AWS S3

This connector is also available on the AWS Marketplace.

Connector Class

io.lenses.streamreactor.connect.aws.s3.source.S3SourceConnector

Example

name=aws-s3SourceConnectorParquet
connector.class=io.lenses.streamreactor.connect.aws.s3.source.S3SourceConnector
tasks.max=1
connect.s3.kcql=insert into $TOPIC_NAME select * from $BUCKET_NAME:$PREFIX_NAME STOREAS `parquet`
connect.s3.aws.region=eu-west-2
connect.s3.aws.secret.key=SECRET_KEY
connect.s3.aws.access.key=ACCESS_KEY
connect.s3.aws.auth.mode=Credentials

KCQL Support

The connector uses a SQL-like syntax to configure the connector behaviour. The full KCQL syntax is:

INSERT INTO $kafka-topic
SELECT *
FROM bucketAddress:pathPrefix
[BATCH=batch]
[STOREAS storage_format]
[LIMIT limit]
[PROPERTIES(
  'property.1'=x,
  'property.2'=x,
)]

Please note that you can employ escaping within KCQL for the INSERT INTO, SELECT * FROM, and PARTITIONBY clauses when necessary. For example, if you need to use a topic name that contains a hyphen, you can escape it as follows:

INSERT INTO `my-topic-with-hyphen`
SELECT *
FROM bucketAddress:pathPrefix

Source Bucket & Path

The S3 source location is defined within the FROM clause. The connector will read all files from the given location considering the data partitioning and ordering options. Each data partition will be read by a single connector task.

The FROM clause format is:

FROM [bucketname]:pathprefix
//my-bucket-called-pears:my-folder-called-apples 

Target Bucket & Path

The target Kafka topic is specified via the INSERT INTO clause. The connector will write all the records to the given topic:

INSERT INTO my-apples-topic SELECT * FROM  my-bucket-called-pears:my-folder-called-apples 

S3 File formats

The connector supports a range of storage formats, each with its own distinct functionality:

• JSON: The connector will read files containing JSON content, each line representing a distinct record.

• Avro: The connector will read Avro-stored messages from S3 and translate them into Kafka’s native format.

• Parquet: The connector will read Parquet-stored messages from S3 and translate them into Kafka’s native format.

• Text: The connector will read files containing lines of text, each line representing a distinct record.

• CSV: The connector will read files containing lines of text, each line representing a distinct record.

• CSV_WithHeaders: The connector will read files containing lines of text, each line representing a distinct record while skipping the header row.

• Bytes: The connector will read files containing bytes, each file is translated to a Kafka message.

Use the STOREAS clause to configure the storage format. The following options are available:

STOREAS `JSON`
STOREAS `Avro`
STOREAS `Parquet`
STOREAS `Text`
STOREAS `CSV`
STOREAS `CSV_WithHeaders`
STOREAS `Bytes`

Text Processing

When using Text storage, the connector provides additional configuration options to finely control how text content is processed.

Regex

In Regex mode, the connector applies a regular expression pattern, and only when a line matches the pattern is it considered a record. For example, to include only lines that start with a number, you can use the following configuration:

connect.s3.kcql=insert into $kafka-topic select * from lensesio:regex STOREAS `text` PROPERTIES('read.text.mode'='regex', 'read.text.regex'='^[1-9].*')

Start-End line

In Start-End Line mode, the connector reads text content between specified start and end lines, inclusive. This mode is useful when you need to extract records that fall within defined boundaries. For instance, to read records where the first line is ‘SSM’ and the last line is an empty line (’’), you can configure it as follows:

connect.s3.kcql=insert into $kafka-topic select * from lensesio:multi_line STOREAS `text` PROPERTIES('read.text.mode'='startEndLine', 'read.text.start.line'='SSM', 'read.text.end.line'='')

To trim the start and end lines, set the read.text.trim property to true:

connect.s3.kcql=insert into $kafka-topic select * from lensesio:multi_line STOREAS `text` PROPERTIES('read.text.mode'='startEndLine', 'read.text.start.line'='SSM', 'read.text.end.line'='', 'read.text.trim'='true')

