Wednesday, 15 February 2017

Spring Boot Starters 1.0.0.Beta1

I'm happy to announce Spring Boot Starters 1.0.0.Beta1.

The changelog includes:

  • Fixed hotrod-client.properties path (now it uses classpath:hotrod-client.properties) 
  • ISPN-7468 Added Spring Cache automatic discovery and creation 
  • Fixed typo in artifact name 
  • Upgraded to the latest artifact versions 
  • Removed deprecated classes from tests
Grab them while they are hot!

Friday, 10 February 2017

Infinispan 9.0.0.CR1

Those busy hackers over in the Infinispan dungeon have brewed up a new release, and it is the first candidate on the road to the final 9.
Infinispan 9.0.0.CR1 (codenamed "Ruppaner") includes a number of fixes and component upgrades over the last Beta release. You can read all about these in the fixed issues
 
We have also done a lot of work to restructure the user guide, upgrade guide and server admin guide to make it easier to find the answers you need.

So, please head over to the download page and try it out. If you have an issue, please report it in our bug tracker, ask us on the forum, or join us for a friendly chat on the #infinispan IRC channel on Freenode.

Prost,
Your friendly Infinispan team

Wednesday, 8 February 2017

Hotrod clients C++/C# 8.1.0.CR1 released!

Dears,

we're pleased to announce that 8.1.0.CR1 release for C++/C# clients is out! Downloading the code you'll find these changes (and may more):
  • C++11 instead of the old portable custom classes
  • less bugs
  • more safety through TLS client authentication
We're getting closer to a final release, more updates on what's going on here:



Enjoy!

Tuesday, 24 January 2017

Infinispan 9.0.0.Beta2 and 8.2.6.Final are out!

It's release day at Infinispan HQ and we've just released a couple of new versions:
  • Infinispan 9.0.0.Beta2 includes:
    • New:
      • Multi-tenancy support for Hot Rod and REST endpoints improve Infinispan Server experience on OpenShift.
      • Transactional support for Functional API (thx Radim!)
      • Internal data container changes, see Will's blog posts (here and here) for more info.
      • Off-heap bounded data container has been added.
      • ElasticSearch storage for indexes.
      • Multiple additions and enhancements to the management console.
      • Further performance improvements.
    • Backwards compatibility:
      • Binary and mixed JDBC cache stores have been removed. To migrate data over, use the JDBC cache store migrator.
      • Dropped default cache inheritance.
    • Full release notes.

Cheers,
Galder

Monday, 23 January 2017

Data Container Changes Part 2

Before the end of the year I wrote a blog post detailing some of the more recent changes that Infinispan introduced with the in memory data container.  As was mentioned in the previous post we would be detailing some other new changes. If you poked around in our new schema after Beta 1 you may have spoiled the surprise for yourself.

With the upcoming 9.0 Beta 2, I am excited to announce that Infinispan will have support for entries being stored off heap, as in outside of the JVM heap. This has some interesting benefits and drawbacks, but we hope you can agree the benefits in many cases far outweigh the drawbacks. But before we get into that lets first see how you can configure your cache to utilize off heap.

New Configuration


The off heap configuration is another option under the new memory element that was discussed in the previous post. It is used in the same way that either OBJECT or BINARY is used.  You can use either COUNT or MEMORY eviciton types, the example below shows the latter.

XML


DECLARATIVE

As you can see the configuration is almost identical to the other types of storage. The only real difference is the new address pointer argument, which will be explained below.

Requirements


Our off heap implementation supports all existing features of Infinispan. There are some limitations and drawbacks of using the feature. This section will describe these in further detail.

Serialization


Off Heap runs in essentially BINARY mode, which requires entries to be serialized into their byte[] forms. Thus all keys and entries must be Serializable or have provided Infinispan Externalizers.

Size


Currently a key and a value must be able to be stored in a byte[]. Therefore a key or value in serialized form cannot be more than just over 2 Gigabytes.  This could be enhanced possibly at a later point, if the need arose.  I hope you aren't transferring this over your network though!


Implementation Details 


Our off heap implementation uses the Java Unsafe to allocate memory outside of the Java heap. This data is stored as a bucket of linked list pointers, just like a standard Java HashMap. When an entry is added the key's serialized byte[] is hashed and an appropriate offset is found in the bucket. Then the entry is added to the bucket as the first element or if an entry(ies) is present it is added to the rear of the linked list.

All of this data is protected by an array of ReadWriteLock instances.  The number of address pointers is evenly divisible by the number of lock instances.  The number of lock instances is how many cores your machines doubled and rounded to the nearest power of two.  Thus each lock protects an equivalent amount of address spaces.  This provides for good lock granularity and reads will not block each other but unfortunately writes will wait and block all reads.

If you are using a bounded off heap container either by count or memory this will create a backing LRU doubly linked list to keep track of which elements were accessed most recently and removes the least recently accessed element when there are too many present in the cache.

 

Memory Overhead


As with all cache implementations there is overhead required to store these entries. We have a fixed and variable overhead which scales with the amount of entries. I will detail these and briefly mention what they are used for.

