error creating bean with name sqlSessionFactory defined in class path resource spring/spring-mvc

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原创 最新推荐文章于 2026-05-22 09:03:05 发布 4.1k 阅读 AI 写同款· GEO 优化 ›
谷粒商城基础篇报错集合 谷粒商城基础篇报错集合 1.完成third-party模块阿里云oss对象存储功能后，发现renren-fast模块无法启动 并报以下错误： Error creating bean with name 'ossClient' defined in class path resource [com/alibaba/alicloud/context/oss/OssContextAutoConfiguration.class]: Bean instantiation via factory method fai 阅读详情

找这个问题花了差不多一下午时间才找，其实从报错信息中查看主要是mapper包没有被项目编译生成mybatis对应的xml文件。

Related cause: org.springframework.beans.factory.BeanCreationException: Error creating bean with name 'userDao' defined in file [D:\workspace\springaop\target\classes\com\tfq\springaop\dao\UserDao.class]: Cannot resolve reference to bean 'sqlSessionFactory' while setting bean property 'sqlSessionFactory'; nested exception is org.springframework.beans.factory.BeanCreationException: Error creating bean with name 'sqlSessionFactory' defined in class path resource [spring/spring-mvc.xml]: Cannot resolve reference to bean 'dataSource' while setting bean property 'dataSource'; nested exception is org.springframework.beans.factory.BeanCreationException: Error creating bean with name 'dataSource' defined in class path resource [spring/spring-mvc.xml]: Initialization of bean failed; nested exception is org.springframework.beans.ConversionNotSupportedException: Failed to convert property value of type 'java.lang.String' to required type 'java.sql.Driver' for property 'driver'; nested exception is java.lang.IllegalStateException: Cannot convert value of type [java.lang.String] to required type [java.sql.Driver] for property 'driver': no matching editors or conversion strategy found
	at org.springframework.context.annotation.CommonAnnotationBeanPostProcessor.postProcessPropertyValues(CommonAnnotationBeanPostProcessor.java:311)
	at org.springframework.beans.factory.support.AbstractAutowireCapableBeanFactory.populateBean(AbstractAutowireCapableBeanFactory.java:1214)
	at org.springframework.beans.factory.support.AbstractAutowireCapableBeanFactory.doCreateBean(AbstractAutowireCapableBeanFactory.java:543)
	at org.springframework.beans.factory.support.AbstractAutowireCapableBeanFactory.createBean(AbstractAutowireCapableBeanFactory.java:482)
	at org.springframework.beans.factory.support.AbstractBeanFactory$1.getObject(AbstractBeanFactory.java:305)
	at org.springframework.beans.factory.support.DefaultSingletonBeanRegistry.getSingleton(DefaultSingletonBeanRegistry.java:230)
	at org.springframework.beans.factory.support.AbstractBeanFactory.doGetBean(AbstractBeanFactory.java:301)
	at org.springframework.beans.factory.support.AbstractBeanFactory.getBean(AbstractBeanFactory.java:196)
	at org.springframework.beans.factory.support.DefaultListableBeanFactory.preInstantiateSingletons(DefaultListableBeanFactory.java:772)
	at org.springframework.context.support.AbstractApplicationContext.finishBeanFactoryInitialization(AbstractApplicationContext.java:835)
	at org.springframework.context.support.AbstractApplicationContext.refresh(AbstractApplicationContext.java:537)
	at org.springframework.web.context.ContextLoader.configureAndRefreshWebApplicationContext(ContextLoader.java:446)
	at org.springframework.web.context.ContextLoader.initWebApplicationContext(ContextLoader.java:328)
	at org.springframework.web.context.ContextLoaderListener.contextInitialized(ContextLoaderListener.java:107)
	at org.apache.catalina.core.StandardContext.listenerStart(StandardContext.java:4939)
	at org.apache.catalina.core.StandardContext.startInternal(StandardContext.java:5434)
	at org.apache.catalina.util.LifecycleBase.start(LifecycleBase.java:150)
	at org.apache.catalina.core.ContainerBase$StartChild.call(ContainerBase.java:1559)
	at org.apache.catalina.core.ContainerBase$StartChild.call(ContainerBase.java:1549)
	at java.util.concurrent.FutureTask.run(FutureTask.java:262)
	at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
	at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
	at java.lang.Thread.run(Thread.java:744)
