Hibernate操作Blob数据
首先看数据库,数据库中新建一个BlobTable表,表中有两个字段,一个id(主键)一个picture字段是Blob类型字段。然后使用Hibernate向该数据库中写入和读取数据 在POJO类中picture属性用的是Blob类型数据。 下面看操作源码 package dao;import java.io.File;im
首先看数据库,数据库中新建一个BlobTable表,表中有两个字段,一个id(主键)一个picture字段是Blob类型字段。然后使用Hibernate向该数据库中写入和读取数据
在POJO类中picture属性用的是Blob类型数据。
下面看操作源码
package dao; import java.io.File; import java.io.FileInputStream; import java.io.FileOutputStream; import java.io.IOException; import java.io.InputStream; import java.io.OutputStream; import java.math.BigDecimal; import java.sql.Blob; import org.hibernate.LobHelper; import org.hibernate.Query; import org.hibernate.Session; import org.hibernate.Transaction; import Factory.HibernateSessionFactory; import entity.Blobtable; public class BlobDao { private Session session = null; private Transaction tran = null; public BlobDao(){ this.session = HibernateSessionFactory.getSession(); } public void saveBlob(Blobtable bigdate,String path) throws IOException{ /*InputStream in = this.getClass().getResourceAsStream(path); byte[] bytes = new byte[in.available()]; in.read(bytes); in.close();*/ File file = new File(path); FileInputStream fis = new FileInputStream(file); byte[] bytes = new byte[fis.available()]; fis.read(bytes); LobHelper lh = session.getLobHelper(); bigdate.setPicture(lh.createBlob(bytes)); tran = session.beginTransaction(); try{ session.save(bigdate); tran.commit(); System.out.println("插入成功!"); }catch(Exception e){ System.out.println("插入失败!"); tran.rollback(); }finally{ HibernateSessionFactory.closeSession(); fis.close(); } } public void getBlob(BigDecimal id,String targetpath) throws Exception{ String hql = "From Blobtable where id = ?"; Query query = session.createQuery(hql); query.setBigDecimal(0, id); Blobtable bt = (Blobtable) query.uniqueResult(); Blob image = bt.getPicture(); InputStream in = image.getBinaryStream(); OutputStream os = new FileOutputStream(targetpath); int n = -1; while((n=in.read())!=-1){ os.write(n); } in.close(); os.close(); } }
package Test; import java.io.IOException; import java.math.BigDecimal; import dao.BlobDao; import entity.Blobtable; public class Test { public static void main(String[] args) { BlobDao bb = new BlobDao(); Blobtable bt = new Blobtable(); bt.setId(new BigDecimal(5)); try { String path = "f:\\a.jpg"; bb.saveBlob(bt, path); } catch (IOException e) { e.printStackTrace(); } BlobDao bd = new BlobDao(); try { bd.getBlob(new BigDecimal(1), "e:\\a.jpg"); System.out.println("写出成功!"); } catch (Exception e) { e.printStackTrace(); } } }

Hot AI Tools

Undresser.AI Undress
AI-powered app for creating realistic nude photos

AI Clothes Remover
Online AI tool for removing clothes from photos.

Undress AI Tool
Undress images for free

Clothoff.io
AI clothes remover

AI Hentai Generator
Generate AI Hentai for free.

Hot Article

Hot Tools

Notepad++7.3.1
Easy-to-use and free code editor

SublimeText3 Chinese version
Chinese version, very easy to use

Zend Studio 13.0.1
Powerful PHP integrated development environment

Dreamweaver CS6
Visual web development tools

SublimeText3 Mac version
God-level code editing software (SublimeText3)

Hot Topics



Facing lag, slow mobile data connection on iPhone? Typically, the strength of cellular internet on your phone depends on several factors such as region, cellular network type, roaming type, etc. There are some things you can do to get a faster, more reliable cellular Internet connection. Fix 1 – Force Restart iPhone Sometimes, force restarting your device just resets a lot of things, including the cellular connection. Step 1 – Just press the volume up key once and release. Next, press the Volume Down key and release it again. Step 2 – The next part of the process is to hold the button on the right side. Let the iPhone finish restarting. Enable cellular data and check network speed. Check again Fix 2 – Change data mode While 5G offers better network speeds, it works better when the signal is weaker

I cry to death. The world is madly building big models. The data on the Internet is not enough. It is not enough at all. The training model looks like "The Hunger Games", and AI researchers around the world are worrying about how to feed these data voracious eaters. This problem is particularly prominent in multi-modal tasks. At a time when nothing could be done, a start-up team from the Department of Renmin University of China used its own new model to become the first in China to make "model-generated data feed itself" a reality. Moreover, it is a two-pronged approach on the understanding side and the generation side. Both sides can generate high-quality, multi-modal new data and provide data feedback to the model itself. What is a model? Awaker 1.0, a large multi-modal model that just appeared on the Zhongguancun Forum. Who is the team? Sophon engine. Founded by Gao Yizhao, a doctoral student at Renmin University’s Hillhouse School of Artificial Intelligence.

