Multi-threaded Remote Calls vs. Python imterpreter Lock

Hi, 

 

I've got an interesting problem and I'm wondering if there is a solution
for it

 

First I create a connection and get two cursors:

 

con = psycopg2.connect("dbname=test user=test password=test)

cursor = con.cursor(cursor_factory = psycopg2.extras.DictCursor)

cursor2 = con.cursor(cursor_factory = psycopg2.extras.DictCursor)

 

Then I start three threads, two of which execute a (very slow) SQL
statement using the separate cursors. I also start a third thread that
is doing additions and printouts in a tight loop (no sleeping).

 

t1 = CursorThread(cursor) 

t2 = CursorThread(cursor2)

t3 = RuniingCrazyThread()

 

t1.start()

t2.start()

t3.start()

.

.

.

t1.join()

t2.join()

t3.join()

 

 

 

When I run this against the local Postgresql engine I see that the third
thread is not blocked. It is running happily while the cursor threads
are waiting for Postgres to return the data.

 

Now if I change the connect statement to target a remote host

 

con = psycopg2.connect("dbname=test user=test password=test
hosr=10.10.0.2)

 

but everything else remains the same, the third thread is blocked until
the cursor threads (or perhaps at least one of them) are done. 

Everything works fine if I change the setup by starting only one cursor
thread. Unfortunately I need two threads both using the same
transaction. 

Everything works also, if I create two connections and use one cursor
within each. Again, I need to process data in the same transaction from
multiple threads.

 

So my questions are:

1)       Why does psycopg work differently when targeting a local and a
remote Postgres?

2)       More importantly, what can I do to force psycopg to release the
global python lock when targeting the remote host in this situation?

 

Thank you for your help!

Jozsef Szalay

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