull.OverwriteOldestData) // Required. .withPersistence(Persistence.File) // Default is File. .withFlushOnWrite(false) // Default is false. .withExportDefinition( // Optional. Choose where/how the stream is exported to the Amazon Web Services 云. new ExportDefinition() .withKinesis(null) .withIotAnalytics(null) .withIotSiteWise(null) .withS3(null) ) ); } catch (e) { // Properly handle errors. } }); client.onError((err) => { // Properly handle connection errors. // This is called only when the connection to the StreamManager server fails. });

Node.js 开发工具包参考:createMessageStream|MessageStreamDefinition

有关配置导出目标的更多信息,请参阅导出配置以获得支持Amazon Web Services 云目的地.

附加消息

要将数据发送到流管理器以导出,您的 Greengrass 组件会将数据附加到目标流。导出目标决定要传递给此方法的数据类型。

要求

此操作具有以下要求:

  • 流管理器开发工具包版本:Python:1.1.0 | Java:1.1.0 | Node.js:1.1.0

示例

Amazon IoT Analytics或 Kinesis Data Streams 导出目标

以下代码段将消息附加到名为 StreamName 的流。适用于Amazon IoT Analytics或者 Kinesis Data Streams 目标,您的 Greengrass 组件会附加一组数据。

此代码段具有以下要求:

  • 流管理器开发工具包版本:Python:1.1.0 | Java:1.1.0 | Node.js:1.1.0

Python
client = StreamManagerClient() try: sequence_number = client.append_message(stream_name="StreamName", data=b'Arbitrary bytes data') except StreamManagerException: pass # Properly handle errors. except ConnectionError or asyncio.TimeoutError: pass # Properly handle errors.

Python 开发工具包参考:append_message

Java
try (final StreamManagerClient client = StreamManagerClientFactory.standard().build()) { long sequenceNumber = client.appendMessage("StreamName", "Arbitrary byte array".getBytes()); } catch (StreamManagerException e) { // Properly handle exception. }

Java SDK 参考:appendMessage

Node.js
const client = new StreamManagerClient(); client.onConnected(async () => { try { const sequenceNumber = await client.appendMessage("StreamName", Buffer.from("Arbitrary byte array")); } catch (e) { // Properly handle errors. } }); client.onError((err) => { // Properly handle connection errors. // This is called only when the connection to the StreamManager server fails. });

Node.js 开发工具包参考:appendMessage

Amazon IoT SiteWise出口目标

以下代码段将消息附加到名为 StreamName 的流。适用于Amazon IoT SiteWise目的地,你的 Greengrass 组件会附加序列化PutAssetPropertyValueEntry对象。有关更多信息,请参阅 导出到 Amazon IoT SiteWise

注意

当你将数据发送给Amazon IoT SiteWise,您的数据必须满足BatchPutAssetPropertyValueaction. 有关更多信息,请参阅 Amazon IoT SiteWise API 参考中的 BatchPutAssetPropertyValue

此代码段具有以下要求:

  • 流管理器开发工具包版本:Python:1.1.0 | Java:1.1.0 | Node.js:1.1.0

Python
client = StreamManagerClient() try: # SiteWise requires unique timestamps in all messages and also needs timestamps not earlier # than 10 minutes in the past. Add some randomness to time and offset. # Note: To create a new asset property data, you should use the classes defined in the # greengrasssdk.stream_manager module. time_in_nanos = TimeInNanos( time_in_seconds=calendar.timegm(time.gmtime()) - random.randint(0, 60), offset_in_nanos=random.randint(0, 10000) ) variant = Variant(double_value=random.random()) asset = [AssetPropertyValue(value=variant, quality=Quality.GOOD, timestamp=time_in_nanos)] putAssetPropertyValueEntry = PutAssetPropertyValueEntry(entry_id=str(uuid.uuid4()), property_alias="PropertyAlias", property_values=asset) sequence_number = client.append_message(stream_name="StreamName", Util.validate_and_serialize_to_json_bytes(putAssetPropertyValueEntry)) except StreamManagerException: pass # Properly handle errors. except ConnectionError or asyncio.TimeoutError: pass # Properly handle errors.

