在本周TDD課程的運行中，我認為編寫一些夾具以簡化dbUnit的使用將很有趣。 我最初的想法只是教dbUnit有關JSON的知識，但事實證明Lieven Doclo已經做到了。 因此，我決定更進一步，還將dbUnit與JUnit Rules結合起來，并提供HSQLDB內存對象存儲的自動引導。
以下測試顯示了我最終得到的結果：
以下測試顯示了我最終得到的結果：
package com.danhaywood.tdd.dbunit.test;import static org.hamcrest.Matchers.equalTo;
import static org.hamcrest.Matchers.is;
import static org.junit.Assert.assertThat;import java.sql.ResultSet;
import java.sql.Statement;import org.dbunit.Assertion;
import org.dbunit.dataset.ITable;
import org.hsqldb.jdbcDriver;
import org.junit.Rule;
import org.junit.Test;import com.danhaywood.tdd.dbunit.DbUnitRule;
import com.danhaywood.tdd.dbunit.DbUnitRule.Ddl;
import com.danhaywood.tdd.dbunit.DbUnitRule.JsonData;public class DbUnitRuleExample {@Rulepublic DbUnitRule dbUnit = new DbUnitRule(DbUnitRuleExample.class, jdbcDriver.class,"jdbc:hsqldb:file:src/test/resources/testdb", "SA", "");@Ddl("customer.ddl")@JsonData("customer.json")@Testpublic void update_lastName() throws Exception {// whenStatement statement = dbUnit.getConnection().createStatement();statement.executeUpdate("update customer set last_name='Bloggs' where id=2");// then (verify directly)ResultSet rs2 = dbUnit.executeQuery("select last_name from customer where id = 2");assertThat(rs2.next(), is(true));assertThat(rs2.getString("last_name"), equalTo("Bloggs"));// then (verify using datasets)ITable actualTable = dbUnit.createQueryTable("customer", "select * from customer order by id");ITable expectedTable = dbUnit.jsonDataSet("customer-updated.json").getTable("customer");Assertion.assertEquals(expectedTable, actualTable);}
}其中customer.ddl是：
drop table customer if exists;
create table customer (id int not null primary key,first_name varchar(30) not null,initial varchar(1) null,last_name varchar(30) not null
)和customer.json （初始數據集）為：
{"customer":[{"id": 1,"first_name": "John","initial": "K","last_name": "Smith"},{"id": 2,"first_name": "Mary","last_name": "Jones"}]
}和customer-updated.json （最終數據集）為：
{"customer":[{"id": 1,"first_name": "John","initial": "K","last_name": "Smith"},{"id": 2,"first_name": "Mary","last_name": "Bloggs"}]
}您可能已經發現， @Ddl注釋可以選擇指定要針對數據庫運行的DDL腳本，而@JsonData定義了JSON格式的數據集。
DbUnitRule類的實際實現是：
package com.danhaywood.tdd.dbunit;import java.lang.annotation.ElementType;
import java.lang.annotation.Retention;
import java.lang.annotation.RetentionPolicy;
import java.lang.annotation.Target;
import java.nio.charset.Charset;
import java.sql.Connection;
import java.sql.ResultSet;
import java.sql.SQLException;import org.dbunit.IDatabaseTester;
import org.dbunit.JdbcDatabaseTester;
import org.dbunit.database.IDatabaseConnection;
import org.dbunit.dataset.DataSetException;
import org.dbunit.dataset.IDataSet;
import org.dbunit.dataset.ITable;
import org.junit.rules.MethodRule;
import org.junit.runners.model.FrameworkMethod;
import org.junit.runners.model.Statement;import com.google.common.io.Resources;public class DbUnitRule implements MethodRule {@Retention(RetentionPolicy.RUNTIME)@Target({ ElementType.METHOD })public static @interface Ddl {String[] value();}@Retention(RetentionPolicy.RUNTIME)@Target({ ElementType.METHOD })public static @interface JsonData {String value();}private final Class<?> resourceBase;private IDatabaseTester databaseTester;private IDatabaseConnection dbUnitConnection;private Connection connection;private java.sql.Statement statement;public DbUnitRule(Class<?> resourceBase, Class<?> driver, String url, String user, String password) {this.resourceBase = resourceBase;try {databaseTester = new JdbcDatabaseTester(driver.getName(), url, user, password);dbUnitConnection = databaseTester.getConnection();connection = dbUnitConnection.getConnection();statement = connection.createStatement();} catch (Exception e) {throw new RuntimeException(e);}}@Overridepublic Statement apply(final Statement base, final FrameworkMethod method, final Object target) {return new Statement() {@Overridepublic void evaluate() throws Throwable {try {Ddl ddl = method.getAnnotation(Ddl.class);if (ddl != null) {String[] values = ddl.value();for (String value : values) {executeUpdate(Resources.toString(resourceBase.getResource(value), Charset.defaultCharset()));}}JsonData data = method.getAnnotation(JsonData.class);if (data != null) {IDataSet ds = new JSONDataSet(resourceBase.getResourceAsStream(data.value()));databaseTester.setDataSet(ds);}databaseTester.onSetup();base.evaluate();} finally {databaseTester.onTearDown();}}};}public java.sql.Connection getConnection() {return connection;}public void executeUpdate(String sql) throws SQLException {statement.executeUpdate(sql);}public ResultSet executeQuery(String sql) throws SQLException {return statement.executeQuery(sql);}public IDataSet jsonDataSet(String datasetResource) {return new JSONDataSet(resourceBase.getResourceAsStream(datasetResource));}public ITable createQueryTable(String string, String string2) throws DataSetException, SQLException {return dbUnitConnection.createQueryTable(string, string2);}
