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SpannerAsyncClient(*, credentials: Optional[google.auth.credentials.Credentials] = None, transport: Union[str, google.cloud.spanner_v1.services.spanner.transports.base.SpannerTransport] = 'grpc_asyncio', client_options: Optional[google.api_core.client_options.ClientOptions] = None, client_info: google.api_core.gapic_v1.client_info.ClientInfo = <google.api_core.gapic_v1.client_info.ClientInfo object>)
Cloud Spanner API The Cloud Spanner API can be used to manage sessions and execute transactions on data stored in Cloud Spanner databases.
Properties
transport
Returns the transport used by the client instance.
Returns | |
---|---|
Type | Description |
SpannerTransport | The transport used by the client instance. |
Methods
SpannerAsyncClient
SpannerAsyncClient(*, credentials: Optional[google.auth.credentials.Credentials] = None, transport: Union[str, google.cloud.spanner_v1.services.spanner.transports.base.SpannerTransport] = 'grpc_asyncio', client_options: Optional[google.api_core.client_options.ClientOptions] = None, client_info: google.api_core.gapic_v1.client_info.ClientInfo = <google.api_core.gapic_v1.client_info.ClientInfo object>)
Instantiates the spanner client.
Parameters | |
---|---|
Name | Description |
credentials |
Optional[google.auth.credentials.Credentials]
The authorization credentials to attach to requests. These credentials identify the application to the service; if none are specified, the client will attempt to ascertain the credentials from the environment. |
transport |
Union[str,
The transport to use. If set to None, a transport is chosen automatically. |
client_options |
ClientOptions
Custom options for the client. It won't take effect if a |
Exceptions | |
---|---|
Type | Description |
google.auth.exceptions.MutualTlsChannelError | If mutual TLS transport creation failed for any reason. |
batch_create_sessions
batch_create_sessions(request: Optional[Union[google.cloud.spanner_v1.types.spanner.BatchCreateSessionsRequest, dict]] = None, *, database: Optional[str] = None, session_count: Optional[int] = None, retry: Union[google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())
Creates multiple new sessions. This API can be used to initialize a session cache on the clients. See https://goo.gl/TgSFN2 for best practices on session cache management.
from google.cloud import spanner_v1
async def sample_batch_create_sessions():
# Create a client
client = spanner_v1.SpannerAsyncClient()
# Initialize request argument(s)
request = spanner_v1.BatchCreateSessionsRequest(
database="database_value",
session_count=1420,
)
# Make the request
response = await client.batch_create_sessions(request=request)
# Handle the response
print(response)
Parameters | |
---|---|
Name | Description |
request |
Union[google.cloud.spanner_v1.types.BatchCreateSessionsRequest, dict]
The request object. The request for |
database |
Required. The database in which the new sessions are created. This corresponds to the |
session_count |
Required. The number of sessions to be created in this batch call. The API may return fewer than the requested number of sessions. If a specific number of sessions are desired, the client can make additional calls to BatchCreateSessions (adjusting |
retry |
google.api_core.retry.Retry
Designation of what errors, if any, should be retried. |
timeout |
float
The timeout for this request. |
metadata |
Sequence[Tuple[str, str]]
Strings which should be sent along with the request as metadata. |
Returns | |
---|---|
Type | Description |
google.cloud.spanner_v1.types.BatchCreateSessionsResponse | The response for BatchCreateSessions][google.spanner.v1.Spanner.BatchCreateSessions] . |
begin_transaction
begin_transaction(request: Optional[Union[google.cloud.spanner_v1.types.spanner.BeginTransactionRequest, dict]] = None, *, session: Optional[str] = None, options: Optional[google.cloud.spanner_v1.types.transaction.TransactionOptions] = None, retry: Union[google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())
Begins a new transaction. This step can often be skipped:
Read][google.spanner.v1.Spanner.Read]
,
ExecuteSql][google.spanner.v1.Spanner.ExecuteSql]
and
Commit][google.spanner.v1.Spanner.Commit]
can begin a new
transaction as a side-effect.