Start-End tag

In Start-End Tag mode, the connector reads text content between specified start and end tags, inclusive. This mode is particularly useful when a single line of text in S3 corresponds to multiple output Kafka messages. For example, to read XML records enclosed between ‘’ and ‘’, configure it as follows:

connect.s3.kcql=insert into $kafka-topic select * from lensesio:xml STOREAS `text` PROPERTIES('read.text.mode'='startEndTag', 'read.text.start.tag'='<SSM>', 'read.text.end.tag'='</SSM>')

Storage output matrix

Depending on the storage format of Kafka topics’ messages, the need for replication to a different cluster, and the specific data analysis requirements, there exists a guideline on how to effectively utilize converters for both sink and source operations. This guidance aims to optimize performance and minimize unnecessary CPU and memory usage.

Projections

Currently, the connector does not offer support for SQL projection; consequently, anything other than a SELECT * query is disregarded. The connector will faithfully write all the record fields to Kafka exactly as they are.

Ordering

The S3 sink employs zero-padding in file names to ensure precise ordering, leveraging optimizations offered by the S3 API, guaranteeing the accurate sequence of files.

When using the S3 source alongside the S3 sink, the connector can adopt the same ordering method, ensuring data processing follows the correct chronological order. However, there are scenarios where S3 data is generated by applications that do not maintain lexical file name order.

In such cases, to process files in the correct sequence, the source needs to list all files in the bucket and sort them based on their last modified timestamp. To enable this behavior, set the connect.s3.source.ordering.type to LastModified. This ensures that the source correctly arranges and processes the data based on the timestamps of the files.

Throttling

To limit the number of file names the source reads from S3 in a single poll. The default value, if not specified, is 1000:

BATCH = 100

To limit the number of result rows returned from the source in a single poll operation, you can use the LIMIT clause. The default value, if not specified, is 10000.

LIMIT 10000

File Extension Filtering

The AWS S3 Source Connector allows you to filter the files to be processed based on their extensions. This is controlled by two properties: connect.s3.source.extension.excludes and connect.s3.source.extension.includes.

Excluding File Extensions

The connect.s3.source.extension.excludes property is a comma-separated list of file extensions to exclude from the source file search. If this property is not configured, all files are considered. For example, to exclude .txt and .csv files, you would set this property as follows:

connect.s3.source.extension.excludes=txt,csv

Including File Extensions

The connect.s3.source.extension.includes property is a comma-separated list of file extensions to include in the source file search. If this property is not configured, all files are considered. For example, to include only .json and .xml files, you would set this property as follows:

connect.s3.source.extension.includes=json,xml

Note: If both connect.s3.source.extension.excludes and connect.s3.source.extension.includes are set, the connector first applies the exclusion filter and then the inclusion filter.

Properties

The PROPERTIES clause is optional and adds a layer of configuration to the connector. It enhances versatility by permitting the application of multiple configurations (delimited by ‘,’). The following properties are supported:

Authentication

The connector offers two distinct authentication modes:

• Default: This mode relies on the default AWS authentication chain, simplifying the authentication process.

• Credentials: In this mode, explicit configuration of AWS Access Key and Secret Key is required for authentication.

When selecting the “Credentials” mode, it is essential to provide the necessary access key and secret key properties. Alternatively, if you prefer not to configure these properties explicitly, the connector will follow the credentials retrieval order as described here.

Here’s an example configuration for the “Credentials” mode:

connect.s3.aws.auth.mode=Credentials
connect.s3.aws.region=eu-west-2
connect.s3.aws.access.key=$AWS_ACCESS_KEY
connect.s3.aws.secret.key=$AWS_SECRET_KEY

For enhanced security and flexibility when using the “Credentials” mode, it is highly advisable to utilize Connect Secret Providers. This approach ensures robust security practices while handling access credentials.

API Compatible systems

The connector can also be used against API compatible systems provided they implement the following:

listObjectsV2
listObjectsV2Pagbinator
putObject
getObject
headObject
deleteObjects
deleteObject

Option Reference