Prerequisites
- Ensure you have the AWS SDK for Java integrated into your project. You can include it by adding the necessary dependencies to your Maven `pom.xml` or your Gradle `build.gradle` file.
- Ensure IAM permissions for your application to interact with Kinesis Firehose appropriately. You need permissions like `firehose:PutRecord` and `firehose:PutRecordBatch`.
Initialize the KinesisFirehoseClient
- You'll want to initialize the client using AWS SDK. This will serve as the medium through which your application communicates with the Kinesis Firehose service.
import software.amazon.awssdk.services.firehose.FirehoseClient;
import software.amazon.awssdk.regions.Region;
FirehoseClient firehoseClient = FirehoseClient.builder()
.region(Region.US_EAST_1) // Change region as per your requirement
.build();
Prepare Data for Streaming
- Data needs to be converted into a byte buffer or a string format that the API accepts. You may need to serialize your data appropriately.
import java.nio.charset.StandardCharsets;
import software.amazon.awssdk.core.SdkBytes;
String jsonData = "{\"key\":\"value\"}";
SdkBytes sdkBytes = SdkBytes.fromByteArray(jsonData.getBytes(StandardCharsets.UTF_8));
Define a Delivery Stream
- If you haven't set up a delivery stream yet, this is a concept you should be familiar with—this is essentially the target destination for the data. Normally, this would be configured in the AWS console, not in your code.
Put a Single Record
- Utilize the `putRecord` operation to send a single data record to your delivery stream. This is useful for infrequent updates or in scenarios where aggregation doesn't provide significant benefit.
import software.amazon.awssdk.services.firehose.model.PutRecordRequest;
import software.amazon.awssdk.services.firehose.model.Record;
Record record = Record.builder()
.data(sdkBytes)
.build();
PutRecordRequest putRecordRequest = PutRecordRequest.builder()
.deliveryStreamName("your_delivery_stream_name")
.record(record)
.build();
firehoseClient.putRecord(putRecordRequest);
Put Records in Batches
- For larger volumes of data, use `putRecordBatch`, which allows sending data in groups of records. This helps to achieve higher throughput and reduce costs.
import software.amazon.awssdk.services.firehose.model.PutRecordBatchRequest;
import software.amazon.awssdk.services.firehose.model.PutRecordBatchResponse;
import software.amazon.awssdk.services.firehose.model.PutRecordBatchResponseEntry;
List<Record> records = new ArrayList<>();
records.add(Record.builder().data(sdkBytes).build());
PutRecordBatchRequest putRecordBatchRequest = PutRecordBatchRequest.builder()
.deliveryStreamName("your_delivery_stream_name")
.records(records)
.build();
PutRecordBatchResponse putRecordBatchResponse = firehoseClient.putRecordBatch(putRecordBatchRequest);
for (PutRecordBatchResponseEntry responseEntry : putRecordBatchResponse.requestResponses()) {
if (responseEntry.errorCode() != null) {
// Handle the error as needed
}
}
Handle Responses and Errors
- Check the response from the Firehose API to ensure that records were delivered successfully. Implement error checking and handling in case of failed deliveries.
Close the KinesisFirehoseClient
- When done streaming data, release resources by closing the `FirehoseClient` instance.
firehoseClient.close();
Remember, this is a simple example, and in production, you'd need to consider implementing retries, exponential backoff, and comprehensive logging for better resilience and troubleshooting. Adjust the region, delivery stream name, and data input as per your application requirements.
