Generating JAX-RS client stubs

In the CXF JAX-WS world, when giving out API's to the clients to use, the steps to be followed were:

• Annotate the service and service methods with the @WebService and@WebMethod annotation in the business module
• Generate a WSDL corresponding to the given service methods using the java2wsdlutility as part of the maven build of the business module
• Define a separate ws-api module that uses the wsdl2java utility to create the client stubs using the WSDL file generated by the business module as an input. The target of this module is what is given to the outside world

How do we do this in a CXF JAX-RS world where though we have a wadl2java utility, we don't have a java2wadl utility - and where concept of WADL by itself is largely contentious?

Suppose, we have an interface that we wish to expose in a JAX-RS way - say SpecialService.java. Now this service interface can expose methods which produce complex java objects which in turn may have other non-primitive fields. The rs-api jar that we wish to give to the clients of this interface should contain only the relevant objects required and should be spared from the implementation classes that are used by the business module itself (like done by the ws-api jar in the JAX-WS world). ProGuard is one utility that helps us out here. ProGuard is more known for being a class file obfuscator for distributing android packages (now being superseded by DexGuard) so that clients are not able to reverse-engineer the original logic. However, it is also a pretty nifty optimizer - in the sense that it can do static code analysis to see which class files are needed corresponding to a given starting point. And that is really what we wanted - we want to see which classes are needed given SpecialService class as the starting point.

The configuration is as simple as:

    <configuration>
        <obfuscate>false</obfuscate>
        <injar>../../proguard-tester-business/target/proguard-tester-business-0.0.1-SNAPSHOT.jar</injar>
        <inFilter>!**.xml</inFilter>
        <outjar>${project.build.finalName}.jar</outjar>
        <outputDirectory>${project.build.directory}</outputDirectory>
        <options>
            <option>-dontnote</option>
            <option>-keepattributes</option>
            <option>-keep @javax.ws.rs.Path public interface com.kilo.SpecialService { *;}</option>
            <option>-keepclassmembers class * { *;}</option>
            <!-- Additional classes as needed -->
            <option>-keep public class com.kilo.MixinSetter { *;}</option>
            <option>-keep public class com.kilo.ApplicationParamConverterProvider { *;}</option>
        </options>
    </configuration>

This configuration will create a stub for all the methods in the interface that have been annotated with the @Path annotation and will pull in its dependent classes. Hence, if you have certain methods as part of your interface which are not annotated will not figure in the interface that is being provided to your clients - which is great. But, one should also consider why both methods are part of the same interface if they are serving such varied needs - anyway, that is upto the designers of the interface. Any additional classes needed can also be mentioned and the rs-api jar is thus self-sufficient and directly usable by the client. And no dependency on WADL whatsoever. Sample setup available here.

The ProGuard usage manual has an exhaustive explanation of the different options and I found community support for this good as well.

Next step would be to see how we can get a source jar generated for these client stubs so that debugging would be useful, but that is for another post. Hope this helps!

References:

• http://jcp.org/en/jsr/detail?id=224
• http://en.wikipedia.org/wiki/Web_Services_Description_Language
• http://cxf.apache.org/docs/wsdl-to-java.html
• http://cxf.apache.org/docs/java-to-wsdl.html
• http://www.w3.org/Submission/wadl/
• http://cxf.apache.org/docs/jaxrs-services-description.html#JAXRSServicesDescription-wadl2javacommandlinetool
• http://proguard.sourceforge.net/
• http://www.saikoa.com/dexguard
• http://proguard.sourceforge.net/#manual/usage.html
• https://github.com/kilokahn/proguard-tester

Quick embedded db for integration tests

Our implementation of bitemporal library had a sample client. The integration test cases in the client project run nightly to affirm the veracity of the actions. To see the client in action, it needed an underlying table on a dataserver. To get the ball rolling, we initially housed it in the sandbox DB of a dev dataserver. However, it regularly went missing giving us monday morning pains. Next, we decided to move it to one of the databases that we owned on the dev dataserver. However, the monday morning pain changed to a monthly pain coinciding with the data server refresh cycles when the tables on the database would go missing again. We could have considered moving these tables to the production data server, but it would be undesired clutter to a newcomer. As an alternate route, we just pointed it to a local dataserver instance running on one of our colleagues machines. And yes, you guessed it right – when the machine was down for reboots or other maintenance, again failures though we needed to be especially unlucky for that to happen! Here an embedded database seemed to fit the bill nicely

Mixin it up Jackson style

We have already discovered the goodness of Jackson for vending out JSON data in a JAX-RS setup. In many cases, our domain objects have references to other domain objects that are not under our control (e.g. classes from third-party JARs). We can easily add annotations to our domain objects to indicate which fields to ignore, but what do we do for the third party objects? One could choose to write custom bean serializers, but that is pretty onerous on the part of the user and one that requires higher maintenance since it is away from the original class. Here is where Jackson Mixins comes to the rescue.