from google.cloud import spanner_v1
async def sample_begin_transaction():
# Create a client
client = spanner_v1.SpannerAsyncClient()
# Initialize request argument(s)
request = spanner_v1.BeginTransactionRequest(
session="session_value",
)
# Make the request
response = await client.begin_transaction(request=request)
# Handle the response
print(response)
Parameters | |
---|---|
Name | Description |
request |
Union[google.cloud.spanner_v1.types.BeginTransactionRequest, dict]
The request object. The request for |
session |
Required. The session in which the transaction runs. This corresponds to the |
options |
TransactionOptions
Required. Options for the new transaction. This corresponds to the |
retry |
google.api_core.retry.Retry
Designation of what errors, if any, should be retried. |
timeout |
float
The timeout for this request. |
metadata |
Sequence[Tuple[str, str]]
Strings which should be sent along with the request as metadata. |
Returns | |
---|---|
Type | Description |
google.cloud.spanner_v1.types.Transaction | A transaction. |
commit
commit(request: Optional[Union[google.cloud.spanner_v1.types.spanner.CommitRequest, dict]] = None, *, session: Optional[str] = None, transaction_id: Optional[bytes] = None, mutations: Optional[Sequence[google.cloud.spanner_v1.types.mutation.Mutation]] = None, single_use_transaction: Optional[google.cloud.spanner_v1.types.transaction.TransactionOptions] = None, retry: Union[google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())
Commits a transaction. The request includes the mutations to be applied to rows in the database.
Commit
might return an ABORTED
error. This can occur at
any time; commonly, the cause is conflicts with concurrent
transactions. However, it can also happen for a variety of other
reasons. If Commit
returns ABORTED
, the caller should
re-attempt the transaction from the beginning, re-using the same
session.
On very rare occasions, Commit
might return UNKNOWN
.
This can happen, for example, if the client job experiences a 1+
hour networking failure. At that point, Cloud Spanner has lost
track of the transaction outcome and we recommend that you
perform another read from the database to see the state of
things as they are now.
from google.cloud import spanner_v1
async def sample_commit():
# Create a client
client = spanner_v1.SpannerAsyncClient()
# Initialize request argument(s)
request = spanner_v1.CommitRequest(
transaction_id=b'transaction_id_blob',
session="session_value",
)
# Make the request
response = await client.commit(request=request)
# Handle the response
print(response)
Parameters | |
---|---|
Name | Description |
request |
Union[google.cloud.spanner_v1.types.CommitRequest, dict]
The request object. The request for |
session |
Required. The session in which the transaction to be committed is running. This corresponds to the |
transaction_id |
Commit a previously-started transaction. This corresponds to the |
mutations |
:class:
The mutations to be executed when this transaction commits. All mutations are applied atomically, in the order they appear in this list. This corresponds to the |
single_use_transaction |
TransactionOptions
Execute mutations in a temporary transaction. Note that unlike commit of a previously-started transaction, commit with a temporary transaction is non-idempotent. That is, if the |
retry |
google.api_core.retry.Retry
Designation of what errors, if any, should be retried. |
timeout |
float
The timeout for this request. |
metadata |
Sequence[Tuple[str, str]]
Strings which should be sent along with the request as metadata. |
Returns | |
---|---|
Type | Description |
google.cloud.spanner_v1.types.CommitResponse | The response for Commit][google.spanner.v1.Spanner.Commit] . |
common_billing_account_path
common_billing_account_path(billing_account: str)
Returns a fully-qualified billing_account string.
common_folder_path
common_folder_path(folder: str)
Returns a fully-qualified folder string.
common_location_path
common_location_path(project: str, location: str)
Returns a fully-qualified location string.
common_organization_path
common_organization_path(organization: str)
Returns a fully-qualified organization string.
common_project_path
common_project_path(project: str)
Returns a fully-qualified project string.
create_session
create_session(request: Optional[Union[google.cloud.spanner_v1.types.spanner.CreateSessionRequest, dict]] = None, *, database: Optional[str] = None, retry: Union[google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())
Creates a new session. A session can be used to perform transactions that read and/or modify data in a Cloud Spanner database. Sessions are meant to be reused for many consecutive transactions.
