My application needs to cache non-serializable objects for performance reasons. These non-serializable objects are in-memory models built from an external resource. For example, a validation template is stored as XML in the database, and an in-memory model is constructed by parsing the XML. The in-memory model is relatively expensive to build, so caching improves performance. However, the in-memory model needs to be reloaded from the database when the underlying record is changed.
In a single application scenario, I stored the objects in a simple map. When a record is changed in the database, the in-memory model is rebuilt and replaced the old entry in the map.
In a distributed scenario, I need the invalidation message to propagate across the cluster so that all nodes rebuild the in-memory model when the record changes. I have looked at Infinispan and Hazelcast and they both require all cached objects to be serializable. However, if the cache operates in an invalidation mode (where data is not sent across the wire), I don't see why the cached objects need to be serializable.
What techniques are commonly used in this scenario? Is this scenario unusual (i.e. should I be doing something different)?
However, if the cache operates in an invalidation mode (where data is
not sent across the wire)
not exactly sure what this means, why store objects in distributed cache then?
And how did you get them in the cache in a first place?
Your objects do not have to be serializable in a pure Java sense, i.e., they do not have to implement Serializable interface. But since your cache is distributed, be it Hazelcast or Memcached or EhCache, you need to get your Java objects across the wire and store them in cache in some external format, and then be able to get them back from cache and restore as Java objects. This is called marshaling /unmarshaling, or ... serialization/deserialization. The are variety of formats you can consider: XML, Json, Bson, Yaml, Thrift, etc. There are numerous frameworks and libraries that can help you work with these different serialization schemas. XStream, JAXB, Jackson, Apache Camel, etc.
As far as Hazelcast goes, its documentation explicitly says: "All your distributed objects such as your key and value objects, objects you offer into distributed queue and your distributed callable/runnable objects have to be Serializable." May be you could consider Guava in-memory cache?
Related
I have used the cache2k in my java project and it was so simple (key-value pair) and easy to use. Now I want to know is if cache2k is a persistent or non-persistent cache.
I found the answer in here
https://stackoverflow.com/a/23709996/12605243 which was said at 2014 stated that it was gonna be updated to persistent cache.
So my question is 'Am I using a persistent or non persistent cache?'. I have read their docs but unable to find it.
Basically its possible to add persitence via CacheLoader and CacheWriter. We use that in several ways to use file system or database as storage. When adding persistence this way the cache operates in the so called "cache through" mode. Some operations of the cache, especially get and put operate transparently and read or write the data via the loader and writer to the storage. Other operations, like CAS operations, just interact with the in-memory cache.
The persistence feature as it was planed was meant to be transparent for all cache operations. Although its feasible and the basic work is done in the internal infrastructure, we don't have a big need for it. Other features and tasks seem more important. However, I am happy to hear about potential use cases.
Cache Invalidation
There are options like Ehcache, DynaCache and JCS for Invalidation.
Before I start understanding and learning the library I would like know which Cache provider I should consider. Any suggestions?
It depends what you are shooting for , in a nutshell
JCS is targeted to boost up dynamic web applications. JCS uses pluggable controller for a cache region(or Composite Cache). The regions are divided into Memory, Disk, Lateral, and Remote. Regarding faileover,
JCS provides a framework with no point of failure, allowing for full
session failover (in clustered environments), including session data
across up to 256 servers JCS has a wick nested categorical removal,
data expiration (idle time and max life) Extensible framework, fully
configurable runtime parameters, and remote synchronization, remote
store recovery, Non-blocking "zombie" (balking facade) pattern
Ehcache
Is a java distributed cache for general purpose caching, J2EE and
light-weight containers tuned for large size cache objects. It
features memory and disk stores, replicate by copy and invalidate,
listeners, a gzip caching servlet filter, Fast, Simple.One of its features is to cache domain objects that map to database entities. As the domain objects that maps to database entities is the core of any ORM system that’s why Ehcache is the default cache for HibernateWith Ehcache you can serialize both Serializable objects and Non-serializable.
For more details you can refer here
In Java, I have a HashMap containing objects (which can be serializable, if it helps). Elsewhere on a network, I have another HashMap in another copy of the application that I would like to stay in sync with the first.
For example if on computer A, someone runs myMap.put("Hello", "World"); and on computer B, someone runs myMap.put("foo", "bar");, then after some time delay for changes to propagate, both computers would have mayMap.get("Hello") == "World" and mayMap.get("foo") == "bar".
Is this requirement met by an existing facility in the Java language, a library, or some other program? If this is already a "solved problem" it would be great not to have to write my own code for this.
If there are multiple ways of achieving this I would prefer, in priority order:
Changes are guaranteed to propagate 100% of the time (doesn't matter how long it takes)
Changes propagate rapidly
Changes propagate with minimal bandwidth use between computers.
