Skip to main content

Pitfalls of the MyBatis Caches with Apache Ignite

UPD1: This blog has been published in Java Dzone https://dzone.com/articles/pitfalls-of-the-mybatis-caches-with-apache-ignite
UPD2: This blog also published in Habrahabr for Russian reader https://habrahabr.ru/company/at_consulting/blog/280452
UPD3: See also the sample chapter of the book "High performance in-memory computing with Apache Ignite" here.

A week ago, MyBatis and Apache ignite announced of support apache ignite as a MyBatis cache (L2 cache).
technically MyBatis support two levels of Caches:
  1. Local cache, which is always enable by default
  2. L2 cache, optional
As Apache Ignite project is fast growing with it's various functionality, in this blog post we are going to examine the MyBatis support in some details.
The second level cache stores the entity data, but NOT the entities or objects themselves. The data is stored in a 'serialised' format which looks like a hash map where the key is the entity Id, and the value is a list of primitive values.
Here is an example how the cache entries looks like in Apache ignite:
Where
Cache Key: CacheKey [idHash=1499858, hash=2019660929, checksum=800710994, count=6, multiplier=37, hashcode=2019660929, updateList=[com.blu.ignite.mapper.UserMapper.getUserObject, 0, 2147483647, SELECT * FROM all_objects t where t.OBJECT_TYPE='TABLE' and t.object_name=?, USERS, SqlSessionFactoryBean]]
Value class: java.util.ArrayList
Cache Value: [UserObject [idHash=243119413, hash=1658511469, owner=C##DONOTDELETE, object_type=TABLE, object_id=94087, created=Mon Feb 15 13:59:41 MSK 2016, object_name=USERS]]
As for Example, i selected the 'all_objects' objects and the following query from the Oracle Database
SELECT count(*) FROM all_objects;

SELECT * FROM all_objects t where t.OBJECT_TYPE='TABLE' and t.object_name='EMP';

SELECT * FROM all_objects t where t.OBJECT_TYPE='TABLE';
In my case, this given query execution time is ~660 ms in average.
SELECT count(*) FROM all_objects;
And the next following query execution time is more than 700ms:
SELECT t.object_type, count(*) FROM all_objects t group by t.OBJECT_TYPE;
lets add apache ignite as a second level cache and examine the result. If you want to know how to install and configure apache ignite with spring and myBatis, please refer to my previous blog post. Moreover, all the source you can find in github repositories.
As a quick start, lets add the myBatis maven dependency in project.
<dependency>
    <groupId>org.mybatis.caches</groupId>
    <artifactId>mybatis-ignite</artifactId>
    <version>1.0.0-beta1</version>
</dependency>
Then, just specify it in the mapper XML as follows
<mapper namespace="com.blu.ignite.mapper.UserMapper">

    <cache type="org.mybatis.caches.ignite.IgniteCacheAdapter" />

    <select id="getUserObject" parameterType="String" resultType="com.blu.ignite.dto.UserObject" useCache="true">
        SELECT * FROM all_objects t where t.OBJECT_TYPE='TABLE' and t.object_name=#{objectName}
    </select>
    <select id="getAllObjectsTypeByGroup" parameterType="String" resultType="com.blu.ignite.dto.UobjectGroupBy" useCache="true">
        SELECT t.object_type, count(*) as cnt FROM all_objects t group by t.OBJECT_TYPE
    </select>

    <select id="allObjectCount" parameterType="String" resultType="String" useCache="true">
        SELECT count(*) FROM all_objects
    </select>
</mapper>
Also i have the following java mapper
public interface UserMapper {
    User getUser( String id);
    List<string> getUniqueJob();
    UserObject getUserObject(String objectName);
    String allObjectCount();
    List<uobjectgroupby> getAllObjectsTypeByGroup();
}
and the web service as follows:
@WebService(name = "BusinessRulesServices",
        serviceName="BusinessRulesServices",
        targetNamespace = "http://com.blu.rules/services")
public class WebServices {
    private UserServices userServices;

