Setup failover for a distributed cache

Hello,
For our production setup we will have 4 app servers one clone per each app server. so there will be 4 clones to a cluster. And we will have 2 jvms for our distributed cache - one being a failover, both of those will be in cluster.
How would i configure the failover for the distributed cache?
Thanks

user644269 wrote:
Right - so each of the near cache schemes defined would need to have the back map high-units set to where it could take on 100% of data.Specifically the near-scheme/back-scheme/distributed-scheme/backing-map-scheme/local-scheme/high-units value (take a look at the [Cache Configuration Elements|http://coherence.oracle.com/display/COH34UG/Cache+Configuration+Elements] ).
There are two options:
1) No Expiry -- In this case you would have to size the storage enabled JVMs to that an individual JVM could store all of the data.
or
2) Expiry -- In this case you would set the high-units a value that you determine. If you want it to store all the data then it needs to be set higher than the total number of objects that you will store in the cache at any given time or you can set it lower with the understanding that once that high-units is reached Coherence will evict some data from the cluster (i.e. remove it from the "cluster memory").
user644269 wrote:
Other than that - there is not configuration needed to ensure that these JVM's act as a failover in the event one goes down.Correct, data fault tolerance is on by default (set to one level of redundancy).
:Rob:
Coherence Team

Similar Messages

Set request timeout for distributed cache

Hi,
Coherence provides 3 parameters we can tune for the distributed cache
tangosol.coherence.distributed.request.timeout      The default client request timeout for distributed cache services
tangosol.coherence.distributed.task.timeout      The default server execution timeout for distributed cache services
tangosol.coherence.distributed.task.hung      the default time before a thread is reported as hung by distributed cache services
It seems these timeout values are used for both system activities (node discovery, data re-balance etc.) and user activities (get, put). We would like to set the request timeout for get/put. But a low threshold like 10 ms sometimes causes the system activities to fail. Is there a way for us to separately set the timeout values? Or even is it possible to setup timeout on individual calls (like get(key, timeout))?
-thanks

Hi,
not necessarily for get and put methods, but for queries, entry-processor and entry-aggregator and invocable agent sending, you can make the sent filter or aggregator or entry-processor or agent implement PriorityTask, which allows you to make QoS expectations known to Coherence. Most or all stock aggregators and entry-processors implement PriorityTask, if I correctly remember.
For more info, look at the documentation of PriorityTask.
Best regards,
Robert

Need Help regarding initial configuration for distributed cache

Hi ,
I am new to tangosol and trying to setup a basic partitioned distributed cache ,But I am not being able to do so
Here is my Scenario,
My Application DataServer create the instance of Tangosolcache .
I have this config.xml set in my machine where my application start.
<?xml version="1.0"?>
<!DOCTYPE cache-config SYSTEM "cache-config.dtd">
<cache-config>
<caching-scheme-mapping>

<cache-mapping>
<cache-name>*</cache-name>
<scheme-name>default-distributed</scheme-name>
</cache-mapping>
</caching-scheme-mapping>
<caching-schemes>

<distributed-scheme>
<scheme-name>default-distributed</scheme-name>
<service-name>DistributedCache</service-name>
<backing-map-scheme>
<class-scheme>
<scheme-ref>default-backing-map</scheme-ref>
</class-scheme>
</backing-map-scheme>
<autostart>true</autostart>
</distributed-scheme>

<class-scheme>
<scheme-name>default-backing-map</scheme-name>
<class-name>com.tangosol.util.SafeHashMap</class-name>
<init-params></init-params>
</class-scheme>
</caching-schemes>
</cache-config>
Now on the same machine I start a different client using the command
java -Dtangosol.coherence.distributed.localstorage=false -Dtangosol.coherence.cacheconfig=near-cache-config.xml -classpath
"C:/calypso/software/release/build" -jar ../lib/coherence.jar
The problem I am facing is
1)If I do not start the client even then my application server cache the data .Ideally my config.xml setting is set to
distributed so under no case it should cache the data in its local ...
2)I want to bind my differet cache on different process on different machine .
say
for e.g
machine1 should cache cache1 object
machine2 should cache cache2 object
and so on .......but i could not find any documentation which explain how to do this setting .Can some one give me example of
how to do it ....
3)I want to know the details of cache stored in any particular node how do I know say for e.g machine1 contains so and so
cache and it corresponding object values ... etc .....
Regards
Mahesh