Fixed overhead

As was mentioned there is a new address count parameter when configuring off heap. This value is used to determine how many linked list pointers are available. Normally you want to have more node pointers than you have entries in the cache, since then chances are you have one element in each linked list.  This is very similar to the int argument constructor for HashMap.  It is also rounded up to the nearest power of two.  The big difference being that this off heap implementation will not resize.  Thus your read/write times will be slower if you have a lot of collisions. The overhead of a pointer is 8 bytes, so for approximately one million pointers it will be 8 Megabytes of off heap.

Bounded off heap requires very little fixed memory, just 32 bytes for head/tail pointers and a counter and an additional Java lock object.

Variable overhead

Unfortunately to store your entries we may need to wrap them with some data. Thus for every entry you add to the cache we store an additional 25 bytes for each entry.  This data is used for header information and also our linked list forward pointer.

Bounded off heap requires additional housekeeping for its LRU list nodes.  Thus each entry adds an additional 36 bytes above the number above. It is larger due to requiring a doubly linked list and having to have pointers to and from the entry and eviction node.

Performance


The off heap container was designed with the intent that key lookups are quite fast. In general these should be about the same performance. However local reads and stream operations can be a little slower as there is an additional deserialization phase required.

Summary


We hope you all try out our new off heap feature! Please make sure to contact us if you have any feedback, find any bugs or have any questions!  You can get in contact with us on our forum, issue tracker, or directly on IRC freenode channel Infinispan

9.x JDBC Store Improvements

Infinispan 9 introduces several changes to the JDBC stores, in summary:
  • Configuration of DB version
  • Upsert support for store writes
  • Timestamp indexing
  • c3p0 connection pool replaced by HikariCP

DB Version Configuration


Previously when configuring a JDBC store it was only possible for a user to specify the vendor of the underlying DB. Consequently, it was not possible for Infinispan to utilise more recent features of DB as the SQL utilised by our JDBC stores had to satisfy the capabilities of the oldest supported DB version.

In Infinispan 9 we have completely refactored the code responsible for generating SQL queries.  Enabling our JDBC stores to take greater advantage of optimisations and features applicable to a given database vendor and version. See the below gist for examples of how to specify the major and minor versions of your database.

Programmatic config:
XML Config:
Note: If no version information is provided, then we attempt to retrieve version data via the JDBC driver.  This is not always possible and in such cases we default to SQL queries which are compatible with the lowest supported version of the specified DB dialect.

Upsert Support


As a consequence of the refactoring mentioned above, writes to the JDBC stores finally utilise upserts. Previously, the JDBC stores had to first select an entry, before inserting or updating a DB row depending on whether the entry previously existed.  Now, in supported DBs, store writes are performed atomically via a single SQL statement.

In some cases it may be desirable for the previous store behaviour to be utilised, in such cases the following property should be passed to your store's configuration and set to true: `infinispan.jdbc.upsert.disabled`.

Timestamp Indexing


By default an index is now created on the `timestamp-column` of a JDBC store when the "create-on-start" option is set to true for a store's table.  The advantage of this index is that it prevents the DB from having to perform full table searches when purging a table of expired cache entries.  Similar to upsert support, this index is optional an can be disabled by setting the property `infinispan.jdbc.indexing.disabled` to true.  

Hello HikariCP


In Infinispan 9 we welcome HikariCP as the new default implementation for the JDBC PooledConnectionFactory. HikariCP provides superior performance to c3p0 (the previous default), whilst also providing a much smaller footprint. The PooledConnectionFactoryConfiguration remains the same as before, expect we now include the ability to explicitly define a properties file where additional configuration parameters can be specified for the underlying HikariCP. For a full list of the available HikariCP configuration properties, please see the official documentation

Note: Support for c3p0 has been deprecated and will be removed in a future release. However, users can force c3p0 to be utilised as before by providing the system property `-Dinfinispan.jdbc.c3p0.force=true`.


Summary


We have introduced the above new features to the JDBC stores in order to improve performance and to enable us to further the store's capabilities in the future. If you're a user of the JDBC stores and have any feedback on the latest changes, or would like to request some new features/optimisations, let us know via the forumissue tracker or the #infinispan channel on Freenode. 

Wednesday, 11 January 2017

Near Cache for native C++/C# Client example

Dear Readers,

as mentioned in our previous post about the new C++/C# release 8.1.0.Beta1, clients are now equipped with near cache support.

The near cache is an additional cache level that keeps the most recently used cache entries in an "in memory" data structure. Near cached objects are synchronized with the remote server value in the background and can be get as fast as a map[] operation.

So, your client tends to periodically focus the operations on a subset of your entries? This feature could be of help: it's easy to use, just enable it and you'll have near cache seamless under the wood.

A C++ example of a cache with near cache configuration
The last line does the magic, the INVALIDATED mode is the active mode for the near cache (default mode is DISABLED which means no near cache, see Java docs), maxEntries is the maximum number of entries that can be stored nearly. If the near cache is full the oldest entry will be evicted. Set maxEntries=0 for unbounded cache (do you have enough memory?)
Now a full example of application that just does some gets and puts and counts how many of them are served remote and how many are served nearly. As you can see the cache object is an instance of the "well known" RemoteCache class
Entries values in the near cache are kept aligned with the remote cache state via the events subsystem: if something changes in the server, an update event (modified, expired, removed) is sent to the client that updates the cache accordingly.

By the way: do you know that C++/C# clients can subscribe listener to events? In the next "native" post we will see how.

Cheers!
and thank you for reading.