Batches schreiben Batches mit gemeinsamen Attributen schreiben Verärgert Beispiel für ein Attribut mit mehreren Kennzahlen Umgang mit Schreibfehlern

Daten schreiben (Einfügungen und Upserts)

Themen

Stapel von Datensätzen schreiben
Schreiben von Datensatzstapeln mit gemeinsamen Attributen
Datensätze werden aktualisiert
Beispiel für ein Attribut mit mehreren Kennzahlen
Behandlung von Schreibfehlern

Stapel von Datensätzen schreiben

Sie können die folgenden Codefragmente verwenden, um Daten in eine Amazon Timestream-Tabelle zu schreiben. Das Schreiben von Daten in Batches hilft dabei, die Schreibkosten zu optimieren. Weitere Informationen finden Sie unter Berechnung der Anzahl der Schreibvorgänge.

Anmerkung

Diese Codefragmente basieren auf vollständigen Beispielanwendungen auf. GitHub Weitere Informationen zu den ersten Schritten mit den Beispielanwendungen finden Sie unter. Beispielanwendung

Java


  public void writeRecords() {
    System.out.println("Writing records");
    // Specify repeated values for all records
    List<Record> records = new ArrayList<>();
    final long time = System.currentTimeMillis();

    List<Dimension> dimensions = new ArrayList<>();
    final Dimension region = new Dimension().withName("region").withValue("us-east-1");
    final Dimension az = new Dimension().withName("az").withValue("az1");
    final Dimension hostname = new Dimension().withName("hostname").withValue("host1");

    dimensions.add(region);
    dimensions.add(az);
    dimensions.add(hostname);

    Record cpuUtilization = new Record()
        .withDimensions(dimensions)
        .withMeasureName("cpu_utilization")
        .withMeasureValue("13.5")
        .withMeasureValueType(MeasureValueType.DOUBLE)
        .withTime(String.valueOf(time));
    Record memoryUtilization = new Record()
        .withDimensions(dimensions)
        .withMeasureName("memory_utilization")
        .withMeasureValue("40")
        .withMeasureValueType(MeasureValueType.DOUBLE)
        .withTime(String.valueOf(time));

    records.add(cpuUtilization);
    records.add(memoryUtilization);

    WriteRecordsRequest writeRecordsRequest = new WriteRecordsRequest()
        .withDatabaseName(DATABASE_NAME)
        .withTableName(TABLE_NAME)
        .withRecords(records);

    try {
      WriteRecordsResult writeRecordsResult = amazonTimestreamWrite.writeRecords(writeRecordsRequest);
      System.out.println("WriteRecords Status: " + writeRecordsResult.getSdkHttpMetadata().getHttpStatusCode());
    } catch (RejectedRecordsException e) {
      System.out.println("RejectedRecords: " + e);
      for (RejectedRecord rejectedRecord : e.getRejectedRecords()) {
        System.out.println("Rejected Index " + rejectedRecord.getRecordIndex() + ": "
            + rejectedRecord.getReason());
      }
      System.out.println("Other records were written successfully. ");
    } catch (Exception e) {
      System.out.println("Error: " + e);
    }
  }

Java v2


  public void writeRecords() {
    System.out.println("Writing records");
    // Specify repeated values for all records
    List<Record> records = new ArrayList<>();
    final long time = System.currentTimeMillis();

    List<Dimension> dimensions = new ArrayList<>();
    final Dimension region = Dimension.builder().name("region").value("us-east-1").build();
    final Dimension az = Dimension.builder().name("az").value("az1").build();
    final Dimension hostname = Dimension.builder().name("hostname").value("host1").build();

    dimensions.add(region);
    dimensions.add(az);
    dimensions.add(hostname);

    Record cpuUtilization = Record.builder()
        .dimensions(dimensions)
        .measureValueType(MeasureValueType.DOUBLE)
        .measureName("cpu_utilization")
        .measureValue("13.5")
        .time(String.valueOf(time)).build();

    Record memoryUtilization = Record.builder()
        .dimensions(dimensions)
        .measureValueType(MeasureValueType.DOUBLE)
        .measureName("memory_utilization")
        .measureValue("40")
        .time(String.valueOf(time)).build();

    records.add(cpuUtilization);
    records.add(memoryUtilization);

    WriteRecordsRequest writeRecordsRequest = WriteRecordsRequest.builder()
        .databaseName(DATABASE_NAME).tableName(TABLE_NAME).records(records).build();

    try {
      WriteRecordsResponse writeRecordsResponse = timestreamWriteClient.writeRecords(writeRecordsRequest);
      System.out.println("WriteRecords Status: " + writeRecordsResponse.sdkHttpResponse().statusCode());
    } catch (RejectedRecordsException e) {
      System.out.println("RejectedRecords: " + e);
      for (RejectedRecord rejectedRecord : e.rejectedRecords()) {
        System.out.println("Rejected Index " + rejectedRecord.recordIndex() + ": "
            + rejectedRecord.reason());
      }
      System.out.println("Other records were written successfully. ");
    } catch (Exception e) {
      System.out.println("Error: " + e);
    }
  }

Go


now := time.Now()
currentTimeInSeconds := now.Unix()
writeRecordsInput := &timestreamwrite.WriteRecordsInput{
  DatabaseName: aws.String(*databaseName),
  TableName:  aws.String(*tableName),
  Records: []*timestreamwrite.Record{
    &timestreamwrite.Record{
      Dimensions: []*timestreamwrite.Dimension{
        &timestreamwrite.Dimension{
          Name:  aws.String("region"),
          Value: aws.String("us-east-1"),
        },
        &timestreamwrite.Dimension{
          Name:  aws.String("az"),
          Value: aws.String("az1"),
        },
        &timestreamwrite.Dimension{
          Name:  aws.String("hostname"),
          Value: aws.String("host1"),
        },
      },
      MeasureName:    aws.String("cpu_utilization"),
      MeasureValue:   aws.String("13.5"),
      MeasureValueType: aws.String("DOUBLE"),
      Time:       aws.String(strconv.FormatInt(currentTimeInSeconds, 10)),
      TimeUnit:  aws.String("SECONDS"),
    },
    &timestreamwrite.Record{
      Dimensions: []*timestreamwrite.Dimension{
        &timestreamwrite.Dimension{
          Name:  aws.String("region"),
          Value: aws.String("us-east-1"),
        },
        &timestreamwrite.Dimension{
          Name:  aws.String("az"),
          Value: aws.String("az1"),
        },
        &timestreamwrite.Dimension{
          Name:  aws.String("hostname"),
          Value: aws.String("host1"),
        },
      },
      MeasureName:    aws.String("memory_utilization"),
      MeasureValue:   aws.String("40"),
      MeasureValueType: aws.String("DOUBLE"),
      Time:       aws.String(strconv.FormatInt(currentTimeInSeconds, 10)),
      TimeUnit:  aws.String("SECONDS"),
    },
  },
}

_, err = writeSvc.WriteRecords(writeRecordsInput)

if err != nil {
  fmt.Println("Error:")
  fmt.Println(err)
} else {
  fmt.Println("Write records is successful")
}

Python


  def write_records(self):
    print("Writing records")
    current_time = self._current_milli_time()

    dimensions = [
      {'Name': 'region', 'Value': 'us-east-1'},
      {'Name': 'az', 'Value': 'az1'},
      {'Name': 'hostname', 'Value': 'host1'}
    ]

    cpu_utilization = {
      'Dimensions': dimensions,
      'MeasureName': 'cpu_utilization',
      'MeasureValue': '13.5',
      'MeasureValueType': 'DOUBLE',
      'Time': current_time
    }

    memory_utilization = {
      'Dimensions': dimensions,
      'MeasureName': 'memory_utilization',
      'MeasureValue': '40',
      'MeasureValueType': 'DOUBLE',
      'Time': current_time
    }

    records = [cpu_utilization, memory_utilization]

    try:
      result = self.client.write_records(DatabaseName=Constant.DATABASE_NAME, TableName=Constant.TABLE_NAME,
                         Records=records, CommonAttributes={})
      print("WriteRecords Status: [%s]" % result['ResponseMetadata']['HTTPStatusCode'])
    except self.client.exceptions.RejectedRecordsException as err:
      self._print_rejected_records_exceptions(err)
    except Exception as err:
      print("Error:", err)

  @staticmethod
  def _print_rejected_records_exceptions(err):
    print("RejectedRecords: ", err)
    for rr in err.response["RejectedRecords"]:
      print("Rejected Index " + str(rr["RecordIndex"]) + ": " + rr["Reason"])
      if "ExistingVersion" in rr:
        print("Rejected record existing version: ", rr["ExistingVersion"])

  @staticmethod
  def _current_milli_time():
    return str(int(round(time.time() * 1000)))

Node.js

Der folgende Codeausschnitt verwendet den AWS SDK for JavaScript V2-Stil. Es basiert auf der Beispielanwendung unter Node.js Beispiel Amazon Timestream für die LiveAnalytics Anwendung auf GitHub.


async function writeRecords() {
  console.log("Writing records");
  const currentTime = Date.now().toString(); // Unix time in milliseconds

  const dimensions = [
    {'Name': 'region', 'Value': 'us-east-1'},
    {'Name': 'az', 'Value': 'az1'},
    {'Name': 'hostname', 'Value': 'host1'}
  ];

  const cpuUtilization = {
    'Dimensions': dimensions,
    'MeasureName': 'cpu_utilization',
    'MeasureValue': '13.5',
    'MeasureValueType': 'DOUBLE',
    'Time': currentTime.toString()
  };

  const memoryUtilization = {
    'Dimensions': dimensions,
    'MeasureName': 'memory_utilization',
    'MeasureValue': '40',
    'MeasureValueType': 'DOUBLE',
    'Time': currentTime.toString()
  };

  const records = [cpuUtilization, memoryUtilization];

  const params = {
    DatabaseName: constants.DATABASE_NAME,
    TableName: constants.TABLE_NAME,
    Records: records
  };

  const request = writeClient.writeRecords(params);

  await request.promise().then(
    (data) => {
      console.log("Write records successful");
    },
    (err) => {
      console.log("Error writing records:", err);
      if (err.code === 'RejectedRecordsException') {
        const responsePayload = JSON.parse(request.response.httpResponse.body.toString());
        console.log("RejectedRecords: ", responsePayload.RejectedRecords);
        console.log("Other records were written successfully. ");
      }
    }
  );
}

