Le 11/05/15 22:17, Howard Chu a écrit :
Emmanuel Lécharny wrote:
Restarting this thread...
we have had some interesting discussion today that I wanted to share.
Hypothesis : 1 server has been down for a long time, and the contextCSN is older than the one of the other servers, forcing a refresh mode with more than the content of the AccessLog.
Quanah said that in some heavily servers, the only way for the consumer to catch up is to slapcat/slapadd/restart the consumer. I wonder if it would not be a way to deal with server that are to far behind the running server, but as a mechanism that is included in the refresh phase (ie, the restarted server will detect that it has to grab the set of entries and load them, os if a human being was doing a slapcat/slapadd/restart).
More specifically, is there a way to know how many entries we will have to update, and is there a way to know when it will be faster to be brutal (the Quanah way) compared to let the refresh mechanism doing its job.
Not a worthwhile direction to pursue. Doing the equivalent of a full slapcat/slapadd across the network will use even more bandwidth than the current syncrepl. None of this addresses the underlying causes of why the consumer is slow, so the original problem will remain.
IMHO, network congestion is not a real pb. Assuming you are running a 1Gb ethernet network, the time it takes to transmit 1 milion 1Kb entries is only 10 seconds. It will be barely noticable compared to the time it will take to load those 1 M entries into your consumer. Even with a 100Gb ethernet newtork, this is not a big part of the problem.
There are two main problems:
- the AVL tree used for presentlist is still extremely inefficient
in both CPU and memory use. 2) the consumer does twice as much work for a single modification as the provider. I.e., the consumer does a write op to the backend for the modification, and then a second write op to update its contextCSN.
Updating the contextCSN is an extra operation on the consumer, but as you have to update potentially tens of indexes when updating an entry (on both teh consumer and the producer), it's not really twoce more work. It's an additianal operation, but that would not double the time it costs on the producer.
The question would be : how do we update the contextCSN only periodically, to mitigate this extra cost, and it seems you proposed to batch the updates for this reason. By using btaches of 500 updates, this extra cost will be almost unnoticable, and one would expect the work on the consumer to be the same as on the producer side, right ?
The provider only does the original modification, and caches the contextCSN update.
If we fix both of these issues, consumer speed should be much faster. Nothing else is worth investigating until these two areas are reworked.
Agreed in most of the case. Although for use cases of an important number of updates have occured while a consumer is off line, another strategy might work. That this other strategy is to stop the consumer, slapcat the producer, slapadd the result and restart the server, all with the command line, instead of having it implemented in the server code, was what I was suggesting, but this is another story for a corner case that is not frequent. Plus we don't know at which point this would be the correct strategy (ie, for how many updates should we consider it as a better startegy than the current implementation ?).
For (1) I've been considering a stripped down memory-only version of LMDB. There are plenty of existing memory-only Btree implementations out there already though, if anyone has a favorite it would probably save us some time to use an existing library. The Linux kernel has one (lib/btree.c) but it's under GPL so we can't use it directly.
Q : do you need to keep the presentList ina BTree at all ?
Another point : as soon as the server is restarted, it can receive incoming requests, which will send back outdated response, until the refresh is completed (and i'm not talking about updates that could also be applied on an outdated base, with the consequences if there are some missing parents). In many cases, that would be a real problem, typically if the LDAP servers are considered as part of a shared pool of server, with a load balance mecahnism to spread the load. Wouldn't be more realistic to simply consider the server as not available until the refresh phase is completed ?
This was ITS#7616. We tried it and it caused a lot of problems. It has been reverted.
The two options were to either send a referral (not ideal, as we have no control whatesoever on the client API) and LDAP_BUSY. A third option would be possible : chaining the request to the server from which the replication updates are coming from. Doing so will guarantee that the client will gets a updated version of the data, as the producer is up to date. There is still an issue though if both servers are replicating each other (pretty much the pb with referrals). OTOH, if the other server is also in refresh mode, it should be possible to return a LDAP_BUSY if it is capable of detecting that the requests come from another server, not for a client. Maybe it's far fetched...