Documentation
NoSQLUnit Core
Overview
Unit testing is a method by which the smallest testable part of an application is validated. Unit tests must follow the FIRST Rules; these are Fast, Isolated, Repeatable, Self-Validated and Timely.
It is strange to think about a JEE application without persistence layer (typical Relational databases or new NoSQL databases) so should be interesting to write unit tests of persistence layer too. When we are writing unit tests of persistence layer we should focus on to not break two main concepts of FIRST rules, the fast and the isolated ones.
Our tests will be fast if they don't access network nor filesystem, and in case of persistence systems network and filesystem are the most used resources. In case of RDBMS ( SQL ), many Java in-memory databases exist like Apache Derby , H2 or HSQLDB . These databases, as their name suggests are embedded into your program and data are stored in memory, so your tests are still fast. The problem is with NoSQL systems, because of their heterogeneity. Some systems work using Document approach (like MongoDb ), other ones Column (like Hbase ), or Graph (like Neo4J ). For this reason the in-memory mode should be provided by the vendor, there is no a generic solution.
Our tests must be isolated from themselves. It is not acceptable that one test method modifies the result of another test method. In case of persistence tests this scenario occurs when previous test method insert an entry to database and next test method execution finds the change. So before execution of each test, database should be found in a known state. Note that if your test found database in a known state, test will be repeatable, if test assertion depends on previous test execution, each execution will be unique. For homogeneous systems like RDBMS , DBUnit exists to maintain database in a known state before each execution. But there is no like DBUnit framework for heterogeneous NoSQL systems.
NoSQLUnit resolves this problem by providing a JUnit extension which helps us to manage lifecycle of NoSQL systems and also take care of maintaining databases into known state.
Requirements
To run NoSQLUnit , JUnit 4.10 or later must be provided. This is because of NoSQLUnit is using Rules , and they have changed from previous versions to 4.10.
Although it should work with JDK 5 , jars are compiled using JDK 6 .
NoSQLUnit
NoSQLUnit is a JUnit extension to make writing unit and integration tests of systems that use NoSQL backend easier and is composed by two sets of Rules and a group of annotations.
First set of Rules are those responsible of managing database lifecycle; there are two for each supported backend.
-
The first one (in case it is possible) it is the in-memory mode. This mode takes care of starting and stopping database system in " in-memory " mode. This mode will be typically used during unit testing execution.
-
The second one is the managed mode. This mode is in charge of starting NoSQL server but as remote process (in local machine) and stopping it. This will typically used during integration testing execution.
Second set of Rules are those responsible of maintaining database into known state. Each supported backend will have its own, and can be understood as a connection to defined database which will be used to execute the required operations for maintaining the stability of the system.
Note that because NoSQL databases are heterogeneous, each system will require its own implementation.
And finally two annotations are provided, @UsingDataSet and @ShouldMatchDataSet , (thank you so much Arquillian people for the name).
Seeding Database
@UsingDataSet is used to seed database with defined data set. In brief data sets are files that contain all data to be inserted to configured database. In order to seed your database, use @UsingDataSet annotation, you can define it either on the test itself or on the class level. If there is definition on both, test level annotation takes precedence. This annotation has two attributes locations and loadStrategy .
With locations attribute you can specify classpath datasets location. Locations are relative to test class location. Note that more than one dataset can be specified.
Also withSelectiveLocations attribute can be used to specify datasets location. See Advanced Usage chapter for more information.
If files are not specified explicitly, next strategy is applied:
-
First searches for a file on classpath in same package of test class with next file name,
[test class name]#[test method name].[format](only if annotation is present at test method). -
If first rule is not met or annotation is defined at class scope, next file is searched on classpath in same package of test class,
[test class name].[default format].
Warning
datasets must reside into classpath and format depends on NoSQL vendor.
Second attribute provides strategies for inserting data. Implemented strategies are:
INSERT Insert defined datasets before executing any test method. DELETE_ALL Deletes all elements of database before executing any test method. CLEAN_INSERT This is the most used strategy. It deletes all elements of database and then insert defined datasets before executing any test method.
: Load Strategies
An example of usage:
@UsingDataSet(locations="my_data_set.json", loadStrategy=LoadStrategyEnum.INSERT)
Verifying Database
Sometimes it might imply a huge amount of work asserting database state directly from testing code. By using @ShouldMatchDataSet on test method, NoSQLUnit will check if database contains expected entries after test execution. As with @ShouldMatchDataSet annotation you can define classpath file location, or using withSelectiveMatche, see Advanced Usage chapter for more information. If it is not dataset supplied next convention is used:
-
First searches for a file on classpath in same package of test class with next file name,
[test class name]#[test method name]-expected.[format](only if annotation is present at test method). -
If first rule is not met or annotation is defined at class scope, file is searched on classpath in same package of test class,
[test class name]-expected.[default format].
Warning
datasets must reside into classpath and format depends on NoSQL vendor.
An example of usage:
@ShouldMatchDataSet(location="my_expected_data_set.json")
MongoDb Engine
MongoDb
MongoDb is a NoSQL database that stores structured data as JSON-like documents with dynamic schemas.
NoSQLUnit supports MongoDb by using next classes:
In Memory com.lordofthejars.nosqlunit.mongodb.InMemoryMongoDb Managed com.lordofthejars.nosqlunit.mongodb.ManagedMongoDb
: Lifecycle Management Rules
NoSQLUnit Management com.lordofthejars.nosqlunit.mongodb.MongoDbRule
: Manager Rule
Maven Setup
To use NoSQLUnit with MongoDb you only need to add next dependency:
<dependency>
<groupId>com.lordofthejars</groupId>
<artifactId>nosqlunit-mongodb</artifactId>
<version>${version.nosqlunit}</version>
</dependency>
Note that if you are plannig to use in-memory approach an extra dependency is required. In-memory mode is implemented using jmockmongo . JMockmongo is a new project that help with unit testing Java-based MongoDb Applications by starting an in-process Netty server that speaks the MongoDb protocol and maintains databases and collections in JVM memory. It is not a true embedded mode becuase it will starts a server, but in fact for now it is the best way to write MongoDb unit tests. As his author says it is an incomplete tool and will be improved every time a new feature is required.
Warning
During development of this documentation, current jmockmongo version was 0.0.2-SNAPSHOT. Author is imporoving version often so before using one specific version, take a look at its website .
To install add next repository and dependency :
<repositories>
<repository>
<id>thiloplanz-snapshot</id>
<url>http://repository-thiloplanz.forge.cloudbees.com/snapshot/</url>
</repository>
</repositories>
<dependency>
<groupId>jmockmongo</groupId>
<artifactId>jmockmongo</artifactId>
<version>${mongomock.version}</version>
</dependency>
Dataset Format
Default dataset file format in MongoDb module is json .
Datasets must have next format :
{
"name_collection1": [
{
"attribute_1":"value1",
"attribute_2":"value2"
},
{
"attribute_3":2,
"attribute_4":"value4"
}
],
"name_collection2": [
...
],
....
}
Notice that if attributes value are integers, double quotes are not required.
Getting Started
Lifecycle Management Strategy
First step is defining which lifecycle management strategy is required for your tests. Depending on kind of test you are implementing (unit test, integration test, deployment test, ...) you will require an in-memory approach, managed approach or remote approach.
To configure in-memory approach you should only instantiate next rule :
@ClassRule
InMemoryMongoDb inMemoryMongoDb = new InMemoryMongoDb();
To configure the managed way, you should use ManagedMongoDb rule and may require some configuration parameters.
import static com.lordofthejars.nosqlunit.mongodb.ManagedMongoDb.MongoServerRuleBuilder.newManagedMongoDbRule;
@ClassRule
public static ManagedMongoDb managedMongoDb = newManagedMongoDbRule().build();
By default managed MongoDb rule uses next default values:
-
MongoDb installation directory is retrieved from
MONGO_HOMEsystem environment variable. -
Target path, that is the directory where MongoDb server is started, is
target/mongo-temp. -
Database path is at
{target path}/mongo-dbpath. -
Because after execution of tests all generated data is removed, in
{target path}/logpathwill remain log file generated by the server. -
In Windows systems executable should be found as
bin/mongod.exemeanwhile in MAC OS and *nix should be found asbin/mongod.