Hi Thanks for answer.
After digging into the wiki lot i found out something related to KeyAssociation I think what I need is something like implementation of KeyAssociation and that
store the particular cache type object on particular node or group of node
Say for e,g I want to have this kind of setup
Cache1-->node1,node2 as I forecast this would take lot of memory (So i assign this jvms like 10 G)
Cache2-->node3 to assign small memory (like 2G)
and so on ...
From the wiki documentation i see
Key Association
By default the specific set of entries assigned to each partition is transparent to the application. In some cases it may be advantageous to keep certain related entries within the same cluster node. A key-associator may be used to indicate related entries, the partitioned cache service will ensure that associated entries reside on the same partition, and thus on the same cluster node. Alternatively, key association may be specified from within the application code by using keys which implement the com.tangosol.net.cache.KeyAssociation interface.
Do someone have any example of explaining how this is done in the simplest way ..

How can i configure Distributed cache servers and front-end servers for Streamlined topology in share point 2013??

my question is regarding SharePoint 2013 Farm topology. if i want go with Streamlined topology and having (2 distribute cache and Rm servers+ 2 front-end servers+ 2 batch-processing servers+ cluster sql server) then how distributed servers will
be connecting to front end servers? Can i use windows 2012 NLB feature? if i use NLB and then do i need to install NLB to all distributed servers and front-end servers and split-out services? What will be the configuration regarding my scenario.
Thanks in Advanced!

For the Distributed Cache servers, you simply make them farm members (like any other SharePoint servers) and turn on the Distributed Cache service (while making sure it is disabled on all other farm members). Then, validate no other services (except for
the Foundation Web service due to ease of solution management) is enabled on the DC servers and no end user requests or crawl requests are being routed to the DC servers. You do not need/use NLB for DC.
Trevor Seward
Follow or contact me at...
&nbsp&nbsp
This post is my own opinion and does not necessarily reflect the opinion or view of Microsoft, its employees, or other MVPs.

Error handling for distributed cache synchronization

Hello,
Can somebody explain to me how the error handling works for the distributed cache synchronization ?
Say I have four nodes of a weblogic cluster and 4 different sessions on each one of those nodes.
On Node A an update happens on object B. This update is going to be propogated to all the other nodes B, C, D. But for some reason the connection between node A and node B is lost.
In the following xml
<cache-synchronization-manager>
<clustering-service>...</clustering-service>
<should-remove-connection-on-error>true</should-remove-connection-on-error>
If I set this to true does this mean that the Toplink will stop sending updates from node A to node B ? I presume all of this is transparent. In order to handle any errors I do not have to write any code to capture this kind of error .
Is that correct ?
Aswin.

This "should-remove-connection-on-error" option mainly applies to RMI or RMI_IIOP cache synchronization. If you use JMS for cache synchronization, then connectivity and error handling is provided by the JMS service.
For RMI, when this is set to true (which is the default) if a communication exception occurs in sending the cache synchronization to a server, that server will be removed and no longer synchronized with. The assumption is that the server has gone down, and when it comes back up it will rejoin the cluster and reconnect to this server and resume synchronization. Since it will have an empty cache when it starts back up, it will not have missed anything.
You do not have to perform any error handling, however if you wish to handle cache synchronization errors you can use a TopLink Session ExceptionHandler. Any cache synchronization errors will be sent to the session's exception handler and allow it to handle the error or be notified of the error. Any errors will also be logged to the TopLink session's log.

High-units reflect twice the amount with dual JVM's in a distributed cache

HI all,
I have a question - i have a near cache scheme defined - running 4 JVM's with my application deployed to it (localstorage=false) - and 2 JVM's for the distributed cache (localstorage=true)
The high-units is set to 2000 - but the cache is allowing 4000. Is this b/c each JVM will allow for 2000 high-units each?
I was under the impression that as long as coherence is running in the same multi-cast address and port - that the total high-units would be 2000 not 4000.
Thanks...

user644269 wrote:
HI all,
I have a question - i have a near cache scheme defined - running 4 JVM's with my application deployed to it (localstorage=false) - and 2 JVM's for the distributed cache (localstorage=true)
The high-units is set to 2000 - but the cache is allowing 4000. Is this b/c each JVM will allow for 2000 high-units each?
I was under the impression that as long as coherence is running in the same multi-cast address and port - that the total high-units would be 2000 not 4000.
Thanks...Hi,
the high-unit setting is per-backing map, so in your case it means 2000 units per storage-enabled nodes.
From 3.5 it will become a bit more complex with the partition aware backing maps.
Best regards,
Robert

Distributed cache performance?

