要在Apache Beam中使用BigQuery的Upsert(更新或插入)功能,可以使用BigQuery的Java客户端库和Beam的ParDo转换。下面是一个示例代码:
import org.apache.beam.sdk.Pipeline;
import org.apache.beam.sdk.coders.AvroCoder;
import org.apache.beam.sdk.io.gcp.bigquery.BigQueryIO;
import org.apache.beam.sdk.transforms.DoFn;
import org.apache.beam.sdk.transforms.ParDo;
import org.apache.beam.sdk.values.PCollection;
import org.apache.beam.sdk.values.Row;
import org.apache.beam.sdk.values.TypeDescriptor;
public class UpsertExample {
public static void main(String[] args) {
// 创建一个Pipeline
Pipeline pipeline = Pipeline.create();
// 读取BigQuery表中的数据
PCollection input = pipeline.apply(
BigQueryIO.readTableRows().from("project-id:dataset.table"));
// 将数据转换为UpsertRow对象
PCollection upsertRows = input.apply(
ParDo.of(new ConvertToUpsertRowFn())
.withOutputType(TypeDescriptor.of(UpsertRow.class)));
// 将UpsertRow对象写入BigQuery表中
upsertRows.apply(
BigQueryIO.writeTableRows()
.to("project-id:dataset.table")
.withFormatFunction(row -> row.toTableRow())
.withWriteDisposition(BigQueryIO.Write.WriteDisposition.WRITE_APPEND)
.withCreateDisposition(BigQueryIO.Write.CreateDisposition.CREATE_NEVER));
// 运行Pipeline
pipeline.run();
}
// 自定义DoFn用于将Row对象转换为UpsertRow对象
static class ConvertToUpsertRowFn extends DoFn {
@ProcessElement
public void processElement(ProcessContext c) {
Row row = c.element();
UpsertRow upsertRow = new UpsertRow(row.getString("id"), row.getString("name"));
c.output(upsertRow);
}
}
// UpsertRow对象包含要插入或更新的数据
static class UpsertRow {
public String id;
public String name;
public UpsertRow(String id, String name) {
this.id = id;
this.name = name;
}
public TableRow toTableRow() {
return new TableRow()
.set("id", id)
.set("name", name);
}
}
}
在这个示例中,我们首先读取了BigQuery表中的数据,并将其转换为UpsertRow对象。然后,我们使用BigQueryIO将UpsertRow对象写入BigQuery表中。在ConvertToUpsertRowFn中,我们使用自定义的DoFn将Row对象转换为UpsertRow对象。最后,我们将UpsertRow对象转换为TableRow对象,并将其写入BigQuery表中。