Class Bigtable (5.0.0)

const {Bigtable} = require('@google-cloud/bigtable');
const bigtable = new Bigtable();

const {Bigtable} = require('@google-cloud/bigtable');
const bigtable = new Bigtable({
  projectId: 'your-project-id',
  keyFilename: '/path/to/keyfile.json'
});

// Make sure you have the {@link https://cloud.google.com/sdk/downloads gcloud SDK installed}, then run:
$ gcloud beta emulators bigtable start

// Before running your Node.js app, set the environment variables that this
// library will look for to connect to the emulator:

$ $(gcloud beta emulators bigtable env-init)

// Before you create your table, you first need to create a Bigtable Instance
// and cluster for the table to be served from.

const {Bigtable} = require('@google-cloud/bigtable');
const bigtable = new Bigtable();

const callback = (err, instance, operation) => {
  operation
    .on('error', console.log)
    .on('complete', () => {
      // `instance` is your newly created Instance object.
    });
};

const instance = bigtable.instance('my-instance');

instance.create({
  clusters: [
    {
      id: 'my-cluster',
      location: 'us-central1-b',
      nodes: 3
    }
  ]
}, callback);

// This can also be done from either the Google Cloud Platform Console or the
// `gcloud` cli tool. Please refer to the
// {@link https://cloud.google.com/bigtable/docs/creating-instance official Bigtable documentation}
// for more information.

// After creating your instance and enabling the Bigtable APIs, you are now
// ready to create your table with {@link Instance#createTable}.
instance.createTable('prezzy', function(err, table) {
  // `table` is your newly created Table object.
});

// Column families are used to group together various pieces of data within
// your table. You can think of column families as a mechanism to categorize
// all of your data.
//
// We can create a column family with {@link Table#createFamily}.
const table = instance.table('prezzy');

table.createFamily('follows', function(err, family) {
  // `family` is your newly created Family object.
});

// It is also possible to create your column families when creating a new
// table.
const options = {
  families: ['follows']
};

instance.createTable('prezzy', options, function(err, table) {});

// New rows can be created within your table using
// {@link Table#insert}. You must provide a unique key for each row
// to be inserted, this key can then be used to retrieve your row at a later
// time.
//
// With Bigtable, all columns have a unique id composed of a column family
// and a column qualifier. In the example below `follows` is the column
// family and `tjefferson` is the column qualifier. Together they could be
// referred to as `follows:tjefferson`.
const rows = [
  {
    key: 'wmckinley',
    data: {
      follows: {
        tjefferson: 1
      }
    }
  }
];

table.insert(rows, err => {
  if (!err) {
    // Your rows were successfully inserted.
  }
});

// If you're anticipating a large number of rows to be returned, we suggest
// using the {@link Table#getRows} streaming API.
table.createReadStream()
  .on('error', console.error)
  .on('data', row => {
    // `row` is a Row object.
  });

// If you're not anticpating a large number of results, a callback mode
// is also available.
const callback = (err, rows) => {
  // `rows` is an array of Row objects.
};

table.getRows(callback);

// A range of rows can be retrieved by providing `start` and `end` row keys.
const options = {
  start: 'gwashington',
  end: 'wmckinley'
};

table.getRows(options, callback);

// Retrieve an individual row with {@link Row#get}.
const row = table.row('alincoln');

row.get(err => {
  // `row.data` is now populated.
});

// When retrieving rows, upon success the `row.data` property will be
// populated by an object. That object will contain additional objects
// for each family in your table that the row has data for.
//
// By default, when retrieving rows, each column qualifier will provide you
// with all previous versions of the data. So your `row.data` object could
// resemble the following.
{
  follows: {
    wmckinley: [
      {
        value: 1,
        timestamp: 1466017315951
      }, {
        value: 2,
        timestamp: 1458619200000
      }
    ]
  }
}

// The `timestamp` field can be used to order cells from newest to oldest.
// If you only wish to retrieve the most recent version of the data, you
// can specify the number of cells with a {@link Filter} object.
const filter = [
  {
    column: {
      cellLimit: 1
    }
  }
];

table.getRows({
  filter: filter
}, callback);

// We can delete all of an individual row's cells using {@link Row#delete}.
const callback = err => {
  if (!err) {
    // All cells for this row were deleted successfully.
  }
};

row.delete(callback);

// To delete a specific set of cells, we can provide an array of
// column families and qualifiers.
const cells = [
  'follows:gwashington',
  'traits'
];

row.delete(cells, callback);

// If you wish to delete multiple rows entirely, we can do so with
// {@link Table#deleteRows}. You can provide this method with a
// row key prefix.
const options = {
  prefix: 'gwash'
};

table.deleteRows(options, err => {
  if (!err) {
    // Rows were deleted successfully.
  }
});

// If you omit the prefix, you can delete all rows in your table.
table.deleteRows(err => {
  if (!err) {
    // All rows were deleted successfully.
  }
});