Sessions can only execute one transaction at a time. To execute multiple concurrent read-write/write-only transactions, create multiple sessions. Note that standalone reads and queries use a transaction internally, and count toward the one transaction limit.
Active sessions use additional server resources, so it is a good
idea to delete idle and unneeded sessions. Aside from explicit
deletes, Cloud Spanner may delete sessions for which no
operations are sent for more than an hour. If a session is
deleted, requests to it return NOT_FOUND
.
Idle sessions can be kept alive by sending a trivial SQL query
periodically, e.g., "SELECT 1"
.
from google.cloud import spanner_v1
async def sample_create_session():
# Create a client
client = spanner_v1.SpannerAsyncClient()
# Initialize request argument(s)
request = spanner_v1.CreateSessionRequest(
database="database_value",
)
# Make the request
response = await client.create_session(request=request)
# Handle the response
print(response)
Parameters | |
---|---|
Name | Description |
request |
Union[google.cloud.spanner_v1.types.CreateSessionRequest, dict]
The request object. The request for |
database |
Required. The database in which the new session is created. This corresponds to the |
retry |
google.api_core.retry.Retry
Designation of what errors, if any, should be retried. |
timeout |
float
The timeout for this request. |
metadata |
Sequence[Tuple[str, str]]
Strings which should be sent along with the request as metadata. |
Returns | |
---|---|
Type | Description |
google.cloud.spanner_v1.types.Session | A session in the Cloud Spanner API. |
database_path
database_path(project: str, instance: str, database: str)
Returns a fully-qualified database string.
delete_session
delete_session(request: Optional[Union[google.cloud.spanner_v1.types.spanner.DeleteSessionRequest, dict]] = None, *, name: Optional[str] = None, retry: Union[google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())
Ends a session, releasing server resources associated with it. This will asynchronously trigger cancellation of any operations that are running with this session.
from google.cloud import spanner_v1
async def sample_delete_session():
# Create a client
client = spanner_v1.SpannerAsyncClient()
# Initialize request argument(s)
request = spanner_v1.DeleteSessionRequest(
name="name_value",
)
# Make the request
await client.delete_session(request=request)
Parameters | |
---|---|
Name | Description |
request |
Union[google.cloud.spanner_v1.types.DeleteSessionRequest, dict]
The request object. The request for |
name |
Required. The name of the session to delete. This corresponds to the |
retry |
google.api_core.retry.Retry
Designation of what errors, if any, should be retried. |
timeout |
float
The timeout for this request. |
metadata |
Sequence[Tuple[str, str]]
Strings which should be sent along with the request as metadata. |
execute_batch_dml
execute_batch_dml(request: Optional[Union[google.cloud.spanner_v1.types.spanner.ExecuteBatchDmlRequest, dict]] = None, *, retry: Union[google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())
Executes a batch of SQL DML statements. This method allows many
statements to be run with lower latency than submitting them
sequentially with
ExecuteSql][google.spanner.v1.Spanner.ExecuteSql]
.
Statements are executed in sequential order. A request can
succeed even if a statement fails. The
ExecuteBatchDmlResponse.status][google.spanner.v1.ExecuteBatchDmlResponse.status]
field in the response provides information about the statement
that failed. Clients must inspect this field to determine
whether an error occurred.
