Cloud Storage Sink Connector for Pulsar

The Cloud Storage sink connector supports exporting data from Pulsar topics to cloud storage (such as AWS S3 and Google GCS) either in Avro, JSON, Parquet or other formats. According to your environment, the Cloud Storage sink connector can guarantee exactly-once support for exporting data to cloud storage.

Installation

There are two ways to install the Cloud Storage sink connector.

• Install the the Cloud Storage sink connector through the NAR file.
• Install the the Cloud Storage sink connector from the source code.

To build the the Cloud Storage sink connector from the source code, follow these steps.

1. Clone the project from GitHub to your local.

   git clone https://github.com/streamnative/pulsar-io-cloud-storage.git
   cd pulsar-io-cloud-storage

2. Build the project.

   mvn clean install -DskipTests

   You can find the NAR file in the following directory.

   ./pulsar-io-cloud-storage/target/pulsar-io-cloud-storage-${version}.nar

Configuration

The Cloud Storage sink connector supports the following properties.

Cloud Storage sink connector configuration

Storage Provider: AWS S3

Name	Type	Required	Default	Description
provider	String	True	null	The Cloud Storage type, such as aws-s3,s3v2(s3v2 uses the AWS client but not the JCloud client).
accessKeyId	String	True	null	The Cloud Storage access key ID. It requires permission to write objects.
secretAccessKey	String	True	null	The Cloud Storage secret access key.
role	String	False	null	The Cloud Storage role.
roleSessionName	String	False	null	The Cloud Storage role session name.
endpoint	String	True	null	The Cloud Storage endpoint.
bucket	String	True	null	The Cloud Storage bucket.
formatType	String	False	"json"	The data format type. Available options are JSON, Avro, Bytes, or Parquet. By default, it is set to JSON.
partitionerType	String	False	"partition"	The partitioning type. It can be configured by topic partitions or by time. By default, the partition type is configured by topic partitions.
timePartitionPattern	String	False	"yyyy-MM-dd"	The format pattern of the time-based partitioning. For details, refer to the Java date and time format.
timePartitionDuration	String	False	"86400000"	The time interval for time-based partitioning. Support formatted interval string, such as 30d, 24h, 30m, 10s, and also support number in milliseconds precision, such as 86400000 refers to 24h or 1d.
batchSize	int	False	10	The number of records submitted in batch.
batchTimeMs	long	False	1000	The interval for batch submission.
sliceTopicPartitionPath	Boolean	False	false	When it is set to true, split the partitioned topic name into separate folders in the bucket path.
withMetadata	Boolean	False	false	Save message attributes to metadata.
useHumanReadableMessageId	Boolean	False	false	Use a human-readable format string for messageId in message metadata. The messageId is in a format like ledgerId:entryId:partitionIndex:batchIndex. Otherwise, the messageId is a Hex-encoded string.
withTopicPartitionNumber	Boolean	False	true	When it is set to true, include the topic partition number to the object path.
bytesFormatTypeSeparator	String	False	"0x10"	It is inserted between records for the formatType of bytes. By default, it is set to '0x10'. An input record that contains the line separator looks like multiple records in the output object.
pendingQueueSize	int	False	100	The number of records buffered in queue. By default, it is batchSize * 10. You can set it manually.
useHumanReadableSchemaVersion	Boolean	False	false	Use a human-readable format string for the schema version in the message metadata. If it is set to true, the schema version is in plain string format. Otherwise, the schema version is in hex-encoded string format.
skipFailedMessages	Boolean	False	false	Configure whether to skip a message which it fails to be processed. If it is set to true, the connector will skip the failed messages by ack it. Otherwise, the connector will fail the message.