Hi,
I have a question about the performance of a cluster using a distributed cache:
A distributed cache is available in the the cluster, using the expiry-delay functionality. Each node first inserts new entries in the cache and then periodically updates the entries as long as the entry is needed in the cluster (entries that are no longer periodically updated will be removed due to the expiry-delay).
I performed a small test using a cluster with two nodes that each inserted ~2000 entries in the distributed cache. The nodes then periodically update their entries at 5 minutes intervals (using the Map.put(key, value) method). The nodes never access the same entries, so there will be no synchronization issues.
The problem is that the CPU load on the machines running the nodes are very high, ~70% (and this is quite powerful machines with 4 CPUs running Linux). To be able to find the reason for the high CPU load, I used a profiler tool on the application running on one of the nodes. It showed that the application spent ~70% of the time in com.tangosol.coherence.component.net.socket.UdpSocket.receive. Is this normal?
Since each node has a lot of other things to do, it is not acceptable that 70% of the CPU is used only for this purpose. Can this be a cache configuration issue, or do I have to find some other approach to perform this task?
Regards
Andreas

Hi Andreas,
Can you provide us with some additional information. You can e-mail it to our support account.
- JProfiler snapshot of the profiling showing high CPU utilization
- multiple full thread dumps for the process taken a few seconds apart, these should be taken when running outside of the profiler
- Your override file (tangosol-coherence-override.xml)
- Your cache configuration file (coherence-cache-config.xml)
- logs from the high CPU event, please also include -verbose:gc in the logs, directing the output to the coherence log file
- estimates on the sizes of the objects being updated in the cache
As this is occurring even when you are not actively adding data to the cache, can you describe what else your application is doing at this time. It would be extremely odd for Coherence to consume any noticeable amount of CPU if you are not making heavy use of the cache.
Note that when using the Map.put method the old value is returned to the caller, which for a distributed cache means extra network load, you may wish to consider switching to Map.putAll() as this does not need to return the old value, and is more efficient even if you are only operating on a single entry.
thanks,
Mark

Using Tangosol Coherence in conjunction with Kodo JDO for distributing caching

JDO currently has a perception problem in terms of performance. Transparent
persistence is perceived to have a significant performance overhead compared
to hand-coded JDBC. That was certainly true a while ago, when the first JDO
implementations were evaluated. They typically performed about half as well
and with higher resource requirements. No doubt JDO vendors have closed that
gap by caching PreparedStatements, queries, data, and by using other
optimizations.
Aside from the ease of programming through transparent persistence, I
believe that using JDO in conjunction with distributed caching techniques in
a J2EE managed environment has the opportunity to transparently give
scalability, performance, and availability improvements that would otherwise
be much more difficult to realize through other persistence techniques.
In particular, it looks like Tangosol is doing a lot of good work in the
area of distributed caching for J2EE. For example, executing parallelized
searches in a cluster is a capability that is pretty unique and potentially
very valuable to many applications. It would appear to me to be a lot of
synergy between Kodo JDO and Tangosol Coherence. Using Coherence as an
implementation of Kodo JDO's distributed cache would be a natural desire for
enterprise applications that have J2EE clustering requirements for high
scalability, performance, and availability.
I'm wondering if Solarmetric has any ideas or plans for closer integration
(e.g., pluggability) of Tangosol Coherence into Kodo JDO. This is just my
personal opinion, but I think a partnership between your two organizations
to do this integration would be mutually advantageous, and it would
potentially be very attractive to your customers.
Ben