    @WebMethod(operationName = "getUserName")
    public String getUserName(String userId){
        User user = userServices.getUser(userId);
        return user.getuName();
    }
    @WebMethod(operationName = "getUserObject")
    public UserObject getUserObject(String objectName){
        return userServices.getUserObject(objectName);
    }
    @WebMethod(operationName = "getUniqueJobs")
    public List<string> getUniqueJobs(){
        return userServices.getUniqueJobs();
    }
    @WebMethod(exclude = true)
    public void setDao(UserServices userServices){
        this.userServices = userServices;
    }
    @WebMethod(operationName = "allObjectCount")
    public String allObjectCount(){
        return userServices.allObjectCount();
    }
    @WebMethod(operationName = "getAllObjectsTypeCntByGroup")
    public List<uobjectgroupby> getAllObjectsTypeCntByGroup(){
        return userServices.getAllObjectCntbyGroup();
    }

}
If i will invoke the web method 'getAllObjectsTypeCntByGroup' in soupUI, first time it will get very high response time, approximately 1700 ms, because the result is not in the cache. From the second times, response time will be ~4 to ~5 ms.

Invoke web method first time will look like this:
Response time of the second or later invoke of web method
In apache ignite cache entry will look like as follows:

Cache Key: CacheKey [idHash=46158416, hash=1558187086, checksum=2921583030, count=5, multiplier=37, hashcode=1558187086, updateList=[com.blu.ignite.mapper.UserMapper.getAllObjectsTypeByGroup, 0, 2147483647, SELECT t.object_type, count(*) as cnt FROM all_objects t group by t.OBJECT_TYPE, SqlSessionFactoryBean]]
Value class: java.util.ArrayList
Cache Value: [UobjectGroupBy [idHash=2103707742, hash=1378996400, cnt=1, object_type=EDITION], UobjectGroupBy [idHash=333378159, hash=872886462, cnt=444, object_type=INDEX PARTITION], UobjectGroupBy [idHash=756814918, hash=1462794064, cnt=32, object_type=TABLE SUBPARTITION], UobjectGroupBy [idHash=931078572, hash=953621437, cnt=2, object_type=CONSUMER GROUP], UobjectGroupBy [idHash=1778706917, hash=1681913927, cnt=256, object_type=SEQUENCE], UobjectGroupBy [idHash=246231872, hash=1764800190, cnt=519, object_type=TABLE PARTITION], UobjectGroupBy [idHash=1138665719, hash=1030673983, cnt=4, object_type=SCHEDULE], UobjectGroupBy [idHash=232948577, hash=1038362844, cnt=1, object_type=RULE], UobjectGroupBy [idHash=1080301817, hash=646054631, cnt=310, object_type=JAVA DATA], UobjectGroupBy [idHash=657724550, hash=1248576975, cnt=201, object_type=PROCEDURE], UobjectGroupBy [idHash=295410055, hash=33504659, cnt=54, object_type=OPERATOR], UobjectGroupBy [idHash=150727006, hash=499210168, cnt=2, object_type=DESTINATION], UobjectGroupBy [idHash=1865360077, hash=727903197, cnt=9, object_type=WINDOW], UobjectGroupBy [idHash=582342926, hash=1060308675, cnt=4, object_type=SCHEDULER GROUP], UobjectGroupBy [idHash=1968399647, hash=1205380883, cnt=1306, object_type=PACKAGE], UobjectGroupBy [idHash=1495061270, hash=1345537223, cnt=1245, object_type=PACKAGE BODY], UobjectGroupBy [idHash=1328790450, hash=1823695135, cnt=228, object_type=LIBRARY], UobjectGroupBy [idHash=1128429299, hash=1267824468, cnt=10, object_type=PROGRAM], UobjectGroupBy [idHash=760711193, hash=1240703242, cnt=17, object_type=RULE SET], UobjectGroupBy [idHash=317487814, hash=61657487, cnt=10, object_type=CONTEXT], UobjectGroupBy [idHash=1079028994, hash=1960895356, cnt=229, object_type=TYPE BODY], UobjectGroupBy [idHash=276147733, hash=873140579, cnt=44, object_type=XML SCHEMA], UobjectGroupBy [idHash=24378178, hash=1621363993, cnt=1014, object_type=JAVA RESOURCE], UobjectGroupBy [idHash=1891142624, hash=90282027, cnt=10, object_type=DIRECTORY], UobjectGroupBy [idHash=902107208, hash=1995006200, cnt=593, object_type=TRIGGER], UobjectGroupBy [idHash=142411235, hash=444983119, cnt=14, object_type=JOB CLASS], UobjectGroupBy [idHash=373966405, hash=1518992835, cnt=3494, object_type=INDEX], UobjectGroupBy [idHash=580466919, hash=1394644601, cnt=2422, object_type=TABLE], UobjectGroupBy [idHash=1061370796, hash=1861472837, cnt=37082, object_type=SYNONYM], UobjectGroupBy [idHash=1609659322, hash=1543110475, cnt=6487, object_type=VIEW], UobjectGroupBy [idHash=458063471, hash=1317758482, cnt=346, object_type=FUNCTION], UobjectGroupBy [idHash=1886921697, hash=424653540, cnt=7, object_type=INDEXTYPE], UobjectGroupBy [idHash=1455482905, hash=1776171634, cnt=30816, object_type=JAVA CLASS], UobjectGroupBy [idHash=49819096, hash=2110362533, cnt=2, object_type=JAVA SOURCE], UobjectGroupBy [idHash=1916179950, hash=1760023032, cnt=10, object_type=CLUSTER], UobjectGroupBy [idHash=1138808674, hash=215713426, cnt=2536, object_type=TYPE], UobjectGroupBy [idHash=305229607, hash=340664529, cnt=23, object_type=JOB], UobjectGroupBy [idHash=1365509716, hash=623631686, cnt=12, object_type=EVALUATION CONTEXT]]

