tfio.bigtable.BigtableTable

Entry point for reading data from Cloud Bigtable. This object represents

tfio.bigtable.BigtableTable(
    client_resource: tf.Tensor,
    table_id: str
)

a Bigtable Table and provides basic methods for reading from it.

Methods

`parallel_read_rows`

View source

parallel_read_rows(
    columns: List[str],
    num_parallel_calls=tf.data.AUTOTUNE,
    row_set: bigtable_row_set.RowSet = None,
    filter: filters.BigtableFilter = None,
    output_type=tf.string
)

Retrieves values from Google Bigtable in parallel. The ammount of work is split between workers based on SampleRowKeys. Keep in mind that when reading in parallel, rows are not read in any particular order. Args: columns (List[str]): the list of columns to read from; the order on this list will determine the order in the output tensors num_parallel_calls: number of workers assigned to reading the data. row_set (RowSet): set of rows to read.

Returns
A `tf.data.Dataset` returning the cell contents.

`read_rows`

View source

read_rows(
    columns: List[str],
    row_set: bigtable_row_set.RowSet,
    filter: filters.BigtableFilter = None,
    output_type=tf.string
)

Retrieves values from Google Bigtable sorted by RowKeys.

Args
columns (List[str]): the list of columns to read from; the order on this list will determine the order in the output tensors row_set (RowSet): set of rows to read.

Returns
A `tf.data.Dataset` returning the cell contents.