Execution stops after the first failed statement; the remaining statements are not executed.
from google.cloud import spanner_v1
async def sample_execute_batch_dml():
# Create a client
client = spanner_v1.SpannerAsyncClient()
# Initialize request argument(s)
statements = spanner_v1.Statement()
statements.sql = "sql_value"
request = spanner_v1.ExecuteBatchDmlRequest(
session="session_value",
statements=statements,
seqno=550,
)
# Make the request
response = await client.execute_batch_dml(request=request)
# Handle the response
print(response)
Parameters | |
---|---|
Name | Description |
request |
Union[google.cloud.spanner_v1.types.ExecuteBatchDmlRequest, dict]
The request object. The request for |
retry |
google.api_core.retry.Retry
Designation of what errors, if any, should be retried. |
timeout |
float
The timeout for this request. |
metadata |
Sequence[Tuple[str, str]]
Strings which should be sent along with the request as metadata. |
Returns | |
---|---|
Type | Description |
google.cloud.spanner_v1.types.ExecuteBatchDmlResponse | The response for ExecuteBatchDml][google.spanner.v1.Spanner.ExecuteBatchDml] . Contains a list of ResultSet][google.spanner.v1.ResultSet] messages, one for each DML statement that has successfully executed, in the same order as the statements in the request. If a statement fails, the status in the response body identifies the cause of the failure. To check for DML statements that failed, use the following approach: 1. Check the status in the response message. The google.rpc.Code][google.rpc.Code] enum value OK indicates that all statements were executed successfully. 2. If the status was not OK, check the number of result sets in the response. If the response contains N ResultSet][google.spanner.v1.ResultSet] messages, then statement N+1 in the request failed. Example 1: - Request: 5 DML statements, all executed successfully. - Response: 5 ResultSet][google.spanner.v1.ResultSet] messages, with the status OK. Example 2: - Request: 5 DML statements. The third statement has a syntax error. - Response: 2 ResultSet][google.spanner.v1.ResultSet] messages, and a syntax error (INVALID_ARGUMENT) status. The number of ResultSet][google.spanner.v1.ResultSet] messages indicates that the third statement failed, and the fourth and fifth statements were not executed. |
execute_sql
execute_sql(request: Optional[Union[google.cloud.spanner_v1.types.spanner.ExecuteSqlRequest, dict]] = None, *, retry: Union[google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())
Executes an SQL statement, returning all results in a single
reply. This method cannot be used to return a result set larger
than 10 MiB; if the query yields more data than that, the query
fails with a FAILED_PRECONDITION
error.
Operations inside read-write transactions might return
ABORTED
. If this occurs, the application should restart the
transaction from the beginning. See
Transaction][google.spanner.v1.Transaction]
for more details.
Larger result sets can be fetched in streaming fashion by
calling
ExecuteStreamingSql][google.spanner.v1.Spanner.ExecuteStreamingSql]
instead.
from google.cloud import spanner_v1
async def sample_execute_sql():
# Create a client
client = spanner_v1.SpannerAsyncClient()
# Initialize request argument(s)
request = spanner_v1.ExecuteSqlRequest(
session="session_value",
sql="sql_value",
)
# Make the request
response = await client.execute_sql(request=request)
# Handle the response
print(response)
Parameters | |
---|---|
Name | Description |
request |
Union[google.cloud.spanner_v1.types.ExecuteSqlRequest, dict]
The request object. The request for |
retry |
google.api_core.retry.Retry
Designation of what errors, if any, should be retried. |
timeout |
float
The timeout for this request. |
metadata |
Sequence[Tuple[str, str]]
Strings which should be sent along with the request as metadata. |
Returns | |
---|---|
Type | Description |
google.cloud.spanner_v1.types.ResultSet | Results from Read][google.spanner.v1.Spanner.Read] or ExecuteSql][google.spanner.v1.Spanner.ExecuteSql] . |
execute_streaming_sql
execute_streaming_sql(request: Optional[Union[google.cloud.spanner_v1.types.spanner.ExecuteSqlRequest, dict]] = None, *, retry: Union[google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())
Like ExecuteSql][google.spanner.v1.Spanner.ExecuteSql]
, except
returns the result set as a stream. Unlike
ExecuteSql][google.spanner.v1.Spanner.ExecuteSql]
, there is no
limit on the size of the returned result set. However, no
individual row in the result set can exceed 100 MiB, and no
column value can exceed 10 MiB.
