Table

User-friendly container for Google Cloud Bigtable Table.

class google.cloud.bigtable.table.ClusterState(replication_state)

Bases: object

Representation of a Cluster State.

  • Parameters

    replication_state (int) – enum value for cluster state Possible replications_state values are 0 for STATE_NOT_KNOWN: The replication state of the table is unknown in this cluster. 1 for INITIALIZING: The cluster was recently created, and the table must finish copying over pre-existing data from other clusters before it can begin receiving live replication updates and serving Data API requests. 2 for PLANNED_MAINTENANCE: The table is temporarily unable to serve Data API requests from this cluster due to planned internal maintenance. 3 for UNPLANNED_MAINTENANCE: The table is temporarily unable to serve Data API requests from this cluster due to unplanned or emergency maintenance. 4 for READY: The table can serve Data API requests from this cluster. Depending on replication delay, reads may not immediately reflect the state of the table in other clusters.

_eq_(other)

Checks if two ClusterState instances(self and other) are equal on the basis of instance variable ‘replication_state’.

  • Parameters

    other (ClusterState) – ClusterState instance to compare with.

  • Return type

    Boolean value

  • Returns

    True if two cluster state instances have same replication_state.

_ne_(other)

Checks if two ClusterState instances(self and other) are not equal.

  • Parameters

    other (ClusterState.) – ClusterState instance to compare with.

  • Return type

    Boolean value.

  • Returns

    True if two cluster state instances are not equal.

_repr_()

Representation of cluster state instance as string value for cluster state.

  • Return type

    ClusterState instance

  • Returns

    ClusterState instance as representation of string value for cluster state.

google.cloud.bigtable.table.DEFAULT_RETRY( = <google.api_core.retry.Retry object )

The default retry strategy to be used on retry-able errors.

Used by mutate_rows().

class google.cloud.bigtable.table.Table(table_id, instance, mutation_timeout=None, app_profile_id=None)

Bases: object

Representation of a Google Cloud Bigtable Table.

NOTE: We don’t define any properties on a table other than the name. The only other fields are column_families and granularity, The column_families are not stored locally and granularity is an enum with only one value.

We can use a Table to:

  • create() the table

  • delete() the table

  • list_column_families() in the table

  • Parameters

    • table_id (str) – The ID of the table.

    • instance (Instance) – The instance that owns the table.

    • app_profile_id (str) – (Optional) The unique name of the AppProfile.

append_row(row_key)

Create a AppendRow associated with this table.

For example:

    from google.cloud.bigtable import Client

    client = Client(admin=True)
    instance = client.instance(INSTANCE_ID)
    table = instance.table(TABLE_ID)

    row_keys = [b"row_key_1", b"row_key_2"]
    row1_obj = table.append_row(row_keys[0])
    row2_obj = table.append_row(row_keys[1])

  • Parameters

    row_key (bytes) – The key for the row being created.

  • Returns

    A row owned by this table.

column_family(column_family_id, gc_rule=None)

Factory to create a column family associated with this table.

For example:

    from google.cloud.bigtable import Client

    client = Client(admin=True)
    instance = client.instance(INSTANCE_ID)

    table = instance.table(TABLE_ID)
    column_family_obj = table.column_family(COLUMN_FAMILY_ID)

  • Parameters

    • column_family_id (str) – The ID of the column family. Must be of the form [_a-zA-Z0-9][-_.a-zA-Z0-9]\*.

    • gc_rule (GarbageCollectionRule) – (Optional) The garbage collection settings for this column family.

  • Return type

    ColumnFamily

  • Returns

    A column family owned by this table.

conditional_row(row_key, filter_)

Create a ConditionalRow associated with this table.

For example:

    from google.cloud.bigtable import Client
    from google.cloud.bigtable.row_filters import PassAllFilter

    client = Client(admin=True)
    instance = client.instance(INSTANCE_ID)
    table = instance.table(TABLE_ID)

    row_keys = [b"row_key_1", b"row_key_2"]
    filter_ = PassAllFilter(True)
    row1_obj = table.conditional_row(row_keys[0], filter_=filter_)
    row2_obj = table.conditional_row(row_keys[1], filter_=filter_)

  • Parameters

    • row_key (bytes) – The key for the row being created.