Marc,
Thanks for pointing that out. That is truly excellent!
Ben
"Marc Prud'hommeaux" <[email protected]> wrote in message
news:[email protected]...
Ben-
We do currently have a plug-in for backing our data cache with a
Tangosol cache.
See: http://docs.solarmetric.com/manual.html#datastore_cache_config
In article <[email protected]>, Ben Eng wrote:
JDO currently has a perception problem in terms of performance.
Transparent
persistence is perceived to have a significant performance overheadcompared
to hand-coded JDBC. That was certainly true a while ago, when the firstJDO
implementations were evaluated. They typically performed about half aswell
and with higher resource requirements. No doubt JDO vendors have closedthat
gap by caching PreparedStatements, queries, data, and by using other
optimizations.
Aside from the ease of programming through transparent persistence, I
believe that using JDO in conjunction with distributed cachingtechniques in
a J2EE managed environment has the opportunity to transparently give
scalability, performance, and availability improvements that wouldotherwise
be much more difficult to realize through other persistence techniques.
In particular, it looks like Tangosol is doing a lot of good work in the
area of distributed caching for J2EE. For example, executingparallelized
searches in a cluster is a capability that is pretty unique andpotentially
very valuable to many applications. It would appear to me to be a lot of
synergy between Kodo JDO and Tangosol Coherence. Using Coherence as an
implementation of Kodo JDO's distributed cache would be a natural desirefor
enterprise applications that have J2EE clustering requirements for high
scalability, performance, and availability.
I'm wondering if Solarmetric has any ideas or plans for closerintegration
(e.g., pluggability) of Tangosol Coherence into Kodo JDO. This is justmy
personal opinion, but I think a partnership between your twoorganizations
to do this integration would be mutually advantageous, and it would
potentially be very attractive to your customers.
Ben--
Marc Prud'hommeaux [email protected]
SolarMetric Inc. http://www.solarmetric.com

Cache config for distributed cache and TCP*Extend

Hi,
I want to use distributed cache with TCP*Extend. We have defined "remote-cache-scheme" as the default cache scheme. I want to use a distributed cache along with a cache-store. The configuration I used for my scheme was
<distributed-scheme>
<scheme-name>MyScheme</scheme-name>
<backing-map-scheme>
    <read-write-backing-map-scheme>
      <internal-cache-scheme>
        <class-scheme>
          <class-name>com.tangosol.util.ObservableHashMap</class-name>
        </class-scheme>
      </internal-cache-scheme>
      <cachestore-scheme>
        <class-scheme>
          <class-name>MyCacheStore</class-name>
        </class-scheme>
        <remote-cache-scheme>
          <scheme-ref>default-scheme</scheme-ref>
        </remote-cache-scheme>
      </cachestore-scheme>
      <rollback-cachestore-failures>true</rollback-cachestore-failures>
    </read-write-backing-map-scheme>
</backing-map-scheme>
</distributed-scheme>
<remote-cache-scheme>
<scheme-name>default-scheme</scheme-name>
<initiator-config>
    <tcp-initiator>
      <remote-addresses>
        <socket-address>
          <address>XYZ</address>
          <port>9909</port>
        </socket-address>
      </remote-addresses>
    </tcp-initiator>
</initiator-config>
</remote-cache-scheme>I know that the configuration defined for "MyScheme" is wrong but I do not know how to configure "MyScheme" correctly to make my distributed cache the part of the same cluster to which all other caches, which uses the default scheme, are joined. Currently, this ain't happening.
Thanks.
RG
Message was edited by:
user602943

Hi,
Is it that I need to define my distributed scheme with the CacheStore in the server-coherence-cache-config.xml and then on the client side use remote cache scheme to connect to get my distributed cache?
Thanks,

Object locking in Distributed cache

Hi,
     I have gone through some of the posts on the forum regarding the locking issues.
     Thread at http://www.tangosol.net/forums/thread.jspa?messageID=3416 specifies that
     ..locks block locks, not gets or puts. If one member locks a key, it prevents another member from locking the key. It does not prevent the other member from getting/putting that key.
     What exactly do we mean by the above statement?
     I'm using distributed cache and would like to lock an object before "put" or "remove" operations. But I want "read" operation to be without locks. Now my questions are,
     1) In a distributed cache setup, if I try to obtain a lock before put or remove and discover that i cannot obtain it (i.e false is returned) because someone else has locked it, then how do I discover when the other entity releases lock and when should i retry for the lock?
     2) Again, if i lock USING "LOCK(OBJECT KEY)" method, can i be sure that no other cluster node would be writing/reading to that node until I release that lock?
     3) The first post in the thread http://www.tangosol.net/forums/thread.jspa?forumID=37&threadID=588 suggests that in distributed setup locks are of no effect to other cluster nodes. But i want locks to be valid across cluster. If item locked, then no one else shud be able to transact with it. How to get that?
     Regards,
     Mohnish