from google.cloud import spanner_v1
async def sample_execute_streaming_sql():
# Create a client
client = spanner_v1.SpannerAsyncClient()
# Initialize request argument(s)
request = spanner_v1.ExecuteSqlRequest(
session="session_value",
sql="sql_value",
)
# Make the request
stream = await client.execute_streaming_sql(request=request)
# Handle the response
async for response in stream:
print(response)
Parameters | |
---|---|
Name | Description |
request |
Union[google.cloud.spanner_v1.types.ExecuteSqlRequest, dict]
The request object. The request for |
retry |
google.api_core.retry.Retry
Designation of what errors, if any, should be retried. |
timeout |
float
The timeout for this request. |
metadata |
Sequence[Tuple[str, str]]
Strings which should be sent along with the request as metadata. |
Returns | |
---|---|
Type | Description |
AsyncIterable[google.cloud.spanner_v1.types.PartialResultSet] | Partial results from a streaming read or SQL query. Streaming reads and SQL queries better tolerate large result sets, large rows, and large values, but are a little trickier to consume. |
from_service_account_file
from_service_account_file(filename: str, *args, **kwargs)
Creates an instance of this client using the provided credentials file.
Parameter | |
---|---|
Name | Description |
filename |
str
The path to the service account private key json file. |
Returns | |
---|---|
Type | Description |
SpannerAsyncClient | The constructed client. |
from_service_account_info
from_service_account_info(info: dict, *args, **kwargs)
Creates an instance of this client using the provided credentials info.
Parameter | |
---|---|
Name | Description |
info |
dict
The service account private key info. |
Returns | |
---|---|
Type | Description |
SpannerAsyncClient | The constructed client. |
from_service_account_json
from_service_account_json(filename: str, *args, **kwargs)
Creates an instance of this client using the provided credentials file.
Parameter | |
---|---|
Name | Description |
filename |
str
The path to the service account private key json file. |
Returns | |
---|---|
Type | Description |
SpannerAsyncClient | The constructed client. |
get_mtls_endpoint_and_cert_source
get_mtls_endpoint_and_cert_source(
client_options: Optional[google.api_core.client_options.ClientOptions] = None,
)
Return the API endpoint and client cert source for mutual TLS.
The client cert source is determined in the following order:
(1) if GOOGLE_API_USE_CLIENT_CERTIFICATE
environment variable is not "true", the
client cert source is None.
(2) if client_options.client_cert_source
is provided, use the provided one; if the
default client cert source exists, use the default one; otherwise the client cert
source is None.
The API endpoint is determined in the following order:
(1) if client_options.api_endpoint
if provided, use the provided one.
(2) if GOOGLE_API_USE_CLIENT_CERTIFICATE
environment variable is "always", use the
default mTLS endpoint; if the environment variabel is "never", use the default API
endpoint; otherwise if client cert source exists, use the default mTLS endpoint, otherwise
use the default API endpoint.
More details can be found at https://google.aip.dev/auth/4114.
