firehose_pyio 0.1.0

Apache Beam Python I/O connector for Amazon Firehose

firehose_pyio

Amazon Data Firehose is a fully managed service for delivering real-time streaming data to destinations such as Amazon Simple Storage Service (Amazon S3), Amazon Redshift, Amazon OpenSearch Service and Amazon OpenSearch Serverless. The Apache Beam Python I/O connector for Amazon Data Firehose (firehose_pyio) provides a data sink feature that facilitates integration with those services.

Installation

$ pip install firehose_pyio

Usage

The connector has the main composite transform (WriteToFirehose), and it expects a list or tuple PCollection element. If the element is a tuple, the tuple's first element is taken. If the element is not of the accepted types, you can apply the GroupIntoBatches or BatchElements transform beforehand. Then, the element is sent into a Firehose delivery stream using the put_record_batch method of the boto3 package. Note that the above batch transforms can also be useful to overcome the API limitation listed below.

• Each PutRecordBatch request supports up to 500 records. Each record in the request can be as large as 1,000 KB (before base64 encoding), up to a limit of 4 MB for the entire request. These limits cannot be changed.

The transform also has options that control individual records or handling failed records.

• jsonify - A flag that indicates whether to convert a record into Json. Note that a record should be of bytes, bytearray or file-like object, and, if it is not of a supported type (e.g. integer), we can convert it into a Json string by specifying this flag to True.
• multiline - A flag that indicates whether to add a new line character (\n) to each record. It is useful to save records into a CSV or Jsonline file.
• max_trials - The maximum number of trials when there is one or more failed records - it defaults to 3. Note that failed records after all trials are returned, which allows users to determine how to handle them subsequently.

Example

If a PCollection element is key-value pair (i.e. keyed stream), it can be batched in group using the GroupIntoBatches transform before it is connected into the main transform.

import apache_beam as beam
from apache_beam import GroupIntoBatches
from firehose_pyio.io import WriteToFirehose

with beam.Pipeline(options=pipeline_options) as p:
    (
        p
        | beam.Create([(1, "one"), (2, "three"), (1, "two"), (2, "four")])
        | GroupIntoBatches(batch_size=2)
        | WriteToFirehose(
            delivery_stream_name=delivery_stream_name,
            jsonify=True,
            multiline=True,
            max_trials=3
        )
    )

For a list element (i.e. unkeyed stream), we can apply the BatchElements transform instead.

import apache_beam as beam
from apache_beam.transforms.util import BatchElements
from firehose_pyio.io import WriteToFirehose

with beam.Pipeline(options=pipeline_options) as p:
    (
        p
        | beam.Create(["one", "two", "three", "four"])
        | BatchElements(min_batch_size=2, max_batch_size=2)
        | WriteToFirehose(
            delivery_stream_name=delivery_stream_name,
            jsonify=True,
            multiline=True,
            max_trials=3
        )
    )

See this post for more examples.

Contributing

Interested in contributing? Check out the contributing guidelines. Please note that this project is released with a Code of Conduct. By contributing to this project, you agree to abide by its terms.

License

firehose_pyio was created by Beam PyIO [e-mail]. It is licensed under the terms of the Apache License 2.0 license.

Credits

firehose_pyio was created with cookiecutter and the pyio-cookiecutter template.