Hi Mohnish,
     >> 1) In a distributed cache setup, if I try to obtain
     >> a lock before put or remove and discover that i cannot
     >> obtain it (i.e false is returned) because someone else
     >> has locked it, then how do I discover when the other
     >> entity releases lock and when should i retry for the
     >> lock?
     You may try to acquire a lock (waiting indefinitely for lock acquisition) by calling <tt>cache.lock(key, -1)</tt>; you may try for a specified time period by calling <tt>cache.lock(key, cMillis)</tt>. With either of these approaches, your thread will block until the other thread releases the lock (or the timeout is reached). In either case, if the other node releases its lock your lock request will complete immediately and your thread will resume execution.
     >> 2) Again, if i lock USING "LOCK(OBJECT KEY)" method,
     >> can i be sure that no other cluster node would be
     >> writing/reading to that node until I release that lock?
     If you want to prevent other threads from writing/reading a cache entry, you must ensure that those other threads lock the key prior to writing/reading it. If they do not lock it prior to writing, they may have dirty writes (overwriting your write or vice versa); if they do not lock prior to reading, they may have dirty reads (having the underlying data change after they've read it).
     >> 3) The first post in the thread
     http://www.tangosol.net/forums/thread.jspa?forumID=37&threadID=588
     >> suggests that in distributed setup locks are of no
     >> effect to other cluster nodes. But i want locks to be
     >> valid across cluster. If item locked, then no one else
     >> shud be able to transact with it. How to get that?
     The first post in that thread states that if the second thread doesn't lock, then it will overwrite the first thread (even if the first thread has locked). However, there is an inconsistency in that the Replicated cache topology has a stronger memory model than the Distributed/Near topologies. In the Replicated topoplogy, locks not only block out locks from other nodes, they also prevent puts from other nodes.
     Jon Purdy
     Tangosol, Inc.

Different distributed caches within the cluster

Hi,
i've three machines n1 , n2 and n3 respectively that host tangosol. 2 of them act as the primary distributed cache and the third one acts as the secondary cache. i also have weblogic running on n1 and based on some requests pumps data on to the distributed cache on n1 and n2. i've a listener configured on n1 and n2 and on the entry deleted event i would like to populate tangosol distributed service running on n3. all the 3 nodes are within the same cluster.
i would like to ensure that the data directly coming from weblogic should only be distributed across n1 and n2 and NOT n3. for e.g. i do not start an instance of tangosol on node n3. and an object gets pruned from either n1 or n2. so ideally i should get a storage not configured exception which does not happen.
The point is the moment is say CacheFactory.getCache("Dist:n3") in the cache listener, tangosol does populate the secondary cache by creating an instance of Dist:n3 on either n1 or n2 depending from where the object has been pruned.
from my understanding i dont think we can have a config file on n1 and n2 that does not have a scheme for n3. i tried doing that and got an illegalstate exception.
my next step was to define the Dist:n3 scheme on n1 and n2 with local storage false and have a similar config file on n3 with local-storage for Dist:n3 as true and local storage for the primary cache as false.
can i configure local-storage specific to a cache rather than to a node.
i also have an EJB deployed on weblogic that also entertains a getData request. i.e. this ejb will also check the primary cache and the secondary cache for data. i would have the statement
NamedCahe n3 = CacheFactory.getCache("n3") in the bean as well.

Hi Jigar,
i've three machines n1 , n2 and n3 respectively that
host tangosol. 2 of them act as the primary
distributed cache and the third one acts as the
secondary cache.First, I am curious as to the requirements that drive this configuration setup.
i would like to ensure that the data directly coming
from weblogic should only be distributed across n1
and n2 and NOT n3. for e.g. i do not start an
instance of tangosol on node n3. and an object gets
pruned from either n1 or n2. so ideally i should get
a storage not configured exception which does not
happen.
The point is the moment is say
CacheFactory.getCache("Dist:n3") in the cache
listener, tangosol does populate the secondary cache
by creating an instance of Dist:n3 on either n1 or n2
depending from where the object has been pruned.
from my understanding i dont think we can have a
config file on n1 and n2 that does not have a scheme
for n3. i tried doing that and got an illegalstate
exception.
my next step was to define the Dist:n3 scheme on n1
and n2 with local storage false and have a similar
config file on n3 with local-storage for Dist:n3 as
true and local storage for the primary cache as
false.
can i configure local-storage specific to a cache
rather than to a node.
i also have an EJB deployed on weblogic that also
entertains a getData request. i.e. this ejb will also
check the primary cache and the secondary cache for
data. i would have the statement
NamedCahe n3 = CacheFactory.getCache("n3") in the
bean as well.In this scenario, I would recommend having the "primary" and "secondary" caches on different cache services (i.e. distributed-scheme/service-name). Then you can configure local storage on a service by service basis (i.e. distributed-scheme/local-storage).
Later,
Rob Misek
Tangosol, Inc.

