README.md

Flink BigQuery Connector

This project provides a BigQuery sink that allows writing data with exactly-once or at-least guarantees.

Usage

There are builder classes to simplify constructing a BigQuery sink. The code snippet below shows an example of building a BigQuery sink in Java:

var credentials = new JsonCredentialsProvider("key");

var clientProvider = new BigQueryProtoClientProvider<String>(credentials,
    WriterSettings.newBuilder()
                 .build()
);

var bigQuerySink = BigQueryStreamSink.<String>newBuilder()
    .withClientProvider(clientProvider)
    .withDeliveryGuarantee(DeliveryGuarantee.EXACTLY_ONCE)
    .withRowValueSerializer(new NoOpRowSerializer<>())
    .build();

Async connector for at least once delivery

var credentials = new JsonCredentialsProvider("key");

var clientProvider = new AsyncClientProvider<String>(credentials,
    WriterSettings.newBuilder()
                 .build()
);

var sink = AsyncBigQuerySink.builder()
        .setRowSerializer(new NoOpRowSerializer<>())
        .setClientProvider(clientProvider)
        .setMaxBatchSize(30)
        .setMaxBufferedRequests(10)
        .setMaxBatchSizeInBytes(10000)
        .setMaxInFlightRequests(4)
        .setMaxRecordSizeInBytes(10000)
        .build();

The sink takes in a batch of records. Batching happens outside the sink by opening a window. Batched records need to implement the BigQueryRecord interface.

var trigger = BatchTrigger.<Record, GlobalWindow>builder()
    .withCount(100)
    .withTimeout(Duration.ofSeconds(1))
    .withSizeInMb(1)
    .withResetTimerOnNewRecord(true)
    .build();

var processor = new BigQueryStreamProcessor()
    .withDeliveryGuarantee(DeliveryGuarantee.AT_LEAST_ONCE)
    .build();

source.key(s -> s)
    .window(GlobalWindows.create())
    .trigger(trigger)
    .process(processor);

To write to BigQuery, you need to:

• Define credentials
• Create a client provider
• Batch records
• Create a value serializer
• Sink to BigQuery

Credentials

There are two types of credentials:

• Loading from a file

new FileCredentialsProvider("/path/to/file")

• Passing as a JSON string

new JsonCredentialsProvider("key")

Types of Streams

BigQuery supports two types of data formats: json and proto. When creating a stream, you can choose these types by creating the appropriate client and using the builder methods.

• JSON

var clientProvider = new BigQueryJsonClientProvider<String>(credentials,
    WriterSettings.newBuilder()
                 .build()
);

var bigQuerySink = BigQueryStreamSink.<String>newBuilder()

• Proto

var clientProvider = new BigQueryProtoClientProvider(credentials,
    WriterSettings.newBuilder()
                 .build()
);

var bigQuerySink = BigQueryStreamSink.<String>newBuilder();

Exactly once

It utilizes a buffered stream, managed by the BigQueryStreamProcessor, to assign and process data batches. If a stream is inactive or closed, a new stream is created automatically. The BigQuery sink writer appends and flushes data to the latest offset upon checkpoint commit.

At least once

Data is written to the default stream and handled by the BigQueryStreamProcessor, which batches and sends rows to the sink for processing.

Serializers

For the proto stream, you need to implement ProtoValueSerializer, and for the JSON stream, you need to implement JsonRowValueSerializer.

Metrics

Scope	Metrics	Description	Type
Stream	stream_offset	Current offset for the stream. When using at least once, the offset is always 0	Gauge
	batch_count	Number of records in the appended batch	Gauge
	batch_size_mb	Appended batch size in mb	Gauge
	split_batch_count	Number of times the batch hit the BigQuery limit and was split into two parts	Gauge