Read table from BigQuery and convert to SpecifcAvro record

Google Cloud Data Analytics
1

I want to read records as a specific avro record in my Java API. I have tried to follow this example StorageSampleWithAvroBQ.

I have also generated an Avro class via this gradle plugin.

However, I cannot seem to make it work. Whenever I run my cloud function locally the error I get is

Caused by: java.lang.ClassCastException: class org.apache.avro.generic.GenericData$Record cannot be cast to class com.tdcx.cwfm.model.CwfmAbs (org.apache.avro.generic.GenericData$Record and com.tdcx.cwfm.model.CwfmAbs are in unnamed module of loader com.google.cloud.functions.invoker.runner.Invoker$FunctionClassLoader @7de26db8).

Kindly guide me in ensuring that I can read and process bigquery records as a specific class ( in this situation its CwfmAbs ).

jpjaymetdcx_0-1682661431168.png
jpjaymetdcx_0-1682661431168.png296Ă—402 7.71 KB

Avro Schema

{"namespace": "com.tdcx.cwfm.model",
  "type": "record",
  "name": "CwfmAbs",
  "fields": [
    {"name": "BCP", "type": "string"},
    {"name": "Project",  "type": "string"},
    {"name": "Site", "type": "string"},
    {"name": "LOB", "type": "string"},
    {"name": "Date",
      "type": {
        "type": "int",
        "logicalType": "date"
      }
    },
    {"name": "Emp_ID", "type": "string"},
    {"name": "Name", "type": "string"},
    {"name": "Supervisor", "type": "string"},
    {"name": "Manager", "type": "string"},
    {"name": "Scheduled_Hours_Less_Lunch", "type": "float"},
    {"name": "Absent_Hours_Less_Lunch", "type": "float"},
    {"name": "Late_Hours", "type": "float"}
.
.
.
}
2

The error you’re encountering indicates that you’re trying to cast a GenericData.Record object to a specific Avro class (CwfmAbs). To resolve the issue, you need to use a specific datum reader that works with the generated Avro class.

Please follow these steps to read and process BigQuery records as a specific class:

  1. Use the AvroCoder to work with your specific Avro class instead of using the default GenericData.Record:

import com.tdcx.cwfm.model.CwfmAbs;
import org.apache.beam.sdk.coders.AvroCoder;

// Replace with your specific Avro class
AvroCoder avroCoder = AvroCoder.of(CwfmAbs.class);

  1. When you read the records from BigQuery, make sure you’re using the specific Avro class and the AvroCoder:

import org.apache.beam.sdk.Pipeline;
import org.apache.beam.sdk.io.gcp.bigquery.BigQueryIO;
import org.apache.beam.sdk.values.PCollection;

Pipeline pipeline = Pipeline.create(options);
PCollection records = pipeline
.apply(BigQueryIO.read(avroCoder)
.from(“your-project:your_dataset.your_table”)
.usingStandardSql());

  1. After reading the records, you can use the PCollection<CwfmAbs> to process the records as instances of your specific Avro class (CwfmAbs).
3

Hi,

I checked the Apache Beam documentation page and apparently BigQueryIO.read is deprecated. From their page -

Note: BigQueryIO.read() is deprecated as of Beam SDK 2.2.0. Instead, use read(SerializableFunction<SchemaAndRecord, T>) to parse BigQuery rows

Can you give an example with this new syntax?

4

Here’s an example of how you can use the new syntax:

import org.apache.beam.sdk.Pipeline;
import org.apache.beam.sdk.io.gcp.bigquery.BigQueryIO;
import org.apache.beam.sdk.io.gcp.bigquery.BigQueryIO.TypedRead;
import org.apache.beam.sdk.io.gcp.bigquery.SchemaAndRecord;
import org.apache.beam.sdk.values.PCollection;
import com.google.api.services.bigquery.model.TableRow;

Pipeline p = Pipeline.create();

PCollection rows = p.apply(
“Read from BigQuery”,
BigQueryIO.read(new SerializableFunction<SchemaAndRecord, TableRow>() {
public TableRow apply(SchemaAndRecord schemaAndRecord) {
// Convert the BigQuery record into a TableRow object.
return schemaAndRecord.getRecord();
}
})
.from(“your-project-id:your_dataset.your_table”)
.withMethod(TypedRead.Method.DIRECT_READ));

In this example, the SerializableFunction is defined inline and simply returns the TableRow associated with each SchemaAndRecord object. You can replace this with your own function to perform more complex transformations as necessary.

The TypedRead.Method.DIRECT_READ indicates that we want to read directly from BigQuery storage. Note that this method requires the BigQuery Storage API to be enabled in your GCP project.

1 Like
5

Thank you!

On a related note, is this the only approach in reading data from BQ tables without using Apache Beam?

6

Besides Apache Beam or Dataflow, there are several other options available for reading data from BigQuery and converting it to Avro. Some of these options include:

  1. BigQuery API: You can use the BigQuery API directly to retrieve the data from BigQuery and then perform the conversion to Avro in your own code. The BigQuery API provides client libraries for various programming languages, allowing you to make requests to the API and retrieve the query results.

  2. Google Cloud Storage: Instead of directly converting the data from BigQuery to Avro, you can export the BigQuery table to Google Cloud Storage in a format like CSV or JSON. Then, you can read the exported files from Cloud Storage and convert them to Avro using a library or tool of your choice.

  3. Apache Spark: Apache Spark is a popular distributed data processing framework that supports reading data from BigQuery using its BigQuery Connector. You can use Spark’s DataFrame API or SQL interface to read data from BigQuery, perform transformations, and then convert it to Avro. Spark provides libraries like Avro4s or Spark Avro to help with Avro serialization.

  4. Python libraries: If you are working with Python, you can leverage libraries like pandas and pyarrow to read data from BigQuery into a pandas DataFrame and then convert it to Avro using the avro-python3 library. This approach gives you flexibility in manipulating the data using pandas before converting it to Avro.

1 Like
7

I was trying the solution in #1 with this question I posted. I want to retrieve data using Bigquery API and deserialized into a specific Avro class (CwfmAbs) but you referred Apache Beam. I’m confused in this. Can you clarify or atleast give an example without Beam?

For my current implementation, here is a pastebin link where my BigQueryReader method code is. I still get the error

org.apache.avro.AvroRuntimeException: Malformed data. Length is negative: -44

and

Caused by: java.lang.ClassCastException: class org.apache.avro.generic.GenericData$Record cannot be cast to class com.tdcx.cwfm.model.CwfmAbs (org.apache.avro.generic.GenericData$Record and com.tdcx.cwfm.model.CwfmAbs are in unnamed module of loader com.google.cloud.functions.invoker.runner.Invoker$FunctionClassLoader @7de26db8).