Layanan BigQuery

Layanan BigQuery memungkinkan Anda menggunakan Google BigQuery API di Apps Script. API ini memberi pengguna kemampuan untuk mengelola project BigQuery, mengupload data baru, dan menjalankan kueri.

Referensi

Untuk mengetahui informasi mendetail tentang layanan ini, lihat dokumentasi referensi untuk BigQuery API. Seperti semua layanan lanjutan di Apps Script, layanan BigQuery menggunakan objek, metode, dan parameter yang sama dengan API publik. Untuk mengetahui informasi selengkapnya, lihat Cara menentukan tanda tangan metode.

Untuk melaporkan masalah dan menemukan dukungan lainnya, lihat panduan dukungan Google Cloud.

Kode contoh

Contoh kode di bawah menggunakan API versi 2.

Jalankan kueri

Contoh ini membuat kueri daftar istilah Google Penelusuran teratas harian.

advanced/bigquery.gs
/**
 * Runs a BigQuery query and logs the results in a spreadsheet.
 */
function runQuery() {
  // Replace this value with the project ID listed in the Google
  // Cloud Platform project.
  const projectId = 'XXXXXXXX';

  const request = {
    // TODO (developer) - Replace query with yours
    query: 'SELECT refresh_date AS Day, term AS Top_Term, rank ' +
      'FROM `bigquery-public-data.google_trends.top_terms` ' +
      'WHERE rank = 1 ' +
      'AND refresh_date >= DATE_SUB(CURRENT_DATE(), INTERVAL 2 WEEK) ' +
      'GROUP BY Day, Top_Term, rank ' +
      'ORDER BY Day DESC;',
    useLegacySql: false
  };
  let queryResults = BigQuery.Jobs.query(request, projectId);
  const jobId = queryResults.jobReference.jobId;

  // Check on status of the Query Job.
  let sleepTimeMs = 500;
  while (!queryResults.jobComplete) {
    Utilities.sleep(sleepTimeMs);
    sleepTimeMs *= 2;
    queryResults = BigQuery.Jobs.getQueryResults(projectId, jobId);
  }

  // Get all the rows of results.
  let rows = queryResults.rows;
  while (queryResults.pageToken) {
    queryResults = BigQuery.Jobs.getQueryResults(projectId, jobId, {
      pageToken: queryResults.pageToken
    });
    rows = rows.concat(queryResults.rows);
  }

  if (!rows) {
    console.log('No rows returned.');
    return;
  }
  const spreadsheet = SpreadsheetApp.create('BigQuery Results');
  const sheet = spreadsheet.getActiveSheet();

  // Append the headers.
  const headers = queryResults.schema.fields.map(function(field) {
    return field.name;
  });
  sheet.appendRow(headers);

  // Append the results.
  const data = new Array(rows.length);
  for (let i = 0; i < rows.length; i++) {
    const cols = rows[i].f;
    data[i] = new Array(cols.length);
    for (let j = 0; j < cols.length; j++) {
      data[i][j] = cols[j].v;
    }
  }
  sheet.getRange(2, 1, rows.length, headers.length).setValues(data);

  console.log('Results spreadsheet created: %s', spreadsheet.getUrl());
}

Memuat data CSV

Contoh ini membuat tabel baru dan memuat file CSV dari Google Drive ke dalamnya.

advanced/bigquery.gs
/**
 * Loads a CSV into BigQuery
 */
function loadCsv() {
  // Replace this value with the project ID listed in the Google
  // Cloud Platform project.
  const projectId = 'XXXXXXXX';
  // Create a dataset in the BigQuery UI (https://bigquery.cloud.google.com)
  // and enter its ID below.
  const datasetId = 'YYYYYYYY';
  // Sample CSV file of Google Trends data conforming to the schema below.
  // https://docs.google.com/file/d/0BwzA1Orbvy5WMXFLaTR1Z1p2UDg/edit
  const csvFileId = '0BwzA1Orbvy5WMXFLaTR1Z1p2UDg';

  // Create the table.
  const tableId = 'pets_' + new Date().getTime();
  let table = {
    tableReference: {
      projectId: projectId,
      datasetId: datasetId,
      tableId: tableId
    },
    schema: {
      fields: [
        {name: 'week', type: 'STRING'},
        {name: 'cat', type: 'INTEGER'},
        {name: 'dog', type: 'INTEGER'},
        {name: 'bird', type: 'INTEGER'}
      ]
    }
  };
  try {
    table = BigQuery.Tables.insert(table, projectId, datasetId);
    console.log('Table created: %s', table.id);
  } catch (err) {
    console.log('unable to create table');
  }
  // Load CSV data from Drive and convert to the correct format for upload.
  const file = DriveApp.getFileById(csvFileId);
  const data = file.getBlob().setContentType('application/octet-stream');

  // Create the data upload job.
  const job = {
    configuration: {
      load: {
        destinationTable: {
          projectId: projectId,
          datasetId: datasetId,
          tableId: tableId
        },
        skipLeadingRows: 1
      }
    }
  };
  try {
    const jobResult = BigQuery.Jobs.insert(job, projectId, data);
    console.log(`Load job started. Status: ${jobResult.status.state}`);
  } catch (err) {
    console.log('unable to insert job');
  }
}