(Note: I have had trouble searching for solutions as results are dominated by questions about synchronizing access to a Map from multiple threads in the same application. This is not what my question is about.)
You could look at the hazelcast in-memory database.
It's an open source solution designed for distributed architectures.
It maps really well to your problem since the hazelcast IMap extends java.util.Map.
Link: Hazelcast IMap
what you are trying to do is call clustering between two node
here i have some solution
you can achieve your requirement using serialization make your map
serializable read and write state of map in each interval of time
and sync it.this is core and basic way to achieve your
functionality.but by using serialization you have to manually manage
sync of map(i.e you have to do code for that)
Hazelcast open source distributed caching mechanism hazelcast
is best api and have reach libarary to achive cluster environment
and share data between different node
coherence web also provide mechanism to achieve clustering by
Oracle
Ehcache is a cache library introduced in 2003 to improve
performance by reducing the load on underlying resources. Ehcache is
not for both general-purpose caching and caching Hibernate
(second-level cache), data access objects, security credentials, and
web pages. It can also be used for SOAP and RESTful server caching,
application persistence, and distributed caching
among all of above Hazelcast is best api go through it will sure help you
I've a web app that makes external web service calls on behalf of it's clients. I want to cache the data returns by some web services in the web app so that other clients can reuse this data and run filters and queries on this cached data.
The current architecture of the web app uses Apache Camel, Spring and Jetty. I'm looking for options (pros/cons) of in-memory database options.
Hazelcast (Java API) - you can distribute the in-memory datagrid (with map, multimap, sets, lists, queues, topics) over multiple nodes very easily & use load/store interface implementation with a disk based DB. You can do something similar with EHCache.
Redis is another option (use the Java client to access it). You can simply configure the conf file to write data to disk (or avoid it altogether) & should not have to write your own load/store classes.
Besides these, there are a number of options you could use. Not sure if you are only looking at open source options, looking at distributed options or not.
Hope it helps.
Have you considered using MemCached? It is not a database, but a caching system you can control from inside your application.
Here are a few more thoughts about in-memory databases. First almost every modern RDBMS has a memory caching system inside it. The more memory you give to the database server (and configure it for caching) the more that it will store in memory for later. If you put together a system with enough memory to cache all the tables, you will have an "in memory" cache without the overhead of another database.
Most total "in memory" databases are used for high volume/large data systems where performance is totally key. And, because they are for extreme performance systems, you are going to pay for them. Or more specifically, pay extra for them. For example, the SAP/Sybase DB's that support full in-memory can cost you from 40% to 300% more than our existing products.
So, in answer to your question, do you really need one?
Try Redisson - distributed and scalable familar Java data structures (Set, Map, ConcurrentMap, List, Queue, Lock, AtomicLong, CountDownLatch, Publish / Subscribe) on top of in-memory db Redis.
A couple of Relational DB tables are managed by a single object cache that resides in a process. When the cache is committed the tables are updated. The DB relational tables are updated by regular SQL queries and not anything more fancier like hibernate.
Eventually, other processes got into the business of modifying this object without communicating with one another i.e, Each process would initialize this object (read from DB) and update it( commit to DB), & other process would not know about it holding on to a stale cache.
I have to fix this workflow. I have thought of couple of methods.
One is to make this object an mBean. So, the object would reside on one process and every process would eventually modify the object in that process by mBean method invocations.
However, this approach has a couple of problems.
1) Every object returned by this cache has be an mBean, which could make the method invocations quite chatty.
2) Also there is a requirement that every process should see a consistent data model(cache) of the DB, and it should merge its contents to the DB if possible. (like a transaction). If the DB was updated by some other process significantly, it is OK for the merge to fail.
What technologies in Java will help to solve this problem?
You should have a look at Terracotta. They have technology that makes multiple JVMs (can be on different servers) appear unified. If you update an object on one JVM, Terracotta will update the instance transparently on all JVMs in the cluster in a safe way.
If you wanted to keep the object model, you could use java object cache for centralized storage before committing. Or you could keep a shared lock using zookeeper.
But it sounds like you should really abandon the self-managed cache. Use hibernate or another JPA implementation, which you mentioned. JPA addresses the cache issues and maintains a L2 shared cache, so they've thought about this for you.
I agree with John - use a second level cache in hibernate with support for clustering. Much more straightforward way to manage data by using a simplified data access model and let Hibernate manage the details.
Terracotta Ehcache is one such cache, so is JBoss, Coherence, etc.
More info on Hibernate Second Level Cache can be had here and in the official Hibernate docs on Chapter 19. Improving Performance (note that the while the Hibernate docs do list second level cache providers, the list is woefully out of date, for example who uses Swarm Cache? The last release of that was in 2003)