.NET


   public async Task WriteRecords()
   {
     Console.WriteLine("Writing records");

     DateTimeOffset now = DateTimeOffset.UtcNow;
     string currentTimeString = (now.ToUnixTimeMilliseconds()).ToString();

     List<Dimension> dimensions = new List<Dimension>{
       new Dimension { Name = "region", Value = "us-east-1" },
       new Dimension { Name = "az", Value = "az1" },
       new Dimension { Name = "hostname", Value = "host1" }
     };

     var cpuUtilization = new Record
     {
       Dimensions = dimensions,
       MeasureName = "cpu_utilization",
       MeasureValue = "13.6",
       MeasureValueType = MeasureValueType.DOUBLE,
       Time = currentTimeString
     };

     var memoryUtilization = new Record
     {
       Dimensions = dimensions,
       MeasureName = "memory_utilization",
       MeasureValue = "40",
       MeasureValueType = MeasureValueType.DOUBLE,
       Time = currentTimeString
     };


     List<Record> records = new List<Record> {
       cpuUtilization,
       memoryUtilization
     };

     try
     {
       var writeRecordsRequest = new WriteRecordsRequest
       {
         DatabaseName = Constants.DATABASE_NAME,
         TableName = Constants.TABLE_NAME,
         Records = records
       };
       WriteRecordsResponse response = await writeClient.WriteRecordsAsync(writeRecordsRequest);
       Console.WriteLine($"Write records status code: {response.HttpStatusCode.ToString()}");
     }
     catch (RejectedRecordsException e) {
       Console.WriteLine("RejectedRecordsException:" + e.ToString());
       foreach (RejectedRecord rr in e.RejectedRecords) {
         Console.WriteLine("RecordIndex " + rr.RecordIndex + " : " + rr.Reason);
       }
       Console.WriteLine("Other records were written successfully. ");
     }
     catch (Exception e)
     {
       Console.WriteLine("Write records failure:" + e.ToString());
     }
   }

Schreiben von Datensatzstapeln mit gemeinsamen Attributen

Wenn Ihre Zeitreihendaten Kennzahlen und/oder Dimensionen aufweisen, die vielen Datenpunkten gemeinsam sind, können Sie auch die folgende optimierte Version von verwenden, writeRecords API um Daten in Timestream for einzufügen. LiveAnalytics Durch die Verwendung von gemeinsamen Attributen bei der Batchverarbeitung können die Schreibkosten weiter optimiert werden, wie unter beschrieben. Berechnung der Anzahl der Schreibvorgänge

Anmerkung

Diese Codefragmente basieren auf vollständigen Beispielanwendungen auf. GitHub Weitere Informationen zu den ersten Schritten mit den Beispielanwendungen finden Sie unter. Beispielanwendung

Java


  public void writeRecordsWithCommonAttributes() {
    System.out.println("Writing records with extracting common attributes");
    // Specify repeated values for all records
    List<Record> records = new ArrayList<>();
    final long time = System.currentTimeMillis();

    List<Dimension> dimensions = new ArrayList<>();
    final Dimension region = new Dimension().withName("region").withValue("us-east-1");
    final Dimension az = new Dimension().withName("az").withValue("az1");
    final Dimension hostname = new Dimension().withName("hostname").withValue("host1");

    dimensions.add(region);
    dimensions.add(az);
    dimensions.add(hostname);

    Record commonAttributes = new Record()
        .withDimensions(dimensions)
        .withMeasureValueType(MeasureValueType.DOUBLE)
        .withTime(String.valueOf(time));

    Record cpuUtilization = new Record()
        .withMeasureName("cpu_utilization")
        .withMeasureValue("13.5");
    Record memoryUtilization = new Record()
        .withMeasureName("memory_utilization")
        .withMeasureValue("40");

    records.add(cpuUtilization);
    records.add(memoryUtilization);

    WriteRecordsRequest writeRecordsRequest = new WriteRecordsRequest()
        .withDatabaseName(DATABASE_NAME)
        .withTableName(TABLE_NAME)
        .withCommonAttributes(commonAttributes);
    writeRecordsRequest.setRecords(records);

    try {
      WriteRecordsResult writeRecordsResult = amazonTimestreamWrite.writeRecords(writeRecordsRequest);
      System.out.println("writeRecordsWithCommonAttributes Status: " + writeRecordsResult.getSdkHttpMetadata().getHttpStatusCode());
    } catch (RejectedRecordsException e) {
      System.out.println("RejectedRecords: " + e);
      for (RejectedRecord rejectedRecord : e.getRejectedRecords()) {
        System.out.println("Rejected Index " + rejectedRecord.getRecordIndex() + ": "
            + rejectedRecord.getReason());
      }
      System.out.println("Other records were written successfully. ");
    } catch (Exception e) {
      System.out.println("Error: " + e);
    }
  }

Java v2


  public void writeRecordsWithCommonAttributes() {
    System.out.println("Writing records with extracting common attributes");
    // Specify repeated values for all records
    List<Record> records = new ArrayList<>();
    final long time = System.currentTimeMillis();

    List<Dimension> dimensions = new ArrayList<>();
    final Dimension region = Dimension.builder().name("region").value("us-east-1").build();
    final Dimension az = Dimension.builder().name("az").value("az1").build();
    final Dimension hostname = Dimension.builder().name("hostname").value("host1").build();

    dimensions.add(region);
    dimensions.add(az);
    dimensions.add(hostname);

    Record commonAttributes = Record.builder()
        .dimensions(dimensions)
        .measureValueType(MeasureValueType.DOUBLE)
        .time(String.valueOf(time)).build();

    Record cpuUtilization = Record.builder()
        .measureName("cpu_utilization")
        .measureValue("13.5").build();
    Record memoryUtilization = Record.builder()
        .measureName("memory_utilization")
        .measureValue("40").build();

    records.add(cpuUtilization);
    records.add(memoryUtilization);

    WriteRecordsRequest writeRecordsRequest = WriteRecordsRequest.builder()
        .databaseName(DATABASE_NAME)
        .tableName(TABLE_NAME)
        .commonAttributes(commonAttributes)
        .records(records).build();

    try {
      WriteRecordsResponse writeRecordsResponse = timestreamWriteClient.writeRecords(writeRecordsRequest);
      System.out.println("writeRecordsWithCommonAttributes Status: " + writeRecordsResponse.sdkHttpResponse().statusCode());
    } catch (RejectedRecordsException e) {
      System.out.println("RejectedRecords: " + e);
      for (RejectedRecord rejectedRecord : e.rejectedRecords()) {
        System.out.println("Rejected Index " + rejectedRecord.recordIndex() + ": "
            + rejectedRecord.reason());
      }
      System.out.println("Other records were written successfully. ");
    } catch (Exception e) {
      System.out.println("Error: " + e);
    }
  }

Go


now = time.Now()
currentTimeInSeconds = now.Unix()
writeRecordsCommonAttributesInput := &timestreamwrite.WriteRecordsInput{
	DatabaseName: aws.String(*databaseName),
	TableName:  aws.String(*tableName),
	CommonAttributes: &timestreamwrite.Record{
		Dimensions: []*timestreamwrite.Dimension{
			&timestreamwrite.Dimension{
				Name:  aws.String("region"),
				Value: aws.String("us-east-1"),
			},
			&timestreamwrite.Dimension{
				Name:  aws.String("az"),
				Value: aws.String("az1"),
			},
			&timestreamwrite.Dimension{
				Name:  aws.String("hostname"),
				Value: aws.String("host1"),
			},
		},
		MeasureValueType: aws.String("DOUBLE"),
		Time:       aws.String(strconv.FormatInt(currentTimeInSeconds, 10)),
		TimeUnit:     aws.String("SECONDS"),
	},
	Records: []*timestreamwrite.Record{
		&timestreamwrite.Record{
			MeasureName:  aws.String("cpu_utilization"),
			MeasureValue: aws.String("13.5"),
		},
		&timestreamwrite.Record{
			MeasureName:  aws.String("memory_utilization"),
			MeasureValue: aws.String("40"),
		},
	},
}

_, err = writeSvc.WriteRecords(writeRecordsCommonAttributesInput)

if err != nil {
	fmt.Println("Error:")
	fmt.Println(err)
} else {
	fmt.Println("Ingest records is successful")
}

Python


  def write_records_with_common_attributes(self):
    print("Writing records extracting common attributes")
    current_time = self._current_milli_time()

    dimensions = [
      {'Name': 'region', 'Value': 'us-east-1'},
      {'Name': 'az', 'Value': 'az1'},
      {'Name': 'hostname', 'Value': 'host1'}
    ]

    common_attributes = {
      'Dimensions': dimensions,
      'MeasureValueType': 'DOUBLE',
      'Time': current_time
    }

    cpu_utilization = {
      'MeasureName': 'cpu_utilization',
      'MeasureValue': '13.5'
    }

    memory_utilization = {
      'MeasureName': 'memory_utilization',
      'MeasureValue': '40'
    }

    records = [cpu_utilization, memory_utilization]

    try:
      result = self.client.write_records(DatabaseName=Constant.DATABASE_NAME, TableName=Constant.TABLE_NAME,
                         Records=records, CommonAttributes=common_attributes)
      print("WriteRecords Status: [%s]" % result['ResponseMetadata']['HTTPStatusCode'])
    except self.client.exceptions.RejectedRecordsException as err:
      self._print_rejected_records_exceptions(err)
    except Exception as err:
      print("Error:", err)

