Oracle 数据库定时执行一些脚本
PROCEDURE Broken (job IN binary_integer, Broken IN boolean, next_date IN
DBMS_Job包的用法
包含以下子过程:
Broken()过程。
change()过程。
Interval()过程。
Isubmit()过程。
Next_Date()过程。
Remove()过程。
Run()过程。
Submit()过程。
User_Export()过程。
What()过程。
1、
Broken()过程更新一个已提交的工作的状态,典型地是用来把一个已破工作标记为未破工作。
这个过程有三个参数:job 、broken与next_date。
PROCEDURE Broken (job IN binary_integer,
Broken IN boolean,
next_date IN date :=SYSDATE)
job参数是工作号,它在问题中唯一标识工作。
broken参数指示此工作是否将标记为破——TRUE说明此工作将标记为破,,而FLASE说明此工作将标记为未破。
next_date参数指示在什么时候此工作将再次运行。此参数缺省值为当前日期和时间。
2、
Change()过程用来改变指定工作的设置。
这个过程有四个参数:job、what 、next_date与interval。
PROCEDURE Change (job IN binary_integer,
What IN varchar2,
next_date IN date,
interval IN varchar2)
此job参数是一个整数值,它唯一标识此工作。
What参数是由此工作运行的一块PL/SQL代码块。
next_date参数指示何时此工作将被执行。
interval参数指示一个工作重执行的频度。
3、
Interval()过程用来显式地设置重执行一个工作之间的时间间隔数。
这个过程有两个参数:job与interval。
PROCEDURE Interval (job IN binary_integer,
Interval IN varchar2)
job参数标识一个特定的工作。interval参数指示一个工作重执行的频度。
4、
ISubmit()过程用来用特定的工作号提交一个工作。
这个过程有五个参数:job、what、next_date、interval与no_parse。
PROCEDURE ISubmit (job IN binary_ineger,
What IN varchar2,
next_date IN date,
interval IN varchar2,
no_parse IN booean:=FALSE)
这个过程与Submit()过程的唯一区别在于此job参数作为IN型参数传递且包括一个
由开发者提供的工作号。如果提供的工作号已被使用,将产生一个错误。
5、
Next_Date()过程用来显式地设定一个工作的执行时间。这个过程接收两个参数:job与next_date。
PROCEDURE Next_Date(job IN binary_ineger,
next_date IN date)
job标识一个已存在的工作。next_date参数指示了此工作应被执行的日期与时间。

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

Video Face Swap
Swap faces in any video effortlessly with our completely free AI face swap tool!

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











0.What does this article do? We propose DepthFM: a versatile and fast state-of-the-art generative monocular depth estimation model. In addition to traditional depth estimation tasks, DepthFM also demonstrates state-of-the-art capabilities in downstream tasks such as depth inpainting. DepthFM is efficient and can synthesize depth maps within a few inference steps. Let’s read about this work together ~ 1. Paper information title: DepthFM: FastMonocularDepthEstimationwithFlowMatching Author: MingGui, JohannesS.Fischer, UlrichPrestel, PingchuanMa, Dmytr

DDREASE is a tool for recovering data from file or block devices such as hard drives, SSDs, RAM disks, CDs, DVDs and USB storage devices. It copies data from one block device to another, leaving corrupted data blocks behind and moving only good data blocks. ddreasue is a powerful recovery tool that is fully automated as it does not require any interference during recovery operations. Additionally, thanks to the ddasue map file, it can be stopped and resumed at any time. Other key features of DDREASE are as follows: It does not overwrite recovered data but fills the gaps in case of iterative recovery. However, it can be truncated if the tool is instructed to do so explicitly. Recover data from multiple files or blocks to a single

If you need to know how to use filtering with multiple criteria in Excel, the following tutorial will guide you through the steps to ensure you can filter and sort your data effectively. Excel's filtering function is very powerful and can help you extract the information you need from large amounts of data. This function can filter data according to the conditions you set and display only the parts that meet the conditions, making data management more efficient. By using the filter function, you can quickly find target data, saving time in finding and organizing data. This function can not only be applied to simple data lists, but can also be filtered based on multiple conditions to help you locate the information you need more accurately. Overall, Excel’s filtering function is a very practical

The performance of JAX, promoted by Google, has surpassed that of Pytorch and TensorFlow in recent benchmark tests, ranking first in 7 indicators. And the test was not done on the TPU with the best JAX performance. Although among developers, Pytorch is still more popular than Tensorflow. But in the future, perhaps more large models will be trained and run based on the JAX platform. Models Recently, the Keras team benchmarked three backends (TensorFlow, JAX, PyTorch) with the native PyTorch implementation and Keras2 with TensorFlow. First, they select a set of mainstream

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

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

New SOTA for multimodal document understanding capabilities! Alibaba's mPLUG team released the latest open source work mPLUG-DocOwl1.5, which proposed a series of solutions to address the four major challenges of high-resolution image text recognition, general document structure understanding, instruction following, and introduction of external knowledge. Without further ado, let’s look at the effects first. One-click recognition and conversion of charts with complex structures into Markdown format: Charts of different styles are available: More detailed text recognition and positioning can also be easily handled: Detailed explanations of document understanding can also be given: You know, "Document Understanding" is currently An important scenario for the implementation of large language models. There are many products on the market to assist document reading. Some of them mainly use OCR systems for text recognition and cooperate with LLM for text processing.

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.
