利用管道迁移数据
磁盘空间不足的情况下,利用命名或者匿名管道迁移和导入数据;需要注意命名管道的权限问题。 0. Name PIP 0[pg@h1 ~]$ psql gtlions -ac select t3 tab,count(*) from t3 union all select t4,count(*) from t4;select t3 tab,count(*) from t3 union all se
磁盘空间不足的情况下,利用命名或者匿名管道迁移和导入数据;需要注意命名管道的权限问题。
0. Name PIP 0 [pg@h1 ~]$ psql gtlions -ac "select 't3' tab,count(*) from t3 union all select 't4',count(*) from t4;" select 't3' tab,count(*) from t3 union all select 't4',count(*) from t4; tab | count -----+------- t3 | 100 t4 | 0 (2 rows) [pg@h1 ~]$ mknod syncpip p [pg@h1 ~]$ psql gtlions -p 5432 -c "copy t3 to '/home/pg/sync'"|psql gtlions -p 5432 -c "copy t4 from '/home/pg/sync'" ERROR: could not open file "/home/pg/sync" for reading: No such file or directory [pg@h1 ~]$ psql gtlions -p 5432 -c "copy t3 to '/home/pg/syncpip'"|psql gtlions -p 5432 -c "copy t4 from '/home/pg/syncpip'" COPY 100 [pg@h1 ~]$ psql gtlions -p 5432 -c "copy t3 to '/home/pg/syncpip'"|psql gtlions -p 5432 -c "copy t4 from '/home/pg/syncpip'" COPY 100 [pg@h1 ~]$ psql gtlions -p 5432 -c "copy t3 to '/home/pg/syncpip'"|psql gtlions -p 5432 -c "copy t4 from '/home/pg/syncpip'" COPY 100 [pg@h1 ~]$ psql gtlions -p 5432 -c "copy t3 to '/home/pg/syncpip'"|psql gtlions -p 5432 -c "copy t4 from '/home/pg/syncpip'" COPY 100 [pg@h1 ~]$ psql gtlions -ac "select 't3' tab,count(*) from t3 union all select 't4',count(*) from t4;" select 't3' tab,count(*) from t3 union all select 't4',count(*) from t4; tab | count -----+------- t3 | 100 t4 | 400 (2 rows) 1. Name PIP 1 [pg@h1 ~]$ rm -rf sync* [pg@h1 ~]$ mkfifo syncpip [pg@h1 ~]$ ll syncpip prw-rw-r-- 1 pg pg 0 11月 6 09:15 syncpip [pg@h1 ~]$ psql gtlions -p 5432 -c "copy t3 to '/home/pg/syncpip'"|psql gtlions -p 5432 -c "copy t4 from '/home/pg/syncpip'" COPY 100 [pg@h1 ~]$ psql gtlions -p 5432 -c "copy t3 to '/home/pg/syncpip'"|psql gtlions -p 5432 -c "copy t4 from '/home/pg/syncpip'" COPY 100 [pg@h1 ~]$ psql gtlions -p 5432 -c "copy t3 to '/home/pg/syncpip'"|psql gtlions -p 5432 -c "copy t4 from '/home/pg/syncpip'" COPY 100 [pg@h1 ~]$ psql gtlions -p 5432 -c "copy t3 to '/home/pg/syncpip'"|psql gtlions -p 5432 -c "copy t4 from '/home/pg/syncpip'" COPY 100 [pg@h1 ~]$ psql gtlions -ac "select 't3' tab,count(*) from t3 union all select 't4',count(*) from t4;" select 't3' tab,count(*) from t3 union all select 't4',count(*) from t4; tab | count -----+------- t3 | 100 t4 | 800 (2 rows) 2. UnName PIP [pg@h1 ~]$ psql gtlions -p 5432 -c "copy t3 to stdout"|psql gtlions -p 5432 -c "copy t4 from stdin" [pg@h1 ~]$ psql gtlions -p 5432 -c "copy t3 to stdout"|psql gtlions -p 5432 -c "copy t4 from stdin" [pg@h1 ~]$ psql gtlions -p 5432 -c "copy t3 to stdout"|psql gtlions -p 5432 -c "copy t4 from stdin" [pg@h1 ~]$ psql gtlions -p 5432 -c "copy t3 to stdout"|psql gtlions -p 5432 -c "copy t4 from stdin" [pg@h1 ~]$ psql gtlions -p 5432 -c "copy t3 to '/home/pg/syncpip'"|psql gtlions -p 5432 -c "copy t4 from '/home/pg/syncpip'" COPY 100 [pg@h1 ~]$ psql gtlions -ac "select 't3' tab,count(*) from t3 union all select 't4',count(*) from t4;" select 't3' tab,count(*) from t3 union all select 't4',count(*) from t4; tab | count -----+------- t3 | 100 t4 | 1300 (2 rows)
-EOF-

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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

When creating a virtual machine, you will be asked to select a disk type, you can select fixed disk or dynamic disk. What if you choose fixed disks and later realize you need dynamic disks, or vice versa? Good! You can convert one to the other. In this post, we will see how to convert VirtualBox fixed disk to dynamic disk and vice versa. A dynamic disk is a virtual hard disk that initially has a small size and grows in size as you store data in the virtual machine. Dynamic disks are very efficient at saving storage space because they only take up as much host storage space as needed. However, as disk capacity expands, your computer's performance may be slightly affected. Fixed disks and dynamic disks are commonly used in virtual machines

1. Open the WeChat app on the old device, click [Me] in the lower right corner, select the [Settings] function, and click [Chat]. 2. Select [Chat History Migration and Backup], click [Migrate], and select the platform to which you want to migrate the device. 3. Click [Select chats to be migrated], click [Select all] in the lower left corner, or select chat records yourself. 4. After selecting, click [Start] in the lower right corner to log in to this WeChat account using the new device. 5. Then scan the QR code to start migrating chat records. Users only need to wait for the migration to complete.

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

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.

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.
