A newly created postgresql container will do a following steps. They are quite time consuming in integration testing and add some unpredictable factor. If a integration testing will clean up tables and data, volumes can be used to speed up postgresql container. pg_ctl -D /var/lib/postgresql/data -l logfile start initdb stop postgresql and start again There might be one issue, do I need to maintain the same credential?

Several things learnt from recent preparation of data for testing. Question the way when it takes too long to process data sed: remove last n lines In the past I always thought sed is the fastest way to manipulate data. Is it true for all the cases? I generated 1T testing data in ndjson format, however the last lines of those files are corrupted json data. I had to remove the last line.

One of my past projects is based neural network in 2020. The solution is quite simple: put the feature vectors into postgresql database create distanced based index I adopted the model and algrithm from face_recognition, and my team trained on sample faces from our internal system to improve the accuracy to reduce the human involvement and save costs. During development, we found that there is a limit of postgres: CUBE_MAX_DIM, my team customize the build of postgreql to work around the limit.