Prompt: What does this code do?
public class ReadBigQueryTable { private static final Logger LOG = LoggerFactory.getLogger(ReadBigQueryTable.class); public interface ReadBigQueryTableOptions extends PipelineOptions { @Description("Table from which to read") @Default.String("bigquery-public-data:austin_bikeshare.bikeshare_stations") String getTableName(); void setTableName(String value); } public static void main(String[] args) { ReadTableBQOptions options = PipelineOptionsFactory.fromArgs(args).withValidation().as(ReadBigQueryTableOptions.class); Pipeline p = Pipeline.create(options); p .apply(BigQueryIO.readTableRows().from(options.getTableName())) .apply(ParDo.of(new DoFn<TableRow, String>() { @ProcessElement public void processElement(ProcessContext c) { c.output(c.element().toString()); } }) ); p.run(); } }
Response: This code snippet uses the Apache Beam BigQueryIO connector to read data from a BigQuery table.
The ReadBigQueryTableOptions interface defines the options that can be configured when running the pipeline. In this case, it specifies the BigQuery table to read from. The --tableName command-line argument sets the table name when running the pipeline. The @Description annotation provides a description of the option, while the @Default.String annotation sets a default value for the option.
public interface ReadBigQueryTableOptions extends PipelineOptions { @Description("Table from which to read") @Default.String("bigquery-public-data:austin_bikeshare.bikeshare_stations") String getTableName(); void setTableName(String value); }
In the main method, the PipelineOptionsFactory class creates a ReadBigQueryTableOptions object from the command-line arguments. The Pipeline.create method then creates a new pipeline with the specified options.
ReadTableBQOptions options = PipelineOptionsFactory.fromArgs(args).withValidation().as(ReadBigQueryTableOptions.class); Pipeline p = Pipeline.create(options);
The (BigQueryIO.readTableRows().from(options.getTableName()) method reads data from the specified BigQuery table. The ParDo transform then applies a DoFn to each element of the input PCollection. In this case, the DoFn simply outputs the input element.
p .apply(BigQueryIO.readTableRows().from(options.getTableName())) .apply(ParDo.of(new DoFn<TableRow, String>() { @ProcessElement public void processElement(ProcessContext c) { c.output(c.element().toString()); } }) );
Finally, the run method executes the pipeline.
p.run();