Caused by: org.springframework.beans.factory.BeanCreationException: Error creating bean with name 'bwCar': Injection of autowired dependencies failed; nested exception is org.springframework.beans.factory.BeanCreationException: Could not autowire field: private com.tfq.springaop.dao.UserDao com.tfq.springaop.service.BwCar.userDao; nested exception is org.springframework.beans.factory.NoSuchBeanDefinitionException: No qualifying bean of type [com.tfq.springaop.dao.UserDao] found for dependency: expected at least 1 bean which qualifies as autowire candidate for this dependency. Dependency annotations: {@org.springframework.beans.factory.annotation.Autowired(required=true)}
	at org.springframework.beans.factory.annotation.AutowiredAnnotationBeanPostProcessor.postProcessPropertyValues(AutowiredAnnotationBeanPostProcessor.java:334)
	at org.springframework.beans.factory.support.AbstractAutowireCapableBeanFactory.populateBean(AbstractAutowireCapableBeanFactory.java:1214)
	at org.springframework.beans.factory.support.AbstractAutowireCapableBeanFactory.doCreateBean(AbstractAutowireCapableBeanFactory.java:543)
	at org.springframework.beans.factory.support.AbstractAutowireCapableBeanFactory.createBean(AbstractAutowireCapableBeanFactory.java:482)
	at org.springframework.beans.factory.support.AbstractBeanFactory$1.getObject(AbstractBeanFactory.java:305)
	at org.springframework.beans.factory.support.DefaultSingletonBeanRegistry.getSingleton(DefaultSingletonBeanRegistry.java:230)
	at org.springframework.beans.factory.support.AbstractBeanFactory.doGetBean(AbstractBeanFactory.java:301)
	at org.springframework.beans.factory.support.AbstractBeanFactory.getBean(AbstractBeanFactory.java:201)
	at org.springframework.context.annotation.CommonAnnotationBeanPostProcessor.autowireResource(CommonAnnotationBeanPostProcessor.java:512)
	at org.springframework.context.annotation.CommonAnnotationBeanPostProcessor.getResource(CommonAnnotationBeanPostProcessor.java:486)
	at org.springframework.context.annotation.CommonAnnotationBeanPostProcessor$ResourceElement.getResourceToInject(CommonAnnotationBeanPostProcessor.java:615)
	at org.springframework.beans.factory.annotation.InjectionMetadata$InjectedElement.inject(InjectionMetadata.java:169)
	at org.springframework.beans.factory.annotation.InjectionMetadata.inject(InjectionMetadata.java:88)
	at org.springframework.context.annotation.CommonAnnotationBeanPostProcessor.postProcessPropertyValues(CommonAnnotationBeanPostProcessor.java:308)
	... 22 more
Caused by: org.springframework.beans.factory.BeanCreationException: Could not autowire field: private com.tfq.springaop.dao.UserDao com.tfq.springaop.service.BwCar.userDao; nested exception is org.springframework.beans.factory.NoSuchBeanDefinitionException: No qualifying bean of type [com.tfq.springaop.dao.UserDao] found for dependency: expected at least 1 bean which qualifies as autowire candidate for this dependency. Dependency annotations: {@org.springframework.beans.factory.annotation.Autowired(required=true)}
	at org.springframework.beans.factory.annotation.AutowiredAnnotationBeanPostProcessor$AutowiredFieldElement.inject(AutowiredAnnotationBeanPostProcessor.java:571)
	at org.springframework.beans.factory.annotation.InjectionMetadata.inject(InjectionMetadata.java:88)
	at org.springframework.beans.factory.annotation.AutowiredAnnotationBeanPostProcessor.postProcessPropertyValues(AutowiredAnnotationBeanPostProcessor.java:331)
	... 35 more
Caused by: org.springframework.beans.factory.NoSuchBeanDefinitionException: No qualifying bean of type [com.tfq.springaop.dao.UserDao] found for dependency: expected at least 1 bean which qualifies as autowire candidate for this dependency. Dependency annotations: {@org.springframework.beans.factory.annotation.Autowired(required=true)}
	at org.springframework.beans.factory.support.DefaultListableBeanFactory.raiseNoSuchBeanDefinitionException(DefaultListableBeanFactory.java:1373)
	at org.springframework.beans.factory.support.DefaultListableBeanFactory.doResolveDependency(DefaultListableBeanFactory.java:1119)
	at org.springframework.beans.factory.support.DefaultListableBeanFactory.resolveDependency(DefaultListableBeanFactory.java:1014)
	at org.springframework.beans.factory.annotation.AutowiredAnnotationBeanPostProcessor$AutowiredFieldElement.inject(AutowiredAnnotationBeanPostProcessor.java:543)