    • filter (RowFilter) – (Optional) Filter to be used for conditional mutations. See ConditionalRow for more details.

  • Returns

    A row owned by this table.

create(initial_split_keys=[], column_families={})

Creates this table.

For example:

    from google.cloud.bigtable import Client
    from google.cloud.bigtable import column_family

    client = Client(admin=True)
    instance = client.instance(INSTANCE_ID)

    # Create table without Column families.
    table1 = instance.table("table_id1")
    table1.create()

    # Create table with Column families.
    table2 = instance.table("table_id2")
    # Define the GC policy to retain only the most recent 2 versions.
    max_versions_rule = column_family.MaxVersionsGCRule(2)
    table2.create(column_families={"cf1": max_versions_rule})

NOTE: A create request returns a _generated.table_pb2.Table but we don’t use this response.

  • Parameters

    • initial_split_keys (list) – (Optional) list of row keys in bytes that will be used to initially split the table into several tablets.

    • column_failies – (Optional) A map columns to create. The key is the column_id str and the value is a GarbageCollectionRule

delete()

Delete this table.

For example:

    from google.cloud.bigtable import Client

    client = Client(admin=True)
    instance = client.instance(INSTANCE_ID)
    table = instance.table("table_id_del")

    table.delete()

direct_row(row_key)

Create a DirectRow associated with this table.

For example:

    from google.cloud.bigtable import Client

    client = Client(admin=True)
    instance = client.instance(INSTANCE_ID)
    table = instance.table(TABLE_ID)

    row_keys = [b"row_key_1", b"row_key_2"]
    row1_obj = table.direct_row(row_keys[0])
    row2_obj = table.direct_row(row_keys[1])

  • Parameters

    row_key (bytes) – The key for the row being created.

  • Returns

    A row owned by this table.

drop_by_prefix(row_key_prefix, timeout=None)

For example:

    from google.cloud.bigtable import Client

    client = Client(admin=True)
    instance = client.instance(INSTANCE_ID)
    table = instance.table(TABLE_ID)
    row_key_prefix = b"row_key_2"
    table.drop_by_prefix(row_key_prefix, timeout=200)

  • Parameters

    • row_prefix (bytes) – Delete all rows that start with this row key prefix. Prefix cannot be zero length.

    • timeout (float) – (Optional) The amount of time, in seconds, to wait for the request to complete.

  • Raise

    google.api_core.exceptions.GoogleAPICallError: If the request failed for any reason. google.api_core.exceptions.RetryError: If the request failed due to a retryable error and retry attempts failed. ValueError: If the parameters are invalid.

exists()

Check whether the table exists.

For example:

    from google.cloud.bigtable import Client

    client = Client(admin=True)
    instance = client.instance(INSTANCE_ID)
    table = instance.table(TABLE_ID)
    table_exists = table.exists()

  • Return type

    bool

  • Returns

    True if the table exists, else False.

get_cluster_states()

List the cluster states owned by this table.

For example:

    from google.cloud.bigtable import Client

    client = Client(admin=True)
    instance = client.instance(INSTANCE_ID)
    table = instance.table(TABLE_ID)

    get_cluster_states = table.get_cluster_states()

  • Return type

    dict

  • Returns

    Dictionary of cluster states for this table. Keys are cluster ids and values are :class: ‘ClusterState’ instances.

list_column_families()

List the column families owned by this table.

For example:

    from google.cloud.bigtable import Client

    client = Client(admin=True)
    instance = client.instance(INSTANCE_ID)
    table = instance.table(TABLE_ID)

    column_family_list = table.list_column_families()

  • Return type

    dict

  • Returns

    Dictionary of column families attached to this table. Keys are strings (column family names) and values are ColumnFamily instances.

  • Raises

    ValueError if the column family name from the response does not agree with the computed name from the column family ID.

mutate_rows(rows, retry=<google.api_core.retry.Retry object>)

Mutates multiple rows in bulk.