ManagedMongoDb can be created from scratch, but for making life easier, a DSL is provided using MongoServerRuleBuilder class. For example :
import static com.lordofthejars.nosqlunit.mongodb.ManagedMongoDb.MongoServerRuleBuilder.newManagedMongoDbRule;
@ClassRule
public static ManagedMongoDb managedMongoDb =
newManagedMongoDbRule().mongodPath("/opt/mongo").appendSingleCommandLineArguments("-vvv").build();
In example we are overriding
MONGO_HOME variable (in case has been set) and set mongo home at
/opt/mongo . Moreover we are appending a single argument to MongoDb
executable, in this case setting log level to number 3 (-vvv). Also you
can append property=value arguments using
appendCommandLineArguments(String argumentName, String argumentValue) method.
Warning
when you are specifying command line arguments, remember to add slash (-) and double slash (--) where is necessary.
To stop MongoDb instance, NoSQLUnit sends a shutdown command to
server using Java Mongo AP I. When this command is sent, the server is
stopped and because connection is lost, Java Mongo API logs
automatically an exception (read
here
information about the problem and how to "resolve" it). Do not confuse
with a testing failure. You will see something like:
java.io.EOFException
at org.bson.io.Bits.readFully(Bits.java:37)
at org.bson.io.Bits.readFully(Bits.java:28)
at com.mongodb.Response.<init>;(Response.java:39)
at com.mongodb.DBPort.go(DBPort.java:128)
at com.mongodb.DBPort.call(DBPort.java:79)
at com.mongodb.DBTCPConnector.call(DBTCPConnector.java:218)
at com.mongodb.DBApiLayer$MyCollection.__find(DBApiLayer.java:305)
at com.mongodb.DB.command(DB.java:160)
at com.mongodb.DB.command(DB.java:183)
at com.mongodb.DB.command(DB.java:144)
at
com.lordofthejars.nosqlunit.mongodb.MongoDbLowLevelOps.shutdown(MongoDbLowLevelOps.java:44)
at
com.lordofthejars.nosqlunit.mongodb.ManagedMongoDb.after(ManagedMongoDb.java:157)
at
org.junit.rules.ExternalResource$1.evaluate(ExternalResource.java:48)
at org.junit.rules.RunRules.evaluate(RunRules.java:18)
at org.junit.runners.ParentRunner.run(ParentRunner.java:300)
at
org.apache.maven.surefire.junit4.JUnit4Provider.execute(JUnit4Provider.java:236)
at
org.apache.maven.surefire.junit4.JUnit4Provider.executeTestSet(JUnit4Provider.java:134)
at
org.apache.maven.surefire.junit4.JUnit4Provider.invoke(JUnit4Provider.java:113)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at
sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57)
at
sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:616)
at
org.apache.maven.surefire.util.ReflectionUtils.invokeMethodWithArray(ReflectionUtils.java:189)
at
org.apache.maven.surefire.booter.ProviderFactory$ProviderProxy.invoke(ProviderFactory.java:165)
at
org.apache.maven.surefire.booter.ProviderFactory.invokeProvider(ProviderFactory.java:85)
at
org.apache.maven.surefire.booter.ForkedBooter.runSuitesInProcess(ForkedBooter.java:103)
at
org.apache.maven.surefire.booter.ForkedBooter.main(ForkedBooter.java:74)
Configuring remote approach does not require any special rule because you (or System like Maven ) is the responsible of starting and stopping the server. This mode is used in deployment tests where you are testing your application on real environment.
Configuring MongoDb Connection
Next step is configuring Mongodb rule in charge of maintaining MongoDb database into known state by inserting and deleting defined datasets. You must register MongoDbRule JUnit rule class, which requires a configuration parameter with information like host, port or database name.
To make developer's life easier and code more readable, a fluent interface can be used to create these configuration objects. Two different kind of configuration builders exist.
The first one is for configuring a connection to in-memory jmockmongo server. Default connection values are:
Host 0.0.0.0 Port 2307
: Default In-Memory Configuration Values
Notice that these values are the default ones of jmockmongo project, so if you are thinking to use jmockmongo , no modifications are required.
import static com.lordofthejars.nosqlunit.mongodb.InMemoryMongoDbConfigurationBuilder.inMemoryMongoDb;
@Rule
public MongoDbRule remoteMongoDbRule = new MongoDbRule(inMemoryMongoDb().databaseName("test").build());
The second one is for configuring a connection to remote MongoDb server. Default values are:
Host localhost Port 27017 Authentication No authentication parameters.
: Default Managed Configuration Values
import static com.lordofthejars.nosqlunit.mongodb.MongoDbConfigurationBuilder.mongoDb;
@Rule
public MongoDbRule remoteMongoDbRule = new MongoDbRule(mongoDb().databaseName("test").build());
import static com.lordofthejars.nosqlunit.mongodb.MongoDbConfigurationBuilder.mongoDb;
@Rule
public MongoDbRule remoteMongoDbRule = new MongoDbRule(mongoDb().databaseName("test").host("my_remote_host").build());
Complete Example
Consider a library application, which apart from multiple operations, it allow us to add new books to system. Our model is as simple as:
public class Book {
private String title;
private int numberOfPages;
public Book(String title, int numberOfPages) {
super();
this.title = title;
this.numberOfPages = numberOfPages;
}
public void setTitle(String title) {
this.title = title;
}
public void setNumberOfPages(int numberOfPages) {
this.numberOfPages = numberOfPages;
}
public String getTitle() {
return title;
}
public int getNumberOfPages() {
return numberOfPages;
}
}
Next business class is the responsible of managing access to MongoDb server:
public class BookManager {
private static final Logger LOGGER = LoggerFactory.getLogger(BookManager.class);
private static final MongoDbBookConverter MONGO_DB_BOOK_CONVERTER = new MongoDbBookConverter();
private static final DbObjectBookConverter DB_OBJECT_BOOK_CONVERTER = new DbObjectBookConverter();
private DBCollection booksCollection;
public BookManager(DBCollection booksCollection) {
this.booksCollection = booksCollection;
}
public void create(Book book) {
DBObject dbObject = MONGO_DB_BOOK_CONVERTER.convert(book);
booksCollection.insert(dbObject);
}
}
And now it is time for testing. In next test we are going to validate that a book is inserted correctly into database.
package com.lordofthejars.nosqlunit.demo.mongodb;
public class WhenANewBookIsCreated {
@ClassRule
public static ManagedMongoDb managedMongoDb = newManagedMongoDbRule().mongodPath("/opt/mongo").build();
@Rule
public MongoDbRule remoteMongoDbRule = new MongoDbRule(mongoDb().databaseName("test").build());
@Test
@UsingDataSet(locations="initialData.json", loadStrategy=LoadStrategyEnum.CLEAN_INSERT)
@ShouldMatchDataSet(location="expectedData.json")
public void book_should_be_inserted_into_repository() {
BookManager bookManager = new BookManager(MongoDbUtil.getCollection(Book.class.getSimpleName()));
Book book = new Book("The Lord Of The Rings", 1299);
bookManager.create(book);
}
}
In previous test we have defined that
MongoDb will be managed by test by starting an instance of server
located at /opt/mongo . Moreover we are setting an
initial dataset in file initialData.json
located at classpath
com/lordofthejars/nosqlunit/demo/mongodb/initialData.json and expected
dataset called expectedData.json .
{
"Book":
[
{"title":"The Hobbit","numberOfPages":293}
]
}
{
"Book":
[
{"title":"The Hobbit","numberOfPages":293},
{"title":"The Lord Of The Rings","numberOfPages":1299}
]
}
You can watch full example at github .
Neo4j Engine
Neo4j
Neo4j is a high-performance, NoSQL graph database with all the features of a mature and robust database.