Python 开发工具包参考:append_message|PutAssetPropertyValueEntry

Java
try (final StreamManagerClient client = GreengrassClientBuilder.streamManagerClient().build()) { Random rand = new Random(); // Note: To create a new asset property data, you should use the classes defined in the // com.amazonaws.greengrass.streammanager.model.sitewise package. List<AssetPropertyValue> entries = new ArrayList<>() ; // IoTSiteWise requires unique timestamps in all messages and also needs timestamps not earlier // than 10 minutes in the past. Add some randomness to time and offset. final int maxTimeRandomness = 60; final int maxOffsetRandomness = 10000; double randomValue = rand.nextDouble(); TimeInNanos timestamp = new TimeInNanos() .withTimeInSeconds(Instant.now().getEpochSecond() - rand.nextInt(maxTimeRandomness)) .withOffsetInNanos((long) (rand.nextInt(maxOffsetRandomness))); AssetPropertyValue entry = new AssetPropertyValue() .withValue(new Variant().withDoubleValue(randomValue)) .withQuality(Quality.GOOD) .withTimestamp(timestamp); entries.add(entry); PutAssetPropertyValueEntry putAssetPropertyValueEntry = new PutAssetPropertyValueEntry() .withEntryId(UUID.randomUUID().toString()) .withPropertyAlias("PropertyAlias") .withPropertyValues(entries); long sequenceNumber = client.appendMessage("StreamName", ValidateAndSerialize.validateAndSerializeToJsonBytes(putAssetPropertyValueEntry)); } catch (StreamManagerException e) { // Properly handle exception. }

Java SDK 参考:appendMessage|PutAssetPropertyValueEntry

Node.js
const client = new StreamManagerClient(); client.onConnected(async () => { try { const maxTimeRandomness = 60; const maxOffsetRandomness = 10000; const randomValue = Math.random(); // Note: To create a new asset property data, you should use the classes defined in the // aws-greengrass-core-sdk StreamManager module. const timestamp = new TimeInNanos() .withTimeInSeconds(Math.round(Date.now() / 1000) - Math.floor(Math.random() - maxTimeRandomness)) .withOffsetInNanos(Math.floor(Math.random() * maxOffsetRandomness)); const entry = new AssetPropertyValue() .withValue(new Variant().withDoubleValue(randomValue)) .withQuality(Quality.GOOD) .withTimestamp(timestamp); const putAssetPropertyValueEntry = new PutAssetPropertyValueEntry() .withEntryId(`${ENTRY_ID_PREFIX}${i}`) .withPropertyAlias("PropertyAlias") .withPropertyValues([entry]); const sequenceNumber = await client.appendMessage("StreamName", util.validateAndSerializeToJsonBytes(putAssetPropertyValueEntry)); } catch (e) { // Properly handle errors. } }); client.onError((err) => { // Properly handle connection errors. // This is called only when the connection to the StreamManager server fails. });

Node.js 开发工具包参考:appendMessage|PutAssetPropertyValueEntry

Amazon S3 导出目标

以下代码段将导出任务附加到名为的流。StreamName. 对于 Amazon S3 目的地,您的 Greengrass 组件会附加序列化S3ExportTaskDefinition包含有关源输入文件和目标 Amazon S3 对象的信息的对象。如果指定的对象不存在,Stream Manager 会为您创建它。有关更多信息,请参阅 导出到 Amazon S3

此代码段具有以下要求:

  • 流管理器开发工具包版本:Python:1.1.0 | Java:1.1.0 | Node.js:1.1.0

Python
client = StreamManagerClient() try: # Append an Amazon S3 Task definition and print the sequence number. s3_export_task_definition = S3ExportTaskDefinition(input_url="URLToFile", bucket="BucketName", key="KeyName") sequence_number = client.append_message(stream_name="StreamName", Util.validate_and_serialize_to_json_bytes(s3_export_task_definition)) except StreamManagerException: pass # Properly handle errors. except ConnectionError or asyncio.TimeoutError: pass # Properly handle errors.