  @staticmethod
  def _print_rejected_records_exceptions(err):
    print("RejectedRecords: ", err)
    for rr in err.response["RejectedRecords"]:
      print("Rejected Index " + str(rr["RecordIndex"]) + ": " + rr["Reason"])
      if "ExistingVersion" in rr:
        print("Rejected record existing version: ", rr["ExistingVersion"])

  @staticmethod
  def _current_milli_time():
    return str(int(round(time.time() * 1000)))

Node.js

Der folgende Codeausschnitt verwendet den AWS SDK for JavaScript V2-Stil. Es basiert auf der Beispielanwendung unter Node.js Beispiel Amazon Timestream für die LiveAnalytics Anwendung auf GitHub.


async function writeRecordsWithCommonAttributes() {
  console.log("Writing records with common attributes");
  const currentTime = Date.now().toString(); // Unix time in milliseconds

  const dimensions = [
    {'Name': 'region', 'Value': 'us-east-1'},
    {'Name': 'az', 'Value': 'az1'},
    {'Name': 'hostname', 'Value': 'host1'}
  ];

  const commonAttributes = {
    'Dimensions': dimensions,
    'MeasureValueType': 'DOUBLE',
    'Time': currentTime.toString()
  };

  const cpuUtilization = {
    'MeasureName': 'cpu_utilization',
    'MeasureValue': '13.5'
  };

  const memoryUtilization = {
    'MeasureName': 'memory_utilization',
    'MeasureValue': '40'
  };

  const records = [cpuUtilization, memoryUtilization];

  const params = {
    DatabaseName: constants.DATABASE_NAME,
    TableName: constants.TABLE_NAME,
    Records: records,
    CommonAttributes: commonAttributes
  };

  const request = writeClient.writeRecords(params);

  await request.promise().then(
    (data) => {
      console.log("Write records successful");
    },
    (err) => {
      console.log("Error writing records:", err);
      if (err.code === 'RejectedRecordsException') {
        const responsePayload = JSON.parse(request.response.httpResponse.body.toString());
        console.log("RejectedRecords: ", responsePayload.RejectedRecords);
        console.log("Other records were written successfully. ");
      }
    }
  );
}

.NET


  public async Task WriteRecordsWithCommonAttributes()
  {
    Console.WriteLine("Writing records with common attributes");

    DateTimeOffset now = DateTimeOffset.UtcNow;
    string currentTimeString = (now.ToUnixTimeMilliseconds()).ToString();

    List<Dimension> dimensions = new List<Dimension>{
      new Dimension { Name = "region", Value = "us-east-1" },
      new Dimension { Name = "az", Value = "az1" },
      new Dimension { Name = "hostname", Value = "host1" }
    };

    var commonAttributes = new Record
    {
      Dimensions = dimensions,
      MeasureValueType = MeasureValueType.DOUBLE,
      Time = currentTimeString
    };

    var cpuUtilization = new Record
    {
      MeasureName = "cpu_utilization",
      MeasureValue = "13.6"
    };

    var memoryUtilization = new Record
    {
      MeasureName = "memory_utilization",
      MeasureValue = "40"
    };


    List<Record> records = new List<Record>();
    records.Add(cpuUtilization);
    records.Add(memoryUtilization);

    try
    {
      var writeRecordsRequest = new WriteRecordsRequest
      {
        DatabaseName = Constants.DATABASE_NAME,
        TableName = Constants.TABLE_NAME,
        Records = records,
        CommonAttributes = commonAttributes
      };
      WriteRecordsResponse response = await writeClient.WriteRecordsAsync(writeRecordsRequest);
      Console.WriteLine($"Write records status code: {response.HttpStatusCode.ToString()}");
    }
    catch (RejectedRecordsException e) {
      Console.WriteLine("RejectedRecordsException:" + e.ToString());
      foreach (RejectedRecord rr in e.RejectedRecords) {
        Console.WriteLine("RecordIndex " + rr.RecordIndex + " : " + rr.Reason);
      }
      Console.WriteLine("Other records were written successfully. ");
    }
    catch (Exception e)
    {
      Console.WriteLine("Write records failure:" + e.ToString());
    }
  }

Datensätze werden aktualisiert

Während die Standardschreibvorgänge in Amazon Timestream der Semantik des ersten Writers folgen, bei der Daten nur als Anhängen gespeichert werden und doppelte Datensätze zurückgewiesen werden, gibt es Anwendungen, für die die Fähigkeit erforderlich ist, Daten mithilfe der Semantik des letzten Writers in Amazon Timestream zu schreiben, bei denen der Datensatz mit der höchsten Version im System gespeichert wird. Es gibt auch Anwendungen, die die Möglichkeit erfordern, bestehende Datensätze zu aktualisieren. Um diesen Szenarien zu begegnen, bietet Amazon Timestream die Möglichkeit, Daten zu ändern. Upsert ist eine Operation, die einen Datensatz in das System einfügt, wenn der Datensatz nicht existiert, oder den Datensatz aktualisiert, falls einer existiert.

Sie können Datensätze aktualisieren, indem Sie sie beim Senden einer Version WriteRecords Anfrage in die Datensatzdefinition aufnehmen. Amazon Timestream speichert den Datensatz mit dem höchsten WertVersion. Das folgende Codebeispiel zeigt, wie Sie Daten ändern können:

Anmerkung

Diese Codefragmente basieren auf vollständigen Beispielanwendungen auf. GitHub Weitere Informationen zu den ersten Schritten mit den Beispielanwendungen finden Sie unter. Beispielanwendung

Java


  public void writeRecordsWithUpsert() {
    System.out.println("Writing records with upsert");
    // Specify repeated values for all records
    List<Record> records = new ArrayList<>();
    final long time = System.currentTimeMillis();
    // To achieve upsert (last writer wins) semantic, one example is to use current time as the version if you are writing directly from the data source
    long version = System.currentTimeMillis();

    List<Dimension> dimensions = new ArrayList<>();
    final Dimension region = new Dimension().withName("region").withValue("us-east-1");
    final Dimension az = new Dimension().withName("az").withValue("az1");
    final Dimension hostname = new Dimension().withName("hostname").withValue("host1");

    dimensions.add(region);
    dimensions.add(az);
    dimensions.add(hostname);

    Record commonAttributes = new Record()
        .withDimensions(dimensions)
        .withMeasureValueType(MeasureValueType.DOUBLE)
        .withTime(String.valueOf(time))
        .withVersion(version);

    Record cpuUtilization = new Record()
        .withMeasureName("cpu_utilization")
        .withMeasureValue("13.5");
    Record memoryUtilization = new Record()
        .withMeasureName("memory_utilization")
        .withMeasureValue("40");

    records.add(cpuUtilization);
    records.add(memoryUtilization);

    WriteRecordsRequest writeRecordsRequest = new WriteRecordsRequest()
        .withDatabaseName(DATABASE_NAME)
        .withTableName(TABLE_NAME)
        .withCommonAttributes(commonAttributes);
    writeRecordsRequest.setRecords(records);

    // write records for first time
    try {
      WriteRecordsResult writeRecordsResult = amazonTimestreamWrite.writeRecords(writeRecordsRequest);
      System.out.println("WriteRecords Status for first time: " + writeRecordsResult.getSdkHttpMetadata().getHttpStatusCode());
    } catch (RejectedRecordsException e) {
      printRejectedRecordsException(e);
    } catch (Exception e) {
      System.out.println("Error: " + e);
    }

    // Successfully retry same writeRecordsRequest with same records and versions, because writeRecords API is idempotent.
    try {
      WriteRecordsResult writeRecordsResult = amazonTimestreamWrite.writeRecords(writeRecordsRequest);
      System.out.println("WriteRecords Status for retry: " + writeRecordsResult.getSdkHttpMetadata().getHttpStatusCode());
    } catch (RejectedRecordsException e) {
      printRejectedRecordsException(e);
    } catch (Exception e) {
      System.out.println("Error: " + e);
    }

    // upsert with lower version, this would fail because a higher version is required to update the measure value.
    version -= 1;
    commonAttributes.setVersion(version);

    cpuUtilization.setMeasureValue("14.5");
    memoryUtilization.setMeasureValue("50");

    List<Record> upsertedRecords = new ArrayList<>();
    upsertedRecords.add(cpuUtilization);
    upsertedRecords.add(memoryUtilization);

    WriteRecordsRequest writeRecordsUpsertRequest = new WriteRecordsRequest()
        .withDatabaseName(DATABASE_NAME)
        .withTableName(TABLE_NAME)
        .withCommonAttributes(commonAttributes);
    writeRecordsUpsertRequest.setRecords(upsertedRecords);

    try {
      WriteRecordsResult writeRecordsUpsertResult = amazonTimestreamWrite.writeRecords(writeRecordsUpsertRequest);
      System.out.println("WriteRecords Status for upsert with lower version: " + writeRecordsUpsertResult.getSdkHttpMetadata().getHttpStatusCode());
    } catch (RejectedRecordsException e) {
      System.out.println("WriteRecords Status for upsert with lower version: ");
      printRejectedRecordsException(e);
    } catch (Exception e) {
      System.out.println("Error: " + e);
    }

    // upsert with higher version as new data in generated
    version = System.currentTimeMillis();
    commonAttributes.setVersion(version);

    writeRecordsUpsertRequest = new WriteRecordsRequest()
        .withDatabaseName(DATABASE_NAME)
        .withTableName(TABLE_NAME)
        .withCommonAttributes(commonAttributes);
    writeRecordsUpsertRequest.setRecords(upsertedRecords);

    try {
      WriteRecordsResult writeRecordsUpsertResult = amazonTimestreamWrite.writeRecords(writeRecordsUpsertRequest);
      System.out.println("WriteRecords Status for upsert with higher version: " + writeRecordsUpsertResult.getSdkHttpMetadata().getHttpStatusCode());
    } catch (RejectedRecordsException e) {
      printRejectedRecordsException(e);
    } catch (Exception e) {
      System.out.println("Error: " + e);
    }
  }

