[SOLVED] First call to openrdf-sesame update endpoint it very slow. Is there a way to optimize it?

First call to openrdf-sesame update endpoint it very slow. Is there a way to optimize it?

We have some python scripts to execute both sparql queries and "updates" (an insert/delete). Here is most of the relevant code (I think):

server = "localhost"
repo = "test"
query_endpoint  = "http://%s:8080/openrdf-sesame/repositories/%s" % (server,repo)
update_endpoint = "http://%s:8080/openrdf-sesame/repositories/%s/statements" % (server,repo)


def execute_query(query):
  params = { 'query': query }
  headers = {
    'content-type': 'application/x-www-form-urlencoded',
    'accept': 'application/sparql-results+json'
  }
  (response, content) = httplib2.Http().request(endpoint, 'POST', urllib.urlencode(params),headers=headers)
  return (response,ast.literal_eval(content))

def execute_update(query):
  params = { 'update': query }
  headers = {
    'content-type': 'application/x-www-form-urlencoded',
    'accept': 'application/sparql-results+json'
  }
  (response, content) = httplib2.Http().request(update_endpoint, 'POST', urllib.urlencode(params),headers=headers)
  return True

All of our calls to execute_query are very fast, less than 1 second to complete. However, any call to execute_update takes a really long time to (16 seconds) the first time. Every call after the first one runs in less than 1 second. We're running sesame version 2.7.12 (we thought upgrading from sesame version 2.7.3 might help, but it didn't much). We only have 2 or 3 thousand triples. This is all running from CGI scripts so we can't really just keep a python session alive to make update calls (anyway isn't that workbench's job?). Any ideas on what is taking so long on that first call to the update_endpoint? Are other people having the same issue? Any suggested resolutions?

Thanks!

EDIT I followed RobV's advice, but I'm still having the same problem. Log files from tshark:

 22.577578   10.10.2.43 -> 10.10.2.43   HTTP POST /openrdf-sesame/repositories/test HTTP/1.1 
 22.578261   10.10.2.43 -> 10.10.2.43   HTTP Continuation or non-HTTP traffic
 22.583422   10.10.2.43 -> 10.10.2.43   HTTP HTTP/1.1 200 OK  (application/sparql-results+json)
 22.583857   10.10.2.43 -> 10.10.2.43   HTTP Continuation or non-HTTP traffic
 22.591122   10.10.2.43 -> 10.10.2.43   HTTP POST /openrdf-sesame/repositories/test/statements HTTP/1.1 
 22.591388   10.10.2.43 -> 10.10.2.43   HTTP Continuation or non-HTTP traffic
 35.020398   10.10.2.43 -> 10.10.2.43   HTTP HTTP/1.1 204 No Content 
 35.025605   10.10.2.43 -> 10.10.2.43   HTTP POST /openrdf-sesame/repositories/test/statements HTTP/1.1 
 35.025911   10.10.2.43 -> 10.10.2.43   HTTP Continuation or non-HTTP traffic
 35.040606   10.10.2.43 -> 10.10.2.43   HTTP HTTP/1.1 204 No Content 
 35.045937   10.10.2.43 -> 10.10.2.43   HTTP POST /openrdf-sesame/repositories/test/statements HTTP/1.1 
 35.046080   10.10.2.43 -> 10.10.2.43   HTTP Continuation or non-HTTP traffic
 35.049359   10.10.2.43 -> 10.10.2.43   HTTP HTTP/1.1 204 No Content 
 35.053776   10.10.2.43 -> 10.10.2.43   HTTP POST /openrdf-sesame/repositories/test/statements HTTP/1.1 
 35.053875   10.10.2.43 -> 10.10.2.43   HTTP Continuation or non-HTTP traffic
 35.056937   10.10.2.43 -> 10.10.2.43   HTTP HTTP/1.1 204 No Content

You can see the large gap on the first call to the /statements endpoint.

Solution

When we created the repository we created it as a "In Memory Store" repository. I created a new repository of the "Native Java Store" type, and now my first call is fast (as all are subsequent calls).