我的项目中spring-mvc.xml文件配置有mybatis的映入文件目录，同时在pom.xml中也引入的mybatis的xom包、spring-mybatis包。

<!-- O/X 映射器 使 用 Spring 的 O/X Mapper 的一个最直接的好处是可以通过利用 Spring 框架的其他特性简化配置。Spring 
			的 bean 库支持将实例化的 O/X 编组器注入（即前面提到过的 “依赖项注入”）使用那些编组器的对象。重申一遍，这将加快应用程序开发和部署。 -->
		<dependency>
			<groupId>org.springframework</groupId>
			<artifactId>spring-oxm</artifactId>
			<version>${spring.version}</version>
		</dependency>
        <dependency>
			<groupId>org.mybatis</groupId>
			<artifactId>mybatis</artifactId>
			<version>${mybatis.version}</version>
		</dependency>
		<!-- mybatis/spring包 -->
		<dependency>
			<groupId>org.mybatis</groupId>
			<artifactId>mybatis-spring</artifactId>
			<version>1.2.2</version>
		</dependency>

我用tomcat7的插件运行项目，始终报找不到数据库与实体类(User)映射的UserMapper.xml，找不到datasource。我打开看编译后的项目包中确实没生编译生成mapper文件。所以报错不到UserMapper.xml。于是我在网上查找方法，解决办法是在项目pom.xml中添加如下代码:

<build>
		<finalName>springaop</finalName>
		<resources>
		<resource>
			<directory>src/main/resources</directory>
			<includes>
				<include>**/*.properties</include>
				<include>**/*.xml</include>
			</includes>
			<!-- 这里是false，用true会报 数据库连接 错误 -->
			<filtering>false</filtering>
		</resource>
		<resource>
			<directory>src/main/java</directory>
			<includes>
				<include>**/*.properties</include>
				<include>**/*.xml</include>
			</includes>
			<filtering>true</filtering>
		</resource>
		</resources>
</build>