Java v2


  public void writeRecordsWithUpsert() {
    System.out.println("Writing records with upsert");
    // Specify repeated values for all records
    List<Record> records = new ArrayList<>();
    final long time = System.currentTimeMillis();
    // To achieve upsert (last writer wins) semantic, one example is to use current time as the version if you are writing directly from the data source
    long version = System.currentTimeMillis();

    List<Dimension> dimensions = new ArrayList<>();
    final Dimension region = Dimension.builder().name("region").value("us-east-1").build();
    final Dimension az = Dimension.builder().name("az").value("az1").build();
    final Dimension hostname = Dimension.builder().name("hostname").value("host1").build();

    dimensions.add(region);
    dimensions.add(az);
    dimensions.add(hostname);

    Record commonAttributes = Record.builder()
        .dimensions(dimensions)
        .measureValueType(MeasureValueType.DOUBLE)
        .time(String.valueOf(time))
        .version(version)
        .build();

    Record cpuUtilization = Record.builder()
        .measureName("cpu_utilization")
        .measureValue("13.5").build();
    Record memoryUtilization = Record.builder()
        .measureName("memory_utilization")
        .measureValue("40").build();

    records.add(cpuUtilization);
    records.add(memoryUtilization);

    WriteRecordsRequest writeRecordsRequest = WriteRecordsRequest.builder()
        .databaseName(DATABASE_NAME)
        .tableName(TABLE_NAME)
        .commonAttributes(commonAttributes)
        .records(records).build();

    // write records for first time
    try {
      WriteRecordsResponse writeRecordsResponse = timestreamWriteClient.writeRecords(writeRecordsRequest);
      System.out.println("WriteRecords Status for first time: " + writeRecordsResponse.sdkHttpResponse().statusCode());
    } catch (RejectedRecordsException e) {
      printRejectedRecordsException(e);
    } catch (Exception e) {
      System.out.println("Error: " + e);
    }

    // Successfully retry same writeRecordsRequest with same records and versions, because writeRecords API is idempotent.
    try {
      WriteRecordsResponse writeRecordsResponse = timestreamWriteClient.writeRecords(writeRecordsRequest);
      System.out.println("WriteRecords Status for retry: " + writeRecordsResponse.sdkHttpResponse().statusCode());
    } catch (RejectedRecordsException e) {
      printRejectedRecordsException(e);
    } catch (Exception e) {
      System.out.println("Error: " + e);
    }

    // upsert with lower version, this would fail because a higher version is required to update the measure value.
    version -= 1;
    commonAttributes = Record.builder()
        .dimensions(dimensions)
        .measureValueType(MeasureValueType.DOUBLE)
        .time(String.valueOf(time))
        .version(version)
        .build();

    cpuUtilization = Record.builder()
        .measureName("cpu_utilization")
        .measureValue("14.5").build();
    memoryUtilization = Record.builder()
        .measureName("memory_utilization")
        .measureValue("50").build();

    List<Record> upsertedRecords = new ArrayList<>();
    upsertedRecords.add(cpuUtilization);
    upsertedRecords.add(memoryUtilization);

    WriteRecordsRequest writeRecordsUpsertRequest = WriteRecordsRequest.builder()
        .databaseName(DATABASE_NAME)
        .tableName(TABLE_NAME)
        .commonAttributes(commonAttributes)
        .records(upsertedRecords).build();

    try {
      WriteRecordsResponse writeRecordsResponse = timestreamWriteClient.writeRecords(writeRecordsUpsertRequest);
      System.out.println("WriteRecords Status for upsert with lower version: " + writeRecordsResponse.sdkHttpResponse().statusCode());
    } catch (RejectedRecordsException e) {
      System.out.println("WriteRecords Status for upsert with lower version: ");
      printRejectedRecordsException(e);
    } catch (Exception e) {
      System.out.println("Error: " + e);
    }

    // upsert with higher version as new data in generated
    version = System.currentTimeMillis();
    commonAttributes = Record.builder()
        .dimensions(dimensions)
        .measureValueType(MeasureValueType.DOUBLE)
        .time(String.valueOf(time))
        .version(version)
        .build();

    writeRecordsUpsertRequest = WriteRecordsRequest.builder()
        .databaseName(DATABASE_NAME)
        .tableName(TABLE_NAME)
        .commonAttributes(commonAttributes)
        .records(upsertedRecords).build();

    try {
      WriteRecordsResponse writeRecordsUpsertResponse = timestreamWriteClient.writeRecords(writeRecordsUpsertRequest);
      System.out.println("WriteRecords Status for upsert with higher version: " + writeRecordsUpsertResponse.sdkHttpResponse().statusCode());
    } catch (RejectedRecordsException e) {
      printRejectedRecordsException(e);
    } catch (Exception e) {
      System.out.println("Error: " + e);
    }
  }

Go


// Below code will ingest and upsert cpu_utilization and memory_utilization metric for a host on
// region=us-east-1, az=az1, and hostname=host1
fmt.Println("Ingesting records and set version as currentTimeInMills, hit enter to continue")
reader.ReadString('\n')

// Get current time in seconds.
now = time.Now()
currentTimeInSeconds = now.Unix()
// To achieve upsert (last writer wins) semantic, one example is to use current time as the version if you are writing directly from the data source
version := time.Now().Round(time.Millisecond).UnixNano() / 1e6   // set version as currentTimeInMills

writeRecordsCommonAttributesUpsertInput := &timestreamwrite.WriteRecordsInput{
	DatabaseName: aws.String(*databaseName),
	TableName:  aws.String(*tableName),
	CommonAttributes: &timestreamwrite.Record{
		Dimensions: []*timestreamwrite.Dimension{
			&timestreamwrite.Dimension{
				Name:  aws.String("region"),
				Value: aws.String("us-east-1"),
			},
			&timestreamwrite.Dimension{
				Name:  aws.String("az"),
				Value: aws.String("az1"),
			},
			&timestreamwrite.Dimension{
				Name:  aws.String("hostname"),
				Value: aws.String("host1"),
			},
		},
		MeasureValueType: aws.String("DOUBLE"),
		Time:       aws.String(strconv.FormatInt(currentTimeInSeconds, 10)),
		TimeUnit:  aws.String("SECONDS"),
		Version:      &version,
	},
	Records: []*timestreamwrite.Record{
		&timestreamwrite.Record{
			MeasureName:  aws.String("cpu_utilization"),
			MeasureValue: aws.String("13.5"),
		},
		&timestreamwrite.Record{
			MeasureName:  aws.String("memory_utilization"),
			MeasureValue: aws.String("40"),
		},
	},
}

// write records for first time
_, err = writeSvc.WriteRecords(writeRecordsCommonAttributesUpsertInput)

if err != nil {
	fmt.Println("Error:")
	fmt.Println(err)
} else {
	fmt.Println("Frist-time write records is successful")
}

fmt.Println("Retry same writeRecordsRequest with same records and versions. Because writeRecords API is idempotent, this will success. hit enter to continue")
reader.ReadString('\n')

_, err = writeSvc.WriteRecords(writeRecordsCommonAttributesUpsertInput)

if err != nil {
	fmt.Println("Error:")
	fmt.Println(err)
} else {
	fmt.Println("Retry write records for same request is successful")
}

fmt.Println("Upsert with lower version, this would fail because a higher version is required to update the measure value. hit enter to continue")
reader.ReadString('\n')
version -= 1
writeRecordsCommonAttributesUpsertInput.CommonAttributes.Version = &version

updated_cpu_utilization := &timestreamwrite.Record{
	MeasureName:    aws.String("cpu_utilization"),
	MeasureValue:   aws.String("14.5"),
}
updated_memory_utilization := &timestreamwrite.Record{
	MeasureName:    aws.String("memory_utilization"),
	MeasureValue:   aws.String("50"),
}


writeRecordsCommonAttributesUpsertInput.Records = []*timestreamwrite.Record{
	updated_cpu_utilization,
	updated_memory_utilization,
}

_, err = writeSvc.WriteRecords(writeRecordsCommonAttributesUpsertInput)

if err != nil {
	fmt.Println("Error:")
	fmt.Println(err)
} else {
	fmt.Println("Write records with lower version is successful")
}

fmt.Println("Upsert with higher version as new data in generated, this would success. hit enter to continue")
reader.ReadString('\n')

version = time.Now().Round(time.Millisecond).UnixNano() / 1e6  // set version as currentTimeInMills
writeRecordsCommonAttributesUpsertInput.CommonAttributes.Version = &version

_, err = writeSvc.WriteRecords(writeRecordsCommonAttributesUpsertInput)

if err != nil {
	fmt.Println("Error:")
	fmt.Println(err)
} else {
	fmt.Println("Write records with higher version is successful")
}

Python


  def write_records_with_upsert(self):
    print("Writing records with upsert")
    current_time = self._current_milli_time()
    # To achieve upsert (last writer wins) semantic, one example is to use current time as the version if you are writing directly from the data source
    version = int(self._current_milli_time())

    dimensions = [
          {'Name': 'region', 'Value': 'us-east-1'},
          {'Name': 'az', 'Value': 'az1'},
          {'Name': 'hostname', 'Value': 'host1'}
        ]

    common_attributes = {
      'Dimensions': dimensions,
      'MeasureValueType': 'DOUBLE',
      'Time': current_time,
      'Version': version
    }

    cpu_utilization = {
      'MeasureName': 'cpu_utilization',
      'MeasureValue': '13.5'
    }

    memory_utilization = {
      'MeasureName': 'memory_utilization',
      'MeasureValue': '40'
    }

    records = [cpu_utilization, memory_utilization]

