Apply Side input to BigQueryIO.read operation in Apache Beam

Question

Is there a way to apply a side input to a BigQueryIO.read() operation in Apache Beam.

Say for example I have a value in a PCollection that I want to use in a query to fetch data from a BigQuery table. Is this possible using side input? Or should something else be used in such a case?

I used NestedValueProvider in a similar case but I guess we can use that only when a certain value depends on my runtime value. Or can I use the same thing here? Please correct me if I'm wrong.

The code that I tried:

Bigquery bigQueryClient = start_pipeline.newBigQueryClient(options.as(BigQueryOptions.class)).build();
    Tabledata tableRequest = bigQueryClient.tabledata();

PCollection<TableRow> existingData = readData.apply("Read existing data",ParDo.of(new DoFn<String,TableRow>(){
    @ProcessElement
    public void processElement(ProcessContext c) throws IOException
    {
        List<TableRow> list = c.sideInput(bqDataView);
        String tableName = list.get(0).get("table").toString();
        TableDataList table = tableRequest.list("projectID","DatasetID",tableName).execute();

        for(TableRow row:table.getRows())
        {
            c.output(row);
        }
    }
    }).withSideInputs(bqDataView));

The error that I get is:

Exception in thread "main" java.lang.IllegalArgumentException: unable to serialize BeamTest.StarterPipeline$1@86b455
    at org.apache.beam.sdk.util.SerializableUtils.serializeToByteArray(SerializableUtils.java:53)
    at org.apache.beam.sdk.util.SerializableUtils.clone(SerializableUtils.java:90)
    at org.apache.beam.sdk.transforms.ParDo$SingleOutput.<init>(ParDo.java:569)
    at org.apache.beam.sdk.transforms.ParDo.of(ParDo.java:434)
    at BeamTest.StarterPipeline.main(StarterPipeline.java:158)
Caused by: java.io.NotSerializableException: com.google.api.services.bigquery.Bigquery$Tabledata
    at java.io.ObjectOutputStream.writeObject0(Unknown Source)
    at java.io.ObjectOutputStream.defaultWriteFields(Unknown Source)
    at java.io.ObjectOutputStream.writeSerialData(Unknown Source)
    at java.io.ObjectOutputStream.writeOrdinaryObject(Unknown Source)
    at java.io.ObjectOutputStream.writeObject0(Unknown Source)
    at java.io.ObjectOutputStream.writeObject(Unknown Source)
    at org.apache.beam.sdk.util.SerializableUtils.serializeToByteArray(SerializableUtils.java:49)
    ... 4 more

Pablo Pablo · Accepted Answer · 2017-07-31T17:18:58

The Beam model does not currently support this kind of data-dependent operation very well.

A way of doing it is to code your own DoFn that receives the side input and connects directly to BQ. Unfortunately, this would not give you any parallelism, as the DoFn would run completely on the same thread.

Once Splittable DoFns are supported in Beam, this will be a different story.

In the current state of the world, you would need to use the BQ client library to add code that would query BQ as if you were not in a Beam pipeline.

Given the code in your question, a rough idea on how to implement this is the following:

class ReadDataDoFn extends DoFn<String,TableRow>(){
    private Tabledata tableRequest;

    private Bigquery bigQueryClient;

    private Bigquery createBigQueryClientWithinDoFn() {
        // I'm not sure how you'd implement this, but you had the right idea
    }

    @Setup
    public void setup() {
        bigQueryClient = createBigQueryClientWithinDoFn(); 
        tableRequest = bigQueryClient.tabledata();
    }
    @ProcessElement
    public void processElement(ProcessContext c) throws IOException
    {
        List<TableRow> list = c.sideInput(bqDataView);
        String tableName = list.get(0).get("table").toString();
        TableDataList table = tableRequest.list("projectID","DatasetID",tableName).execute();

        for(TableRow row:table.getRows())
        {
            c.output(row);
        }
    }
}

PCollection<TableRow> existingData = readData.apply("Read existing data",ParDo.of(new ReadDataDoFn()));

Apply Side input to BigQueryIO.read operation in Apache Beam

1 Answers