Storage Provider: Google Cloud Storage

Name	Type	Required	Default	Description
provider	String	True	null	The Cloud Storage type. Google cloud storage only support google-cloud-storage provider.
gcsServiceAccountKeyFilePath	String	False	""	Path to the GCS credentials file. If empty, the credentials file are read from the GOOGLE_APPLICATION_CREDENTIALS environment variable.
gcsServiceAccountKeyFileContent	String	False	""	The contents of the JSON service key file. If empty, credentials are read from gcsServiceAccountKeyFilePath file.
bucket	String	True	null	The Cloud Storage bucket.
formatType	String	False	"json"	The data format type. Available options are JSON, Avro, Bytes, or Parquet. By default, it is set to JSON.
partitionerType	String	False	"partition"	The partitioning type. It can be configured by topic partitions or by time. By default, the partition type is configured by topic partitions.
timePartitionPattern	String	False	"yyyy-MM-dd"	The format pattern of the time-based partitioning. For details, refer to the Java date and time format.
timePartitionDuration	String	False	"86400000"	The time interval for time-based partitioning. Support formatted interval string, such as 30d, 24h, 30m, 10s, and also support number in milliseconds precision, such as 86400000 refers to 24h or 1d.
batchSize	int	False	10	The number of records submitted in batch.
batchTimeMs	long	False	1000	The interval for batch submission.
sliceTopicPartitionPath	Boolean	False	false	When it is set to true, split the partitioned topic name into separate folders in the bucket path.
withMetadata	Boolean	False	false	Save message attributes to metadata.
useHumanReadableMessageId	Boolean	False	false	Use a human-readable format string for messageId in message metadata. The messageId is in a format like ledgerId:entryId:partitionIndex:batchIndex. Otherwise, the messageId is a Hex-encoded string.
withTopicPartitionNumber	Boolean	False	true	When it is set to true, include the topic partition number to the object path.
bytesFormatTypeSeparator	String	False	"0x10"	It is inserted between records for the formatType of bytes. By default, it is set to '0x10'. An input record that contains the line separator looks like multiple records in the output object.
pendingQueueSize	int	False	100	The number of records buffered in queue. By default, it is batchSize * 10. You can set it manually.
useHumanReadableSchemaVersion	Boolean	False	false	Use a human-readable format string for the schema version in the message metadata. If it is set to true, the schema version is in plain string format. Otherwise, the schema version is in hex-encoded string format.
skipFailedMessages	Boolean	False	false	Configure whether to skip a message which it fails to be processed. If it is set to true, the connector will skip the failed messages by ack it. Otherwise, the connector will fail the message.

Configure Cloud Storage sink connector

Before using the Cloud Storage sink connector, you need to create a configuration file through one of the following methods.

• JSON

  {
     "tenant": "public",
     "namespace": "default",
     "name": "cloud-storage-sink",
     "inputs": [
        "user-avro-topic"
     ],
     "archive": "connectors/pulsar-io-cloud-storage-0.0.1.nar",
     "parallelism": 1,
     "configs": {
        "provider": "aws-s3",
        "accessKeyId": "accessKeyId",
        "secretAccessKey": "secretAccessKey",
        "role": "none",
        "roleSessionName": "none",
        "bucket": "testBucket",
        "region": "local",
        "endpoint": "us-standard",
        "formatType": "parquet",
        "partitionerType": "time",
        "timePartitionPattern": "yyyy-MM-dd",
        "timePartitionDuration": "1d",
        "batchSize": 10,
        "batchTimeMs": 1000
     }
  }

• YAML

  tenant: "public"
  namespace: "default"
  name: "Cloud Storage-sink"
  inputs: 
    - "user-avro-topic"
  archive: "connectors/pulsar-io-cloud-storage-0.0.1.nar"
  parallelism: 1
  
  configs:
    provider: "aws-s3",
    accessKeyId: "accessKeyId"
    secretAccessKey: "secretAccessKey"
    role: "none"
    roleSessionName: "none"
    bucket: "testBucket"
    region: "local"
    endpoint: "us-standard"
    formatType: "parquet"
    partitionerType: "time"
    timePartitionPattern: "yyyy-MM-dd"
    timePartitionDuration: "1d"
    batchSize: 10
    batchTimeMs: 1000

Data format types

Cloud Storage Sink Connector provides multiple output format options, including JSON, Avro, Bytes, or Parquet. The default format is JSON. With current implementation, there are some limitations for different formats:

This table lists the Pulsar Schema types supported by the writers.

Pulsar Schema	Writer: Avro	Writer: JSON	Writer: Parquet	Writer: Bytes
Primitive	✗	✔ *	✗	✔
Avro	✔	✔	✔	✔
Json	✔	✔	✔	✔
Protobuf **	✔	✔	✔	✔
ProtobufNative	✔ ***	✗	✔	✔

*: The JSON writer will try to convert the data with a String or Bytes schema to JSON-format data if convertable.

**: The Protobuf schema is based on the Avro schema. It uses Avro as an intermediate format, so it may not provide the best effort conversion.

***: The ProtobufNative record holds the Protobuf descriptor and the message. When writing to Avro format, the connector uses avro-protobuf to do the conversion.

This table lists the support of withMetadata configurations for different writer formats:

Writer Format	withMetadata
Avro	✔
JSON	✔
Parquet	✔ *
Bytes	✗

*: When using Parquet with PROTOBUF_NATIVE format, the connector will write the messages with DynamicMessage format. When withMetadata is set to true, the connector will add __message_metadata__ to the messages with PulsarIOCSCProtobufMessageMetadata format.