For example:

    from google.cloud.bigtable import Client

    client = Client(admin=True)
    instance = client.instance(INSTANCE_ID)
    table = instance.table(TABLE_ID)
    row_keys = [
        b"row_key_1",
        b"row_key_2",
        b"row_key_3",
        b"row_key_4",
        b"row_key_20",
        b"row_key_22",
        b"row_key_200",
    ]
    col_name = b"col-name1"
    rows = []
    for i, row_key in enumerate(row_keys):
        value = "value_{}".format(i).encode()
        row = table.row(row_key)
        row.set_cell(
            COLUMN_FAMILY_ID, col_name, value, timestamp=datetime.datetime.utcnow()
        )
        rows.append(row)
    response = table.mutate_rows(rows)
    # validate that all rows written successfully
    for i, status in enumerate(response):
        if status.code != 0:
            print("Row number {} failed to write".format(i))

The method tries to update all specified rows. If some of the rows weren’t updated, it would not remove mutations. They can be applied to the row separately. If row mutations finished successfully, they would be cleaned up.

Optionally, a retry strategy can be specified to re-attempt mutations on rows that return transient errors. This method will retry until all rows succeed or until the request deadline is reached. To specify a retry strategy of “do-nothing”, a deadline of 0.0 can be specified.

  • Parameters

    • rows (list) – List or other iterable of DirectRow instances.

    • retry (Retry) – (Optional) Retry delay and deadline arguments. To override, the default value DEFAULT_RETRY can be used and modified with the with_delay() method or the with_deadline() method.

  • Return type

    list

  • Returns

    A list of response statuses (google.rpc.status_pb2.Status) corresponding to success or failure of each row mutation sent. These will be in the same order as the rows.

mutations_batcher(flush_count=1000, max_row_bytes=5242880)

Factory to create a mutation batcher associated with this instance.

For example:

    from google.cloud.bigtable import Client

    client = Client(admin=True)
    instance = client.instance(INSTANCE_ID)
    table = instance.table(TABLE_ID)
    batcher = table.mutations_batcher()

  • Parameters

    • table (class) – class:~google.cloud.bigtable.table.Table.

    • flush_count (int) – (Optional) Maximum number of rows per batch. If it reaches the max number of rows it calls finish_batch() to mutate the current row batch. Default is FLUSH_COUNT (1000 rows).

    • max_row_bytes (int) – (Optional) Max number of row mutations size to flush. If it reaches the max number of row mutations size it calls finish_batch() to mutate the current row batch. Default is MAX_ROW_BYTES (5 MB).

property name()

Table name used in requests.

For example:

    from google.cloud.bigtable import Client

    client = Client(admin=True)
    instance = client.instance(INSTANCE_ID)

    table = instance.table(TABLE_ID)
    table_name = table.name

NOTE: This property will not change if table_id does not, but the return value is not cached.

The table name is of the form

"projects/../instances/../tables/{table_id}"

  • Return type

    str

  • Returns

    The table name.

read_row(row_key, filter_=None)

Read a single row from this table.

For example:

    from google.cloud.bigtable import Client

    client = Client(admin=True)
    instance = client.instance(INSTANCE_ID)
    table = instance.table(TABLE_ID)
    row_key = "row_key_1"
    row = table.read_row(row_key)

  • Parameters

    • row_key (bytes) – The key of the row to read from.

    • filter (RowFilter) – (Optional) The filter to apply to the contents of the row. If unset, returns the entire row.

  • Return type

    PartialRowData, NoneType

  • Returns

    The contents of the row if any chunks were returned in the response, otherwise None.

  • Raises

    ValueError if a commit row chunk is never encountered.

read_rows(start_key=None, end_key=None, limit=None, filter_=None, end_inclusive=False, row_set=None, retry=<google.api_core.retry.Retry object>)

Read rows from this table.

For example:

    from google.cloud.bigtable import Client

    client = Client(admin=True)
    instance = client.instance(INSTANCE_ID)
    table = instance.table(TABLE_ID)

    # Read full table
    partial_rows = table.read_rows()
    read_rows = [row for row in partial_rows]

  • Parameters

    • start_key (bytes) – (Optional) The beginning of a range of row keys to read from. The range will include start_key. If left empty, will be interpreted as the empty string.

    • end_key (bytes) – (Optional) The end of a range of row keys to read from. The range will not include end_key. If left empty, will be interpreted as an infinite string.

    • limit (int) – (Optional) The read will terminate after committing to N rows’ worth of results. The default (zero) is to return all results.

    • filter (RowFilter) – (Optional) The filter to apply to the contents of the specified row(s). If unset, reads every column in each row.