}這使用了Lieven Doclo的JSONDataSet（為方便起見在此處復制）：
import org.codehaus.jackson.map.ObjectMapper;import org.dbunit.dataset.*;
import org.dbunit.dataset.datatype.DataType;import java.io.File;
import java.io.FileInputStream;
import java.io.IOException;
import java.io.InputStream;
import java.util.*;/*** DBUnit DataSet format for JSON based datasets. It is similar to the flat XML layout,* but has some improvements (columns are calculated by parsing the entire dataset, not just* the first row). It uses Jackson, a fast JSON processor.* <br/><br/>* The format looks like this:* <br/>* <pre>* {* "<table_name>": [* {* "<column>":<value>,* ...* },* ...* ],* ...* }* </pre>* <br/>* I.e.:* <br/>* <pre>* {* "test_table": [* {* "id":1,* "code":"JSON dataset",* },* {* "id":2,* "code":"Another row",* }* ],* "another_table": [* {* "id":1,* "description":"Foo",* },* {* "id":2,* "description":"Bar",* }* ],* ...* }* </pre>** @author Lieven DOCLO*/
public class JSONDataSet extends AbstractDataSet {// The parser for the dataset JSON fileprivate JSONITableParser tableParser = new JSONITableParser();// The tables after parsingprivate List<ITable> tables;/*** Creates a JSON dataset based on a file* @param file A JSON dataset file*/public JSONDataSet(File file) {tables = tableParser.getTables(file);}/*** Creates a JSON dataset based on an inputstream* @param is An inputstream pointing to a JSON dataset*/public JSONDataSet(InputStream is) {tables = tableParser.getTables(is);}@Overrideprotected ITableIterator createIterator(boolean reverse) throws DataSetException {return new DefaultTableIterator(tables.toArray(new ITable[tables.size()]));}private class JSONITableParser {private ObjectMapper mapper = new ObjectMapper();/*** Parses a JSON dataset file and returns the list of DBUnit tables contained in* that file* @param jsonFile A JSON dataset file* @return A list of DBUnit tables*/public List<ITable> getTables(File jsonFile) {try {return getTables(new FileInputStream(jsonFile));} catch (IOException e) {throw new RuntimeException(e.getMessage(), e);}}/*** Parses a JSON dataset input stream and returns the list of DBUnit tables contained in* that input stream* @param jsonStream A JSON dataset input stream* @return A list of DBUnit tables*/@SuppressWarnings("unchecked")public List<ITable> getTables(InputStream jsonStream) {List<ITable> tables = new ArrayList<ITable>();try {// get the base object tree from the JSON streamMap<String, Object> dataset = mapper.readValue(jsonStream, Map.class);// iterate over the tables in the object treefor (Map.Entry<String, Object> entry : dataset.entrySet()) {// get the rows for the tableList<Map<String, Object>> rows = (List<Map<String, Object>>) entry.getValue();ITableMetaData meta = getMetaData(entry.getKey(), rows);// create a table based on the metadataDefaultTable table = new DefaultTable(meta);int rowIndex = 0;// iterate through the rows and fill the tablefor (Map<String, Object> row : rows) {fillRow(table, row, rowIndex++);}// add the table to the list of DBUnit tablestables.add(table);}} catch (IOException e) {throw new RuntimeException(e.getMessage(), e);}return tables;}/*** Gets the table meta data based on the rows for a table* @param tableName The name of the table* @param rows The rows of the table* @return The table metadata for the table*/private ITableMetaData getMetaData(String tableName, List<Map<String, Object>> rows) {Set<String> columns = new LinkedHashSet<String>();// iterate through the dataset and add the column names to a setfor (Map<String, Object> row : rows) {for (Map.Entry<String, Object> column : row.entrySet()) {columns.add(column.getKey());}}List<Column> list = new ArrayList<Column>(columns.size());// create a list of DBUnit columns based on the column name setfor (String s : columns) {list.add(new Column(s, DataType.UNKNOWN));}return new DefaultTableMetaData(tableName, list.toArray(new Column[list.size()]));}/*** Fill a table row* @param table The table to be filled* @param row A map containing the column values* @param rowIndex The index of the row to te filled*/private void fillRow(DefaultTable table, Map<String, Object> row, int rowIndex) {try {table.addRow();// set the column values for the current rowfor (Map.Entry<String, Object> column : row.entrySet()) {table.setValue(rowIndex, column.getKey(), column.getValue());}} catch (Exception e) {throw new RuntimeException(e.getMessage(), e);}}}
}我為此使用的庫（即依賴項）為：
- hsqldb 2.2.6
- dbunit 2.4.8
- 杰克遜1.9.3
- slf4j-api-1.6.4，slf4j-nop-1.6.4
- 谷歌番石榴10.0.1
- junit 4.8
一如既往，歡迎發表評論。
參考：來自Dan Haywood博客的 JCG合作伙伴 Dan Haywood的dbUnit，JSON，HSQLDB和JUnit Rules的數據庫單元測試 。
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翻譯自: https://www.javacodegeeks.com/2012/01/db-unit-testing-with-dbunit-json-hsqldb.html
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