Distributed Cache errors

On my application Server I am getting periodic entries under the General category
"Unable to write SPDistributedCache call usage entry."
The error is every 5 minutes exactly. It is followed by:
Calling... SPDistributedCacheClusterCustomProvider:: BeginTransaction
Calling... SPDistributedCacheClusterCustomProvider:: GetValue(object transactionContext, string type, string key
Calling... SPDistributedCacheClusterCustomProvider:: GetStoreUtcTime.
Calling... SPDistributedCacheClusterCustomProvider:: Update(object transactionContext, string type, string key, byte[] data, long oldVersion).
Sometimes this group of calls succeeds without an error and the sequence continues maybe for 3 iterations every 5 minutes. Then the error
"Unable to write SPDistributedCache call usage entry.""
happens again.
My Distributed Cache Service is running on my Application Server and on my web front end.
All values are default.
Any idea why this is happening intermittently?
Love them all...regardless. - Buddha

Hi,
From the error message, check whether super accounts were setup correctly.
Refer to the article about configuring object cache user accounts in SharePoint Server 2013::
https://technet.microsoft.com/en-us/library/ff758656(v=office.15).aspx
if the issue exists, please check the SharePoint ULS log located at : C:\Program Files\Common Files\Microsoft Shared\Web Server Extensions\15\LOGS to get a detailed error description.
Best Regards,
Lisa Chen
TechNet Community Support
Please remember to mark the replies as answers if they help, and unmark the answers if they provide no help. If you have feedback for TechNet Support, contact
[email protected]

Distributed Cache service stuck in Starting Provisioning

Hello,
I'm having problem with starting/stopping Distributed Cache service in one of the SharePoint 2013 farm servers. Initially, Distributed Cache was enabled in all the farm servers by default and it was running as a cluster. I wanted to remove it from all hosts
but one (APP server) using below PowerShell commands, which worked fine.
Stop-SPDistributedCacheServiceInstance -Graceful
Remove-SPDistributedCacheServiceInstance
But later I attempted to add the service back to two hosts (WFE servers) using below command and unfortunately one of them got stuck in the process. When I look at the Services on Server from Central Admin, the status says "Starting".
Add-SPDistributedCacheServiceInstance
Also, when I execute below script, the status says "Provisioning".
Get-SPServiceInstance | ? {($_.service.tostring()) -eq "SPDistributedCacheService Name=AppFabricCachingService"} | select Server, Status
I get "cacheHostInfo is null" error when I use "Stop-SPDistributedCacheServiceInstance -Graceful".
I tried below script,
$instanceName ="SPDistributedCacheService Name=AppFabricCachingService"
$serviceInstance = Get-SPServiceInstance | ? {($_.service.tostring()) -eq $instanceName -and ($_.server.name) -eq $env:computername}
$serviceInstance.Unprovision()
$serviceInstance.Delete()
,but it didn't work either, and I got below error.
"SPDistributedCacheServiceInstance", could not be deleted because other objects depend on it. Update all of these dependants to point to null or
different objects and retry this operation. The dependant objects are as follows:
SPServiceInstanceJobDefinition Name=job-service-instance-{GUID}
Has anyone come across this issue? I would appreciate any help.
Thanks!