Python 开发工具包参考:append_message|s3 导出任务定义

Java
try (final StreamManagerClient client = GreengrassClientBuilder.streamManagerClient().build()) { // Append an Amazon S3 export task definition and print the sequence number. S3ExportTaskDefinition s3ExportTaskDefinition = new S3ExportTaskDefinition() .withBucket("BucketName") .withKey("KeyName") .withInputUrl("URLToFile"); long sequenceNumber = client.appendMessage("StreamName", ValidateAndSerialize.validateAndSerializeToJsonBytes(s3ExportTaskDefinition)); } catch (StreamManagerException e) { // Properly handle exception. }

Java SDK 参考:appendMessage|s3 导出任务定义

Node.js
const client = new StreamManagerClient(); client.onConnected(async () => { try { // Append an Amazon S3 export task definition and print the sequence number. const taskDefinition = new S3ExportTaskDefinition() .withBucket("BucketName") .withKey("KeyName") .withInputUrl("URLToFile"); const sequenceNumber = await client.appendMessage("StreamName", util.validateAndSerializeToJsonBytes(taskDefinition))); } catch (e) { // Properly handle errors. } }); client.onError((err) => { // Properly handle connection errors. // This is called only when the connection to the StreamManager server fails. });

Node.js 开发工具包参考:appendMessage|s3 导出任务定义

读取消息

从流中读取消息。

要求

此操作具有以下要求:

  • 流管理器开发工具包版本:Python:1.1.0 | Java:1.1.0 | Node.js:1.1.0

示例

以下代码段读取名为 StreamName 的流中的消息。read 方法接受一个可选 ReadMessagesOptions 对象,该对象指定要开始读取的序列号、要读取的最小数量和最大数量以及读取消息的超时。

Python
client = StreamManagerClient() try: message_list = client.read_messages( stream_name="StreamName", # By default, if no options are specified, it tries to read one message from the beginning of the stream. options=ReadMessagesOptions( desired_start_sequence_number=100, # Try to read from sequence number 100 or greater. By default, this is 0. min_message_count=10, # Try to read 10 messages. If 10 messages are not available, then NotEnoughMessagesException is raised. By default, this is 1. max_message_count=100, # Accept up to 100 messages. By default this is 1. read_timeout_millis=5000 # Try to wait at most 5 seconds for the min_messsage_count to be fulfilled. By default, this is 0, which immediately returns the messages or an exception. ) ) except StreamManagerException: pass # Properly handle errors. except ConnectionError or asyncio.TimeoutError: pass # Properly handle errors.

Python 开发工具包参考:read_messages|ReadMessagesOptions

Java
try (final StreamManagerClient client = StreamManagerClientFactory.standard().build()) { List<Message> messages = client.readMessages("StreamName", // By default, if no options are specified, it tries to read one message from the beginning of the stream. new ReadMessagesOptions() // Try to read from sequence number 100 or greater. By default this is 0. .withDesiredStartSequenceNumber(100L) // Try to read 10 messages. If 10 messages are not available, then NotEnoughMessagesException is raised. By default, this is 1. .withMinMessageCount(10L) // Accept up to 100 messages. By default this is 1. .withMaxMessageCount(100L) // Try to wait at most 5 seconds for the min_messsage_count to be fulfilled. By default, this is 0, which immediately returns the messages or an exception. .withReadTimeoutMillis(Duration.ofSeconds(5L).toMillis()) ); } catch (StreamManagerException e) { // Properly handle exception. }

