Prompt: What does this code do?
class ExampleRow(NamedTuple): id: int name: str class SpannerOptions(PipelineOptions): @classmethod def _add_argparse_args(cls, parser): parser.add_argument( '--project_id', default='your-project-id', help='Google Cloud project ID' ) parser.add_argument( '--instance_id', default='your-instance-id', help='Google Cloud Spanner instance ID' ) parser.add_argument( '--database_id', default='your-database-id', help='Google Cloud Spanner database ID' ) options = SpannerOptions() coders.registry.register_coder(ExampleRow, coders.RowCoder) with beam.Pipeline(options=options) as p: output = (p | "Read from table" >> ReadFromSpanner( project_id=options.project_id, instance_id=options.instance_id, database_id=options.database_id, row_type=ExampleRow, sql="SELECT * FROM example_row" ) | "Log Data" >> Map(logging.info))
Response: This code uses the Apache Beam SpannerIO connector to read data from a Cloud Spanner table example_row from the database your-database-id in the instance your-instance-id. The values your-database-id, your-instance-id, and your-project-id are provided as command-line arguments.
class SpannerOptions(PipelineOptions): @classmethod def _add_argparse_args(cls, parser): parser.add_argument( '--project_id', default='your-project-id', help='Google Cloud project ID' ) parser.add_argument( '--instance_id', default='your-instance-id', help='Google Cloud Spanner instance ID' ) parser.add_argument( '--database_id', default='your-database-id', help='Google Cloud Spanner database ID' ) options = SpannerOptions()
This code uses pipeline options to parse command-line arguments. The SpannerOptions class defines the command-line arguments project_id, instance_id, and database_id, which are used to configure the ReadFromSpanner transform.
class ExampleRow(NamedTuple): id: int name: str
This code defines a NamedTuple object ExampleRow that represents a Cloud Spanner row. The NamedTuple object includes the fields id and name, serving as attributes for a Cloud Spanner row. The ReadFromSpanner transform uses this object as a row type.
coders.registry.register_coder(ExampleRow, coders.RowCoder)
Registering a coder for NamedTuple is required to use NamedTuple as a row type. For more information about how to register a coder for a custom type, see Data encoding and type safety.
output = (p | "Read from table" >> ReadFromSpanner( project_id=options.project_id, instance_id=options.instance_id, database_id=options.database_id, row_type=ExampleRow, sql="SELECT * FROM example_row" ) | "Log Data" >> Map(logging.info))
The ReadFromSpanner transform returns a PCollection of NamedTuple objects, each representing a Cloud Spanner row. For more information about this row object, see ReadFromSpanner transform.
The Apache Beam pipeline logs the data from a Cloud Spanner row to the console.