Performance gain:
With simple calculation we can define the performance gain that we have got: Response Time without cache/Response Time with cache = 1589ms/6ms ~265X faster, or (Response Time without cache - Response Time with Cache)/ Response Time with cache * 100 = (1589-6)/6*100 ~ 26383% percent faster.

Conclusion: Expensive database operation can be reduce by using L2 cache, properly using L2 cache in MyBatis can increase the application performance from 10 to 20 times. Apache Ignite in memory data grid is a very suitable candidate for this purpose, certainly, you can also use Hazelcast, EhCache or any other Caching tools.

If you like this article, you would also like the book

Comments

Popular posts from this blog

Tip: SQL client for Apache Ignite cache

A new SQL client configuration described in  The Apache Ignite book . If it got you interested, check out the rest of the book for more helpful information. Apache Ignite provides SQL queries execution on the caches, SQL syntax is an ANSI-99 compliant. Therefore, you can execute SQL queries against any caches from any SQL client which supports JDBC thin client. This section is for those, who feels comfortable with SQL rather than execute a bunch of code to retrieve data from the cache. Apache Ignite out of the box shipped with JDBC driver that allows you to connect to Ignite caches and retrieve distributed data from the cache using standard SQL queries. Rest of the section of this chapter will describe how to connect SQL IDE (Integrated Development Environment) to Ignite cache and executes some SQL queries to play with the data. SQL IDE or SQL editor can simplify the development process and allow you to get productive much quicker. Most database vendors have their own front-en

8 things every developer should know about the Apache Ignite caching

Any technology, no matter how advanced it is, will not be able to solve your problems if you implement it improperly. Caching, precisely when it comes to the use of a distributed caching, can only accelerate your application with the proper use and configurations of it. From this point of view, Apache Ignite is no different, and there are a few steps to consider before using it in the production environment. In this article, we describe various technics that can help you to plan and adequately use of Apache Ignite as cutting-edge caching technology. Do proper capacity planning before using Ignite cluster. Do paperwork for understanding the size of the cache, number of CPUs or how many JVMs will be required. Let’s assume that you are using Hibernate as an ORM in 10 application servers and wish to use Ignite as an L2 cache. Calculate the total memory usages and the number of Ignite nodes you have to need for maintaining your SLA. An incorrect number of the Ignite nodes can become a b

Load balancing and fail over with scheduler

Every programmer at least develop one Scheduler or Job in their life time of programming. Nowadays writing or developing scheduler to get you job done is very simple, but when you are thinking about high availability or load balancing your scheduler or job it getting some tricky. Even more when you have a few instance of your scheduler but only one can be run at a time also need some tricks to done. A long time ago i used some data base table lock to achieved such a functionality as leader election. Around 2010 when Zookeeper comes into play, i always preferred to use Zookeeper to bring high availability and scalability. For using Zookeeper you have to need Zookeeper cluster with minimum 3 nodes and maintain the cluster. Our new customer denied to use such a open source product in their environment and i was definitely need to find something alternative. Definitely Quartz was the next choose. Quartz makes developing scheduler easy and simple. Quartz clustering feature brings the HA and