- 3.51.0 (latest)
- 3.50.1
- 3.46.0
- 3.45.0
- 3.44.0
- 3.43.0
- 3.42.0
- 3.41.0
- 3.40.1
- 3.39.0
- 3.38.0
- 3.37.0
- 3.36.0
- 3.35.1
- 3.34.0
- 3.33.0
- 3.32.0
- 3.31.0
- 3.30.0
- 3.29.0
- 3.28.0
- 3.27.1
- 3.26.0
- 3.25.0
- 3.24.0
- 3.23.0
- 3.22.2
- 3.21.0
- 3.20.0
- 3.19.0
- 3.18.0
- 3.17.0
- 3.16.0
- 3.15.1
- 3.14.1
- 3.13.0
- 3.12.1
- 3.11.1
- 3.10.0
- 3.9.0
- 3.8.0
- 3.7.0
- 3.6.0
- 3.5.0
- 3.4.0
- 3.3.0
- 3.2.0
- 3.1.0
- 3.0.0
- 2.1.1
- 2.0.0
- 1.19.3
- 1.18.0
- 1.17.1
- 1.16.0
- 1.15.1
- 1.14.0
- 1.13.0
- 1.12.0
- 1.11.0
- 1.10.0
Advanced Session Pool Topics
Custom Session Pool Implementations
You can supply your own pool implementation, which must satisfy the
contract laid out in
AbstractSessionPool
:
from google.cloud.spanner import AbstractSessionPool
class MyCustomPool(AbstractSessionPool):
def __init__(self, custom_param):
super(MyCustomPool, self).__init__()
self.custom_param = custom_param
def bind(self, database):
...
def get(self, read_only=False):
...
def put(self, session, discard_if_full=True):
...
pool = MyCustomPool(custom_param=42)
database = instance.database(DATABASE_NAME, pool=pool)
Lowering latency for read / query operations
Some applications may need to minimize latency for read operations, including
particularly the overhead of making an API request to create or refresh a
session. PingingPool
is designed for such
applications, which need to configure a background thread to do the work of
keeping the sessions fresh.
Create an instance of PingingPool
:
from google.cloud.spanner import Client, PingingPool
client = Client()
instance = client.instance(INSTANCE_NAME)
pool = PingingPool(size=10, default_timeout=5, ping_interval=300)
database = instance.database(DATABASE_NAME, pool=pool)
Set up a background thread to ping the pool’s session, keeping them from becoming stale:
import threading
def background_loop():
while True:
# (Optional) Perform other background tasks here
pool.ping()
background = threading.Thread(target=background_loop, name='ping-pool')
background.daemon = True
background.start()
Lowering latency for mixed read-write operations
Some applications may need to minimize latency for read write operations,
including particularly the overhead of making an API request to create or
refresh a session or to begin a session’s transaction.
TransactionPingingPool
is designed for
such applications, which need to configure a background thread to do the work
of keeping the sessions fresh and starting their transactions after use.
Create an instance of
TransactionPingingPool
:
from google.cloud.spanner import Client, TransactionPingingPool
client = Client()
instance = client.instance(INSTANCE_NAME)
pool = TransactionPingingPool(size=10, default_timeout=5, ping_interval=300)
database = instance.database(DATABASE_NAME, pool=pool)
Set up a background thread to ping the pool’s session, keeping them from becoming stale, and ensuring that each session has a new transaction started before it is used:
import threading
def background_loop():
while True:
# (Optional) Perform other background tasks here
pool.ping()
pool.begin_pending_transactions()
background = threading.Thread(target=background_loop, name='ping-pool')
background.daemon = True
background.start()