AWS SQS

Amazon Simple Queue Service

Amazon Simple Queue Service (Amazon SQS) offers a secure, durable, and available hosted queue that lets you integrate and decouple distributed software systems and components. Amazon SQS offers common constructs such as dead-letter queues and cost allocation tags. It provides a generic web services API and it can be accessed by any programming language that the AWS SDK supports.

For more information about AWS SQS please visit the official documentation.

The AWS SQS connector provides Apache Pekko Stream sources and sinks for AWS SQS queues.

Project Info: Apache Pekko Connectors AWS SQS
Artifact
org.apache.pekko
pekko-connectors-sqs
1.1.0-M1+116-9ab254b5-SNAPSHOT
JDK versions
OpenJDK 8
OpenJDK 11
OpenJDK 17
OpenJDK 21
Scala versions2.13.15, 2.12.20, 3.3.4
JPMS module namepekko.stream.connectors.aws.sqs
License
API documentation
Forums
Release notesGitHub releases
IssuesGithub issues
Sourceshttps://github.com/apache/pekko-connectors

Artifacts

sbt
val PekkoVersion = "1.1.2"
val PekkoHttpVersion = "1.1.0"
libraryDependencies ++= Seq(
  "org.apache.pekko" %% "pekko-connectors-sqs" % "1.1.0-M1+116-9ab254b5-SNAPSHOT",
  "org.apache.pekko" %% "pekko-stream" % PekkoVersion,
  "org.apache.pekko" %% "pekko-http" % PekkoHttpVersion
)
Maven
<properties>
  <pekko.version>1.1.2</pekko.version>
  <pekko.http.version>1.1.0</pekko.http.version>
  <scala.binary.version>2.13</scala.binary.version>
</properties>
<dependencies>
  <dependency>
    <groupId>org.apache.pekko</groupId>
    <artifactId>pekko-connectors-sqs_${scala.binary.version}</artifactId>
    <version>1.1.0-M1+116-9ab254b5-SNAPSHOT</version>
  </dependency>
  <dependency>
    <groupId>org.apache.pekko</groupId>
    <artifactId>pekko-stream_${scala.binary.version}</artifactId>
    <version>${pekko.version}</version>
  </dependency>
  <dependency>
    <groupId>org.apache.pekko</groupId>
    <artifactId>pekko-http_${scala.binary.version}</artifactId>
    <version>${pekko.http.version}</version>
  </dependency>
</dependencies>
Gradle
def versions = [
  PekkoVersion: "1.1.2",
  PekkoHttpVersion: "1.1.0",
  ScalaBinary: "2.13"
]
dependencies {
  implementation "org.apache.pekko:pekko-connectors-sqs_${versions.ScalaBinary}:1.1.0-M1+116-9ab254b5-SNAPSHOT"
  implementation "org.apache.pekko:pekko-stream_${versions.ScalaBinary}:${versions.PekkoVersion}"
  implementation "org.apache.pekko:pekko-http_${versions.ScalaBinary}:${versions.PekkoHttpVersion}"
}

The table below shows direct dependencies of this module and the second tab shows all libraries it depends on transitively.

Setup

Prepare an ActorSystemActorSystem.

Scala
sourceimplicit val system: ActorSystem = ActorSystem()
Java
sourcesystem = ActorSystem.create();

This connector requires an implicit SqsAsyncClient instance to communicate with AWS SQS.

It is your code’s responsibility to call close to free any resources held by the client. In this example it will be called when the actor system is terminated.

Scala
sourceimport software.amazon.awssdk.auth.credentials.{ AwsBasicCredentials, StaticCredentialsProvider }
import software.amazon.awssdk.regions.Region
import software.amazon.awssdk.services.sqs.SqsAsyncClient
import software.amazon.awssdk.services.sqs.model.CreateQueueRequest

