tfio.bigtable.BigtableTable
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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.
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.
|
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Last updated 2022-02-15 UTC.
[null,null,["Last updated 2022-02-15 UTC."],[],[],null,["# tfio.bigtable.BigtableTable\n\n\u003cbr /\u003e\n\n|-------------------------------------------------------------------------------------------------------------------------------------------|\n| [View source on GitHub](https://github.com/tensorflow/io/blob/v0.24.0/tensorflow_io/python/ops/bigtable/bigtable_dataset_ops.py#L42-L133) |\n\nEntry point for reading data from Cloud Bigtable. This object represents \n\n tfio.bigtable.BigtableTable(\n client_resource: tf.Tensor,\n table_id: str\n )\n\na Bigtable Table and provides basic methods for reading from it.\n\nMethods\n-------\n\n### `parallel_read_rows`\n\n[View source](https://github.com/tensorflow/io/blob/v0.24.0/tensorflow_io/python/ops/bigtable/bigtable_dataset_ops.py#L84-L133) \n\n parallel_read_rows(\n columns: List[str],\n num_parallel_calls=tf.data.AUTOTUNE,\n row_set: bigtable_row_set.RowSet = None,\n filter: filters.BigtableFilter = None,\n output_type=tf.string\n )\n\nRetrieves values from Google Bigtable in parallel. The ammount of work\nis split between workers based on SampleRowKeys. Keep in mind that when\nreading in parallel, rows are not read in any particular order.\nArgs:\ncolumns (List\\[str\\]): the list of columns to read from; the order on\nthis list will determine the order in the output tensors\nnum_parallel_calls: number of workers assigned to reading the data.\nrow_set (RowSet): set of rows to read.\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Returns ||\n|---|---|\n| A [`tf.data.Dataset`](https://www.tensorflow.org/api_docs/python/tf/data/Dataset) returning the cell contents. ||\n\n\u003cbr /\u003e\n\n### `read_rows`\n\n[View source](https://github.com/tensorflow/io/blob/v0.24.0/tensorflow_io/python/ops/bigtable/bigtable_dataset_ops.py#L56-L82) \n\n read_rows(\n columns: List[str],\n row_set: bigtable_row_set.RowSet,\n filter: filters.BigtableFilter = None,\n output_type=tf.string\n )\n\nRetrieves values from Google Bigtable sorted by RowKeys.\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Args ||\n|---|---|\n| 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. ||\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Returns ||\n|---|---|\n| A [`tf.data.Dataset`](https://www.tensorflow.org/api_docs/python/tf/data/Dataset) returning the cell contents. ||\n\n\u003cbr /\u003e"]]
View source on GitHub