    # write records for first time
    try:
      result = self.client.write_records(DatabaseName=Constant.DATABASE_NAME, TableName=Constant.TABLE_NAME,
                         Records=records, CommonAttributes=common_attributes)
      print("WriteRecords Status for first time: [%s]" % result['ResponseMetadata']['HTTPStatusCode'])
    except self.client.exceptions.RejectedRecordsException as err:
      self._print_rejected_records_exceptions(err)
    except Exception as err:
      print("Error:", err)

    # Successfully retry same writeRecordsRequest with same records and versions, because writeRecords API is idempotent.
    try:
      result = self.client.write_records(DatabaseName=Constant.DATABASE_NAME, TableName=Constant.TABLE_NAME,
                         Records=records, CommonAttributes=common_attributes)
      print("WriteRecords Status for retry: [%s]" % result['ResponseMetadata']['HTTPStatusCode'])
    except self.client.exceptions.RejectedRecordsException as err:
      self._print_rejected_records_exceptions(err)
    except Exception as err:
      print("Error:", err)

    # upsert with lower version, this would fail because a higher version is required to update the measure value.
    version -= 1
    common_attributes["Version"] = version

    cpu_utilization["MeasureValue"] = '14.5'
    memory_utilization["MeasureValue"] = '50'

    upsertedRecords = [cpu_utilization, memory_utilization]

    try:
      upsertedResult = self.client.write_records(DatabaseName=Constant.DATABASE_NAME, TableName=Constant.TABLE_NAME,
                            Records=upsertedRecords, CommonAttributes=common_attributes)
      print("WriteRecords Status for upsert with lower version: [%s]" % upsertedResult['ResponseMetadata']['HTTPStatusCode'])
    except self.client.exceptions.RejectedRecordsException as err:
      self._print_rejected_records_exceptions(err)
    except Exception as err:
      print("Error:", err)


    # upsert with higher version as new data is generated
    version = int(self._current_milli_time())
    common_attributes["Version"] = version

    try:
      upsertedResult = self.client.write_records(DatabaseName=Constant.DATABASE_NAME, TableName=Constant.TABLE_NAME,
                            Records=upsertedRecords, CommonAttributes=common_attributes)
      print("WriteRecords Upsert Status: [%s]" % upsertedResult['ResponseMetadata']['HTTPStatusCode'])
    except self.client.exceptions.RejectedRecordsException as err:
      self._print_rejected_records_exceptions(err)
    except Exception as err:
      print("Error:", err)

  @staticmethod
  def _current_milli_time():
    return str(int(round(time.time() * 1000)))

Node.js

Der folgende Codeausschnitt verwendet den AWS SDK for JavaScript V2-Stil. Es basiert auf der Beispielanwendung unter Node.js Beispiel Amazon Timestream für die LiveAnalytics Anwendung auf GitHub.


async function writeRecordsWithUpsert() {
  console.log("Writing records with upsert");
  const currentTime = Date.now().toString(); // Unix time in milliseconds
  // To achieve upsert (last writer wins) semantic, one example is to use current time as the version if you are writing directly from the data source
  let version = Date.now();

  const dimensions = [
    {'Name': 'region', 'Value': 'us-east-1'},
    {'Name': 'az', 'Value': 'az1'},
    {'Name': 'hostname', 'Value': 'host1'}
  ];

  const commonAttributes = {
    'Dimensions': dimensions,
    'MeasureValueType': 'DOUBLE',
    'Time': currentTime.toString(),
    'Version': version
  };

  const cpuUtilization = {
    'MeasureName': 'cpu_utilization',
    'MeasureValue': '13.5'
  };

  const memoryUtilization = {
    'MeasureName': 'memory_utilization',
    'MeasureValue': '40'
  };

  const records = [cpuUtilization, memoryUtilization];

  const params = {
    DatabaseName: constants.DATABASE_NAME,
    TableName: constants.TABLE_NAME,
    Records: records,
    CommonAttributes: commonAttributes
  };

  const request = writeClient.writeRecords(params);

  // write records for first time
  await request.promise().then(
    (data) => {
      console.log("Write records successful for first time.");
    },
    (err) => {
      console.log("Error writing records:", err);
      if (err.code === 'RejectedRecordsException') {
        printRejectedRecordsException(request);
      }
    }
  );

  // Successfully retry same writeRecordsRequest with same records and versions, because writeRecords API is idempotent.
  await request.promise().then(
    (data) => {
      console.log("Write records successful for retry.");
    },
    (err) => {
      console.log("Error writing records:", err);
      if (err.code === 'RejectedRecordsException') {
        printRejectedRecordsException(request);
      }
    }
  );

  // upsert with lower version, this would fail because a higher version is required to update the measure value.
  version--;

  const commonAttributesWithLowerVersion = {
    'Dimensions': dimensions,
    'MeasureValueType': 'DOUBLE',
    'Time': currentTime.toString(),
    'Version': version
  };

  const updatedCpuUtilization = {
    'MeasureName': 'cpu_utilization',
    'MeasureValue': '14.5'
  };

  const updatedMemoryUtilization = {
    'MeasureName': 'memory_utilization',
    'MeasureValue': '50'
  };

  const upsertedRecords = [updatedCpuUtilization, updatedMemoryUtilization];

  const upsertedParamsWithLowerVersion = {
    DatabaseName: constants.DATABASE_NAME,
    TableName: constants.TABLE_NAME,
    Records: upsertedRecords,
    CommonAttributes: commonAttributesWithLowerVersion
  };

  const upsertRequestWithLowerVersion = writeClient.writeRecords(upsertedParamsWithLowerVersion);

  await upsertRequestWithLowerVersion.promise().then(
    (data) => {
      console.log("Write records for upsert with lower version successful");
    },
    (err) => {
      console.log("Error writing records:", err);
      if (err.code === 'RejectedRecordsException') {
        printRejectedRecordsException(upsertRequestWithLowerVersion);
      }
    }
  );

  // upsert with higher version as new data in generated
  version = Date.now();

  const commonAttributesWithHigherVersion = {
    'Dimensions': dimensions,
    'MeasureValueType': 'DOUBLE',
    'Time': currentTime.toString(),
    'Version': version
  };

  const upsertedParamsWithHigherVerion = {
    DatabaseName: constants.DATABASE_NAME,
    TableName: constants.TABLE_NAME,
    Records: upsertedRecords,
    CommonAttributes: commonAttributesWithHigherVersion
  };

  const upsertRequestWithHigherVersion = writeClient.writeRecords(upsertedParamsWithHigherVerion);

  await upsertRequestWithHigherVersion.promise().then(
    (data) => {
      console.log("Write records upsert successful with higher version");
    },
    (err) => {
      console.log("Error writing records:", err);
      if (err.code === 'RejectedRecordsException') {
        printRejectedRecordsException(upsertedParamsWithHigherVerion);
      }
    }
  );

}

.NET


  public async Task WriteRecordsWithUpsert()
  {
    Console.WriteLine("Writing records with upsert");

    DateTimeOffset now = DateTimeOffset.UtcNow;
    string currentTimeString = (now.ToUnixTimeMilliseconds()).ToString();
    // To achieve upsert (last writer wins) semantic, one example is to use current time as the version if you are writing directly from the data source
    long version = now.ToUnixTimeMilliseconds();

    List<Dimension> dimensions = new List<Dimension>{
      new Dimension { Name = "region", Value = "us-east-1" },
      new Dimension { Name = "az", Value = "az1" },
      new Dimension { Name = "hostname", Value = "host1" }
    };

    var commonAttributes = new Record
    {
      Dimensions = dimensions,
      MeasureValueType = MeasureValueType.DOUBLE,
      Time = currentTimeString,
      Version = version
    };

    var cpuUtilization = new Record
    {
      MeasureName = "cpu_utilization",
      MeasureValue = "13.6"
    };

    var memoryUtilization = new Record
    {
      MeasureName = "memory_utilization",
      MeasureValue = "40"
    };


    List<Record> records = new List<Record>();
    records.Add(cpuUtilization);
    records.Add(memoryUtilization);

    // write records for first time
    try
    {
      var writeRecordsRequest = new WriteRecordsRequest
      {
        DatabaseName = Constants.DATABASE_NAME,
        TableName = Constants.TABLE_NAME,
        Records = records,
        CommonAttributes = commonAttributes
      };
      WriteRecordsResponse response = await writeClient.WriteRecordsAsync(writeRecordsRequest);
      Console.WriteLine($"WriteRecords Status for first time: {response.HttpStatusCode.ToString()}");
    }
    catch (RejectedRecordsException e) {
      PrintRejectedRecordsException(e);
    }
    catch (Exception e)
    {
      Console.WriteLine("Write records failure:" + e.ToString());
    }

    // Successfully retry same writeRecordsRequest with same records and versions, because writeRecords API is idempotent.
    try
    {
      var writeRecordsRequest = new WriteRecordsRequest
      {
        DatabaseName = Constants.DATABASE_NAME,
        TableName = Constants.TABLE_NAME,
        Records = records,
        CommonAttributes = commonAttributes
      };
      WriteRecordsResponse response = await writeClient.WriteRecordsAsync(writeRecordsRequest);
      Console.WriteLine($"WriteRecords Status for retry: {response.HttpStatusCode.ToString()}");
    }
    catch (RejectedRecordsException e) {
      PrintRejectedRecordsException(e);
    }
    catch (Exception e)
    {
      Console.WriteLine("Write records failure:" + e.ToString());
    }

    // upsert with lower version, this would fail because a higher version is required to update the measure value.
    version--;
    Type recordType = typeof(Record);
    recordType.GetProperty("Version").SetValue(commonAttributes, version);
    recordType.GetProperty("MeasureValue").SetValue(cpuUtilization, "14.6");
    recordType.GetProperty("MeasureValue").SetValue(memoryUtilization, "50");