// Don't encode credentials in your source code!
// see https://pekko.apache.org/docs/pekko-connectors/current/aws-shared-configuration.html
val credentialsProvider = StaticCredentialsProvider.create(AwsBasicCredentials.create("x", "x"))
implicit val awsSqsClient = SqsAsyncClient
  .builder()
  .credentialsProvider(credentialsProvider)
  .region(Region.EU_CENTRAL_1)
  .httpClient(PekkoHttpClient.builder().withActorSystem(system).build())
  // Possibility to configure the retry policy
  // see https://pekko.apache.org/docs/pekko-connectors/current/aws-shared-configuration.html
  // .overrideConfiguration(...)
  .build()

system.registerOnTermination(awsSqsClient.close())
Java
sourceimport software.amazon.awssdk.auth.credentials.AwsBasicCredentials;
import software.amazon.awssdk.auth.credentials.StaticCredentialsProvider;
import software.amazon.awssdk.regions.Region;
import software.amazon.awssdk.services.sqs.SqsAsyncClient;

// Don't encode credentials in your source code!
// see https://pekko.apache.org/docs/pekko-connectors/current/aws-shared-configuration.html
StaticCredentialsProvider credentialsProvider =
    StaticCredentialsProvider.create(AwsBasicCredentials.create("x", "x"));
SqsAsyncClient sqsClient =
    SqsAsyncClient.builder()
        .credentialsProvider(credentialsProvider)
        .region(Region.EU_CENTRAL_1)
        .httpClient(PekkoHttpClient.builder().withActorSystem(system).build())
        // Possibility to configure the retry policy
        // see https://pekko.apache.org/docs/pekko-connectors/current/aws-shared-configuration.html
        // .overrideConfiguration(...)
        .build();

system.registerOnTermination(() -> sqsClient.close());

The example above uses Apache Pekko HTTP as the default HTTP client implementation. For more details about the HTTP client, configuring request retrying and best practices for credentials, see AWS client configuration for more details.

Read from an SQS queue

The SqsSourceSqsSource created source reads AWS Java SDK SQS Message objects from any SQS queue given by the queue URL.

Scala
sourceval messages: Future[immutable.Seq[Message]] =
  SqsSource(
    queueUrl,
    SqsSourceSettings().withCloseOnEmptyReceive(true).withWaitTime(10.millis)).runWith(Sink.seq)
Java
sourcefinal CompletionStage<List<Message>> messages =
    SqsSource.create(
            queueUrl,
            SqsSourceSettings.create()
                .withCloseOnEmptyReceive(true)
                .withWaitTime(Duration.ofMillis(10)),
            sqsClient)
        .runWith(Sink.seq(), system);

In this example we use the closeOnEmptyReceive to let the stream complete when there are no more messages on the queue. In realistic scenarios, you should add a KillSwitch to the stream, see “Controlling stream completion with KillSwitch” in the Apache Pekko documentation.

Source configuration

Scala
sourceval settings = SqsSourceSettings()
  .withWaitTime(20.seconds)
  .withMaxBufferSize(100)
  .withMaxBatchSize(10)
  .withAttributes(immutable.Seq(SenderId, SentTimestamp))
  .withMessageAttribute(MessageAttributeName.create("bar.*"))
  .withCloseOnEmptyReceive(true)
  .withVisibilityTimeout(10.seconds)
Java
sourceSqsSourceSettings settings =
    SqsSourceSettings.create()
        .withWaitTime(Duration.ofSeconds(20))
        .withMaxBufferSize(100)
        .withMaxBatchSize(10)
        .withAttributes(
            Arrays.asList(
                MessageSystemAttributeName.senderId(),
                MessageSystemAttributeName.sentTimestamp()))
        .withMessageAttribute(MessageAttributeName.create("bar.*"))
        .withCloseOnEmptyReceive(true);

Options:

  • maxBatchSize - the maximum number of messages to return per request (allowed values 1-10, see MaxNumberOfMessages in AWS docs). Default: 10
  • maxBufferSize - internal buffer size used by the Source. Default: 100 messages
  • waitTimeSeconds - the duration for which the call waits for a message to arrive in the queue before returning (see WaitTimeSeconds in AWS docs). Default: 20 seconds
  • closeOnEmptyReceive - If true, the source completes when no messages are available.

More details are available in the AWS SQS Receive Message documentation.

An SqsSource can either provide an infinite stream of messages (the default), or can drain its source queue until no further messages are available. The latter behaviour is enabled by setting the closeOnEmptyReceive flag on creation. If set, the Source will receive messages until it encounters an empty reply from the server. It then continues to emit any remaining messages in its local buffer. The stage will complete once the last message has been sent downstream.

Note that for short-polling (waitTimeSeconds of 0), SQS may respond with an empty reply even if there are still messages in the queue. This behavior can be prevented by switching to long-polling (by setting waitTimeSeconds to a nonzero value).