Java SDK 参考:readMessages|ReadMessagesOptions

Node.js
const client = new StreamManagerClient(); client.onConnected(async () => { try { const messages = await client.readMessages("StreamName", // By default, if no options are specified, it tries to read one message from the beginning of the stream. new ReadMessagesOptions() // Try to read from sequence number 100 or greater. By default this is 0. .withDesiredStartSequenceNumber(100) // Try to read 10 messages. If 10 messages are not available, then NotEnoughMessagesException is thrown. By default, this is 1. .withMinMessageCount(10) // Accept up to 100 messages. By default this is 1. .withMaxMessageCount(100) // Try to wait at most 5 seconds for the minMessageCount to be fulfilled. By default, this is 0, which immediately returns the messages or an exception. .withReadTimeoutMillis(5 * 1000) ); } catch (e) { // Properly handle errors. } }); client.onError((err) => { // Properly handle connection errors. // This is called only when the connection to the StreamManager server fails. });

Node.js 开发工具包参考:readMessages|ReadMessagesOptions

列出流

在流管理器中获取流列表。

要求

此操作具有以下要求:

  • 流管理器开发工具包版本:Python:1.1.0 | Java:1.1.0 | Node.js:1.1.0

示例

以下代码段获取流管理器中的流列表(按名称)。

Python
client = StreamManagerClient() try: stream_names = client.list_streams() except StreamManagerException: pass # Properly handle errors. except ConnectionError or asyncio.TimeoutError: pass # Properly handle errors.

Python 开发工具包参考:list_stream

Java
try (final StreamManagerClient client = StreamManagerClientFactory.standard().build()) { List<String> streamNames = client.listStreams(); } catch (StreamManagerException e) { // Properly handle exception. }

Java SDK 参考:listStreams

Node.js
const client = new StreamManagerClient(); client.onConnected(async () => { try { const streams = await client.listStreams(); } catch (e) { // Properly handle errors. } }); client.onError((err) => { // Properly handle connection errors. // This is called only when the connection to the StreamManager server fails. });

Node.js 开发工具包参考:listStreams

描述消息流

获取有关流的元数据,包括流定义、大小和导出状态。

要求

此操作具有以下要求:

  • 流管理器开发工具包版本:Python:1.1.0 | Java:1.1.0 | Node.js:1.1.0

示例

以下代码段获取有关名为 StreamName 的流的元数据,包括流的定义、大小和导出程序状态。

Python
client = StreamManagerClient() try: stream_description = client.describe_message_stream(stream_name="StreamName") if stream_description.export_statuses[0].error_message: # The last export of export destination 0 failed with some error # Here is the last sequence number that was successfully exported stream_description.export_statuses[0].last_exported_sequence_number if (stream_description.storage_status.newest_sequence_number > stream_description.export_statuses[0].last_exported_sequence_number): pass # The end of the stream is ahead of the last exported sequence number except StreamManagerException: pass # Properly handle errors. except ConnectionError or asyncio.TimeoutError: pass # Properly handle errors.

Python 开发工具包参考:describe_message_stream

Java
try (final StreamManagerClient client = StreamManagerClientFactory.standard().build()) { MessageStreamInfo description = client.describeMessageStream("StreamName"); String lastErrorMessage = description.getExportStatuses().get(0).getErrorMessage(); if (lastErrorMessage != null && !lastErrorMessage.equals("")) { // The last export of export destination 0 failed with some error. // Here is the last sequence number that was successfully exported. description.getExportStatuses().get(0).getLastExportedSequenceNumber(); } if (description.getStorageStatus().getNewestSequenceNumber() > description.getExportStatuses().get(0).getLastExportedSequenceNumber()) { // The end of the stream is ahead of the last exported sequence number. } } catch (StreamManagerException e) { // Properly handle exception. }