    • end_inclusive (bool) – (Optional) Whether the end_key should be considered inclusive. The default is False (exclusive).

    • row_set (row_set.RowSet) – (Optional) The row set containing multiple row keys and row_ranges.

    • retry (Retry) – (Optional) Retry delay and deadline arguments. To override, the default value DEFAULT_RETRY_READ_ROWS can be used and modified with the with_delay() method or the with_deadline() method.

  • Return type

    PartialRowsData

  • Returns

    A PartialRowsData a generator for consuming the streamed results.

row(row_key, filter_=None, append=False)

Factory to create a row associated with this table.

For example:

    from google.cloud.bigtable import Client

    client = Client(admin=True)
    instance = client.instance(INSTANCE_ID)
    table = instance.table(TABLE_ID)

    row_keys = [b"row_key_1", b"row_key_2"]
    row1_obj = table.row(row_keys[0])
    row2_obj = table.row(row_keys[1])

WARNING: At most one of filter_ and append can be used in a Row.

  • Parameters

    • row_key (bytes) – The key for the row being created.

    • filter (RowFilter) – (Optional) Filter to be used for conditional mutations. See ConditionalRow for more details.

    • append (bool) – (Optional) Flag to determine if the row should be used for append mutations.

  • Return type

    Row

  • Returns

    A row owned by this table.

  • Raises

    ValueError if both filter_ and append are used.

sample_row_keys()

Read a sample of row keys in the table.

For example:

    from google.cloud.bigtable import Client

    client = Client(admin=True)
    instance = client.instance(INSTANCE_ID)

    table = instance.table("table_id1_samplerow")
    data = table.sample_row_keys()
    actual_keys, offset = zip(*[(rk.row_key, rk.offset_bytes) for rk in data])

The returned row keys will delimit contiguous sections of the table of approximately equal size, which can be used to break up the data for distributed tasks like mapreduces.

The elements in the iterator are a SampleRowKeys response and they have the properties offset_bytes and row_key. They occur in sorted order. The table might have contents before the first row key in the list and after the last one, but a key containing the empty string indicates “end of table” and will be the last response given, if present.

NOTE: Row keys in this list may not have ever been written to or read from, and users should therefore not make any assumptions about the row key structure that are specific to their use case.

The offset_bytes field on a response indicates the approximate total storage space used by all rows in the table which precede row_key. Buffering the contents of all rows between two subsequent samples would require space roughly equal to the difference in their offset_bytes fields.

  • Return type

    GrpcRendezvous

  • Returns

    A cancel-able iterator. Can be consumed by calling next() or by casting to a list and can be cancelled by calling cancel().

truncate(timeout=None)

Truncate the table

For example:

    from google.cloud.bigtable import Client

    client = Client(admin=True)
    instance = client.instance(INSTANCE_ID)
    table = instance.table(TABLE_ID)
    table.truncate(timeout=200)

  • Parameters

    timeout (float) – (Optional) The amount of time, in seconds, to wait for the request to complete.

  • Raise

    google.api_core.exceptions.GoogleAPICallError: If the request failed for any reason. google.api_core.exceptions.RetryError: If the request failed due to a retryable error and retry attempts failed. ValueError: If the parameters are invalid.

yield_rows(**kwargs)

Read rows from this table.

WARNING: This method will be removed in future releases. Please use read_rows instead.

  • Parameters

    • start_key (bytes) – (Optional) The beginning of a range of row keys to read from. The range will include start_key. If left empty, will be interpreted as the empty string.

    • end_key (bytes) – (Optional) The end of a range of row keys to read from. The range will not include end_key. If left empty, will be interpreted as an infinite string.

    • limit (int) – (Optional) The read will terminate after committing to N rows’ worth of results. The default (zero) is to return all results.

    • filter (RowFilter) – (Optional) The filter to apply to the contents of the specified row(s). If unset, reads every column in each row.

    • row_set (row_set.RowSet) – (Optional) The row set containing multiple row keys and row_ranges.

  • Return type

    PartialRowData

  • Returns

    A PartialRowData for each row returned

exception google.cloud.bigtable.table.TableMismatchError()

Bases: ValueError

Row from another table.

exception google.cloud.bigtable.table.TooManyMutationsError()

Bases: ValueError

The number of mutations for bulk request is too big.