Hi ,
Are you able to ping the server that is already running Distributed Cache on this server? For example:
ping WFE01
As you are using more than one cache host in your server farm, you must configure the first cache host running the Distributed Cache service to allow Inbound ICMP (ICMPv4) traffic through the firewall.If an administrator removes the first cache host from
the cluster which was configured to allow Inbound ICMP (ICMPv4) traffic through the firewall, you must configure the first server of the new cluster to allow Inbound ICMP (ICMPv4) traffic through the firewall.
You can create a rule to allow the incoming port.
For more information, you can refer to the blog:
http://habaneroconsulting.com/insights/Distributed-Cache-Needs-Ping#.U4_nmPm1a3A
Thanks,
Eric
Forum Support
Please remember to mark the replies as answers
if they help and unmark them if they provide no help. If you have feedback for TechNet Subscriber Support, contact [email protected]
Eric Tao
TechNet Community Support

Foundation 2013 Farm and Distributed Cache settings

We are on a 3 tier farm - 1 WFE + 1APP + 1SQL - have had many issues with AppFab and Dist Cache; and an additional issue with noderunner/Search Services. Memory and CPU running very high. Read that we shouldn't be running Search
and Dist Cache in the same server, nor using a WFE as a cache host. I don't have the budget to add another server in my environment.
I found an article (IderaWP_CachingFormSharePointPerformance.pdf) saying "To make use of SharePoint's caching capabilities requires a Server version of the platform." because it requires the publishing feature, which Foundation doesn't have.
So, I removed Distributed Cache (using Powershell) from my deployment and disabled the AppFab. This resolved 90% of server errors but performance didn't improve. Now, not only I'm getting errors now on Central Admin. - expects Dist Cache
- but I'm getting disk operations reading of 4000 ms.
Questions:
1) Should I enable AppFab and disable cache?
2) Does Foundation support Dist Cache? Do I need to run Distributed Cache?
3) If so, can I run with just 1 cache host? If I shouldn't run it on a WFE or an App server with Search, do I have to stop Search all together? What happens with 2 tier farms out there?
4) Reading through the labyrinth of links on TechNet and MSDN on the subject, most of them says "Applies to SharePoint Server".
5) Anyone out there on a Foundation 2013 production environment that could share your experience?
Thanks in advance for any help with this!
Monica
Monica

That article is referring to BlobCache, not Distributed Cache. BlobCache requires Publishing, hence Server, but DistributedCache is required on all SharePoint 2013 farms, regardless of edition.
I would leave your DistCache on the WFE, given the App Server likely runs Search. Make sure you install
AppFabric CU5 and make sure you make the changes as noted in the KB for
AppFabric CU3.
You'll need to separately investigate your disk performance issues. Could be poor disk layout, under spec'ed disks, and so on. A detail into the disks that support SharePoint would be valuable (type, kind, RPM if applicable, LUNs in place, etc.).
Trevor Seward
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This post is my own opinion and does not necessarily reflect the opinion or view of Microsoft, its employees, or other MVPs.

Limitation on number of objects in distributed cache

Hi,
Is there a limitation on the number (or total size) of objects in a distributed cache? I am seeing a big increase in response time when the number of objects exceeds 16,000. Normally, the ServiceMBean.RequestAverageDuration value is in the 6-8ms range as long as the number of objects in the cache is less than 16K - I've run our application for weeks at a time without seeing any problems. However, once the number of objects exceeds the magic number of 16K the average request duration almost immediately jumps to over 100ms and continues to climb as more objects are added.
I'm fairly confident that the cache is indexed properly (as Dimitri helped us with that). Are there any configuration changes that could possibly help out here? We are using Coherence 3.3.
Any suggestions would be greatly appreciated.
Thanks,
Jim

Hi Jim,
The results from the load test look quite normal, the system fairly quickly stabilizes at a particular performance level and remains there for the duration of the test. In terms of latency results, we see that the cache.putAll operations are taking ~45ms per bulk operation where each operation is putting 100 1K items, for cache.getAll operations we see about ~15ms per bulk operation. Additionally note that the test runs over 256,000 items, so it is well beyond the 16,000 limit you've encountered.
So it looks like your application are exhibiting different behavior then this test. You may wish to try to configure this test to behave as similarly to yours as possible. For instance you can set the size of the cache to just over/under 16,000 using the -entries parameter, set the size of the entries to 900 bytes using the -size parameter, and set the total number of threads per worker using the -threads parameter.
What is quite interesting is that at 256,000 1K objects the latency measured with this test is apparently less then half the latency you are seeing with a much smaller cache size. This would seem to point at the issue being related to or rooted in your test. Would you be able to provide a more detailed description of how you are using the cache, and the types of operations you are performing.
thanks,
mark

Setup failover for a distributed cache

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