For example, if a message User has the following schema:

syntax = "proto3";
message User {
 string name = 1;
 int32 age = 2;
}

When withMetadata is set to true, the connector will write the message DynamicMessage with the following schema:

syntax = "proto3";
message PulsarIOCSCProtobufMessageMetadata {
 map<string, string> properties = 1;
 string schema_version = 2;
 string message_id = 3;
}
message User {
 string name = 1;
 int32 age = 2;
 PulsarIOCSCProtobufMessageMetadata __message_metadata__ = 3;
}

By default, when the connector receives a message with a non-supported schema type, the connector will fail the message. If you want to skip the non-supported messages, you can set skipFailedMessages to true.

Dead-letter topics

To use a dead-letter topic, you need to set skipFailedMessages to false, and set --max-redeliver-count and --dead-letter-topic when submit the connector with the pulsar-admin CLI tool. For more info about dead-letter topics, see the Pulsar documentation. If a message fails to be sent to the Cloud Storage and there is a dead-letter topic, the connector will send the message to the dead-letter topic.

Usage

1. Prepare the AWS Cloud Storage service. In this example, we use Cloud Storagemock as an example.

   docker pull apachepulsar/s3mock:latest
   docker run -p 9090:9090 -e initialBuckets=pulsar-integtest apachepulsar/s3mock:latest
   

2. Put the pulsar-io-cloud-storage-2.5.1.nar in the Pulsar connector catalog.

   cp pulsar-io-cloud-storage-2.5.1.nar $PULSAR_HOME/connectors/pulsar-io-cloud-storage-2.5.1.nar
   

3. Start Pulsar in the standalone mode.

   $PULSAR_HOME/bin/pulsar standalone
   

4. Run the Cloud Storage sink connector locally.

   $PULSAR_HOME/bin/pulsar-admin sink localrun --sink-config-file cloud-storage-sink-config.yaml
   

5. Send Pulsar messages. Currently, Avro or JSON mode supports formatType json, avro, parquet. No schema mode can only use bytes formatType.

     try (
                PulsarClient pulsarClient = PulsarClient.builder()
                        .serviceUrl("pulsar://localhost:6650")
                        .build();
                Producer<TestRecord> producer = pulsarClient.newProducer(Schema.AVRO(TestRecord.class))
                        .topic("public/default/test-parquet-avro")
                        .create();
                ) {
                List<TestRecord> testRecords = Arrays.asList(
                        new TestRecord("key1", 1, null),
                        new TestRecord("key2", 1, new TestRecord.TestSubRecord("aaa"))
                );
                for (TestRecord record : testRecords) {
                    producer.send(record);
                }
            }

6. Validate Cloud Storage data.

   To get the path, you can use the jclould to verify the file, as shown below.

   Properties overrides = new Properties();
   overrides.put(“jclouds.s3.virtual-host-buckets”, “false”);
   BlobStoreContext blobStoreContext = ContextBuilder.newBuilder(“aws-s3”)
           .credentials(
                   “accessKeyId”,
                   “secretAccessKey”
           )
           .endpoint(“http://localhost:9090”) // replace to s3mock url
           .overrides(overrides)
           .buildView(BlobStoreContext.class);
   BlobStore blobStore = blobStoreContext.getBlobStore();
   final long sequenceId = FunctionCommon.getSequenceId(message.getMessageId());
   final String path = “public/default/test-parquet-avro” + File.separator + “2020-09-14" + File.separator + sequenceId + “.parquet”;
   final boolean blobExists = blobStore.blobExists(“testBucket”, path);
   Assert.assertTrue(“the sink record does not exist”, blobExists);

   You can find the data in your testBucket bucket. The path is something like public/default/test-parquet-avro/2020-09-14/1234.parquet. The path consists of three parts, the basic part of the topic, partition information, and format suffix.

   • Basic part of topic: public/default/test-parquet-avro/ This part consists of the name of the tenant, namespace, and the input topic.
   • Partition information: 2020-09-14/${messageSequenceId} The date is generated based on the partitionerType parameter in the configuration. And the ${messageSequenceId} is generated by FunctionCommon.getSequenceId(message.getMessageId()).
   • Format suffix: .parquet This part is generated based on the formatType parameter in the configuration.

Permissions

AWS S3 permission policies

The suggested permission policies for AWS S3 are:

• s3:AbortMultipartUpload
• s3:GetObject*
• s3:PutObject*
• s3:List*

If you do not want to provide region in the configuration, you should enable s3:GetBucketLocation permission policy as well.