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()