Parameter | |
---|---|
Name | Description |
client_options |
google.api_core.client_options.ClientOptions
Custom options for the client. Only the |
Exceptions | |
---|---|
Type | Description |
google.auth.exceptions.MutualTLSChannelError | If any errors happen. |
Returns | |
---|---|
Type | Description |
Tuple[str, Callable[[], Tuple[bytes, bytes]]] | returns the API endpoint and the client cert source to use. |
get_session
get_session(request: Optional[Union[google.cloud.spanner_v1.types.spanner.GetSessionRequest, dict]] = None, *, name: Optional[str] = None, retry: Union[google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())
Gets a session. Returns NOT_FOUND
if the session does not
exist. This is mainly useful for determining whether a session
is still alive.
from google.cloud import spanner_v1
async def sample_get_session():
# Create a client
client = spanner_v1.SpannerAsyncClient()
# Initialize request argument(s)
request = spanner_v1.GetSessionRequest(
name="name_value",
)
# Make the request
response = await client.get_session(request=request)
# Handle the response
print(response)
Parameters | |
---|---|
Name | Description |
request |
Union[google.cloud.spanner_v1.types.GetSessionRequest, dict]
The request object. The request for |
name |
Required. The name of the session to retrieve. This corresponds to the |
retry |
google.api_core.retry.Retry
Designation of what errors, if any, should be retried. |
timeout |
float
The timeout for this request. |
metadata |
Sequence[Tuple[str, str]]
Strings which should be sent along with the request as metadata. |
Returns | |
---|---|
Type | Description |
google.cloud.spanner_v1.types.Session | A session in the Cloud Spanner API. |
get_transport_class
get_transport_class()
Returns an appropriate transport class.
list_sessions
list_sessions(request: Optional[Union[google.cloud.spanner_v1.types.spanner.ListSessionsRequest, dict]] = None, *, database: Optional[str] = None, retry: Union[google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())
Lists all sessions in a given database.
from google.cloud import spanner_v1
async def sample_list_sessions():
# Create a client
client = spanner_v1.SpannerAsyncClient()
# Initialize request argument(s)
request = spanner_v1.ListSessionsRequest(
database="database_value",
)
# Make the request
page_result = client.list_sessions(request=request)
# Handle the response
async for response in page_result:
print(response)
Parameters | |
---|---|
Name | Description |
request |
Union[google.cloud.spanner_v1.types.ListSessionsRequest, dict]
The request object. The request for |
database |
Required. The database in which to list sessions. This corresponds to the |
retry |
google.api_core.retry.Retry
Designation of what errors, if any, should be retried. |
timeout |
float
The timeout for this request. |
metadata |
Sequence[Tuple[str, str]]
Strings which should be sent along with the request as metadata. |
Returns | |
---|---|
Type | Description |
google.cloud.spanner_v1.services.spanner.pagers.ListSessionsAsyncPager | The response for ListSessions][google.spanner.v1.Spanner.ListSessions] . Iterating over this object will yield results and resolve additional pages automatically. |
parse_common_billing_account_path
parse_common_billing_account_path(path: str)
Parse a billing_account path into its component segments.
parse_common_folder_path
parse_common_folder_path(path: str)
Parse a folder path into its component segments.
parse_common_location_path
parse_common_location_path(path: str)
Parse a location path into its component segments.
parse_common_organization_path
parse_common_organization_path(path: str)
Parse a organization path into its component segments.
parse_common_project_path
parse_common_project_path(path: str)
Parse a project path into its component segments.
parse_database_path
parse_database_path(path: str)
Parses a database path into its component segments.
parse_session_path
parse_session_path(path: str)
Parses a session path into its component segments.
partition_query
partition_query(request: Optional[Union[google.cloud.spanner_v1.types.spanner.PartitionQueryRequest, dict]] = None, *, retry: Union[google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())
Creates a set of partition tokens that can be used to execute a
query operation in parallel. Each of the returned partition
tokens can be used by
ExecuteStreamingSql][google.spanner.v1.Spanner.ExecuteStreamingSql]
to specify a subset of the query result to read. The same
session and read-only transaction must be used by the
PartitionQueryRequest used to create the partition tokens and
the ExecuteSqlRequests that use the partition tokens.