    List<Record> upsertedRecords = new List<Record> {
      cpuUtilization,
      memoryUtilization
    };

    try
    {
      var writeRecordsUpsertRequest = new WriteRecordsRequest
      {
        DatabaseName = Constants.DATABASE_NAME,
        TableName = Constants.TABLE_NAME,
        Records = upsertedRecords,
        CommonAttributes = commonAttributes
      };
      WriteRecordsResponse upsertResponse = await writeClient.WriteRecordsAsync(writeRecordsUpsertRequest);
      Console.WriteLine($"WriteRecords Status for upsert with lower version: {upsertResponse.HttpStatusCode.ToString()}");
    }
    catch (RejectedRecordsException e) {
      PrintRejectedRecordsException(e);
    }
    catch (Exception e)
    {
      Console.WriteLine("Write records failure:" + e.ToString());
    }

    // upsert with higher version as new data in generated
    now = DateTimeOffset.UtcNow;
    version = now.ToUnixTimeMilliseconds();
    recordType.GetProperty("Version").SetValue(commonAttributes, version);

    try
    {
      var writeRecordsUpsertRequest = new WriteRecordsRequest
      {
        DatabaseName = Constants.DATABASE_NAME,
        TableName = Constants.TABLE_NAME,
        Records = upsertedRecords,
        CommonAttributes = commonAttributes
      };
      WriteRecordsResponse upsertResponse = await writeClient.WriteRecordsAsync(writeRecordsUpsertRequest);
      Console.WriteLine($"WriteRecords Status for upsert with higher version:  {upsertResponse.HttpStatusCode.ToString()}");
    }
    catch (RejectedRecordsException e) {
      PrintRejectedRecordsException(e);
    }
    catch (Exception e)
    {
      Console.WriteLine("Write records failure:" + e.ToString());
    }
  }

Beispiel für ein Attribut mit mehreren Kennzahlen

Dieses Beispiel veranschaulicht das Schreiben von Attributen mit mehreren Kennzahlen. Attribute mit mehreren Kennzahlen sind nützlich, wenn ein Gerät oder eine Anwendung, die Sie verfolgen, mehrere Messwerte oder Ereignisse gleichzeitig ausgibt.

Anmerkung

Diese Codefragmente basieren auf vollständigen Beispielanwendungen auf. GitHub Weitere Informationen zu den ersten Schritten mit den Beispielanwendungen finden Sie unter. Beispielanwendung

Java


package com.amazonaws.services.timestream;

import static com.amazonaws.services.timestream.Main.DATABASE_NAME;
import static com.amazonaws.services.timestream.Main.REGION;
import static com.amazonaws.services.timestream.Main.TABLE_NAME;

import java.util.ArrayList;
import java.util.List;

import com.amazonaws.services.timestreamwrite.AmazonTimestreamWrite;
import com.amazonaws.services.timestreamwrite.model.Dimension;
import com.amazonaws.services.timestreamwrite.model.MeasureValue;
import com.amazonaws.services.timestreamwrite.model.MeasureValueType;
import com.amazonaws.services.timestreamwrite.model.Record;
import com.amazonaws.services.timestreamwrite.model.RejectedRecordsException;
import com.amazonaws.services.timestreamwrite.model.WriteRecordsRequest;
import com.amazonaws.services.timestreamwrite.model.WriteRecordsResult;


public class multimeasureAttributeExample {
  AmazonTimestreamWrite timestreamWriteClient;

  public multimeasureAttributeExample(AmazonTimestreamWrite client) {
    this.timestreamWriteClient = client;
  }

  public void writeRecordsMultiMeasureValueSingleRecord() {
    System.out.println("Writing records with multi value attributes");

    List<Record> records = new ArrayList<>();
    final long time = System.currentTimeMillis();
    long version = System.currentTimeMillis();

    List<Dimension> dimensions = new ArrayList<>();
    final Dimension region = new Dimension().withName("region").withValue(REGION);
    final Dimension az = new Dimension().withName("az").withValue("az1");
    final Dimension hostname = new Dimension().withName("hostname").withValue("host1");

    dimensions.add(region);
    dimensions.add(az);
    dimensions.add(hostname);

    Record commonAttributes = new Record()
        .withDimensions(dimensions)
        .withTime(String.valueOf(time))
        .withVersion(version);

    MeasureValue cpuUtilization = new MeasureValue()
        .withName("cpu_utilization")
        .withType(MeasureValueType.DOUBLE)
        .withValue("13.5");
    MeasureValue memoryUtilization = new MeasureValue()
        .withName("memory_utilization")
        .withType(MeasureValueType.DOUBLE)
        .withValue("40");
    Record computationalResources = new Record()
        .withMeasureName("cpu_memory")
        .withMeasureValues(cpuUtilization, memoryUtilization)
        .withMeasureValueType(MeasureValueType.MULTI);

    records.add(computationalResources);

    WriteRecordsRequest writeRecordsRequest = new WriteRecordsRequest()
        .withDatabaseName(DATABASE_NAME)
        .withTableName(TABLE_NAME)
        .withCommonAttributes(commonAttributes)
        .withRecords(records);

    // write records for first time
    try {
      WriteRecordsResult writeRecordResult = timestreamWriteClient.writeRecords(writeRecordsRequest);
      System.out.println(
          "WriteRecords Status for multi value attributes: " + writeRecordResult
              .getSdkHttpMetadata().getHttpStatusCode());
    } catch (RejectedRecordsException e) {
      printRejectedRecordsException(e);
    } catch (Exception e) {
      System.out.println("Error: " + e);
    }
  }

  public void writeRecordsMultiMeasureValueMultipleRecords() {
    System.out.println(
        "Writing records with multi value attributes mixture type");

    List<Record> records = new ArrayList<>();
    final long time = System.currentTimeMillis();
    long version = System.currentTimeMillis();

    List<Dimension> dimensions = new ArrayList<>();
    final Dimension region = new Dimension().withName("region").withValue(REGION);
    final Dimension az = new Dimension().withName("az").withValue("az1");
    final Dimension hostname = new Dimension().withName("hostname").withValue("host1");

    dimensions.add(region);
    dimensions.add(az);
    dimensions.add(hostname);

    Record commonAttributes = new Record()
        .withDimensions(dimensions)
        .withTime(String.valueOf(time))
        .withVersion(version);

    MeasureValue cpuUtilization = new MeasureValue()
        .withName("cpu_utilization")
        .withType(MeasureValueType.DOUBLE)
        .withValue("13");
    MeasureValue memoryUtilization =new MeasureValue()
        .withName("memory_utilization")
        .withType(MeasureValueType.DOUBLE)
        .withValue("40");
    MeasureValue activeCores = new MeasureValue()
        .withName("active_cores")
        .withType(MeasureValueType.BIGINT)
        .withValue("4");


    Record computationalResources = new Record()
        .withMeasureName("computational_utilization")
        .withMeasureValues(cpuUtilization, memoryUtilization, activeCores)
        .withMeasureValueType(MeasureValueType.MULTI);

    records.add(computationalResources);

    WriteRecordsRequest writeRecordsRequest = new WriteRecordsRequest()
        .withDatabaseName(DATABASE_NAME)
        .withTableName(TABLE_NAME)
        .withCommonAttributes(commonAttributes)
        .withRecords(records);

    // write records for first time
    try {
      WriteRecordsResult writeRecordResult = timestreamWriteClient.writeRecords(writeRecordsRequest);
      System.out.println(
          "WriteRecords Status for multi value attributes: " + writeRecordResult
              .getSdkHttpMetadata().getHttpStatusCode());
    } catch (RejectedRecordsException e) {
      printRejectedRecordsException(e);
    } catch (Exception e) {
      System.out.println("Error: " + e);
    }
  }

  private void printRejectedRecordsException(RejectedRecordsException e) {
    System.out.println("RejectedRecords: " + e);
    e.getRejectedRecords().forEach(System.out::println);
  }
}

Java v2


package com.amazonaws.services.timestream;

import java.util.ArrayList;
import java.util.List;

import software.amazon.awssdk.services.timestreamwrite.TimestreamWriteClient;
import software.amazon.awssdk.services.timestreamwrite.model.Dimension;
import software.amazon.awssdk.services.timestreamwrite.model.MeasureValue;
import software.amazon.awssdk.services.timestreamwrite.model.MeasureValueType;
import software.amazon.awssdk.services.timestreamwrite.model.Record;
import software.amazon.awssdk.services.timestreamwrite.model.RejectedRecordsException;
import software.amazon.awssdk.services.timestreamwrite.model.WriteRecordsRequest;
import software.amazon.awssdk.services.timestreamwrite.model.WriteRecordsResponse;

import static com.amazonaws.services.timestream.Main.DATABASE_NAME;
import static com.amazonaws.services.timestream.Main.TABLE_NAME;


public class multimeasureAttributeExample {

  TimestreamWriteClient timestreamWriteClient;

  public multimeasureAttributeExample(TimestreamWriteClient client) {
    this.timestreamWriteClient = client;
  }

  public void writeRecordsMultiMeasureValueSingleRecord() {
    System.out.println("Writing records with multi value attributes");

    List<Record> records = new ArrayList<>();
    final long time = System.currentTimeMillis();
    long version = System.currentTimeMillis();

    List<Dimension> dimensions = new ArrayList<>();
    final Dimension region =
        Dimension.builder().name("region").value("us-east-1").build();
    final Dimension az = Dimension.builder().name("az").value("az1").build();
    final Dimension hostname =
        Dimension.builder().name("hostname").value("host1").build();

    dimensions.add(region);
    dimensions.add(az);
    dimensions.add(hostname);

    Record commonAttributes = Record.builder()
        .dimensions(dimensions)
        .time(String.valueOf(time))
        .version(version)
        .build();