Java SDK 参考:describeMessageStream

Node.js
const client = new StreamManagerClient(); client.onConnected(async () => { try { const description = await client.describeMessageStream("StreamName"); const lastErrorMessage = description.exportStatuses[0].errorMessage; if (lastErrorMessage) { // The last export of export destination 0 failed with some error. // Here is the last sequence number that was successfully exported. description.exportStatuses[0].lastExportedSequenceNumber; } if (description.storageStatus.newestSequenceNumber > description.exportStatuses[0].lastExportedSequenceNumber) { // The end of the stream is ahead of the last exported sequence number. } } catch (e) { // Properly handle errors. } }); client.onError((err) => { // Properly handle connection errors. // This is called only when the connection to the StreamManager server fails. });

Node.js 开发工具包参考:describeMessageStream

更新消息流

更新现有流的属性。如果在创建直播后需求发生变化,则可能需要更新直播。例如:

  • 添加新导出配置为了Amazon Web Services 云目标。

  • 增加流的最大大小以更改导出或保留数据的方式。例如,流大小与完整设置的策略相结合可能会导致数据在直播管理器处理之前被删除或拒绝。

  • 暂停并恢复导出;例如,如果导出任务长时间运行并且您想对上传数据进行配置。

您的 Greengrass 组件遵循以下高级流程来更新直播:

  1. 获取流的描述。

  2. 更新相应的目标属性MessageStreamDefinition和从属对象。

  3. 传递更新的MessageStreamDefinition. 确保包含更新后的直播的完整对象定义。未定义的属性恢复为默认值。

    您可以指定要在导出中用作起始消息的消息的序列号。

要求

此操作具有以下要求:

  • 流管理器开发工具包版本:Python:1.1.0 | Java:1.1.0 | Node.js:1.1.0

示例

以下代码段更新名为的流。StreamName. 它更新导出到 Kinesis Data Streams 的流的多个属性。

Python
client = StreamManagerClient() try: message_stream_info = client.describe_message_stream(STREAM_NAME) message_stream_info.definition.max_size=536870912 message_stream_info.definition.stream_segment_size=33554432 message_stream_info.definition.time_to_live_millis=3600000 message_stream_info.definition.strategy_on_full=StrategyOnFull.RejectNewData message_stream_info.definition.persistence=Persistence.Memory message_stream_info.definition.flush_on_write=False message_stream_info.definition.export_definition.kinesis= [KinesisConfig( # Updating Export definition to add a Kinesis Stream configuration. identifier=str(uuid.uuid4()), kinesis_stream_name=str(uuid.uuid4()))] client.update_message_stream(message_stream_info.definition) except StreamManagerException: pass # Properly handle errors. except ConnectionError or asyncio.TimeoutError: pass # Properly handle errors.

Python 开发工具包参考:更新 MessageStream|MessageStreamDefinition

Java
try (final StreamManagerClient client = GreengrassClientBuilder.streamManagerClient().build()) { MessageStreamInfo messageStreamInfo = client.describeMessageStream(STREAM_NAME); // Update the message stream with new values. client.updateMessageStream( messageStreamInfo.getDefinition() .withStrategyOnFull(StrategyOnFull.RejectNewData) // Required. Updating Strategy on full to reject new data. // Max Size update should be greater than initial Max Size defined in Create Message Stream request .withMaxSize(536870912L) // Update Max Size to 512 MB. .withStreamSegmentSize(33554432L) // Update Segment Size to 32 MB. .withFlushOnWrite(true) // Update flush on write to true. .withPersistence(Persistence.Memory) // Update the persistence to Memory. .withTimeToLiveMillis(3600000L) // Update TTL to 1 hour. .withExportDefinition( // Optional. Choose where/how the stream is exported to the Amazon Web Services 云. messageStreamInfo.getDefinition().getExportDefinition(). // Updating Export definition to add a Kinesis Stream configuration. .withKinesis(new ArrayList<KinesisConfig>() {{ add(new KinesisConfig() .withIdentifier(EXPORT_IDENTIFIER) .withKinesisStreamName("test")); }}) ); } catch (StreamManagerException e) { // Properly handle exception. }

