Prompt: What does this code do?

package parquet;

import java.io.Serializable;
import java.util.Objects;
import org.apache.avro.Schema;
import org.apache.avro.generic.GenericData;
import org.apache.avro.generic.GenericRecord;
import org.apache.avro.reflect.ReflectData;
import org.apache.beam.sdk.Pipeline;
import org.apache.beam.sdk.io.parquet.ParquetIO;
import org.apache.beam.sdk.options.Description;
import org.apache.beam.sdk.options.PipelineOptions;
import org.apache.beam.sdk.options.PipelineOptionsFactory;
import org.apache.beam.sdk.options.Validation;
import org.apache.beam.sdk.transforms.DoFn;
import org.apache.beam.sdk.transforms.ParDo;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;

public class ReadParquetFile {

    private static final Logger LOG = LoggerFactory.getLogger(ReadParquetFile.class);

    public static class ExampleRecord implements Serializable {
        public static final String COLUMN_ID = "id";
        public static final String COLUMN_MONTH = "month";
        public static final String COLUMN_AMOUNT = "amount";

        private int id;
        private String month;
        private String amount;
    }

    public interface ReadParquetFileOptions extends PipelineOptions {
        @Description("A glob file pattern to read Parquet files from")
        @Validation.Required
        String getFilePattern();

        void setFilePattern(String filePattern);
    }

    public static void main(String[] args) {
        ReadParquetFileOptions options =
            PipelineOptionsFactory.fromArgs(args).withValidation().as(ReadParquetFileOptions.class);

        Schema exampleRecordSchema = ReflectData.get().getSchema(ExampleRecord.class);

        Pipeline p = Pipeline.create(options);

        p.apply(
                "Read from Parquet file",
                ParquetIO.read(exampleRecordSchema)
                    .withAvroDataModel(GenericData.get())
                    .from(options.getFilePattern()))
            .apply(
                "Log records",
                ParDo.of(
                    new DoFn<GenericRecord, GenericRecord>() {
                        @ProcessElement
                        public void processElement(ProcessContext c) {
                            GenericRecord record = Objects.requireNonNull(c.element());
                            LOG.info(
                                "Id = {}, Name = {}, Amount = {}",
                                record.get(ExampleRecord.COLUMN_ID),
                                record.get(ExampleRecord.COLUMN_MONTH),
                                record.get(ExampleRecord.COLUMN_AMOUNT));
                            c.output(record);
                        }
                    }));
        p.run();
    }
}

Response: This code reads data from an Apache Parquet file using the ParquetIO.read transform from the ParquetIO connector provided by Apache Beam.

The ExampleRecord class defines the schema of the data in the Parquet file.

    public static class ExampleRecord implements Serializable {
        public static final String COLUMN_ID = "id";
        public static final String COLUMN_MONTH = "month";
        public static final String COLUMN_AMOUNT = "amount";

        private int id;
        private String month;
        private String amount;
    }

The ReadParquetFileOptions class defines the command-line argument --path, which specifies the path to the Parquet file. This code utilizes the pipeline options pattern for parsing command-line arguments.

    public interface ReadParquetFileOptions extends PipelineOptions {
        @Description("A glob file pattern to read Parquet files from")
        @Validation.Required
        String getFilePattern();

        void setFilePattern(String filePattern);
    }

The PipelineOptionsFactory class parses the command-line arguments and instantiates a PipelineOptions object. The ReflectData class defines the Schema object representing the Avro schema of the ExampleRecord class. The code snippet creates a Pipeline object using the PipelineOptions object.

        ReadParquetFileOptions options =
            PipelineOptionsFactory.fromArgs(args).withValidation().as(ReadParquetFileOptions.class);

        Schema exampleRecordSchema = ReflectData.get().getSchema(ExampleRecord.class);

        Pipeline p = Pipeline.create(options);

The pipeline employs the ParquetIO.read transform to extract data from the Parquet file. The withAvroDataModel method specifies that the data should be decoded using the Avro data model, and the from method specifies the path to the Parquet file.

        p.apply(
                "Read from Parquet file",
                ParquetIO.read(exampleRecordSchema)
                    .withAvroDataModel(GenericData.get())
                    .from(options.getFilePattern()))

Subsequently, the ParDo transform logs the records read from the Parquet file. The DoFn processes each element and logs the values of the fields in the ExampleRecord class.

            .apply(
                "Log records",
                ParDo.of(
                    new DoFn<GenericRecord, GenericRecord>() {
                        @ProcessElement
                        public void processElement(ProcessContext c) {
                            GenericRecord record = Objects.requireNonNull(c.element());
                            LOG.info(
                                "Id = {}, Name = {}, Amount = {}",
                                record.get(ExampleRecord.COLUMN_ID),
                                record.get(ExampleRecord.COLUMN_MONTH),
                                record.get(ExampleRecord.COLUMN_AMOUNT));
                            c.output(record);
                        }
                    }));

Finally, the code snippet invokes the Pipeline.run method to execute the pipeline.

        p.run();