Be aware that the SqsSource runs multiple requests to Amazon SQS in parallel. The maximum number of concurrent requests is limited by parallelism = maxBufferSize / maxBatchSize. E.g.: By default maxBatchSize is set to 10 and maxBufferSize is set to 100 so at the maximum, SqsSource will run 10 concurrent requests to Amazon SQS.

Publish messages to an SQS queue

Create a String-accepting sink, publishing to an SQS queue.

Scala
sourceSource
  .single("connectors")
  .runWith(SqsPublishSink(queueUrl))
Java
sourceSource.single("connectors")
    .runWith(
        SqsPublishSink.create(queueUrl, SqsPublishSettings.create(), sqsClient), system);

Create a SendMessageRequest-accepting sink, that publishes an SQS queue.

Scala
source// for fix SQS queue
Source
  .single(SendMessageRequest.builder().messageBody("connectors").build())
  .runWith(SqsPublishSink.messageSink(queueUrl))

// for dynamic SQS queues
Source
  .single(SendMessageRequest.builder().messageBody("connectors").queueUrl(queueUrl).build())
  .runWith(SqsPublishSink.messageSink())
Java
source// for fix SQS queue
Source.single(SendMessageRequest.builder().messageBody("connectors").build())
    .runWith(
        SqsPublishSink.messageSink(queueUrl, SqsPublishSettings.create(), sqsClient),
        system);

// for dynamic SQS queues
Source.single(
        SendMessageRequest.builder().messageBody("connectors").queueUrl(queueUrl).build())
    .runWith(SqsPublishSink.messageSink(SqsPublishSettings.create(), sqsClient), system);

You can also build flow stages which publish messages to SQS queues, backpressure on queue response, and then forward SqsPublishResultSqsPublishResult further down the stream.

Scala
source// for fix SQS queue
Source
  .single(SendMessageRequest.builder().messageBody("connectors").build())
  .via(SqsPublishFlow(queueUrl))
  .runWith(Sink.head)

// for dynamic SQS queues
Source
  .single(SendMessageRequest.builder().messageBody("connectors").queueUrl(queueUrl).build())
  .via(SqsPublishFlow())
  .runWith(Sink.head)
Java
source// for fix SQS queue
Source.single(SendMessageRequest.builder().messageBody("pekko-connectors-flow").build())
    .via(SqsPublishFlow.create(queueUrl, SqsPublishSettings.create(), sqsClient))
    .runWith(Sink.head(), system);

// for dynamic SQS queues
Source.single(
        SendMessageRequest.builder().messageBody("pekko-connectors-flow").queueUrl(queueUrl).build())
    .via(SqsPublishFlow.create(SqsPublishSettings.create(), sqsClient))
    .runWith(Sink.head(), system);

Group messages and publish batches to an SQS queue

Create a sink, that forwards String to the SQS queue. However, the main difference from the previous use case, it batches items and sends as one request and forwards a SqsPublishResultEntrySqsPublishResultEntry further down the stream for each item processed.

Note: There is also another option to send a batch of messages to SQS which is using AmazonSQSBufferedAsyncClient. This client buffers SendMessageRequests under the hood and sends them as a batch instead of sending them one by one. However, beware that AmazonSQSBufferedAsyncClient does not support FIFO Queues. See documentation for client-side buffering.

Scala
sourceval messages = for (i <- 0 until 10) yield s"Message - $i"

val future = Source(messages)
  .runWith(SqsPublishSink.grouped(queueUrl, SqsPublishGroupedSettings.Defaults.withMaxBatchSize(2)))
Java
sourceList<String> messagesToSend = new ArrayList<>();
for (int i = 0; i < 20; i++) {
  messagesToSend.add("message - " + i);
}

CompletionStage<Done> done =
    Source.from(messagesToSend)
        .runWith(
            SqsPublishSink.grouped(queueUrl, SqsPublishGroupedSettings.create(), sqsClient),
            system);

Grouping configuration

Scala
sourceval batchSettings =
  SqsPublishGroupedSettings()
    .withMaxBatchSize(10)
    .withMaxBatchWait(500.millis)
    .withConcurrentRequests(1)
Java
sourceSqsPublishGroupedSettings batchSettings =
    SqsPublishGroupedSettings.create()
        .withMaxBatchSize(10)
        .withMaxBatchWait(Duration.ofMillis(500))
        .withConcurrentRequests(1);

Options:

  • maxBatchSize - the maximum number of messages in batch to send SQS. Default: 10.
  • maxBatchWait - the maximum duration for which the stage waits until maxBatchSize messages arrived. Sends what is collects at the end of the time period even though the maxBatchSize is not fulfilled. Default: 500 milliseconds
  • concurrentRequests - the number of batches sending to SQS concurrently.

