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| <title>PutBigQuery</title> |
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| <h1>Streaming Versus Batching Data</h1> |
| |
| <p> |
| PutBigQuery is record based and is relying on the gRPC based Write API using protocol buffers. The underlying stream supports both streaming and batching approaches. |
| </p> |
| |
| <h3>Streaming</h3> |
| <p> |
| With streaming the appended data to the stream is instantly available in BigQuery for reading. It is configurable how many records (rows) should be appended at once. |
| Only one stream is established per flow file so at the conclusion of the FlowFile processing the used stream is closed and a new one is opened for the next FlowFile. |
| Supports exactly once delivery semantics via stream offsets. |
| </p> |
| |
| <h3>Batching</h3> |
| <p> |
| Similarly to the streaming approach one stream is opened for each FlowFile and records are appended to the stream. However data is not available in BigQuery until it is |
| committed by the processor at the end of the FlowFile processing. |
| </p> |
| |
| <h1>Improvement opportunities</h1> |
| <p> |
| <ul> |
| <li>The table has to exist on BigQuery side it is not created automatically</li> |
| <li>The Write API supports multiple streams for parallel execution and transactionality across streams. This is not utilized at the moment as this would be covered on NiFI framework level.</li> |
| </ul> |
| </p> |
| |
| <p> |
| The official <a href="https://cloud.google.com/bigquery/docs/write-api">Google Write API documentation</a> provides additional details. |
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