    MeasureValue cpuUtilization = MeasureValue.builder()
        .name("cpu_utilization")
        .type(MeasureValueType.DOUBLE)
        .value("13.5").build();
    MeasureValue memoryUtilization = MeasureValue.builder()
        .name("memory_utilization")
        .type(MeasureValueType.DOUBLE)
        .value("40").build();
    Record computationalResources = Record
        .builder()
        .measureName("cpu_memory")
        .measureValues(cpuUtilization, memoryUtilization)
        .measureValueType(MeasureValueType.MULTI)
        .build();

    records.add(computationalResources);

    WriteRecordsRequest writeRecordsRequest = WriteRecordsRequest.builder()
        .databaseName(DATABASE_NAME)
        .tableName(TABLE_NAME)
        .commonAttributes(commonAttributes)
        .records(records).build();

    // write records for first time
    try {
      WriteRecordsResponse writeRecordsResponse = timestreamWriteClient.writeRecords(writeRecordsRequest);
      System.out.println(
          "WriteRecords Status for multi value attributes: " + writeRecordsResponse
              .sdkHttpResponse()
              .statusCode());
    } catch (RejectedRecordsException e) {
      printRejectedRecordsException(e);
    } catch (Exception e) {
      System.out.println("Error: " + e);
    }
  }

  public void writeRecordsMultiMeasureValueMultipleRecords() {
    System.out.println(
        "Writing records with multi value attributes mixture type");

    List<Record> records = new ArrayList<>();
    final long time = System.currentTimeMillis();
    long version = System.currentTimeMillis();

    List<Dimension> dimensions = new ArrayList<>();
    final Dimension region =
        Dimension.builder().name("region").value("us-east-1").build();
    final Dimension az = Dimension.builder().name("az").value("az1").build();
    final Dimension hostname =
        Dimension.builder().name("hostname").value("host1").build();

    dimensions.add(region);
    dimensions.add(az);
    dimensions.add(hostname);

    Record commonAttributes = Record.builder()
        .dimensions(dimensions)
        .time(String.valueOf(time))
        .version(version)
        .build();

    MeasureValue cpuUtilization = MeasureValue.builder()
        .name("cpu_utilization")
        .type(MeasureValueType.DOUBLE)
        .value("13.5").build();
    MeasureValue memoryUtilization = MeasureValue.builder()
        .name("memory_utilization")
        .type(MeasureValueType.DOUBLE)
        .value("40").build();
    MeasureValue activeCores = MeasureValue.builder()
        .name("active_cores")
        .type(MeasureValueType.BIGINT)
        .value("4").build();


    Record computationalResources = Record
        .builder()
        .measureName("computational_utilization")
        .measureValues(cpuUtilization, memoryUtilization, activeCores)
        .measureValueType(MeasureValueType.MULTI)
        .build();

    records.add(computationalResources);

    WriteRecordsRequest writeRecordsRequest = WriteRecordsRequest.builder()
        .databaseName(DATABASE_NAME)
        .tableName(TABLE_NAME)
        .commonAttributes(commonAttributes)
        .records(records).build();

    // write records for first time
    try {
      WriteRecordsResponse writeRecordsResponse = timestreamWriteClient.writeRecords(writeRecordsRequest);
      System.out.println(
          "WriteRecords Status for multi value attributes: " + writeRecordsResponse
              .sdkHttpResponse()
              .statusCode());
    } catch (RejectedRecordsException e) {
      printRejectedRecordsException(e);
    } catch (Exception e) {
      System.out.println("Error: " + e);
    }
  }

  private void printRejectedRecordsException(RejectedRecordsException e) {
    System.out.println("RejectedRecords: " + e);
    e.rejectedRecords().forEach(System.out::println);
  }
}

Go


  now := time.Now()
  currentTimeInSeconds := now.Unix()
  writeRecordsInput := &timestreamwrite.WriteRecordsInput{
    DatabaseName: aws.String(*databaseName),
    TableName:  aws.String(*tableName),
    Records: []*timestreamwrite.Record{
    &timestreamwrite.Record{
      Dimensions: []*timestreamwrite.Dimension{
      &timestreamwrite.Dimension{
        Name:  aws.String("region"),
        Value: aws.String("us-east-1"),
      },
      &timestreamwrite.Dimension{
        Name:  aws.String("az"),
        Value: aws.String("az1"),
      },
      &timestreamwrite.Dimension{
        Name:  aws.String("hostname"),
        Value: aws.String("host1"),
      },
      },
      MeasureName:  aws.String("metrics"),
      MeasureValueType: aws.String("MULTI"),
      Time:     aws.String(strconv.FormatInt(currentTimeInSeconds, 10)),
      TimeUnit:  aws.String("SECONDS"),
      MeasureValues: []*timestreamwrite.MeasureValue{
      &timestreamwrite.MeasureValue{
        Name:  aws.String("cpu_utilization"),
        Value: aws.String("13.5"),
        Type:  aws.String("DOUBLE"),
      }, 
      &timestreamwrite.MeasureValue{
        Name:  aws.String("memory_utilization"),
        Value: aws.String("40"),
        Type:  aws.String("DOUBLE"),
      },
      },
    },
    },
  }
   
  _, err = writeSvc.WriteRecords(writeRecordsInput)
   
  if err != nil {
    fmt.Println("Error:")
    fmt.Println(err)
  } else {
    fmt.Println("Write records is successful")
  }

Python


import time
import boto3
import psutil
import os

from botocore.config import Config

DATABASE_NAME = os.environ['DATABASE_NAME']
TABLE_NAME = os.environ['TABLE_NAME']

COUNTRY = "UK"
CITY = "London"
HOSTNAME = "MyHostname" # You can make it dynamic using socket.gethostname()

INTERVAL = 1 # Seconds

def prepare_common_attributes():
  common_attributes = {
    'Dimensions': [
      {'Name': 'country', 'Value': COUNTRY},
      {'Name': 'city', 'Value': CITY},
      {'Name': 'hostname', 'Value': HOSTNAME}
    ],
    'MeasureName': 'utilization',
    'MeasureValueType': 'MULTI'
  }
  return common_attributes


def prepare_record(current_time):
  record = {
    'Time': str(current_time),
    'MeasureValues': []
  }
  return record


def prepare_measure(measure_name, measure_value):
  measure = {
    'Name': measure_name,
    'Value': str(measure_value),
    'Type': 'DOUBLE'
  }
  return measure


def write_records(records, common_attributes):
  try:
    result = write_client.write_records(DatabaseName=DATABASE_NAME,
                                        TableName=TABLE_NAME,
                                        CommonAttributes=common_attributes,
                                        Records=records)
    status = result['ResponseMetadata']['HTTPStatusCode']
    print("Processed %d records. WriteRecords HTTPStatusCode: %s" %
        (len(records), status))
  except Exception as err:
    print("Error:", err)


if __name__ == '__main__':

  print("writing data to database {} table {}".format(
    DATABASE_NAME, TABLE_NAME))

  session = boto3.Session()
  write_client = session.client('timestream-write', config=Config(
    read_timeout=20, max_pool_connections=5000, retries={'max_attempts': 10}))
  query_client = session.client('timestream-query') # Not used

  common_attributes = prepare_common_attributes()

  records = []

  while True:

    current_time = int(time.time() * 1000)
    cpu_utilization = psutil.cpu_percent()
    memory_utilization = psutil.virtual_memory().percent
    swap_utilization = psutil.swap_memory().percent
    disk_utilization = psutil.disk_usage('/').percent

    record = prepare_record(current_time)
    record['MeasureValues'].append(prepare_measure('cpu', cpu_utilization))
    record['MeasureValues'].append(prepare_measure('memory', memory_utilization))
    record['MeasureValues'].append(prepare_measure('swap', swap_utilization))
    record['MeasureValues'].append(prepare_measure('disk', disk_utilization))

    records.append(record)

    print("records {} - cpu {} - memory {} - swap {} - disk {}".format(
      len(records), cpu_utilization, memory_utilization,
      swap_utilization, disk_utilization))

    if len(records) == 100:
      write_records(records, common_attributes)
      records = []

    time.sleep(INTERVAL)

Node.js

Der folgende Codeausschnitt verwendet den AWS SDK for JavaScript V2-Stil. Es basiert auf der Beispielanwendung unter Node.js Beispiel Amazon Timestream für die LiveAnalytics Anwendung auf GitHub.


  async function writeRecords() {
    console.log("Writing records");
    const currentTime = Date.now().toString(); // Unix time in milliseconds

    const dimensions = [
    {'Name': 'region', 'Value': 'us-east-1'},
    {'Name': 'az', 'Value': 'az1'},
    {'Name': 'hostname', 'Value': 'host1'}
    ];

    const record = {
    'Dimensions': dimensions,
    'MeasureName': 'metrics',
    'MeasureValues': [
      {
        'Name': 'cpu_utilization',
        'Value': '40',
        'Type': 'DOUBLE',
      },
      {
        'Name': 'memory_utilization',
        'Value': '13.5',
        'Type': 'DOUBLE',
      },
      ],
      'MeasureValueType': 'MULTI',
      'Time': currentTime.toString()
    }

    const records = [record];

    const params = {
    DatabaseName: 'DatabaseName',
    TableName: 'TableName',
    Records: records
    };

    const response = await writeClient.writeRecords(params);

    console.log(response);
  }

.NET


using System;
using System.IO;
using System.Collections.Generic;
using Amazon.TimestreamWrite;
using Amazon.TimestreamWrite.Model;
using System.Threading.Tasks;

namespace TimestreamDotNetSample
{
  static class MultiMeasureValueConstants
  {
    public const string MultiMeasureValueSampleDb = "multiMeasureValueSampleDb";
    public const string MultiMeasureValueSampleTable = "multiMeasureValueSampleTable";
  }

  public class MultiValueAttributesExample
  {
    private readonly AmazonTimestreamWriteClient writeClient;

    public MultiValueAttributesExample(AmazonTimestreamWriteClient writeClient)
    {
      this.writeClient = writeClient;
    }

    public async Task WriteRecordsMultiMeasureValueSingleRecord()
    {
      Console.WriteLine("Writing records with multi value attributes");

