I am looking for a migration path for a Java-based project which uses Apache Cassandra 2.2 to Oracle Coherence 12 – and Oracle 12 backend.
The existing application uses CQL to interact with a 3 node Cassandra cluster.
Elswhere we specifically do not use any ORM (e.g. Hibernate/JPA) but use JDBC to interact with the database directly.
Yes, Cassandra is free while the Oracle solution is quite expensive but this is outside the scope of this question.
Any technical suggestions are welcomed.
You have a couple of options depending on your use case.
If you are using the SQL to interact with Cassandra for standard request/response interactions and need to migrate it to use Oracle DB which would require the least code changes and still use a standard approach would be to use an Object Relational Mapping (ORM) tool like Hibernate/JPA and use Coherence as the L2 cache (personally I like MyBatis since you have complete control over the SQL code. You may be able to use this Coherence integration with MyBatis ).
If you have other applications/ops users updating the database directly and need those changes to be available to your application then you will need to implement a CacheStore (use your favorite ORM here if you like) to save updates to the database and use Oracle Golden Gate Hotcache feature to push updates made to the database outside your application to Coherence. Your application will need to be changed to interact with Coherence directly using either their Map interface or using the Coherence Query Language (CQL) which is "SQL like". This approach will have an additional advantage of being able to support any asynchronous use cases you may have as Coherence API supports listening to cache changes (using MapListeners) similar to Cassandra's executeAsync.
I hope this helps.
Related
Is Spring Data JDBC v1.1.5 recommended for Oracle Database and Enterprise Applications? Lot of samples around the net based on Open Source RDBMS (H2 or PostgreSQL). We are using Spring Data JDBC in a Spring Boot Microservice Application, facing following problems.
Force to write custom converters for oracle.sql.TIMESTAMP, oracle.sql.TIMESTAMPTZ and oracle.sql.DATE and oracle.sql.ROWID etc..
Can't type cast oracle.sql.ROWID to java.lang.Number
Identity must not be null after save.
Spring Data JDBC is absolutely recommended for Enterprise Applications.
Not so much for use with Oracle.
Since the necessary resources (database & JDBC driver) weren't available in a form that could be easily used in integration tests on public platforms, Oracle isn't included in regular builds.
Therefore it is likely that one encounters issues when working with Oracle.
Some are already known, for others issues in Jira or even PRs are highly appreciated.
I want to know if there's a way to configure the datasource for Ignite as Elastic Search. I was browsing the web. But I did not find a solution.
I want to implement this integration for a Java application.
If I understand your idea correctly there's a way to do it. As far as I can see Elasticsearch supports SQL table-like data access and it's available through jdbc connection. From the Ignite's side we have 3rd party persistance, it uses jdbc to connect to an underlying store system. To be honest I haven't tested it but I suppose it should work.
Also I need mention that you can use GridGain WebConsole to generate simple Ignite project from existing jdbc connection. This functionality could be found on Configuration tab -> Create Cluster Configuration.
We have a solution which uses the Apache Ignite-provided In-Memory Data Grid as a distributed cache. For newer projects, we ended up using Spring, and as such we wished homogenize our software ecosystem and using Spring for the first solution as well. In addition, we do not use all the features of Ignite to excuse its use (discovery, caching).
Since we currently only use a limited subset of features from Ignite, we are basically looking for a self-managed application-level distributed cache solution (similar to what Ignite provides). This means that dedicated caching infrastructure like Redis, Memcached, etc. is not what we want.
I've researched the topic somewhat and found that there are some possible alternatives like:
Tayzgrid - Last update seems to be quite some time ago, not sure if still actively maintained
Druid - Still incubating, and I have also read that new releases being somewhat broken was not that uncommon
Hazelcast - Seems like the best choice given its maturity and the existence of Spring Data Hazelcast, though I am unsure what the level of support is here.
Has anyone has experience with integrating one of the above IMDGs (aside from Ignite) with Spring Cache? Any pointers in the right direction would be greatly appreciated.
You can use Redisson - Redis Java client with features of
In-Memory Data Grid. It also implements Spring Data support. Here is the documentation.
Hazelcast has official support for Spring Data Hazelcast and also this module has many users as now. I can also suggest you to have a look at the resources below:
Using Hazelcast with Spring Data
Getting Started with Microservices Using Hazelcast IMDG and Spring Boot
I found many examples of using spring boot reactive with document databases, but none with SQL databases.
I see that it may not support sql databases yet, probably because some missing feature on the jpa/jdbc stack.
I also see that there is no point to use reactive services that depend on the a sql database with no reactive support.
The question here is: Is there any ongoing development to make this happen (reactive jpa)?
There is a reactive feature built into many RDBMSs called "Change Data Capture" which writes data to an async transaction log for an enabled table. Usually, reactive systems built to stream this data are built on top of that feature. For example, a well-known open source tool that does this is Debezium. You can find other open source projects online that do something similar, or to write your own using the simple CDC functions that are usually provided to support it.
I am putting together a regular Java EE application on jboss7 that will use JPA in the data tier. I would like to make this application such that it scales up with load. While it is pretty clear how to scale up the web tier: create more machines and throw them behind a load balancer, scaling up the data tier is less so.
I can probably cluster my database (MySQL). Stil, that leaves the JPA layer unclustered. Ideally, JPA will scale up by using in (clustered) memory caching backed by MySQL.
When I look around, all information around JPA scaling seems to be 3-4 years old. People talk about ehcache, memcached and infinispan. I am not sure if this is still current.
Can someone tell me the state of the art in Java EE clustering and scaling, especially in the data tier.
Various caching strategies are still the way to scale JPA/Hibernate (you basically named the most popular options in your question). Nothing extraordinary happend since 4-5 years in this field, as far as I know. One more option you haven't mentioned is JBoss Cache. So the Second Level Cache for JPA/Hibernate still rules in this area.
Why no progress here? My wild guess is that first of all people, who need scalable application tend to ignore JPA and Hibernate in areas where high performance is needed. Usually people go with SQL dressed in Spring Framework JDBCTemplate helpers and transaction management. Then scalability is the matter of database capabilities in this area.
The other trend is to use No-SQL databases. There is plany of solutions: MongoDB, CouchoDB, Cassandra, Redis, to name a few. These are usually Google BigTable like key-value storages (this is oversimplification, but it is more or less the idea behind that approach) and they scale as hell, if you accept their limitations (relations are no longer managed easily, etc.).
There are many solutions, the two main categories of solutions are:
scaling the database
using a clustered cache to reduce database load
EclipseLink supports data partitioning for sharding data across a set of database instances,
see:
http://java-persistence-performance.blogspot.com/2011/05/data-partitioning-scaling-database.html
You can also use MySQL Cluster,
see:
http://www.mysql.com/products/cluster/
Oracle TopLink Grid provides EclipseLink JPA support for integration with Oracle Coherence as a distributed cache,
see:
http://www.oracle.com/technetwork/middleware/ias/tl-grid-097210.html
EclipseLink's cache supports clustering through cache coordination,
see:
http://wiki.eclipse.org/EclipseLink/Examples/JPA/CacheCoordination