Partition tokens become invalid when the session used to create them is deleted, is idle for too long, begins a new transaction, or becomes too old. When any of these happen, it is not possible to resume the query, and the whole operation must be restarted from the beginning.
from google.cloud import spanner_v1
async def sample_partition_query():
# Create a client
client = spanner_v1.SpannerAsyncClient()
# Initialize request argument(s)
request = spanner_v1.PartitionQueryRequest(
session="session_value",
sql="sql_value",
)
# Make the request
response = await client.partition_query(request=request)
# Handle the response
print(response)
Parameters | |
---|---|
Name | Description |
request |
Union[google.cloud.spanner_v1.types.PartitionQueryRequest, dict]
The request object. The request for |
retry |
google.api_core.retry.Retry
Designation of what errors, if any, should be retried. |
timeout |
float
The timeout for this request. |
metadata |
Sequence[Tuple[str, str]]
Strings which should be sent along with the request as metadata. |
Returns | |
---|---|
Type | Description |
google.cloud.spanner_v1.types.PartitionResponse | The response for PartitionQuery][google.spanner.v1.Spanner.PartitionQuery] or PartitionRead][google.spanner.v1.Spanner.PartitionRead] |
partition_read
partition_read(request: Optional[Union[google.cloud.spanner_v1.types.spanner.PartitionReadRequest, dict]] = None, *, retry: Union[google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())
Creates a set of partition tokens that can be used to execute a
read operation in parallel. Each of the returned partition
tokens can be used by
StreamingRead][google.spanner.v1.Spanner.StreamingRead]
to
specify a subset of the read result to read. The same session
and read-only transaction must be used by the
PartitionReadRequest used to create the partition tokens and the
ReadRequests that use the partition tokens. There are no
ordering guarantees on rows returned among the returned
partition tokens, or even within each individual StreamingRead
call issued with a partition_token.
Partition tokens become invalid when the session used to create them is deleted, is idle for too long, begins a new transaction, or becomes too old. When any of these happen, it is not possible to resume the read, and the whole operation must be restarted from the beginning.
from google.cloud import spanner_v1
async def sample_partition_read():
# Create a client
client = spanner_v1.SpannerAsyncClient()
# Initialize request argument(s)
request = spanner_v1.PartitionReadRequest(
session="session_value",
table="table_value",
)
# Make the request
response = await client.partition_read(request=request)
# Handle the response
print(response)
Parameters | |
---|---|
Name | Description |
request |
Union[google.cloud.spanner_v1.types.PartitionReadRequest, dict]
The request object. The request for |
retry |
google.api_core.retry.Retry
Designation of what errors, if any, should be retried. |
timeout |
float
The timeout for this request. |
metadata |
Sequence[Tuple[str, str]]
Strings which should be sent along with the request as metadata. |
Returns | |
---|---|
Type | Description |
google.cloud.spanner_v1.types.PartitionResponse | The response for PartitionQuery][google.spanner.v1.Spanner.PartitionQuery] or PartitionRead][google.spanner.v1.Spanner.PartitionRead] |
read
read(request: Optional[Union[google.cloud.spanner_v1.types.spanner.ReadRequest, dict]] = None, *, retry: Union[google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())
Reads rows from the database using key lookups and scans, as a
simple key/value style alternative to
ExecuteSql][google.spanner.v1.Spanner.ExecuteSql]
. This method
cannot be used to return a result set larger than 10 MiB; if the
read matches more data than that, the read fails with a
FAILED_PRECONDITION
error.
Reads inside read-write transactions might return ABORTED
.
If this occurs, the application should restart the transaction
from the beginning. See
Transaction][google.spanner.v1.Transaction]
for more details.
