Google BigQuery Storage: Node.js Client

 npm install @google-cloud/bigquery-storage 

 // The read stream contains blocks of Avro-encoded bytes. We use the
// 'avsc' library to decode these blocks. Install avsc with the following
// command: npm install avsc
const avro = require('avsc');

// See reference documentation at
// https://cloud.google.com/bigquery/docs/reference/storage
const {BigQueryReadClient} = require(' @google-cloud/bigquery-storage 
');

const client = new BigQueryReadClient 
();

async function bigqueryStorageQuickstart() {
  // Get current project ID. The read session is created in this project.
  // This project can be different from that which contains the table.
  const myProjectId = await client.getProjectId();

  // This example reads baby name data from the public datasets.
  const projectId = 'bigquery-public-data';
  const datasetId = 'usa_names';
  const tableId = 'usa_1910_current';

  const tableReference = `projects/${projectId}/datasets/${datasetId}/tables/${tableId}`;

  const parent = `projects/${myProjectId}`;

  /* We limit the output columns to a subset of those allowed in the table,
   * and set a simple filter to only report names from the state of
   * Washington (WA).
   */
  const readOptions = {
    selectedFields: ['name', 'number', 'state'],
    rowRestriction: 'state = "WA"',
  };

  let tableModifiers = null;
  const snapshotSeconds = 0;

  // Set a snapshot time if it's been specified.
  if (snapshotSeconds > 0) {
    tableModifiers = {snapshotTime: {seconds: snapshotSeconds}};
  }

  // API request.
  const request = {
    parent,
    readSession: {
      table: tableReference,
      // This API can also deliver data serialized in Apache Arrow format.
      // This example leverages Apache Avro.
      dataFormat: 'AVRO',
      readOptions,
      tableModifiers,
    },
  };

  const [session] = await client.createReadSession(request);

  const schema = JSON 
.parse(session.avroSchema.schema);

  const avroType = avro.Type.forSchema(schema);

  /* The offset requested must be less than the last
   * row read from ReadRows. Requesting a larger offset is
   * undefined.
   */
  let offset = 0;

  const readRowsRequest = {
    // Required stream name and optional offset. Offset requested must be less than
    // the last row read from readRows(). Requesting a larger offset is undefined.
    readStream: session.streams[0].name,
    offset,
  };

  const names = new Set();
  const states = [];

  /* We'll use only a single stream for reading data from the table. Because
   * of dynamic sharding, this will yield all the rows in the table. However,
   * if you wanted to fan out multiple readers you could do so by having a
   * reader process each individual stream.
   */
  client
    .readRows(readRowsRequest)
    .on('error', console.error)
    .on('data', data => {
      offset = data.avroRows.serializedBinaryRows.offset;

      try {
        // Decode all rows in buffer
        let pos;
        do {
          const decodedData = avroType.decode(
            data.avroRows.serializedBinaryRows,
            pos
          );

          if (decodedData.value) {
            names.add(decodedData.value.name);

            if (!states.includes(decodedData.value.state)) {
              states.push(decodedData.value.state);
            }
          }

          pos = decodedData.offset;
        } while (pos > 0);
      } catch (error) {
        console.log(error);
      }
    })
    .on('end', () => {
      console.log(`Got ${names.size} unique names in states: ${states}`);
      console.log(`Last offset: ${offset}`);
    });
}