Publish lists as batches to an SQS queue

Create a sink, that publishes Iterable[String]Iterable<String> to the SQS queue.

Scala
sourceval messages = for (i <- 0 until 10) yield s"Message - $i"

val future = Source
  .single(messages)
  .runWith(SqsPublishSink.batch(queueUrl))
Java
sourceList<String> messagesToSend = new ArrayList<>();
for (int i = 0; i < 10; i++) {
  messagesToSend.add("Message - " + i);
}

CompletionStage<Done> done =
    Source.single(messagesToSend)
        .runWith(
            SqsPublishSink.batch(queueUrl, SqsPublishBatchSettings.create(), sqsClient),
            system);

Create a sink, that publishes Iterable[SendMessageRequest]Iterable<SendMessageRequest> to the SQS queue.

Warning

Be aware that the size of the batch must be less than or equal to 10 because Amazon SQS has a limit for batch requests. If the batch has more than 10 entries, the request will fail.

Scala
sourceval messages =
  for (i <- 0 until 10)
    yield SendMessageRequest
      .builder()
      .messageBody(s"Message - $i")
      .delaySeconds(0)
      .build()

val future = Source
  .single(messages)
  .runWith(SqsPublishSink.batchedMessageSink(queueUrl))
Java
sourceList<SendMessageRequest> messagesToSend = new ArrayList<>();
for (int i = 0; i < 10; i++) {
  messagesToSend.add(SendMessageRequest.builder().messageBody("Message - " + i).build());
}

CompletionStage<Done> done =
    Source.single(messagesToSend)
        .runWith(
            SqsPublishSink.batchedMessageSink(
                queueUrl, SqsPublishBatchSettings.create(), sqsClient),
            system);

Batch configuration

Scala
sourceval batchSettings =
  SqsPublishBatchSettings()
    .withConcurrentRequests(1)
Java
sourceSqsPublishBatchSettings batchSettings =
    SqsPublishBatchSettings.create().withConcurrentRequests(1);

Options:

  • concurrentRequests - the number of batches sending to SQS concurrently.

Updating message statuses

SqsAckSink and SqsAckFlow provide the possibility to acknowledge (delete), ignore, or postpone messages on an SQS queue. They accept MessageActionMessageAction sub-classes to select the action to be taken.

For every message you may decide which action to take and push it together with message back to the queue:

  • Delete - delete message from the queue
  • Ignore - don’t change that message, and let it reappear in the queue after the visibility timeout
  • ChangeMessageVisibility(visibilityTimeout) - can be used to postpone a message, or make the message immediately visible to other consumers. See official documentation for more details.

Acknowledge (delete) messages

Scala
sourceSqsSource(queueUrl, sqsSourceSettings)
  .take(1)
  .map(MessageAction.Delete(_))
  .runWith(SqsAckSink(queueUrl))
Java
sourcesource
    .map(m -> MessageAction.delete(m))
    .runWith(SqsAckSink.create(queueUrl, SqsAckSettings.create(), awsClient), system);

Ignore messages

Scala
sourceSqsSource(queueUrl, sqsSourceSettings)
  .take(1)
  .map(MessageAction.Ignore(_))
  .runWith(SqsAckSink(queueUrl))
Java
sourcesource
    .map(m -> MessageAction.ignore(m))
    .via(SqsAckFlow.create(queueUrl, SqsAckSettings.create(), awsClient))
    .runWith(Sink.seq(), system);

Change Visibility Timeout of messages

Scala
sourceSqsSource(queueUrl, sqsSourceSettings)
  .take(1)
  .map(MessageAction.ChangeMessageVisibility(_, 5.minutes))
  .runWith(SqsAckSink(queueUrl))
Java
sourcesource
    .map(m -> MessageAction.changeMessageVisibility(m, 12))
    .runWith(SqsAckSink.create(queueUrl, SqsAckSettings.create(), awsClient), system);