NoSQLUnit supports Neo4j by using next classes:
In Memory com.lordofthejars.nosqlunit.neo4j.InMemoryNeo4j Embedded com.lordofthejars.nosqlunit.neo4j.EmbeddedNeo4j Managed Wrapping com.lordofthejars.nosqlunit.neo4j.ManagedWrappingNeoServer Managed com.lordofthejars.nosqlunit.neo4j.ManagedNeoServer
: Lifecycle Management Rules
NoSQLUnit Management com.lordofthejars.nosqlunit.neo4j.Neo4jRule
: Manager Rule
Maven Setup
To use NoSQLUnit with Neo4j you only need to add next dependency:
<dependency>
<groupId>com.lordofthejars</groupId>
<artifactId>nosqlunit-neo4j</artifactId>
<version>${version.nosqlunit}</version>
</dependency>
Dataset Format
Default dataset file format in Neo4j module is GraphML . GraphML is a comprehensive and easy-to-use file format for graphs.
Datasets must have next format :
<?xml version="1.0" encoding="UTF-8"?>
<graphml xmlns="http://graphml.graphdrawing.org/xmlns">
<key id="attr1" for="edge" attr.name="attr1" attr.type="float"/>
<key id="attr2" for="node" attr.name="attr2" attr.type="string"/>
<graph id="G" edgedefault="directed">
<node id="1">
<data key="attr2">value1</data>
</node>
<node id="2">
<data key="attr2">value2</data>
</node>
<edge id="7" source="1" target="2" label="label1">
<data key="attr1">float</data>
</edge>
</graph>
</graphml>
where:
-
graphml : the root element of the GraphML document
-
key : description for graph element properties, you must define if property type is for nodes or relationships, name, and type of element. In our case string, int, long, float, double and boolean are supported.
-
graph : the beginning of the graph representation. In our case only one level of graphs are supported. Inner graphs will be ignored.
-
node : the beginning of a vertex representation. Please note that id 0 is reserved for reference node, so cannot be used as id.
-
edge : the beginning of an edge representation. Source and target attributes are filled with node id. If you want to link with reference node, use a 0 which is the id of root node. Note that label attribute is not in defined in standard definition of GraphML specification; GraphML supports adding new attributes to all GrpahML elements, and label attribute has been added to facilitate the creation of edge labels.
-
data : the key/value data associated with a graph element. Data value will be validated against type defined in key element.
Getting Started
Lifecycle Management Strategy
First step is defining which lifecycle management strategy is required for your tests. Depending on kind of test you are implementing (unit test, integration test, deployment test, ...) you will require an in-memory approach, embedded approach, managed approach or remote approach.
In-memory Lifecycle
To configure in-memory approach you should only instantiate next rule :
import static com.lordofthejars.nosqlunit.neo4j.InMemoryNeo4j.InMemoryNeo4jRuleBuilder.newInMemoryNeo4j;
@ClassRule
public static InMemoryNeo4j inMemoryNeo4j = newInMemoryNeo4j().build();
Embedded Lifecycle
To configure embedded approach you should only instantiate next rule :
import static com.lordofthejars.nosqlunit.neo4j.EmbeddedNeo4j.EmbeddedNeo4jRuleBuilder.newEmbeddedNeo4jRule;
@ClassRule
public static EmbeddedNeo4j embeddedNeo4j = newEmbeddedNeo4jRule().build();
By default embedded Neo4j rule uses next default values:
Target path This is the directory where Neo4j server is started and is target/neo4j-temp .
: Default Embedded Values
Managed Lifecycle
To configure managed way, two possible approaches can be used:
The first one is using an embedded database wrapped by a server . This is a way to give an embedded database visibility through network (internally we are creating a WrappingNeoServerBootstrapper instance) :
import static com.lordofthejars.nosqlunit.neo4j.ManagedWrappingNeoServer.ManagedWrappingNeoServerRuleBuilder.newWrappingNeoServerNeo4jRule;
@ClassRule
public static ManagedWrappingNeoServer managedWrappingNeoServer = newWrappingNeoServerNeo4jRule().port(8888).build();
By default wrapped managed Neo4j rule uses next default values, but can be configured programmatically as shown in previous example :
Target path The directory where Neo4j server is started and is target/neo4j-temp .
Port Where server is listening incoming messages is 7474.
: Default Wrapped Values
The second strategy is starting and stopping an already installed server on executing machine, by calling start and stop command lines. Next rule should be registered:
import static com.lordofthejars.nosqlunit.neo4j.ManagedNeoServer.Neo4jServerRuleBuilder.newManagedNeo4jServerRule;
@ClassRule
public static ManagedNeoServer managedNeoServer = newManagedNeo4jServerRule().neo4jPath("/opt/neo4j").build();
By default managed Neo4j rule uses next default values, but can be configured programmatically as shown in previous example :
Target path This is the directory where Neo4j process will be started and by default is target/neo4j-temp .
Port Where server is listening incoming messages is 7474.
Neo4jPath Neo4j installation directory which by default is retrieved from NEO4J_HOME system environment variable.
: Default Managed Values
Warning
Versions prior to Neo4j 1.8, port cannot be configured from command line, and port should be changed manually in
conf/neo4j-server.properties. Although this restriction, if you have configured Neo4j to run through a different port, it should be specified too in ManagedNeoServer rule.
Remote Lifecycle
Configuring remote approach does not require any special rule because you (or System like Maven ) is the responsible of starting and stopping the server. This mode is used in deployment tests where you are testing your application on real environment.
Configuring Neo4j Connection
Next step is configuring Neo4j rule in charge of maintaining Neo4j graph into known state by inserting and deleting defined datasets. You must register Neo4jRule JUnit rule class, which requires a configuration parameter with information like host, port, uri or target directory.
To make developer's life easier and code more readable, a fluent interface can be used to create these configuration objects. Two different kind of configuration builders exist.
In-Memory/Embedded Connection
The first one is for configuring a connection to in-memory/embedded Neo4j .
import static com.lordofthejars.nosqlunit.neo4j.EmbeddedNeoServerConfigurationBuilder.newEmbeddedNeoServerConfiguration;
@Rule
public Neo4jRule neo4jRule = new Neo4jRule(newEmbeddedNeoServerConfiguration().build());
If you are only registering one embedded Neo4j instance like previous
example , calling build is enough. If
you are using more than one Neo4j embedded connection like explained
in Simultaneous Engine section,
targetPath shall be provided by using buildFromTargetPath method.
If you are using in-memory approach mixed with embedded approach, target
path for in-memory instance can be found at
InMemoryNeo4j.INMEMORY_NEO4J_TARGET_PATH variable.
Remote Connection
The second one is for configuring a connection to remote Neo4j server (it is irrelevant at this level if it is wrapped or not). Default values are:
Connection URI http://localhost:7474/db/data Authentication No authentication parameters.
: Default Managed Connection Values
import static com.lordofthejars.nosqlunit.neo4j.ManagedNeoServerConfigurationBuilder.newManagedNeoServerConfiguration;
@Rule
public Neo4jRule neo4jRule = new Neo4jRule(newManagedNeoServerConfiguration().build());
Verifying Graph
@ShouldMatchDataSet is also supported for Neo4j graphs but we should keep in mind some considerations.
To compare two graphs, stored graph is exported into GraphML format and then is compared with expected GraphML using XmlUnit framework. This approach implies two aspects to be considered, the first one is that although your graph does not contains any connection to reference node, reference node will appear too with the form ( <node id="0"></node> ). The other aspect is that id's are Neo4j's internal id, so when you write the expected file, remember to follow the same id strategy followed by Neo4j so id attribute of each node could be matched correctly with generated output. Inserted nodes' id starts from 1 (0 is reserved for reference node), meanwhile edges starts from 0.
This way to compare graphs may change in future (although this strategy will be always supported).
As I have noted in verification section I find that using @ShouldMatchDataSet is a bad approach during testing because test readibility is affected negatively. So as general guide, my advice is to try to avoid using @ShouldMatchDataSet in your tests as much as possible.
Full Example
To show how to use NoSQLUnit with Neo4j , we are going to create a very simple application that counts Neo's friends.