Larger result sets can be yielded in streaming fashion by
calling StreamingRead][google.spanner.v1.Spanner.StreamingRead]
instead.
from google.cloud import spanner_v1
async def sample_read():
# Create a client
client = spanner_v1.SpannerAsyncClient()
# Initialize request argument(s)
request = spanner_v1.ReadRequest(
session="session_value",
table="table_value",
columns=['columns_value_1', 'columns_value_2'],
)
# Make the request
response = await client.read(request=request)
# Handle the response
print(response)
Parameters | |
---|---|
Name | Description |
request |
Union[google.cloud.spanner_v1.types.ReadRequest, dict]
The request object. The request for |
retry |
google.api_core.retry.Retry
Designation of what errors, if any, should be retried. |
timeout |
float
The timeout for this request. |
metadata |
Sequence[Tuple[str, str]]
Strings which should be sent along with the request as metadata. |
Returns | |
---|---|
Type | Description |
google.cloud.spanner_v1.types.ResultSet | Results from Read][google.spanner.v1.Spanner.Read] or ExecuteSql][google.spanner.v1.Spanner.ExecuteSql] . |
rollback
rollback(request: Optional[Union[google.cloud.spanner_v1.types.spanner.RollbackRequest, dict]] = None, *, session: Optional[str] = None, transaction_id: Optional[bytes] = None, retry: Union[google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())
Rolls back a transaction, releasing any locks it holds. It is a
good idea to call this for any transaction that includes one or
more Read][google.spanner.v1.Spanner.Read]
or
ExecuteSql][google.spanner.v1.Spanner.ExecuteSql]
requests and
ultimately decides not to commit.
Rollback
returns OK
if it successfully aborts the
transaction, the transaction was already aborted, or the
transaction is not found. Rollback
never returns
ABORTED
.
from google.cloud import spanner_v1
async def sample_rollback():
# Create a client
client = spanner_v1.SpannerAsyncClient()
# Initialize request argument(s)
request = spanner_v1.RollbackRequest(
session="session_value",
transaction_id=b'transaction_id_blob',
)
# Make the request
await client.rollback(request=request)
Parameters | |
---|---|
Name | Description |
request |
Union[google.cloud.spanner_v1.types.RollbackRequest, dict]
The request object. The request for |
session |
Required. The session in which the transaction to roll back is running. This corresponds to the |
transaction_id |
Required. The transaction to roll back. This corresponds to the |
retry |
google.api_core.retry.Retry
Designation of what errors, if any, should be retried. |
timeout |
float
The timeout for this request. |
metadata |
Sequence[Tuple[str, str]]
Strings which should be sent along with the request as metadata. |
session_path
session_path(project: str, instance: str, database: str, session: str)
Returns a fully-qualified session string.
streaming_read
streaming_read(request: Optional[Union[google.cloud.spanner_v1.types.spanner.ReadRequest, dict]] = None, *, retry: Union[google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())
Like Read][google.spanner.v1.Spanner.Read]
, except returns the
result set as a stream. Unlike
Read][google.spanner.v1.Spanner.Read]
, there is no limit on the
size of the returned result set. However, no individual row in
the result set can exceed 100 MiB, and no column value can
exceed 10 MiB.
from google.cloud import spanner_v1
async def sample_streaming_read():
# Create a client
client = spanner_v1.SpannerAsyncClient()
# Initialize request argument(s)
request = spanner_v1.ReadRequest(
session="session_value",
table="table_value",
columns=['columns_value_1', 'columns_value_2'],
)
# Make the request
stream = await client.streaming_read(request=request)
# Handle the response
async for response in stream:
print(response)
Parameters | |
---|---|
Name | Description |
request |
Union[google.cloud.spanner_v1.types.ReadRequest, dict]
The request object. The request for |
retry |
google.api_core.retry.Retry
Designation of what errors, if any, should be retried. |
timeout |
float
The timeout for this request. |
metadata |
Sequence[Tuple[str, str]]
Strings which should be sent along with the request as metadata. |
Returns | |
---|---|
Type | Description |
AsyncIterable[google.cloud.spanner_v1.types.PartialResultSet] | Partial results from a streaming read or SQL query. Streaming reads and SQL queries better tolerate large result sets, large rows, and large values, but are a little trickier to consume. |