Update message status in a flow

The SqsAckFlow forwards a SqsAckResultSqsAckResult sub-class down the stream:

  • DeleteResult to acknowledge message deletion
  • ChangeMessageVisibilityResult to acknowledge message visibility change
  • In case of Ignore action, nothing is performed on the sqs queue, thus no SqsAckResult is forwarded.
Scala
sourceSqsSource(queueUrl, sqsSourceSettings)
  .take(1)
  .map(MessageAction.Delete(_))
  .via(SqsAckFlow(queueUrl))
  .runWith(Sink.head)
Java
sourcesource
    .map(m -> MessageAction.delete(m))
    .via(SqsAckFlow.create(queueUrl, SqsAckSettings.create(), awsClient))
    .runWith(Sink.seq(), system);

SqsAck configuration

Scala
sourceval sinkSettings =
  SqsAckSettings()
    .withMaxInFlight(10)
Java
sourceSqsAckSettings sinkSettings = SqsAckSettings.create().withMaxInFlight(10);

Options:

  • maxInFlight - maximum number of messages being processed by AmazonSQSAsync at the same time. Default: 10

Updating message statuses in batches with grouping

SqsAckFlow.grouped batches actions on their type and forwards a SqsAckResultEntrySqsAckResultEntry sub-class for each item processed:

  • DeleteResultEntry to acknowledge message deletion
  • ChangeMessageVisibilityResultEntry to acknowledge message visibility change
  • In case of Ignore action, nothing is performed on the sqs queue, thus no SqsAckResult is forwarded.

Acknowledge (delete) messages:

Scala
sourceSqsSource(queueUrl, sqsSourceSettings)
  .take(10)
  .map(MessageAction.Delete(_))
  .via(SqsAckFlow.grouped(queueUrl, SqsAckGroupedSettings.Defaults))
  .runWith(Sink.seq)
Java
sourcesource
    .map(m -> MessageAction.delete(m))
    .via(SqsAckFlow.grouped(queueUrl, SqsAckGroupedSettings.create(), awsClient))
    .runWith(Sink.seq(), system);

Ignore messages:

Scala
sourceSource(messages)
  .take(10)
  .map(MessageAction.Ignore(_))
  .via(SqsAckFlow.grouped("queue", SqsAckGroupedSettings.Defaults))
  .runWith(Sink.seq)
Java
sourcesource
    .map(m -> MessageAction.ignore(m))
    .via(SqsAckFlow.grouped(queueUrl, SqsAckGroupedSettings.create(), awsClient))
    .runWith(Sink.seq(), system);

Change Visibility Timeout of messages:

Scala
sourceSqsSource(queueUrl, sqsSourceSettings)
  .take(10)
  .map(MessageAction.ChangeMessageVisibility(_, 5.minutes))
  .via(SqsAckFlow.grouped(queueUrl, SqsAckGroupedSettings.Defaults))
  .runWith(Sink.seq)
Java
sourcesource
    .map(m -> MessageAction.changeMessageVisibility(m, 5))
    .via(SqsAckFlow.grouped(queueUrl, SqsAckGroupedSettings.create(), awsClient))
    .runWith(Sink.seq(), system);

Acknowledge grouping configuration

Scala
sourceval batchSettings =
  SqsAckGroupedSettings()
    .withMaxBatchSize(10)
    .withMaxBatchWait(500.millis)
    .withConcurrentRequests(1)
Java
sourceSqsAckGroupedSettings flowSettings =
    SqsAckGroupedSettings.create()
        .withMaxBatchSize(10)
        .withMaxBatchWait(Duration.ofMillis(500))
        .withConcurrentRequests(1);

Options:

  • maxBatchSize - the maximum number of messages in batch to send SQS. Default: 10.
  • maxBatchWait - the maximum duration for which the stage waits until maxBatchSize messages arrived. Sends what is collects at the end of the time period even though the maxBatchSize is not fulfilled. Default: 500 milliseconds
  • concurrentRequests - the number of batches sending to SQS concurrently.

Integration testing

For integration testing without touching Amazon SQS, Apache Pekko Connectors uses ElasticMQ, a queuing service which serves an AWS SQS compatible API.