注意src/main/java下面的结点filtering要设置为true.问题解决了。

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深度学习工具包Deprecation notice.-----This toolbox is outdated and no longer maintained.There are much better tools available for deep learning than this toolbox, e.g. [Theano](http://deeplearning.net/software/theano/), [torch](http://torch.ch/) or [tensorflow](http://www.tensorflow.org/)I would suggest you use one of the tools mentioned above rather than use this toolbox.Best, Rasmus.DeepLearnToolbox================A Matlab toolbox for Deep Learning.Deep Learning is a new subfield of machine learning that focuses on learning deep hierarchical models of data.It is inspired by the human brain's apparent deep (layered, hierarchical) architecture.A good overview of the theory of Deep Learning theory is[Learning Deep Architectures for AI](http://www.iro.umontreal.ca/~bengioy/papers/ftml_book.pdf)For a more informal introduction, see the following videos by Geoffrey Hinton and Andrew Ng.* [The Next Generation of Neural Networks](http://www.youtube.com/watch?v=AyzOUbkUf3M) (Hinton, 2007)* [Recent Developments in Deep Learning](http://www.youtube.com/watch?v=VdIURAu1-aU) (Hinton, 2010)* [Unsupervised Feature Learning and Deep Learning](http://www.youtube.com/watch?v=ZmNOAtZIgIk) (Ng, 2011)If you use this toolbox in your research please cite [Prediction as a candidate for learning deep hierarchical models of data](http://www2.imm.dtu.dk/pubdb/views/publication_details.php?id=6284)```@MASTERSTHESIS\{IMM2012-06284, author = "R. B. Palm", title = "Prediction as a candidate for learning deep hierarchical models of data", year = "2012",}```Contact: rasmusbergpalm at gmail dot comDirectories included in the toolbox-----------------------------------`NN/` - A library for Feedforward Backpropagation Neural Networks`CNN/` - A library for Convolutional Neural Networks`DBN/` - A library for Deep Belief Networks`SAE/` - A library for Stacked Auto-Encoders`CAE/` - A library for Convolutional Auto-Encoders`util/` - Utility functions used by the libraries`data/` - Data used by the examples`tests/` - unit tests to verify toolbox is workingFor references on each library check REFS.mdSetup-----1. Download.2. addpath(genpath('DeepLearnToolbox'));Example: Deep Belief Network---------------------```matlabfunction test_example_DBNload mnist_uint8;train_x = double(train_x) / 255;test_x = double(test_x) / 255;train_y = double(train_y);test_y = double(test_y);%% ex1 train a 100 hidden unit RBM and visualize its weightsrand('state',0)dbn.sizes = [100];opts.numepochs = 1;opts.batchsize = 100;opts.momentum = 0;opts.alpha = 1;dbn = dbnsetup(dbn, train_x, opts);dbn = dbntrain(dbn, train_x, opts);figure; visualize(dbn.rbm{1}.W'); % Visualize the RBM weights%% ex2 train a 100-100 hidden unit DBN and use its weights to initialize a NNrand('state',0)%train dbndbn.sizes = [100 100];opts.numepochs = 1;opts.batchsize = 100;opts.momentum = 0;opts.alpha = 1;dbn = dbnsetup(dbn, train_x, opts);dbn = dbntrain(dbn, train_x, opts);%unfold dbn to nnnn = dbnunfoldtonn(dbn, 10);nn.activation_function = 'sigm';%train nnopts.numepochs = 1;opts.batchsize = 100;nn = nntrain(nn, train_x, train_y, opts);[er, bad] = nntest(nn, test_x, test_y);assert(er < 0.10, 'Too big error');```Example: Stacked Auto-Encoders---------------------```matlabfunction test_example_SAEload mnist_uint8;train_x = double(train_x)/255;test_x = double(test_x)/255;train_y = double(train_y);test_y = double(test_y);%% ex1 train a 100 hidden unit SDAE and use it to initialize a FFNN% Setup and train a stacked denoising autoencoder (SDAE)rand('state',0)sae = saesetup([784 100]);sae.ae{1}.activation_function = 'sigm';sae.ae{1}.learningRate = 1;sae.ae{1}.inputZeroMaskedFraction = 0.5;opts.numepochs = 1;opts.batchsize = 100;sae = saetrain(sae, train_x, opts);visualize(sae.ae{1}.W{1}(:,2:end)')% Use the SDAE to initialize a FFNNnn = nnsetup([784 100 10]);nn.activation_function = 'sigm';nn.learningRate = 1;nn.W{1} = sae.ae{1}.W{1};% Train the FFNNopts.numepochs = 1;opts.batchsize = 100;nn = nntrain(nn, train_x, train_y, opts);[er, bad] = nntest(nn, test_x, test_y);assert(er < 0.16, 'Too big error');```Example: Convolutional Neural Nets---------------------```matlabfunction test_example_CNNload mnist_uint8;train_x = double(reshape(train_x',28,28,60000))/255;test_x = double(reshape(test_x',28,28,10000))/255;train_y = double(train_y');test_y = double(test_y');%% ex1 Train a 6c-2s-12c-2s Convolutional neural network %will run 1 epoch in about 200 second and get around 11% error. %With 100 epochs you'll get around 1.2% errorrand('state',0)cnn.layers = { struct('type', 'i') %input layer struct('type', 'c', 'outputmaps', 6, 'kernelsize', 5) %convolution layer struct('type', 's', 'scale', 2) %sub sampling layer struct('type', 'c', 'outputmaps', 12, 'kernelsize', 5) %convolution layer struct('type', 's', 'scale', 2) %subsampling layer};cnn = cnnsetup(cnn, train_x, train_y);opts.alpha = 1;opts.batchsize = 50;opts.numepochs = 1;cnn = cnntrain(cnn, train_x, train_y, opts);[er, bad] = cnntest(cnn, test_x, test_y);%plot mean squared errorfigure; plot(cnn.rL);assert(er<0.12, 'Too big error');```Example: Neural Networks---------------------```matlabfunction test_example_NNload mnist_uint8;train_x = double(train_x) / 255;test_x = double(test_x) / 255;train_y = double(train_y);test_y = double(test_y);% normalize[train_x, mu, sigma] = zscore(train_x);test_x = normalize(test_x, mu, sigma);%% ex1 vanilla neural netrand('state',0)nn = nnsetup([784 100 10]);opts.numepochs = 1; % Number of full sweeps through dataopts.batchsize = 100; % Take a mean gradient step over this many samples[nn, L] = nntrain(nn, train_x, train_y, opts);[er, bad] = nntest(nn, test_x, test_y);assert(er < 0.08, 'Too big error');%% ex2 neural net with L2 weight decayrand('state',0)nn = nnsetup([784 100 10]);nn.weightPenaltyL2 = 1e-4; % L2 weight decayopts.numepochs = 1; % Number of full sweeps through dataopts.batchsize = 100; % Take a mean gradient step over this many samplesnn = nntrain(nn, train_x, train_y, opts);[er, bad] = nntest(nn, test_x, test_y);assert(er < 0.1, 'Too big error');%% ex3 neural net with dropoutrand('state',0)nn = nnsetup([784 100 10]);nn.dropoutFraction = 0.5; % Dropout fraction opts.numepochs = 1; % Number of full sweeps through dataopts.batchsize = 100; % Take a mean gradient step over this many samplesnn = nntrain(nn, train_x, train_y, opts);[er, bad] = nntest(nn, test_x, test_y);assert(er < 0.1, 'Too big error');%% ex4 neural net with sigmoid activation functionrand('state',0)nn = nnsetup([784 100 10]);nn.activation_function = 'sigm'; % Sigmoid activation functionnn.learningRate = 1; % Sigm require a lower learning rateopts.numepochs = 1; % Number of full sweeps through dataopts.batchsize = 100; % Take a mean gradient step over this many samplesnn = nntrain(nn, train_x, train_y, opts);[er, bad] = nntest(nn, test_x, test_y);assert(er < 0.1, 'Too big error');%% ex5 plotting functionalityrand('state',0)nn = nnsetup([784 20 10]);opts.numepochs = 5; % Number of full sweeps through datann.output = 'softmax'; % use softmax outputopts.batchsize = 1000; % Take a mean gradient step over this many samplesopts.plot = 1; % enable plottingnn = nntrain(nn, train_x, train_y, opts);[er, bad] = nntest(nn, test_x, test_y);assert(er < 0.1, 'Too big error');%% ex6 neural net with sigmoid activation and plotting of validation and training error% split training data into training and validation datavx = train_x(1:10000,:);tx = train_x(10001:end,:);vy = train_y(1:10000,:);ty = train_y(10001:end,:);rand('state',0)nn = nnsetup([784 20 10]); nn.output = 'softmax'; % use softmax outputopts.numepochs = 5; % Number of full sweeps through dataopts.batchsize = 1000; % Take a mean gradient step over this many samplesopts.plot = 1; % enable plottingnn = nntrain(nn, tx, ty, opts, vx, vy); % nntrain takes validation set as last two arguments (optionally)[er, bad] = nntest(nn, test_x, test_y);assert(er < 0.1, 'Too big error');```[![Bitdeli Badge](https://d2weczhvl823v0.cloudfront.net/rasmusbergpalm/deeplearntoolbox/trend.png)](https://bitdeli.com/free "Bitdeli Badge")

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