Java SDK 参考:update_message _stream|MessageStreamDefinition

Node.js
const client = new StreamManagerClient(); client.onConnected(async () => { try { const messageStreamInfo = await c.describeMessageStream(STREAM_NAME); await client.updateMessageStream( messageStreamInfo.definition // Max Size update should be greater than initial Max Size defined in Create Message Stream request .withMaxSize(536870912) // Default is 256 MB. Updating Max Size to 512 MB. .withStreamSegmentSize(33554432) // Default is 16 MB. Updating Segment Size to 32 MB. .withTimeToLiveMillis(3600000) // By default, no TTL is enabled. Update TTL to 1 hour. .withStrategyOnFull(StrategyOnFull.RejectNewData) // Required. Updating Strategy on full to reject new data. .withPersistence(Persistence.Memory) // Default is File. Update the persistence to Memory .withFlushOnWrite(true) // Default is false. Updating to true. .withExportDefinition( // Optional. Choose where/how the stream is exported to the Amazon Web Services 云. messageStreamInfo.definition.exportDefinition // Updating Export definition to add a Kinesis Stream configuration. .withKinesis([new KinesisConfig().withIdentifier(uuidv4()).withKinesisStreamName(uuidv4())]) ) ); } catch (e) { // Properly handle errors. } }); client.onError((err) => { // Properly handle connection errors. // This is called only when the connection to the StreamManager server fails. });

Node.js 开发工具包参考:更新 MessageStream|MessageStreamDefinition

更新流的限制

更新流时,以下约束适用。除非以下列表中另有说明,否则更新将立即生效。

  • 您无法更新流的持久性。要更改此行为,删除流创建流这定义了新的持久性策略。

  • 只有在以下条件下,您可以更新流的最大大小:

    • 最大大小必须大于等于流的当前大小。要查找这些信息,描述流然后检查退货的存储状态MessageStreamInfo对象。

    • 最大大小必须大于等于流的段大小。

  • 您可以将流片段大小更新为小于流的最大大小的值。更新后的设置适用于新区段。

  • 更新生存时间 (TTL) 属性适用于新追加操作。如果降低此值,直播管理器还可能会删除超过 TTL 的现有区段。

  • 对全部财产策略的更新适用于新的追加操作。如果您将策略设置为覆盖最旧的数据,则流管理器还可能会根据新设置覆盖现有区段。

  • 对 write 时刷新属性的更新适用于新消息。

  • 导出配置的更新适用于新的导出。更新请求必须包括您想支持的所有导出配置。否则,直播管理器将删除它们。

    • 更新导出配置时,请指定目标导出配置的标识符。

    • 要添加导出配置,请为新导出配置指定唯一标识符。

    • 要删除导出配置,请省略导出配置。

  • 目的更新流中导出配置的起始序列号,您必须指定一个小于最新序列号的值。要查找这些信息,描述流然后检查退货的存储状态MessageStreamInfo对象。

删除消息流

删除流。删除流时,流的所有存储数据将从磁盘中删除。

要求

此操作具有以下要求:

  • 流管理器开发工具包版本:Python:1.1.0 | Java:1.1.0 | Node.js:1.1.0

示例

以下代码段删除名为 StreamName 的流。

Python
client = StreamManagerClient() try: client.delete_message_stream(stream_name="StreamName") except StreamManagerException: pass # Properly handle errors. except ConnectionError or asyncio.TimeoutError: pass # Properly handle errors.

Python 开发工具包参考:deleteMessageStream

Java
try (final StreamManagerClient client = StreamManagerClientFactory.standard().build()) { client.deleteMessageStream("StreamName"); } catch (StreamManagerException e) { // Properly handle exception. }

Java SDK 参考:delete_message_stream

Node.js
const client = new StreamManagerClient(); client.onConnected(async () => { try { await client.deleteMessageStream("StreamName"); } catch (e) { // Properly handle errors. } }); client.onError((err) => { // Properly handle connection errors. // This is called only when the connection to the StreamManager server fails. });

Node.js 开发工具包参考:deleteMessageStream

另请参阅