Recently, the military circle has been overwhelmed by the news: US military fighter jets can now complete fully automatic air combat using AI. Yes, just recently, the US military’s AI fighter jet was made public for the first time and the mystery was unveiled. The full name of this fighter is the Variable Stability Simulator Test Aircraft (VISTA). It was personally flown by the Secretary of the US Air Force to simulate a one-on-one air battle. On May 2, U.S. Air Force Secretary Frank Kendall took off in an X-62AVISTA at Edwards Air Force Base. Note that during the one-hour flight, all flight actions were completed autonomously by AI! Kendall said - "For the past few decades, we have been thinking about the unlimited potential of autonomous air-to-air combat, but it has always seemed out of reach." However now,

The latest video of Tesla's robot Optimus is released, and it can already work in the factory. At normal speed, it sorts batteries (Tesla's 4680 batteries) like this: The official also released what it looks like at 20x speed - on a small "workstation", picking and picking and picking: This time it is released One of the highlights of the video is that Optimus completes this work in the factory, completely autonomously, without human intervention throughout the process. And from the perspective of Optimus, it can also pick up and place the crooked battery, focusing on automatic error correction: Regarding Optimus's hand, NVIDIA scientist Jim Fan gave a high evaluation: Optimus's hand is the world's five-fingered robot. One of the most dexterous. Its hands are not only tactile

FP8 and lower floating point quantification precision are no longer the "patent" of H100! Lao Huang wanted everyone to use INT8/INT4, and the Microsoft DeepSpeed team started running FP6 on A100 without official support from NVIDIA. Test results show that the new method TC-FPx's FP6 quantization on A100 is close to or occasionally faster than INT4, and has higher accuracy than the latter. On top of this, there is also end-to-end large model support, which has been open sourced and integrated into deep learning inference frameworks such as DeepSpeed. This result also has an immediate effect on accelerating large models - under this framework, using a single card to run Llama, the throughput is 2.65 times higher than that of dual cards. one

The 2024QS World University Rankings by Subject is here! Overall, there is little change from 2023. According to the official website information, the 2024QS World University Rankings by Subject covers 55 subdivisions and 5 major academic fields. A total of 1,559 universities participated in the ranking, 64 of which are new faces this year (that is, they will not appear in the 2023 ranking). Among these 64 colleges and universities, 14 are truly appearing for the first time. Among them is the University of Chinese Academy of Sciences. According to the refined subjects, Music is a new subject introduced this year. In addition, the data science and artificial intelligence rankings have been expanded, with 51 new universities added to the rankings. The top five in the overall list are: Massachusetts Institute of Technology, University of Cambridge, University of Oxford, and Harvard University

Last week, Microsoft airdropped WizardLM-2, an open source model called GPT-4 level. But I didn’t expect that it would be deleted immediately a few hours after it was posted. Some netizens suddenly discovered that WizardLM’s model weights and announcement posts had all been deleted and were no longer in the Microsoft collection. Apart from the mention of the site, no evidence could be found to prove that this was an official Microsoft project. The GitHub project homepage has become a 404. Project address: https://wizardlm.github.io/ Including the weight of the model on HF, all have disappeared... The whole network is full of confusion, why is WizardLM gone? However, the reason Microsoft did this was because the team forgot to "test" the model. Later, micro

Last week, amid the internal wave of resignations and external criticism, OpenAI was plagued by internal and external troubles: - The infringement of the widow sister sparked global heated discussions - Employees signing "overlord clauses" were exposed one after another - Netizens listed Ultraman's "seven deadly sins" Rumors refuting: According to leaked information and documents obtained by Vox, OpenAI’s senior leadership, including Altman, was well aware of these equity recovery provisions and signed off on them. In addition, there is a serious and urgent issue facing OpenAI - AI safety. The recent departures of five security-related employees, including two of its most prominent employees, and the dissolution of the "Super Alignment" team have once again put OpenAI's security issues in the spotlight. Fortune magazine reported that OpenA