MatrixManager is the business class responsible of inserting new friends and counting the number of Neo's friends.
public class MatrixManager {
public enum RelTypes implements RelationshipType {
NEO_NODE, KNOWS, CODED_BY
}
private GraphDatabaseService graphDb;
public MatrixManager(GraphDatabaseService graphDatabaseService) {
this.graphDb = graphDatabaseService;
}
public int countNeoFriends() {
Node neoNode = getNeoNode();
Traverser friendsTraverser = getFriends(neoNode);
return friendsTraverser.getAllNodes().size();
}
public void addNeoFriend(String name, int age) {
Transaction tx = this.graphDb.beginTx();
try {
Node friend = this.graphDb.createNode();
friend.setProperty("name", name);
Relationship relationship = getNeoNode().createRelationshipTo(friend, RelTypes.KNOWS);
relationship.setProperty("age", age);
tx.success();
} finally {
tx.finish();
}
}
private static Traverser getFriends(final Node person) {
return person.traverse(Order.BREADTH_FIRST, StopEvaluator.END_OF_GRAPH, ReturnableEvaluator.ALL_BUT_START_NODE,
RelTypes.KNOWS, Direction.OUTGOING);
}
private Node getNeoNode() {
return graphDb.getReferenceNode().getSingleRelationship(RelTypes.NEO_NODE, Direction.OUTGOING).getEndNode();
}
}
And now one unit test and one integration test is written:
For unit test we are going to use embedded approach:
import static org.junit.Assert.assertThat;
import static org.hamcrest.CoreMatchers.is;
import static com.lordofthejars.nosqlunit.neo4j.EmbeddedNeo4j.EmbeddedNeo4jRuleBuilder.newEmbeddedNeo4jRule;
import static com.lordofthejars.nosqlunit.neo4j.EmbeddedNeoServerConfigurationBuilder.newEmbeddedNeoServerConfiguration;
import javax.inject.Inject;
import org.junit.ClassRule;
import org.junit.Rule;
import org.junit.Test;
import org.neo4j.graphdb.GraphDatabaseService;
import com.lordofthejars.nosqlunit.annotation.UsingDataSet;
import com.lordofthejars.nosqlunit.core.LoadStrategyEnum;
import com.lordofthejars.nosqlunit.neo4j.EmbeddedNeo4j;
import com.lordofthejars.nosqlunit.neo4j.Neo4jRule;
public class WhenNeoFriendsAreRequired {
@ClassRule
public static EmbeddedNeo4j embeddedNeo4j = newEmbeddedNeo4jRule().build();
@Rule
public Neo4jRule neo4jRule = new Neo4jRule(newEmbeddedNeoServerConfiguration().build(), this);
@Inject
private GraphDatabaseService graphDatabaseService;
@Test
@UsingDataSet(locations="matrix.xml", loadStrategy=LoadStrategyEnum.CLEAN_INSERT)
public void all_direct_and_inderectly_friends_should_be_counted() {
MatrixManager matrixManager = new MatrixManager(graphDatabaseService);
int countNeoFriends = matrixManager.countNeoFriends();
assertThat(countNeoFriends, is(3));
}
}
And as integration test , the managed one:
import static com.lordofthejars.nosqlunit.neo4j.ManagedWrappingNeoServer.ManagedWrappingNeoServerRuleBuilder.newWrappingNeoServerNeo4jRule;
import static com.lordofthejars.nosqlunit.neo4j.ManagedNeoServerConfigurationBuilder.newManagedNeoServerConfiguration;
import javax.inject.Inject;
import org.junit.ClassRule;
import org.junit.Rule;
import org.junit.Test;
import org.neo4j.graphdb.GraphDatabaseService;
import com.lordofthejars.nosqlunit.annotation.ShouldMatchDataSet;
import com.lordofthejars.nosqlunit.annotation.UsingDataSet;
import com.lordofthejars.nosqlunit.core.LoadStrategyEnum;
import com.lordofthejars.nosqlunit.neo4j.ManagedWrappingNeoServer;
import com.lordofthejars.nosqlunit.neo4j.Neo4jRule;
public class WhenNeoMeetsANewFriend {
@ClassRule
public static ManagedWrappingNeoServer managedWrappingNeoServer = newWrappingNeoServerNeo4jRule().build();
@Rule
public Neo4jRule neo4jRule = new Neo4jRule(newManagedNeoServerConfiguration().build(), this);
@Inject
private GraphDatabaseService graphDatabaseService;
@Test
@UsingDataSet(locations="matrix.xml", loadStrategy=LoadStrategyEnum.CLEAN_INSERT)
@ShouldMatchDataSet(location="expected-matrix.xml")
public void friend_should_be_related_into_neo_graph() {
MatrixManager matrixManager = new MatrixManager(graphDatabaseService);
matrixManager.addNeoFriend("The Oracle", 4);
}
}
Note that in both cases we are using the same dataset as initial state, which looks like:
<graphml xmlns="http://graphml.graphdrawing.org/xmlns"
xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
xsi:schemaLocation="http://graphml.graphdrawing.org/xmlns
http://graphml.graphdrawing.org/xmlns/1.0/graphml.xsd">
<key id="name" for="node" attr.name="name" attr.type="string"/>
<key id="age" for="edge" attr.name="age" attr.type="int"/>
<graph id="G" edgedefault="directed">
<node id="1">
<data key="name">Thomas Anderson</data>
</node>
<node id="2">
<data key="name">Trinity</data>
</node>
<node id="3">
<data key="name">Morpheus</data>
</node>
<node id="4">
<data key="name">Agent Smith</data>
</node>
<node id="5">
<data key="name">The Architect</data>
</node>
<edge id="1" source="0" target="1" label="NEO_NODE">
</edge>
<edge id="2" source="1" target="2" label="KNOWS">
<data key="age">3</data>
</edge>
<edge id="3" source="1" target="3" label="KNOWS">
<data key="age">5</data>
</edge>
<edge id="4" source="2" target="3" label="KNOWS">
<data key="age">18</data>
</edge>
<edge id="5" source="3" target="4" label="KNOWS">
<data key="age">20</data>
</edge>
<edge id="6" source="4" target="5" label="CODED_BY">
<data key="age">20</data>
</edge>
</graph>
</graphml>
Cassandra Engine
Cassandra
Cassandra is a BigTable data model running on an Amazon Dynamo-like infrastructure.
NoSQLUnit supports Cassandra by using next classes:
Embedded com.lordofthejars.nosqlunit.cassandra.EmbeddedCassandra Managed com.lordofthejars.nosqlunit.cassandra.ManagedCassandra
: Lifecycle Management Rules
NoSQLUnit Management com.lordofthejars.nosqlunit.cassandra.CassandraRule
: Manager Rule
Maven Setup
To use NoSQLUnit with Cassandra you only need to add next dependency:
<dependency>
<groupId>com.lordofthejars</groupId>
<artifactId>nosqlunit-cassandra</artifactId>
<version>${version.nosqlunit}</version>
</dependency>
Dataset Format
Default dataset file format in Cassandra module is json. To make compatible NoSQLUnit with Cassandra-Unit file format, DataLoader of Cassandra-Unit project is used, so same json format file is used.
Datasets must have next format :
{
"name" : "",
"replicationFactor" : "",
"strategy" : "",
"columnFamilies" : [{
"name" : "",
"type" : "",
"keyType" : "",
"comparatorType" : "",
"subComparatorType" : "",
"defaultColumnValueType" : "",
"comment" : "",
"compactionStrategy" : "",
"compactionStrategyOptions" : [{
"name" : "",
"value": ""
}],
"gcGraceSeconds" : "",
"maxCompactionThreshold" : "",
"minCompactionThreshold" : "",
"readRepairChance" : "",
"replicationOnWrite" : "",
"columnsMetadata" : [{
"name" : "",
"validationClass : "",
"indexType" : "",
"indexName" : ""
},
...
]
"rows" : [{
"key" : "",
"columns" : [{
"name" : "",
"value" : ""
},
...
],
...
// OR
...
"superColumns" : [{
"name" : "",
"columns" : [{
"name" : "",
"value" : ""
},
...
]
},
...