Know your disk latency numbers

I was looking around for a tool that will help quantify the latency difference between a NFS-mounted location to a local location and came across ioping. As the documentation indicates, it tries to represent disk latency in pretty much the same way as the ping command shows network latency to a desired host.

I had to build it from source for our linux installation - but the process went about without a hitch. I first tried it on my NFS mounted home drive where the checked-out code, eclipse workspace and maven repository reside and is the hotspot for IO activity when developing. Using a sample invocation from the documentation site, I tried it for a chunk of size 1MB, ten times.

$>ioping -c 10 -s 1M
--- /home/kilo(nfs fs1.kilo.com:/vol/home/kilo) ioping statistics ---
10 requests completed in 9101.5 ms, 102 iops, 102.1 mb/s
min/avg/max/mdev = 9.5/9.8/10.0/0.2 ms

Next was to test out the performance of our local partition with the same parameters:

--- /local/kilo (ext4 /dev/ssda) ioping statistics ---
10 requests completed in 9052.4 ms, 201 iops, 200.8 mb/s
min/avg/max/mdev = 4.8/5.0/5.6/0.2 ms

Result was roughly a speed-up of 200%!

For kicks, I tried it out on a /tmp location as well with the same parameters:

--- /tmp (tmpfs none) ioping statistics ---
10 requests completed in 9004.1 ms, 5219 iops, 5219.2 mb/s
min/avg/max/mdev = 0.1/0.2/0.3/0.0 ms

That was roughly 30 times faster - but hold on - what is that tmpfs that is mentioned. Digging further, it seems tmpfs is a special filesystem that doesn't reside on a physical disk but rather stored in the physical memory (albeit volatile) - so the speed-up in access is kind of expected. Which also means that we should be extra nice about what goes in /tmp in such a setup. Keeping a lot of garbage in there and not cleaning up will come and bite us at unpredictable times. Guess many people already know about this

Coming back to the utility itself, there are options to change working set sizes, offsets into files that wish to be seeked, etc. One particularly interesting feature is the option to use write IO, but that option was not available in the 0.6 that I downloaded. An issue indicates that this is a yet to be released feature and will be interesting to see it in action.

I think this will a good utility to have in our linux installations by default. If there are other utilities that do similar stuff but comes out of the box from a stock RHEL installation, please let me know. Hope this helps!

References:

1. https://code.google.com/p/ioping/

2. http://en.wikipedia.org/wiki/Tmpfs

3. https://code.google.com/p/ioping/wiki/man

Lets go uber!

ow do you run your non-webapp maven-based java program from command line? One might be using exec:java route and specify the main class. The only sticking point here is that the classpath will be filled with references to the user’s local repository (usually NFS mounted). I would be much more comfortable if I had all the set of jars that I would be dependent on packaged WAR-style and be ready at my disposal. In that sense, the application would be much more self-contained. It also becomes that much easy for someone to testdrive your application. Hence the concept of an “uber” jar – a unified jar that will house all classes/resources of the project along with classes/resources of its transitive dependencies.

Blocked persistence nuance with GET*DATE()

Noticed an interesting (and desired) behavior when dealing with persisting timestamps that is blocked by a competing transaction, which might be useful for others as well. For unitemporal and bitemporal tables, we frequently update the knowledge_date as either GETDATE() or GETUTCDATE(), but it is not guaranteeing that the wall-clock time of when record got persisted to the db is the same as the value noted in the knowledge_date column.

To illustrate this, let's say we have a table as

CREATE TABLE special_table (
special_key INT PRIMARY KEY,
special_value INT,
knowledge_date DATETIME)

An we insert a few values into it:

INSERT INTO special_table VALUES(1, 100, GETUTCDATE())
INSERT INTO special_table VALUES(2, 100, GETUTCDATE())
INSERT INTO special_table VALUES(100, 10000, GETUTCDATE())

Now, let's say, we've got two competing transactions, one a read and another a write with the read preceding the write and the read transaction taking a lot more time to finish (simulated with a WAITFOR DELAY).

Read Transaction (at isolation level repeatable read):

BEGIN TRANSACTION
SELECT GETUTCDATE() --ts1
SELECT * FROM special_table WHERE special_key = 2
WAITFOR DELAY '00:00:10'
SELECT * FROM special_table WHERE special_key = 2
SELECT GETUTCDATE() --ts2
COMMIT

Write Transaction (at isolation level read committed):

BEGIN TRANSACTION
SELECT GETUTCDATE() --ts3
UPDATE special_table
   SET special_value = special_value + 1, knowledge_date=GETUTCDATE()
 WHERE special_key = 2
SELECT GETUTCDATE() --ts4
SELECT * FROM special_table WHERE special_key = 2
COMMIT

Execute these two batches in two windows of SSMS with the read preceding the write. Since the read started before the write, ts1+10 ~= ts2 because the read transaction will experience no blocking. The write operation was kicked off a little after read was kicked off (say with interval d). Hence ts1 + d = ts3.

