Ignite has two modes, one is Server mode, and the other is client mode.I am reading https://apacheignite.readme.io/docs/clients-vs-servers, but didn't get a good understanding of these two modes.
In my opinion, there are two use cases:
If the Ignite is used as an embedded server in a java application, they the Ignite should be in server mode, that is, Ignite should be started with
Ignite ignite = Ignition.start(configFile)
If I have setup an Ignite cluster that are running as standalone processes. Then in my java code, I should start Ignite in client mode, so that the client mode Ignite can connect to the Ignite cluster, and CRUD the cache data that resides in the ignite cluster?
Ignition.setClientMode(true);
Ignite ignite = Ignition.start(configFile)
Yeah, this is correct understanding.
Ignite client mode intended as lightweight mode (which do not store data and do not execute compute tasks). Client node should communicate with a cluster and should not utilize self resources.
Client does not even started without server node presented in topology.
In order to further add to #Makros answer, Ignite Client stores data if near cache is enabled. This is done in order to increase the performance of cache retrievals.
Yeah, you are right in ignite client has IgniteConfiguration.setClientMode(true); and for server IgniteConfiguration.setClientMode(false);, which is default value. if set IgniteConfiguration.setClientMode(false); in you code or forget to set setClientMode(); it will work as server.
Related
One of my backend service uses Ignite. The backend service itself is stateless, meaning, the service doesn't have any internal or shared states, and can scale up and down on the need. The backend service is deployed in Kubernetes.
I have used the Ignite, now, in the embedded way, with cache mode set to REPLICATED, and native persistence enabled. Additionally I have also enabled the baselineAutoAdjustEnabled. The reason for using replicated mode is to have the data available to all the backend instances locally & consistent way.
The application seems to work correctly -
as and when data is modifies the data gets replicated across all the instances of the backend
data replication works even if a new instance joins the topology after (long time) the initial baseline is set & activated.
The question now is, is this is the right approach in running the Ignite in embedded (server mode), with full replication, and native persistence?
In general your design looks well. But be careful with using of baselineAutoAdjustEnabled. This feature works only in case of topology changes do not leads to lost partitions. But in your case, as you use only replicated caches, any node stoping should not lead to lost partitions.
Embeded mode in this case does not have any matter.
I am trying to build an apache ignite thinclient poc and am able to connect to a cluster and also read the data using a ScanQuery. But am stuck at creating a Listener for any cache updates. I looked through but could not find anything for thin clients. Does ignite thin client even support listening on cache updates? How do I do that?
No, thin clients don't support Continuous Queries. You'll need to use a thick client to get that functionality.
We are trying to prevent our application startups from just spinning if we cannot reach the remote cluster. From what I've read Force Server Mode states
In this case, discovery will happen as if all the nodes in topology
were server nodes.
What i want to know is:
Does this client then permanently act as a server which would run computes and store caching data?
If connection to the cluster does not happen at first, a later connection to an establish cluster cause issue with consistency? What would be the expect behavior with a Topology version mismatch? Id their potential for a split brain scenario?
No, it's still a client node, but behaves as a server on discovery protocol level. For example, it can start without any server nodes running.
Client node can never cause data inconsistency as it never stores the data. This does not depend forceServerMode flag.
I would like to know answers for below questions:
1) In case if Ignite server is restarted, I need to restart the client (web applications). Is there any way client can reconnect to server on server restart. I know when server restarts it allocates a different ID and because of this the current existing connection becomes stale. Is there way to overcome this problem and if so, which version of Ignite supports this feature. Currently I utilize version 1.7
2) Can I have client cache like how Ehcache provides. I don’t want client cache as a front–end to a distributed cache. When I looked at the Near Cache API, it doesn’t have cache name properties like cache configuration and it acts only as a front-end to a distributed cache. Is it possible to create client only cache in Ignite
3) If I have a large object to cache, I find Serialization and Deserialization takes a longer time in Ignite and retrieving from distributed cache is slow. Is there any way we can speed up large objects retrieval from Ignite DataGrid.
This topic is discussed on Apache Ignite users mailing list: http://apache-ignite-users.70518.x6.nabble.com/Questions-on-Client-Reconnect-and-Client-Cache-td10018.html
I've been doing some experiments with Apache Ignite and I've started to look into WAN replication. By this I mean there would be 2 (or more) data centres each running an Ignite cluster. There would be some caches that I would like kept in sync between the two data centres.
Does Apache Ignite support this? If so how is this configured as I can't find any mention of this in the documentation.
At the moment Ignite does not support caches spanning multiple clusters(nor cache mirroring). If however you mean there is only one Ignite cluster consisting of nodes located in different data centers(WAN),that would be possible though would most likely be inefficient! since you will have to use the Replicated Mode.
GridGain provides asynchronous WAN replication on top of Ignite as part of their payed solution: https://www.gridgain.com/docs/latest/administrators-guide/data-center-replication/configuring-replication