]
},
...
]
},
...
]
}
See Cassandra-Unit Dataset format for more information.
Getting Started
Lifecycle Management Strategy
First step is defining which lifecycle management strategy is required for your tests. Depending on kind of test you are implementing (unit test, integration test, deployment test, ...) you will require an embedded approach, managed approach or remote approach.
Embedded Lifecycle
To configure embedded approach you should only instantiate next rule :
@ClassRule
public static EmbeddedCassandra embeddedCassandraRule = newEmbeddedCassandraRule().build();
By default embedded Cassandra rule uses next default values:
Target path This is the directory where Cassandra server is started and is target/cassandra-temp .
Cassandra Configuration File Location of yaml configuration file. By default a configuration file is provided with correct default parameters.
Host localhost
Port By default port used is 9171. Port cannot be configured, and cannot be changed if you provide an alternative Cassandra Configuration File.
: Default Embedded Values
Managed Lifecycle
To configure managed approach you should only instantiate next rule :
@ClassRule
public static ManagedCassandra managedCassandra = newManagedCassandraRule().build();
By default managed Cassandra rule uses next default values but can be configured programmatically:
Target path This is the directory where Cassandra server is started and is target/cassandra-temp .
CassandraPath Cassandra installation directory which by default is retrieved from CASSANDRA_HOME system environment variable.
Port By default port used is 9160. If port is changed in Cassandra configuration file, this port should be configured too here.
: Default Managed Values
Warning
To start Cassandra java.home must be set. Normally this variable is already configured, you would need to do nothing.
Remote Lifecycle
Configuring remote approach does not require any special rule because you (or System like Maven ) is the responsible of starting and stopping the server. This mode is used in deployment tests where you are testing your application on real environment.
Configuring Cassandra Connection
Next step is configuring Cassandra rule in charge of maintaining Cassandra graph into known state by inserting and deleting defined datasets. You must register CassandraRule JUnit rule class, which requires a configuration parameter with information like host, port, or cluster name.
To make developer's life easier and code more readable, a fluent interface can be used to create these configuration objects. Three different kind of configuration builders exist.
Embedded Connection
The first one is for configuring a connection to embedded Cassandra .
import static com.lordofthejars.nosqlunit.cassandra.EmbeddedCassandraConfigurationBuilder.newEmbeddedCassandraConfiguration;
@Rule
public CassandraRule cassandraRule = new CassandraRule(newEmbeddedCassandraConfiguration().clusterName("Test Cluster").build());
Host and port parameters are already configured.
Managed Connection
The first one is for configuring a connection to managed Cassandra .
import static com.lordofthejars.nosqlunit.cassandra.ManagedCassandraConfigurationBuilder.newManagedCassandraConfiguration;
@Rule
public CassandraRule cassandraRule = new CassandraRule(newManagedCassandraConfiguration().clusterName("Test Cluster").build());
Host and port parameters are already configured with default parameters of managed lifecycle. If port is changed, this class provides a method to set it.
Remote Connection
Configuring a connection to remote Cassandra .
import static com.lordofthejars.nosqlunit.cassandra.RemoteCassandraConfigurationBuilder.newRemoteCassandraConfiguration;
@Rule
public CassandraRule cassandraRule = new CassandraRule(newRemoteCassandraConfiguration().host("192.168.1.1").clusterName("Test Cluster").build());
Port parameter is already configured with default parameter of managed lifecycle. If port is changed, this class provides a method to set it. Note that host parameter must be specified in this case.
Verifying Data
@ShouldMatchDataSet is also supported for Cassandra data but we should keep in mind some considerations.
Warning
In NoSQLUnit , expectations can only be used over data, not over configuration parameters, so for example fields set in dataset file like compactionStrategy, gcGraceSeconds or maxCompactionThreshold are not used. Maybe in future will be supported but for now only data (keyspace, columnfamilyname, columns, supercolumns, ...) are supported.
Full Example
To show how to use NoSQLUnit with Cassandra , we are going to create a very simple application.
PersonManager is the business class responsible of getting and updating person's car.
public class PersonManager {
private ColumnFamilyTemplate<String, String> template;
public PersonManager(String clusterName, String keyspaceName, String host) {
Cluster cluster = HFactory.getOrCreateCluster(clusterName, host);
Keyspace keyspace = HFactory.createKeyspace(keyspaceName, cluster);
template = new ThriftColumnFamilyTemplate<String, String>(keyspace,
"personFamilyName",
StringSerializer.get(),
StringSerializer.get());
}
public String getCarByPersonName(String name) {
ColumnFamilyResult<String, String> queryColumns = template.queryColumns(name);
return queryColumns.getString("car");
}
public void updateCarByPersonName(String name, String car) {
ColumnFamilyUpdater<String, String> createUpdater = template.createUpdater(name);
createUpdater.setString("car", car);
template.update(createUpdater);
}
}
And now one unit test and one integration test is written:
For unit test we are going to use embedded approach:
import static org.junit.Assert.assertThat;
import static org.hamcrest.CoreMatchers.is;
import static com.lordofthejars.nosqlunit.cassandra.EmbeddedCassandra.EmbeddedCassandraRuleBuilder.newEmbeddedCassandraRule;
import static com.lordofthejars.nosqlunit.cassandra.EmbeddedCassandraConfigurationBuilder.newEmbeddedCassandraConfiguration;
import org.junit.ClassRule;
import org.junit.Rule;
import org.junit.Test;
import com.lordofthejars.nosqlunit.annotation.UsingDataSet;
import com.lordofthejars.nosqlunit.cassandra.CassandraRule;
import com.lordofthejars.nosqlunit.cassandra.EmbeddedCassandra;
import com.lordofthejars.nosqlunit.core.LoadStrategyEnum;
public class WhenPersonWantsToKnowItsCar {
@ClassRule
public static EmbeddedCassandra embeddedCassandraRule = newEmbeddedCassandraRule().build();
@Rule
public CassandraRule cassandraRule = new CassandraRule(newEmbeddedCassandraConfiguration().clusterName("Test Cluster").build());
@Test
@UsingDataSet(locations="persons.json", loadStrategy=LoadStrategyEnum.CLEAN_INSERT)
public void car_should_be_returned() {
PersonManager personManager = new PersonManager("Test Cluster", "persons", "localhost:9171");
String car = personManager.getCarByPersonName("mary");
assertThat(car, is("ford"));
}
}
And as integration test , the managed one:
import static com.lordofthejars.nosqlunit.cassandra.ManagedCassandraConfigurationBuilder.newManagedCassandraConfiguration;
import static com.lordofthejars.nosqlunit.cassandra.ManagedCassandra.ManagedCassandraRuleBuilder.newManagedCassandraRule;
import org.junit.ClassRule;
import org.junit.Rule;
import org.junit.Test;
import com.lordofthejars.nosqlunit.annotation.ShouldMatchDataSet;
import com.lordofthejars.nosqlunit.annotation.UsingDataSet;
import com.lordofthejars.nosqlunit.cassandra.CassandraRule;
import com.lordofthejars.nosqlunit.cassandra.ManagedCassandra;
import com.lordofthejars.nosqlunit.core.LoadStrategyEnum;
public class WhenPersonWantsToUpdateItsCar {
static {
System.setProperty("CASSANDRA_HOME", "/opt/cassandra");
}
@ClassRule
public static ManagedCassandra managedCassandra = newManagedCassandraRule().build();
@Rule
public CassandraRule cassandraRule = new CassandraRule(newManagedCassandraConfiguration().clusterName("Test Cluster").build());
@Test
@UsingDataSet(locations="persons.json", loadStrategy=LoadStrategyEnum.CLEAN_INSERT)
@ShouldMatchDataSet(location="expected-persons.json")
public void new_car_should_be_updated() {
PersonManager personManager = new PersonManager("Test Cluster", "persons", "localhost:9171");
personManager.updateCarByPersonName("john", "opel");
}
}
Note that in both cases we are using the same dataset as initial state, which looks like:
{
"name" : "persons",
"columnFamilies" : [{
"name" : "personFamilyName",
"keyType" : "UTF8Type",
"defaultColumnValueType" : "UTF8Type",
"comparatorType" : "UTF8Type",
"rows" : [{
"key" : "john",
"columns" : [{
"name" : "age",
"value" : "22"
},
{
"name" : "car",
"value" : "toyota"
}]
},
{
"key" : "mary",
"columns" : [{
"name" : "age",
"value" : "33"
},
{
"name" : "car",
"value" : "ford"
}]
}]
}]
}
Redis Engine
Redis
Redis is an open source, advanced key-value store. It is often referred to as a data structure server since keys can contain strings, hashes, lists, sets and sorted sets.
