The Rick Astley of Timeouts: maxTimeMS

tl;dr: Use maxTimeMS instead of client-side socket timeouts.

Some time ago, a MongoDB user opened PHP-1164 to report that connections had started to pile up on their server due to some long-running queries. The user was particularly concerned because the connection count had greatly exceeded the number of PHP workers on their app server(s).

Unlike most of our multi-threaded drivers, the single-threaded PHP driver uses persistent connections instead of pooling. You should generally expect each worker to keep a single connection per MongoDB endpoint (i.e. host, port, and auth combination) and reuse that socket between requests. For instance, an application that always connects to a three-node replica set would maintain three sockets per worker (one to each node). When the number of connections in mongostat starts to exceed your worker pool, that warrants some investigation.

Thankfully, the user was able to attach a small script that reproduced his problem:

MongoCursor::$timeout = 100;

$mc = new MongoClient();
$coll = $mc->test->php1164;

$cursor = $coll->find([
  ''=> new MongoRegex('/^Edmunds/i'),


This is pretty straightforward: we connect, execute a (hopefully) indexed query using an anchored regex pattern, and finally iterate through the cursor and dump our results. Apart from using the deprecated MongoCursor::$timeout property instead of MongoCursor::timeout() or the socketTimeoutMS connection option, it was fairly innocuous.

When benchmarking the script with 10 concurrent requests via ab, they found active connections on the server climb to 1000+. netstat reported that the majority of sockets local to the server were lingering in the CLOSE_WAIT state. From the driver’s perspective, any sockets listed were reported as FIN_WAIT or TIME_WAIT. This meant that the driver had closed its side of the connection but we were still waiting for the server to acknowledge that.

The following state diagram1 helps put this into perspective:

"TCP state diagram"

Without access to the user’s data files, I had to resort to other means of reproducing the problem locally. I immediately thought of the $where operator, which allows us to execute arbitrary JavaScript during query evaluation2. Querying a non-empty collection with {"$where": "sleep(1000)"} allows us to delay the match evaluation for each document by one second. Combined with a 100 millisecond client-side timeout, we could simulate the original issue and force the driver to abandon connections and queries that were still executing on the server. The following script does just that:

$mc = new MongoClient(null, ['socketTimeoutMS' => 100]);
$coll = $mc->test->php1164;

$cursor = $coll->find([
  '$where' => 'sleep(1000) || true',


Before benchmarking, I tweaked my FPM pool configuration to allow the number of web workers to scale up to 1000. I usually have a static pool of two workers on my development machine, but we were going to need quite a bit more than that for this test:

pm = dynamic
pm.max_children = 1000
pm.min_spare_servers = 5
pm.max_spare_servers = 50
pm.start_servers = 5

With FPM restarted and the PHP script deployed to a virtual host, I kicked off a hundred thousand requests (500 at a time):

ab -r -n 100000 -c 500 http://php1164.local/

When running this test against MongoDB 2.6, I had mixed luck watching the server load with mongostat. Execution of the serverStatus command it uses was delayed by our blast of $where queries, which left gaps in the poll intervals. For the record, MongoDB 3.0 did a much better job of reporting its stats under heavy load. Here’s a snippet of the output during our test on 2.6:

query command     qr|qw   ar|aw  netIn netOut  conn       time
   *0     1|0       0|0     0|0    62b     3k     1   16:08:47
   56   169|0       0|0    56|0    10k    57k    57   16:08:48
   43   121|0      10|1    91|0     7k    42k    93   16:08:52
  926  2380|0       1|1   798|0   151k   772k   799   16:09:07
 1788   658|0       0|1   216|0    99k   269k   221   16:09:11
  418     1|0       0|0     0|0    16k    18k     1   16:09:12

The gaps between poll intervals made it impossible to see the true query and connection load on the server; however, tailing the server logs provided a more accurate look at our connection load. Open connections on the server reached a peak of 969 before the first queries finished executing and connections began to close. Bumping the sleep() delay in our $where criteria up to 10 seconds resulted in a peak of 2305 connections before the load began to subside.

While using $where for this test was a bit contrived, it did succinctly demonstrate the problem with client-side socket timeouts. Having the driver abruptly close sockets for long-running operations can inadvertently cause of DoS attack against your database server given a high enough request load.