Question: will the knowledge_date updated be closer to ts3 or ts4?

One might think that the knowledge_date value is closer to ts4 when the write transaction actually gets unblocked, however, this is not the case. For Sql Server itself to figure out whether or not the transaction needs to get blocked (because of the default page level locking scheme followed), the query needs to be evaluated and hence the value to be assigned to knowledge_date has to be evaluated at a time closer to ts3 itself. Hence the knowledge_date timestamp will be persisted to the DB at a wall-clock time closer to ts4even if the DB claims the timestamp as closer to ts3.

This can be verified with the output from the read and writes where there is a marked delay between the knowledge_date updated and the ts4. This becomes even more interesting when you have multiple updates in the same write transaction - some of which can proceed - till the point that it gets blocked because of the read and one can notice varying knowledge_date across records even though they were all kicked off in the same transaction.

BEGIN TRANSACTION
SELECT GETUTCDATE() --ts1
UPDATE special_table
   SET special_value = special_value + 1, knowledge_date=GETUTCDATE() --ts
 WHERE special_key = 100
SELECT GETUTCDATE() --ts2
UPDATE special_table
   SET special_value = special_value + 1, knowledge_date=GETUTCDATE() --tss
 WHERE special_key = 2
SELECT GETUTCDATE() --ts3
SELECT * FROM special_table WHERE special_key = 2
COMMIT

Here, knowledge_date for key 100 would be closer to ts1 due to it not getting blocked by the read and the knowledge_date for key 2 would be closer to ts3 and away from ts2 since it was blocked by the read.

BTW, this should not haunt the trigger based td_bl temporal tables as the trigger gets only fired after the base table is updated and effectively captures the timestamp of when the base table was changed (but may not be the exact time when the temporal record got persisted to the db due to blocking concerns).

Hope this helps!

References:

• http://en.wikipedia.org/wiki/Isolation_(database_systems)#Repeatable_reads
• http://en.wikipedia.org/wiki/Isolation_(database_systems)#Read_committed

Quick headless JAX-RS servers with CXF

If one needs to vend out JSON data in a JAX-RS compatible way with minimal setup fuss, CXF + Spring provides good out-of-the-box solution for you.

The steps would be:

1. Write your service class (interface and impl preferably)
2. Annotate your service impl methods with
1. @Path annotation indicating the URI on which it will serve the resource
2. @Get/@Post indicating the HTTP method which it serves
3. @Produces("application/json") indicating that the output format is JSON
3. Define a jaxrs:server directive in your spring context file indicating the address and resource path on which the service is hosted
4. Add maven dependencies of javax.ws.rs-api (for annotations), cxf-rt-core (for stubbing RS communication over a http conduit) and cxf-rt-transports-http-jetty (for embedded jetty)

and voila you are done.

Concretely:

public interface SpecialService {
    String getSomeText();
}

public class SpecialServiceImpl implements SpecialService {

    @GET
    @Produces("application/json")
    @Path("/someText/")
    @Override
    public String getSomeText() {
        return "kilo";
    }
}

    <bean id="specialService" class="com.kilo.SpecialServiceImpl"/>

    <bean id="inetAddress" class="java.net.InetAddress" factory-method="getLocalHost" />

    <jaxrs:server id="specialServiceRS"
        address="http://#{inetAddress.hostName}:${com.kilo.restful.port}/specialServiceRS">
        <jaxrs:serviceBeans>
            <ref bean="specialService" />
        </jaxrs:serviceBeans>
    </jaxrs:server>

And now hit http://yourhostname:yourportnum/specialServiceRS/someText to get the response as "kilo". If you examine the request via some developer tools, you will see that the content type is application/json.

CXF JAX-RS uses an embedded jetty as the http container, so we don't really need a tomcat for setting this up. This might bring up the question of Tomcat vs Jetty overall and here are my thoughts:

Tomcat

• Lightweight
• Servlet 3 style async threading in the works
• Known beast in terms of configuration

Jetty

• Even more lightweight
• Implements servlet 3 style async thread allocation (like node) and hence more responsive and efficient
• Easy to have an embedded server with cxf (embeddability is synonymous with jetty)
• Ability to have multiple simple java processes that act as headless servers quickly

Overall, I believe we should give Jetty a chance and see how it performs. If it ever lets us down, it is easy to take the process and house it in a Tomcat container.

We will try to cover some more involved use cases of passing in inputs via JAX-RS, dealing with complex objects, CORS and GZIP in subsequent posts (the samples already have them explained).

References:

• Setup @ https://github.com/kilokahn/spring-testers/tree/master/spring-cxf-jaxrs-headless-tester
• https://www.webtide.com/choose/jetty.jsp
• http://www.asjava.com/jetty/jetty-vs-tomcat-performance-comparison/ 
• http://www.slideshare.net/noriaki/jetty-vs-tomcat