NoSQLUnit supports Redis by using next classes:
Embedded com.lordofthejars.nosqlunit.redis.EmbeddedRedis Managed com.lordofthejars.nosqlunit.redis.ManagedRedis
: Lifecycle Management Rules
NoSQLUnit Management com.lordofthejars.nosqlunit.redis.RedisRule
: Manager Rule
Maven Setup
To use NoSQLUnit with Redis you only need to add next dependency:
<dependency>
<groupId>com.lordofthejars</groupId>
<artifactId>nosqlunit-redis</artifactId>
<version>${version.nosqlunit}</version>
</dependency>
Dataset Format
Default dataset file format in Redis module is json.
Datasets must have next format :
{
"data":[
{"simple": [
{
"key":"key1",
"value":"value1"
}
]
},
{"list": [{
"key":"key3",
"values":[
{"value":"value3"},
{"value":"value4"}
]
}]
},
{"sortset": [{
"key":"key4",
"values":[
{"score":2, "value":"value5" },{"score":3, "value":1 }, {"score":1, "value":"value6" }]
}]
},
{"hash": [
{
"key":"user",
"values":[
{"field":"name", "value":"alex"},
{"field":"password", "value":"alex"}
]
}
]
},
{"set":[{
"key":"key3",
"values":[
{"value":"value3"},
{"value":"value4"}
]
}]
}
]
}
Root element must be called data , and then depending on kind of structured data we need to store, one or more of next elements should appear. Note that key field is used to set the key of the element, and value field is used to set a value.
-
simple : In case we want to store simple key/value elements. This element will contain an array of key/value entries.
-
list : In case we want to store a key with a list of values. This element contain a key field for key name and values field with an array of values.
-
set In case we want to store a key within a set (no duplicates allowed). Structure is the same as list element.
-
sortset : In case we want to store a key within a sorted set. This element contain the key, and an array of values, which each one, apart from value field, also contain score field of type Number, to set the order into sorted set.
-
hash : In case we want to store a key within a map of field/value. In this case field element set the field name, and value set the value of that field.
Getting Started
Lifecycle Management Strategy
First step is defining which lifecycle management strategy is required for your tests. Depending on kind of test you are implementing (unit test, integration test, deployment test, ...) you will require an embedded approach, managed approach or remote approach.
Embedded Lifecycle
To configure embedded approach you should only instantiate next rule :
@ClassRule
public static EmbeddedRedis embeddedRedis = newEmbeddedRedisRule().build();
By default managed Redis rule uses next default values but can be configured programmatically:
Target path This is the directory where Redis embedded instance is started and is target/redis-test-data/impermanent-db .
: Default Embedded Values
Note that target path is only used as a configuration parameter to allow multiple instances of embedded in-memory Redis engine.
For more information about embedded in-memory Redis take a tour to section: Embedded In-Memory Redis
Managed Lifecycle
To configure managed approach you should only instantiate next rule :
@ClassRule
public static ManagedRedis managedRedis = newManagedRedisRule().redisPath("/opt/redis-2.4.16").build();
By default managed Redis rule uses next default values but can be configured programmatically:
Target path This is the directory where Redis server is started and is target/redis-temp .
RedisPath Cassandra installation directory which by default is retrieved from REDIS_HOME system environment variable.
Port By default port used is 6379. If port is changed in Redis configuration file, this port should be configured too here.
Configuration File By default Redis can work with no configuration file, it uses default values, but if we need to start Redis with an specific configuration file located in any directory file path should be set.
: Default Managed Values
Remote Lifecycle
Configuring remote approach does not require any special rule because you (or System like Maven ) is the responsible of starting and stopping the server. This mode is used in deployment tests where you are testing your application on real environment.
Configuring Redis Connection
Next step is configuring Redis rule in charge of maintaining Redis store into known state by inserting and deleting defined datasets. You must register RedisRule JUnit rule class, which requires a configuration parameter with information like host, port, or cluster name.
To make developer's life easier and code more readable, a fluent interface can be used to create these configuration objects. Three different kind of configuration builders exist.
Embedded Connection
The first one is for configuring an embedded connection to managed Redis .
import static com.lordofthejars.nosqlunit.redis.RedisRule.RedisRuleBuilder.newRedisRule;
@Rule
public RedisRule redisRule = newRedisRule().defaultEmbeddedRedis();
Managed Connection
Configuring a connection to managed Redis .
import static com.lordofthejars.nosqlunit.redis.ManagedRedisConfigurationBuilder.newManagedRedisConfiguration;
@Rule
public RedisRule redisRule = new RedisRule(newManagedRedisConfiguration().build());
Host and port parameters are already configured with default parameters of managed lifecycle. If port is changed, this class provides a method to set it.
Remote Connection
Configuring a connection to remote Redis .
import static com.lordofthejars.nosqlunit.redis.RemoteRedisConfigurationBuilder.newRemoteRedisConfiguration;
@Rule
public RedisRule redisRule = new RedisRule(newRemoteRedisConfiguration().host("192.168.1.1").build());
Port parameter is already configured with default parameter of managed lifecycle. If port is changed, this class provides a method to set it. Note that host parameter must be specified in this case.
Shard Connection
Redis connection also be configured as shard using ShardedJedis capabilities.
import static com.lordofthejars.nosqlunit.redis.RemoteRedisConfigurationBuilder.newRemoteRedisConfiguration;
@Rule
public RedisRule redisRule = new RedisRule(newShardedRedisConfiguration()
.shard(host("127.0.0.1"), port(ManagedRedis.DEFAULT_PORT))
.password("a")
.timeout(1000)
.weight(1000)
.shard(host("127.0.0.1"), port(ManagedRedis.DEFAULT_PORT + 1))
.password("b")
.timeout(3000)
.weight(3000)
.build(););
Note that only host and port is mandatory, the other ones uses default values.
-
password : In case repository is protected with password this attribute is used as password. Default values is null.
-
timeout : Timeout for shard. By default timeout is set to 2 seconds.
-
weight : The weight of that shard over the other ones. By default is 1.
Verifying Data
@ShouldMatchDataSet is also supported for Redis engine.
Full Example
To show how to use NoSQLUnit with Redis , we are going to create a very simple application.
BookManager is the business class responsible of inserting new books and finding books by their title.