  • Sockets, file descriptors, and threads are limited resources. In this test, we were letting connections (i.e. threads with sockets) accumulate on the server as it needlessly prepares a response the driver will never read!
  • Creating connections has overhead. Closing a socket on a long-running query prevents the driver from persisting that connection for the worker to re-use in a subsequent request.

Client-side timeouts certainly have their uses in allowing an application to remain responsive despite network latency or connectivity issues, but they are not a general tool for curtailing long-running operations. Thankfully, MongoDB 2.6 introduced the maxTimeMS query and command option expressly for that purpose.

Let’s see how replacing socketTimeoutMS with a call to MongoCursor::maxTimeMS() can eliminate the DoS side-effect of our original script.

$mc = new MongoClient;
$coll = $mc->test->php1164;

$cursor = $coll->find([
  '$where' => 'sleep(1000) || true',



This script relies on the driver’s default socket timeouts but trusts the server to gracefully abort the query on its own after 100 milliseconds of execution time (think CPU time vs. wall time). In contrast to our previous test, the driver will actually read a response from the server (albeit an error message) and keep the connection open for the next request. From the developer’s perspective, the only difference should be that a MongoExecutionTimeoutException will be thrown instead of a MongoCursorTimeoutException.

Running the revised script yields the following, abridged output from mongostat:

query command     qr|qw   ar|aw  netIn netOut  conn       time
   *0     1|0       0|0     0|0    79b    10k    51   17:23:06
   97   104|0       0|0    51|0     6k    24k    52   17:23:07
  107     7|0       0|0    53|0     6k    17k    54   17:23:08
   76    13|0       0|0    57|0     6k    19k    58   17:23:09
   74    17|0       0|0    62|0     7k    21k    63   17:23:10
  315    64|0       0|0   270|0    32k    44k   288   17:23:55
  328    82|0       0|0   277|0    34k    45k   293   17:23:56
  316   116|0       0|0   281|0    37k    48k   298   17:23:57
  345    87|0       0|0   286|0    37k    48k   303   17:23:58
  404    91|0       0|0   307|0    38k    50k   308   17:23:59
   13    16|0       0|0   275|0     1k    16k   498   17:24:38
  879   308|0       0|0   298|0    75k    94k   503   17:24:39
   15    12|0       0|0   294|0     2k    15k   506   17:24:40
  433    91|0       0|0   398|0    18k    28k   506   17:24:41
  457   294|0       0|0   297|0    64k    74k   506   17:24:42

We can see connections slowly ramp up to about 500, which is consistent with our concurrency level. The initial connection count of 51 is also consistent with pm.max_spare_servers from our FPM configuration, as the log was captured on a subsequenty run after FPM had scaled down to an idle state.

In addition to the cursor method we used above, which sets the $maxTimeMS meta operator on the query, most commands support a maxTimeMS option (support for write commands is forthcoming in SERVER-13622). If you’re using MongoDB::command(), the maxTimeMS option goes directly on the command document itself, instead of in the array you might have previously used to specify socketTimeoutMS. Other command helper methods are documented accordingly.

While this won’t match the blazing performance of our DoS attack, it uses server and driver resources much more responsibly. This is doubly important given the PHP driver’s lack of connection pooling. Our persistent connection model means that the expected connection load for a single mongod comes down to:

web servers × worker pool size × mongod connections

Workers (i.e. driver instances) will typically require a single mongod connection. Multiple connections could be required if different sets of auth credentials are involved, but the number should still be predictable. But the equation breaks down when workers can consume more than their fair share of server resources, which is made all too easy with hasty socket timeouts. At scale, that can lead to a domino effect of abandoned connections. That said, maxTimeMS is the Rick Astley of timeouts—at least as far as sockets are concerned.

Never gonna give you up ♫
Never gonna let you down ♬
Never gonna SO_RCVTIMEO and desert you ♫

  1. TCP State Transition Diagram 

  2. $where should be used sparingly. It is best used in conjunction with other, selective query criteria, which can take advantage of an index and limit the number of JavaScript executions required. Including it in a collection scan (as we do here) is generally a bad idea unless you know what you’re doing.