      DateTimeOffset now = DateTimeOffset.UtcNow;
      string currentTimeString = (now.ToUnixTimeMilliseconds()).ToString();

      List<Dimension> dimensions = new List<Dimension>{
        new Dimension { Name = "region", Value = "us-east-1" },
        new Dimension { Name = "az", Value = "az1" },
        new Dimension { Name = "hostname", Value = "host1" }
      };

      var commonAttributes = new Record
      {
        Dimensions = dimensions,
        Time = currentTimeString
      };

      var cpuUtilization = new MeasureValue
      {
        Name = "cpu_utilization",
        Value = "13.6",
        Type = "DOUBLE"
      };

      var memoryUtilization = new MeasureValue
      {
        Name = "memory_utilization",
        Value = "40",
        Type = "DOUBLE"
      };

      var computationalRecord = new Record
      {
        MeasureName = "cpu_memory",
        MeasureValues = new List<MeasureValue> {cpuUtilization, memoryUtilization},
        MeasureValueType = "MULTI"
      };


      List<Record> records = new List<Record>();
      records.Add(computationalRecord);

      try
      {
        var writeRecordsRequest = new WriteRecordsRequest
        {
          DatabaseName = MultiMeasureValueConstants.MultiMeasureValueSampleDb,
          TableName = MultiMeasureValueConstants.MultiMeasureValueSampleTable,
          Records = records,
          CommonAttributes = commonAttributes
        };
        WriteRecordsResponse response = await writeClient.WriteRecordsAsync(writeRecordsRequest);
        Console.WriteLine($"Write records status code: {response.HttpStatusCode.ToString()}");
      }
      catch (Exception e)
      {
        Console.WriteLine("Write records failure:" + e.ToString());
      }
    }

    public async Task WriteRecordsMultiMeasureValueMultipleRecords()
    {
      Console.WriteLine("Writing records with multi value attributes mixture type");

      DateTimeOffset now = DateTimeOffset.UtcNow;
      string currentTimeString = (now.ToUnixTimeMilliseconds()).ToString();

      List<Dimension> dimensions = new List<Dimension>{
        new Dimension { Name = "region", Value = "us-east-1" },
        new Dimension { Name = "az", Value = "az1" },
        new Dimension { Name = "hostname", Value = "host1" }
      };

      var commonAttributes = new Record
      {
        Dimensions = dimensions,
        Time = currentTimeString
      };

      var cpuUtilization = new MeasureValue
      {
        Name = "cpu_utilization",
        Value = "13.6",
        Type = "DOUBLE"
      };

      var memoryUtilization = new MeasureValue
      {
        Name = "memory_utilization",
        Value = "40",
        Type = "DOUBLE"
      };

      var activeCores = new MeasureValue
      {
        Name = "active_cores",
        Value = "4",
        Type = "BIGINT"
      };

      var computationalRecord = new Record
      {
        MeasureName = "computational_utilization",
        MeasureValues = new List<MeasureValue> {cpuUtilization, memoryUtilization, activeCores},
        MeasureValueType = "MULTI"
      };

      var aliveRecord = new Record
      {
        MeasureName = "is_healthy",
        MeasureValue = "true",
        MeasureValueType = "BOOLEAN"
      };

      List<Record> records = new List<Record>();
      records.Add(computationalRecord);
      records.Add(aliveRecord);

      try
      {
        var writeRecordsRequest = new WriteRecordsRequest
        {
          DatabaseName = MultiMeasureValueConstants.MultiMeasureValueSampleDb,
          TableName = MultiMeasureValueConstants.MultiMeasureValueSampleTable,
          Records = records,
          CommonAttributes = commonAttributes
        };
        WriteRecordsResponse response = await writeClient.WriteRecordsAsync(writeRecordsRequest);
        Console.WriteLine($"Write records status code: {response.HttpStatusCode.ToString()}");
      }
      catch (Exception e)
      {
        Console.WriteLine("Write records failure:" + e.ToString());
      }
    }
  }
}

Behandlung von Schreibfehlern

Schreibvorgänge in Amazon Timestream können aus einem oder mehreren der folgenden Gründe fehlschlagen:

Es gibt Datensätze mit Zeitstempeln, die außerhalb der Aufbewahrungsdauer des Speicherspeichers liegen.
Es gibt Datensätze, die Dimensionen und/oder Kennzahlen enthalten, die die von Timestream definierten Grenzwerte überschreiten.
Amazon Timestream hat doppelte Datensätze erkannt. Datensätze werden als doppelt markiert, wenn es mehrere Datensätze mit denselben Dimensionen, Zeitstempeln und Kennzahlnamen gibt, aber:
- Die Kennzahlwerte sind unterschiedlich.
- Version ist in der Anforderung nicht vorhanden, oder der Wert der Version im neuen Datensatz ist gleich oder niedriger als der vorhandene Wert. Wenn Amazon Timestream Daten aus diesem Grund ablehnt, enthält das ExistingVersion Feld in der die RejectedRecords aktuelle Version des Datensatzes, wie sie in Amazon Timestream gespeichert ist. Um eine Aktualisierung zu erzwingen, können Sie die Anfrage erneut senden, wobei eine Version für den Datensatz auf einen Wert gesetzt ist, der größer als der ist. ExistingVersion

Weitere Informationen zu Fehlern und abgelehnten Datensätzen finden Sie unter Fehler und RejectedRecord.

Wenn Ihre Anwendung RejectedRecordsException beim Versuch, Datensätze in Timestream zu schreiben, eine Meldung erhält, können Sie die abgelehnten Datensätze analysieren, um mehr über die Schreibfehler zu erfahren, wie unten dargestellt.

Anmerkung

Diese Codefragmente basieren auf vollständigen Beispielanwendungen auf. GitHub Weitere Informationen zu den ersten Schritten mit den Beispielanwendungen finden Sie unter. Beispielanwendung

Java


  try {
    WriteRecordsResult writeRecordsResult = amazonTimestreamWrite.writeRecords(writeRecordsRequest);
    System.out.println("WriteRecords Status: " + writeRecordsResult.getSdkHttpMetadata().getHttpStatusCode());
  } catch (RejectedRecordsException e) {
    System.out.println("RejectedRecords: " + e);
    for (RejectedRecord rejectedRecord : e.getRejectedRecords()) {
      System.out.println("Rejected Index " + rejectedRecord.getRecordIndex() + ": "
          + rejectedRecord.getReason());
    }
    System.out.println("Other records were written successfully. ");
  } catch (Exception e) {
    System.out.println("Error: " + e);
  }

Java v2


    try {
      WriteRecordsResponse writeRecordsResponse = timestreamWriteClient.writeRecords(writeRecordsRequest);
      System.out.println("writeRecordsWithCommonAttributes Status: " + writeRecordsResponse.sdkHttpResponse().statusCode());
    } catch (RejectedRecordsException e) {
      System.out.println("RejectedRecords: " + e);
      for (RejectedRecord rejectedRecord : e.rejectedRecords()) {
        System.out.println("Rejected Index " + rejectedRecord.recordIndex() + ": "
            + rejectedRecord.reason());
      }
      System.out.println("Other records were written successfully. ");
    } catch (Exception e) {
      System.out.println("Error: " + e);
    }

Go


_, err = writeSvc.WriteRecords(writeRecordsInput)

if err != nil {
  fmt.Println("Error:")
  fmt.Println(err)
} else {
  fmt.Println("Write records is successful")
}

Python


try:
  result = self.client.write_records(DatabaseName=Constant.DATABASE_NAME, TableName=Constant.TABLE_NAME, Records=records, CommonAttributes=common_attributes)
  print("WriteRecords Status: [%s]" % result['ResponseMetadata']['HTTPStatusCode'])
except self.client.exceptions.RejectedRecordsException as err:
  print("RejectedRecords: ", err)
  for rr in err.response["RejectedRecords"]:
    print("Rejected Index " + str(rr["RecordIndex"]) + ": " + rr["Reason"])
  print("Other records were written successfully. ")
except Exception as err:
  print("Error:", err)

Node.js

Der folgende Codeausschnitt verwendet den AWS SDK for JavaScript V2-Stil. Es basiert auf der Beispielanwendung unter Node.js Beispiel Amazon Timestream für die LiveAnalytics Anwendung auf GitHub.


await request.promise().then(
    (data) => {
      console.log("Write records successful");
    },
    (err) => {
      console.log("Error writing records:", err);
      if (err.code === 'RejectedRecordsException') {
        const responsePayload = JSON.parse(request.response.httpResponse.body.toString());
        console.log("RejectedRecords: ", responsePayload.RejectedRecords);
        console.log("Other records were written successfully. ");
      }
    }
  );

.NET


  try
  {
    var writeRecordsRequest = new WriteRecordsRequest
    {
      DatabaseName = Constants.DATABASE_NAME,
      TableName = Constants.TABLE_NAME,
      Records = records,
      CommonAttributes = commonAttributes
    };
    WriteRecordsResponse response = await writeClient.WriteRecordsAsync(writeRecordsRequest);
    Console.WriteLine($"Write records status code: {response.HttpStatusCode.ToString()}");
  }
  catch (RejectedRecordsException e) {
    Console.WriteLine("RejectedRecordsException:" + e.ToString());
    foreach (RejectedRecord rr in e.RejectedRecords) {
      Console.WriteLine("RecordIndex " + rr.RecordIndex + " : " + rr.Reason);
    }
    Console.WriteLine("Other records were written successfully. ");
  }
  catch (Exception e)
  {
    Console.WriteLine("Write records failure:" + e.ToString());
  }

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