public class BookManager {
private static final String TITLE_FIELD_NAME = "title";
private static final String NUMBER_OF_PAGES = "numberOfPages";
private Jedis jedis;
public BookManager(Jedis jedis) {
this.jedis = jedis;
}
public void insertBook(Book book) {
Map<String, String> fields = new HashMap<String, String>();
fields.put(TITLE_FIELD_NAME, book.getTitle());
fields.put(NUMBER_OF_PAGES, Integer.toString(book.getNumberOfPages()));
jedis.hmset(book.getTitle(), fields);
}
public Book findBookByTitle(String title) {
Map<String, String> fields = jedis.hgetAll(title);
return new Book(fields.get(TITLE_FIELD_NAME), Integer.parseInt(fields.get(NUMBER_OF_PAGES)));
}
}
And now one integration test is written:
import static com.lordofthejars.nosqlunit.redis.RedisRule.RedisRuleBuilder.newRedisRule;
import static com.lordofthejars.nosqlunit.redis.ManagedRedis.ManagedRedisRuleBuilder.newManagedRedisRule;
import static org.junit.Assert.assertThat;
import static org.hamcrest.CoreMatchers.is;
import org.junit.ClassRule;
import org.junit.Rule;
import org.junit.Test;
import redis.clients.jedis.Jedis;
import com.lordofthejars.nosqlunit.annotation.UsingDataSet;
import com.lordofthejars.nosqlunit.core.LoadStrategyEnum;
import com.lordofthejars.nosqlunit.demo.model.Book;
import com.lordofthejars.nosqlunit.redis.ManagedRedis;
import com.lordofthejars.nosqlunit.redis.RedisRule;
public class WhenYouFindABook {
static {
System.setProperty("REDIS_HOME", "/opt/redis-2.4.16");
}
@ClassRule
public static ManagedRedis managedRedis = newManagedRedisRule().build();
@Rule
public RedisRule redisRule = newRedisRule().defaultManagedRedis();
@Test
@UsingDataSet(locations="book.json", loadStrategy=LoadStrategyEnum.CLEAN_INSERT)
public void book_should_be_returned_if_title_is_in_database() {
BookManager bookManager = new BookManager(new Jedis("localhost"));
Book findBook = bookManager.findBookByTitle("The Hobbit");
assertThat(findBook, is(new Book("The Hobbit", 293)));
}
}
And dataset used is:
{
"data":[
{"hash": [
{
"key":"The Hobbit",
"values":[
{"field":"title", "value":"The Hobbit"},
{"field":"numberOfPages", "value":"293"}
]
}
]
}
]
}
HBase Engine
HBase
Apache HBase is an open-source, distributed, versioned, column-oriented store.
NoSQLUnit supports HBase by using next classes:
Embedded com.lordofthejars.nosqlunit.hbase.EmbeddedHBase Managed com.lordofthejars.nosqlunit.hbase.ManagedHBase
: Lifecycle Management Rules
NoSQLUnit Management com.lordofthejars.nosqlunit.hbase.HBaseRule
: Manager Rule
Maven Setup
To use NoSQLUnit with HBase you only need to add next dependency:
<dependency>
<groupId>com.lordofthejars</groupId>
<artifactId>nosqlunit-hbase</artifactId>
<version>${version.nosqlunit}</version>
</dependency>
Dataset Format
Default dataset file format in HBase module is json. Dataset in HBase is the same used by Cassandra-Unit but not all fields are supported. Only fields available in TSV HBase application can be set into dataset.
So as summary datasets must have next format :
{
"name" : "tablename",
"columnFamilies" : [{
"name" : "columnFamilyName",
"rows" : [{
"key" : "key1",
"columns" : [{
"name" : "columnName",
"value" : "columnValue"
},
...
]
},
...
]
},
...
]
}
Getting Started
Lifecycle Management Strategy
First step is defining which lifecycle management strategy is required for your tests. Depending on kind of test you are implementing (unit test, integration test, deployment test, ...) you will require an embedded approach, managed approach or remote approach.
Embedded Lifecycle
To configure embedded approach you should only instantiate next rule :
@ClassRule
public static EmbeddedHBase embeddedHBase = newEmbeddedHBaseRule().build();
By default embedded Embedded rule uses HBaseTestingUtility default values:
Target path This is the directory where HBase stores data and is target/data .
Host localhost
Port By default port used is 60000.
File Permissions Depending on your umask configuration, HBaseTestingUtility will create some directories that will not be accessible during runtime. By default this value is set to 775, but depending on your OS you may require a different value.
: Default Embedded Values
Managed Lifecycle
To configure managed approach you should only instantiate next rule :
@ClassRule
public static ManagedHBase managedHBase = newManagedHBaseServerRule().build();
By default managed HBase rule uses next default values but can be configured programmatically:
Target path This is the directory where HBase server is started and is target/hbase-temp .
CassandraPath HBase installation directory which by default is retrieved from HBASE_HOME system environment variable.
Port By default port used is 60000. If port is changed in HBase configuration file, this port should be configured too here.
: Default Managed Values
Warning
To start HBASE JAVA_HOME must be set. Normally this variable is already configured, so you would need to do nothing.
Remote Lifecycle
Configuring remote approach does not require any special rule because you (or System like Maven ) is the responsible of starting and stopping the server. This mode is used in deployment tests where you are testing your application on real environment.
Configuring HBase Connection
Next step is configuring HBase rule in charge of maintaining HBase columns into known state by inserting and deleting defined datasets. You must register HBaseRule JUnit rule class, which requires a configuration parameter with some information.
To make developer's life easier and code more readable, a fluent interface can be used to create these configuration objects. Three different kind of configuration builders exist.
Embedded Connection
The first one is for configuring a connection to embedded HBase .
import static com.lordofthejars.nosqlunit.hbase.EmbeddedHBase.EmbeddedHBaseRuleBuilder.newEmbeddedHBaseRule;
@Rule
public HBaseRule hBaseRule = newHBaseRule().defaultEmbeddedHBase();
Embedded HBase does not require any special parameter. Configuration object is copied from Embedded rule directly to HBaseRule.
Managed Connection
This is for configuring a connection to managed HBase .
import static com.lordofthejars.nosqlunit.hbase.ManagedHBaseConfigurationBuilder.newManagedHBaseConfiguration;
@Rule
public HBaseRule hbaseRule = new HBaseRule(newManagedHBaseConfiguration().build());
By default configuration used is the one loaded by calling HBaseConfiguration.create() method. HBaseConfiguration.create() which uses hbase-site.xml and hbase-default.xml classpath files.
But also a method setProperty method is provided to modify any
parameter of generated configuration object.
Remote Connection
Configuring a connection to remote HBase uses same approach like ManagedHBase configuration object but using com.lordofthejars.nosqlunit.hbase.RemoteHBaseConfigurationBuilder class instead of com.lordofthejars.nosqlunit.hbase.ManagedHBaseConfigurationBuilder. .
Warning
Working with Apache HBase required a bit of knowledge about how it works. For example your /etc/hosts file cannot contain a reference to your host name with ip 127.0.1.1.
Moreover NoSQLUnit uses HBase-0.94.1 and this version should be also installed in your computer to work with managed or remote approach. If you install another version, you should exclude these artifacts from NoSQLUnit dependencies, and add the new ones manually to your pom file.
Verifying Data
@ShouldMatchDataSet is also supported for HBase data but we should keep in mind some considerations.
If you plan to verify data with @ShouldMatchDataSet in Managed and Remote approach, you should enable Aggregate coprocessor by editing hbase-site-xml file and adding next lines:
<property>
<name>hbase.coprocessor.user.region.classes</name>
<value>org.apache.hadoop.hbase.coprocessor.AggregateImplementation</value>
</property>
Full Example
To show how to use NoSQLUnit with HBase , we are going to create a very simple application.
PersonManager is the business class responsible of getting and updating person's car.
public class PersonManager {
private Configuration configuration;
public PersonManager(Configuration configuration) {
this.configuration = configuration;
}
public String getCarByPersonName(String personName) throws IOException {
HTable table = new HTable(configuration, "person");
Get get = new Get("john".getBytes());
Result result = table.get(get);
return new String(result.getValue(toByteArray().convert("personFamilyName"), toByteArray().convert("car")));
}
private Converter<String, byte[]> toByteArray() {
return new Converter<String, byte[]>() {
@Override
public byte[] convert(String element) {
return element.getBytes();
}
};
}
}
And now one unit test is written:
For unit test we are going to use embedded approach:
public class WhenPersonWantsToKnowItsCar {
@ClassRule
public static EmbeddedHBase embeddedHBase = newEmbeddedHBaseRule().build();
@Rule
public HBaseRule hBaseRule = newHBaseRule().defaultEmbeddedHBase(this);
@Inject
private Configuration configuration;
@Test
@UsingDataSet(locations="persons.json", loadStrategy=LoadStrategyEnum.CLEAN_INSERT)
public void car_should_be_returned() throws IOException {
PersonManager personManager = new PersonManager(configuration);
String car = personManager.getCarByPersonName("john");
assertThat(car, is("toyota"));
}
}
And dataset used is:
{
"name" : "person",
"columnFamilies" : [{
"name" : "personFamilyName",
"rows" : [{
"key" : "john",
"columns" : [{
"name" : "age",
"value" : "22"
},
{
"name" : "car",
"value" : "toyota"
}]
},
{
"key" : "mary",
"columns" : [{
"name" : "age",
"value" : "33"
},
{
"name" : "car",
"value" : "ford"
}]
}]
}]
}
Advanced Usage
Embedded In-Memory Redis
When you are writing unit tests you should keep in mind that they must run fast, which implies, among other things, no interaction with IO subsystem (disk, network, ...). To avoid this interaction in database unit tests, there are embedded in-memory databases like H2 , HSQLDB , Derby or in case of NoSQL , engines like Neo4j or Cassandra have their own implementation. But Redis does not have any way to create an embedded in-memory instance in Java. For this reason I have written an embedded in-memory Redis implementation based on Jedis project.
If you are using NoSQLUnit you only have to register embedded Redis rule as described here , and internally NoSQLUnit will create instance for you, and you will be able to inject the instance into your code.
But also can be used outside umbrella of NoSQLUnit , by instantiating manually, as described in next example:
EmbeddedRedisBuilder embeddedRedisBuilder = new EmbeddedRedisBuilder();
Jedis jedis = embeddedRedisBuilder.createEmbeddedJedis();
Notice that Jedis class is the main class defined by Jedis project but proxied to use in-memory data instead of sending requests to remote server.
Almost all Redis operations have been implemented but it has some limitations:
-
Connection commands do nothing, they do not throw any exception but neither do any action. In fact would not have sense that they do something.
-
Scripting commands are not supported, and an UnsupportedOperationException will be thrown if they are called.
-
Transaction commands are not supported, but they do not throw any exception, simply returns a null value and in cases of List return type, an empty list is returned.
-
Pub/Sub commands do nothing.
-
Server commands are implemented, but there are some commands that have no sense and returns a constant result:
move always return 1.
debug commands throws an UnsupportedOperationException.
bgrewriteaof, save, bgsave, configSet, configResetStat, salveOf, slaveOfNone and slowLogReset returns an OK.
configGet, slowLogGet and slowLogGetBinary returns an empty list.
-
From Key commands, only sort by pattern is not supported.
All the other operations, including flushing, expiration control, and each operation of every datatype is supported in the same way Jedis support it. Note that expiration management is also implemented as described in Redis manual.
Warning
This implementation of Redis is provided for testing purposes not as a substitution of Redis. Feel free to notify any issue of this implementation so can be fixed or implemented.
Managing lifecycle of multiple instances
Sometimes your test will require that more than one instance of same database server (running in different ports) was started. For example for testing database sharding. In next example we see how to configure NoSQLUnit to manage lifecycle of multiple instances.
@ClassRule
public static ManagedRedis managedRedis79 = newManagedRedisRule().redisPath("/opt/redis-2.4.16")
.targetPath("target/redis1")
.configurationPath(getAbsoluteFilePath("src/test/resources/redis_6379.conf"))
.port(6379)
.build();
@ClassRule
public static ManagedRedis managedRedis80 = newManagedRedisRule().redisPath("/opt/redis-2.4.16")
.targetPath("target/redis2")
.configurationPath(getAbsoluteFilePath("src/test/resources/redis_6380.conf"))
.port(6380)
.build();
Warning
Note that target path should be set to different values for each instance, if not some started processes could not be shutdown.
Fast Way
When you instantiate a Rule for maintaining database into known state ( MongoDbRule , Neo4jRule , ...) NoSQLUnit requires you set a configuration object with properties like host, port, database name, ... but although most of the time default values are enough, we still need to create the configuration object, which means our code becomes harder to read.
We can avoid this by using an inner builder inside each rule, which creates for us a Rule with default parameters set. For example for Neo4jRule :
import static com.lordofthejars.nosqlunit.neo4j.Neo4jRule.Neo4jRuleBuilder.newNeo4jRule;
@Rule
public Neo4jRule neo4jRule = newNeo4jRule().defaultEmbeddedNeo4j();
In previous example Neo4jRule is configured to be used as embedded approach with default parameters.
Another example using CassandraRule in managed way.
import static com.lordofthejars.nosqlunit.cassandra.CassandraRule.CassandraRuleBuilder.newCassandraRule;
@Rule
public CassandraRule cassandraRule = newCassandraRule().defaultManagedCassandra("Test Cluster");
And each Rule contains their builder class to create default values.
Simultaneous engines
Sometimes applications will contain more than one NoSQL engine, for example some parts of your model will be expressed better as a graph ( Neo4J for example), but other parts will be more natural in a column way (for example using Cassandra ). NoSQLUnit supports this kind of scenarios by providing in integration tests a way to not load all datasets into one system, but choosing which datasets are stored in each backend.
For declaring more than one engine, you must give a name to each
database Rule using connectionIdentifier() method in configuration
instance.
@Rule
public MongoDbRule remoteMongoDbRule1 = new MongoDbRule(mongoDb()
.databaseName("test").connectionIdentifier("one").build() ,this);
And also you need to provide an identified dataset for each engine, by
using withSelectiveLocations attribute of @UsingDataSet annotation.
You must set up the pair "named connection" / datasets.
@UsingDataSet(withSelectiveLocations =
{ @Selective(identifier = "one", locations = "test3") },
loadStrategy = LoadStrategyEnum.REFRESH)
In example we are refreshing database declared on previous example with data located at test3 file.
Also works in expectations annotation:
@ShouldMatchDataSet(withSelectiveMatcher =
{ @SelectiveMatcher(identifier = "one", location = "test3")
})
When you use more than one engine at a time you should take under consideration next rules:
- If location attribute is set, it will use it and will ignore withSelectiveMatcher attribute data. Location data is populated through all registered systems.
- If location is not set, then system tries to insert data defined in withSelectiveMatcher attribute to each backend.
- If withSelectiveMatcher attribute is not set, then default strategy (explained in section ) is taken. Note that default strategy will replicate all datasets to defined engines.
You can also use the same approach for inserting data into same engine but in different databases. If you have one MongoDb instance with two databases, you can also write tests for both databases at one time. For example:
@Rule
public MongoDbRule remoteMongoDbRule1 = new MongoDbRule(mongoDb()
.databaseName("test").connectionIdentifier("one").build() ,this);
@Rule
public MongoDbRule remoteMongoDbRule2 = new MongoDbRule(mongoDb()
.databaseName("test2").connectionIdentifier("two").build() ,this);
@Test
@UsingDataSet(withSelectiveLocations = {
@Selective(identifier = "one", locations = "json.test"),
@Selective(identifier = "two", locations = "json3.test") },
loadStrategy = LoadStrategyEnum.CLEAN_INSERT)
public void my_test() {...}
Support for JSR-330
NoSQLUnit supports two annotations of JSR-330 aka Dependency Injection for Java. Concretely @Inject and @Named annotations.
During test execution you may need to access underlying class used to load and assert data to execute extra operations to backend. NoSQLUnit will inspect @Inject annotations of test fields, and try to set own driver to attribute. For example in case of MongoDb , com.mongodb.Mongo instance will be injected.
@Rule
public MongoDbRule remoteMongoDbRule1 = new MongoDbRule(mongoDb()
.databaseName("test").build() ,this);
@Inject
private Mongo mongo;
Warning
Note that in example we are setting
thisas second parameter to the Rule.
But if you are using more than one engine at same time (see chapter ) you need a way to distinguish each connection. For fixing this problem, you must use @Named annotation by putting the identifier given in configuration instance. For example:
@Rule
public MongoDbRule remoteMongoDbRule1 = new MongoDbRule(mongoDb()
.databaseName("test").connectionIdentifier("one").build() ,this);
@Rule
public MongoDbRule remoteMongoDbRule2 = new MongoDbRule(mongoDb()
.databaseName("test2").connectionIdentifier("two").build() ,this);
@Named("one")
@Inject
private Mongo mongo1;
@Named("two")
@Inject
private Mongo mongo2;
Stay In Touch
Stay in Touch
Email: asotobu at gmail.com Blog: Lord Of The Jars Twitter: @alexsotob Github: NoSQLUnit Github
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